Latest Blogs

How Do You Promote Your Research After Publication?

15 January 2026

Navigating Your Career

How Do You Promote Your Research After Publication?

For many researchers, the acceptance and publication of a paper feels like the culmination of their work. However, this often leads to a critical oversight—failing to ensure the research reaches and resonates with its intended audience. Post-publication promotion is not simply an optional addition to the researcher’s toolkit. It is a fundamental component of their scholarly responsibility and a critical driver of their work’s ultimate significance and reach. Effective promotion helps ensure that research is discoverable, accessible, and understandable across disciplines, and that its influence extends beyond traditional citations to broader academic and societal contexts. A successful strategy may follow these 3 steps: Build your hub; Visualize for impact; Distribute smartly. Step 1: Build your hub Before sharing your work across social media or conferences, it is essential to establish a clear and centralized digital presence—a place where all attention and traffic can converge. SciProfiles serves as this foundation. As an academic community, SciProfiles supports connection, communication, and collaboration among researchers by providing a dedicated space to present research, highlight expertise, and engage directly with peers who share similar research interests. SciProfiles allows researchers to bring together publications, academic experience and activities in one accessible place, supporting the dissemination of research, encouraging scholarly discussion, and helping scholars build academic connections that contribute to sustained visibility and research impact. Source: Dr. Violeta Popovici’s SciProfile SciProfiles can be complemented by other scholarly identifiers and platforms. Registering for an ORCID iD ensures accurate author identification and consistent visibility across publishers, indexing services, and research databases, while maintaining profiles on other platforms such as ResearchGate, Academia, Google Scholar, Kudos, The Conversation, and Researchmap further supports discoverability. Together, these services reinforce your academic presence. Step 2: Visualize for impact After establishing a hub, visualizing research content becomes increasingly important, as text-only formats often struggle to capture attention in information-dense environments. Multimedia formats help lower cognitive barriers, making research more engaging, easier to remember, and more widely shareable across both academic and public channels. Create a video abstract A video abstract is a short, two-to-five-minute visual summary of your paper that introduces the background, methods, key findings, and implications using narration, imagery, and simple text. Why video matters? User-behavior research on YouTube indicates that although Entertainment and Music dominate overall searches, Science and Technology content remains among the top trending categories, suggesting strong public interest in science delivered through video. Data shows that papers accompanied by video abstracts tend to perform better: 📈 +35% Article Views 🏆 +25% Altmetric Scores 🔗 +15% Citation Rates These improvements reflect how much easier it is for broader audiences to discover, understand, and share research when a video version is available. What’s more, animated video abstracts can extend this impact even further, helping authors increase visibility and reach wider communities on social media. Source: Encyclopedia Academic Video Service Develop infographics Infographics provide clear, visual summaries of complex findings, enabling quick comprehension and making them ideal for academic communication, public outreach, presentations, and social media. Research shows that infographic articles generate significantly greater social media attention and achieve higher Altmetric scores than standard original research articles, underscoring their value in enhancing research visibility. Source: Encyclopedia Scientific Inforgraphic MDPI’s Encyclopedia has launched the Scientific Infographic Service to support researchers in presenting complex scientific findings through clear and professionally prepared visual summaries. The service is now open for applications and is provided free of charge. For more information, feel free to contact office@encyclopedia.pub. Step 3: Distribute smartly With a well-established academic profile and clear visual materials in place, public and social networks extend your research reach, enabling broader conversations and greater societal impact. Share your work on SciProfiles to ensure that it reaches relevant peers within a scholarly community, fostering focused discussion and meaningful academic connections. Share across social platforms including X (formerly Twitter), LinkedIn, Facebook, WeChat, and Weibo, helping to spark conversation and attract attention from journalists, policymakers, practitioners, and interdisciplinary audiences. Make access easy by providing shareable links. Send your article directly to colleagues, add the link to your email signature, and update personal, laboratory, or institutional webpages with the article title and permanent link. Write blog posts that highlight your key findings, explain their significance, and discuss broader implications. Blogs make your research accessible to non-experts and support broader engagement. Including a link to your published article further enhances visibility and citation potential. You can also publish blog posts on MDPI’s Encyclopedia platform to reach an even wider readership. In parallel, active participation in academic conferences broadens research visibility and helps establish meaningful professional connections. This allows these assets to be shared consistently across both online and offline channels. Presenting your work—whether at in-person meetings or online sessions—allows you to share findings with informed audiences, receive constructive feedback, and spark new collaborations. Joining international events, including those hosted on platforms such as Sciforum, further expands your reach across regions and disciplines. These interactions often lead to new partnerships, fresh research ideas, and additional academic opportunities. From publication to impact Promoting research after publication is no longer a linear or isolated task. By building a centralized hub, visualizing research outputs, and distributing them strategically across online and offline channels, researchers can ensure that their work not only gets published—but gets seen, discussed, and used. Last updated on: July 25, 2026
SciProfiles OfficialSciProfiles Official
SciProfiles Official

1564

Utility and Limitations of AI as Academic Tools

17 December 2025

The Latest in Global Science

Utility and Limitations of AI as Academic Tools

While AI can dramatically accelerate workflows and improve efficiency, its effectiveness depends on the quality of input and access to accurate, reliable data, supported by stringent human oversight. High-quality outputs require well-defined objectives, carefully curated datasets, and continuous validation to avoid bias or misinformation. Despite its expanding role in research, healthcare, and education, AI remains a tool—powerful, but not infallible—capable of augmenting rather than replacing human expertise. Critical thinking, ethical judgment, and academic rigor remain irreplaceable, ensuring that AI complements rather than compromises scholarly integrity. When integrated responsibly, with adherence to scholarly values and professional ethics, AI holds transformative potential, particularly for academics and healthcare professionals seeking to enhance productivity, expand knowledge, and improve decision-making. Utility of AI platforms AI-driven platforms enhance manuscript writing by refining grammar, coherence, and structure, and by identifying redundancies and logical flaws. However, relying on AI to write manuscripts is poor practice; instead, authors should use it to support and refine their work. Integrated citation tools also streamline referencing and cross-verification, saving time and improving academic precision. AI as augmenter, not replacer AI excels in pattern recognition and test selection, enabling rapid analysis of vast, complex datasets to identify trends and guide diagnostic reasoning. However, AI lacks empathy, moral judgment, and clinical intuition—virtues essential to patient-centered care. A recent study reported that while GPT-4 alone demonstrated significantly higher diagnostic accuracy than clinicians using conventional tools, physicians who were assisted by GPT-4 performed no better than those relying solely on traditional resources. This finding underscores a critical barrier: without proper training and integration into workflows, AI’s strengths may not translate effectively into improved outcomes. To harness its full potential, AI must be introduced as a supplement to, not a replacement for, human expertise—preserving the indispensable judgment and relational nuances that clinicians bring to healing. Using AI in academia AI offers tremendous potential in healthcare research, serving as a powerful ally in bridging theoretical knowledge with real-world clinical application. It enhances diagnostics, improves precision in treatment planning, and accelerates the pace of discovery by sifting through complex datasets far more rapidly than humans can. AI-driven insights—from predicting recovery outcomes to optimizing investigation pathways—can transform patient care when wielded thoughtfully. However, this technological promise comes with critical caveats. The surge in AI-powered tools—from literature-review systems to diagnostic algorithms—demands rigorous oversight and methodological soundness. As the literature emphasizes, AI should augment, not replace, human expertise. Ethical concerns such as bias, lack of transparency, and hallucinated outputs highlight the necessity for researchers and practitioners to approach AI with both enthusiasm and caution. By marrying AI capabilities with critical human judgement, the medical and academic communities can harness its benefits responsibly—to improve outcomes, foster innovation, and uphold integrity. Limitations and responsibilities of AI use Despite these advantages, AI is not a panacea. Its outputs are entirely dependent on the quality of input data, model training, and prompt specificity. As with computers, often it is summarized by the adage: “garbage in, garbage out”—the integrity and usefulness of AI-generated content hinge predominantly on human oversight. Without critical engagement, there is a risk of reinforcing bias, misinterpretation, or spreading misinformation. Researchers and academics must therefore remain actively involved in evaluating AI outputs, applying domain expertise, and ensuring alignment with ethical standards. AI should be seen as a co-pilot—not an autopilot—for research. Generative AI for optimizing healthcare and reducing costs Generative AI and advanced analytics transform healthcare by tackling rising costs, inefficiencies, fragmented data, polypharmacy, and inconsistent outcomes. Predictive analytics, real-time monitoring, and automated decision support enable earlier diagnoses, optimized treatments, and fewer unnecessary interventions, yielding savings and improved outcomes. This shift replaces reactive care with proactive, personalized, data-driven precision. Technology will strengthen decision-making and empower care teams to act faster using evidence-based insights, while patients receive focused, coordinated care. Policy reforms should advance preventive care by promoting health education, ensuring access to disease prevention resources, affordable, nutritious foods, consistent physical activity, and routine screenings. Implementing these measures should substantially reduce costs. Strategic investments in AI-driven technologies, machine learning analytics, and shifting care from hospitals to community-based programs will improve population health, expand access, cut costs, and build a resilient, future-ready healthcare infrastructure. Within five years, integrating cybernetic systems with generative AI could transform delivery, diagnostics, treatments, and follow-up care at far lower cost. This integration will enable real-time monitoring, predictive analytics, and early detection of health issues, facilitating timely interventions and personalized care that prevent disease progression and improve long-term outcomes. Ethical and epistemological boundaries AI cannot replicate the intellectual depth, moral reasoning, or contextual understanding that define rigorous scholarship. Critical thinking, creativity, and ethical judgment remain irreplaceably human qualities. AI lacks the capacity for intuition, empathy, and the kind of deep domain knowledge that emerges from years of focused study and experience. Academic institutions and publishers must also address ethical concerns around plagiarism, authorship, data privacy, and algorithmic transparency. Establishing guidelines for responsible AI use in academia is essential to ensure trustworthiness and academic integrity. Embracing AI as a complementary tool Academics must approach AI with both curiosity, enthusiasm, and caution—embracing it as a tool to augment their intellectual endeavors, not replace them. When used responsibly, AI can significantly enhance the efficiency, precision, and depth of scholarly output in a short time. Researchers who learn to use AI tools effectively and recognize their limits from the beginning can produce more impactful, high-quality work that benefits science and society. AI can be used effectively for Pattern Recognition – Detecting trends in symptoms, diagnostics, and outcomes, Medical Imaging – Enhancing accuracy in X-rays, MRIs, and CT scans, Virtual Assistance – Supporting clinicians and patients with real-time guidance, and Patient Data Analysis – Streamlining records, predicting risks, and personalizing care. Synergy between human and machine intelligence The future of academic inquiry lies in a synergistic relationship between human intellect and machine intelligence. AI’s potential to accelerate research is enormous—but it must be guided by scholarly discipline, ethical reflection, and human oversight. By integrating AI thoughtfully and strategically into the academic process, we can expand the frontiers of knowledge while preserving the rigor and values that define scholarship. AI technologies are transforming how researchers conduct, analyze, and present academic work. Tools like generative AI enhance productivity by automating literature reviews, improving manuscript quality, and revealing novel connections across disciplines. However, their utility depends on thoughtful, ethical, and skilled use by researchers. AI cannot replicate human intellect, contextual understanding, or moral reasoning. For meaningful and credible outcomes, academics must apply AI critically and judiciously. The future of scholarship and advances lies in synergizing AI’s computational power with human creativity and wisdom—elevating both the quality and impact of academic research for the greater good. Disclaimer The views, thoughts, and opinions expressed in this article belong solely to the author, and do not necessarily reflect the position or opinions of MDPI or its employees. MDPI takes no responsibility for the content or ideas expressed in this article. Last updated on: July 25, 2026
Sunil J. WimalawansaSunil J. Wimalawansa
Sunil J. Wimalawansa

2944

Harnessing AI for Academic Research and Scholarly Writing: Emerging Tools and Trends

16 December 2025

The Latest in Global Science

Harnessing AI for Academic Research and Scholarly Writing: Emerging Tools and Trends

Artificial Intelligence (AI) is revolutionizing academic research and essential scholarly writing. It helps to streamline key tasks across the research cycle. This process includes literature review and data analysis, writing, and citation management. Generative AI, in particular, enables cross-disciplinary exploration and the rapid synthesis of vast knowledge bases, enhancing hypothesis generation and trend identification. AI’s transformative role in academia Artificial Intelligence (AI) is transforming academic research and scholarly writing by significantly amplifying the quality, speed, and breadth of intellectual exploration. Rather than simply surfing the internet and using AI-generated text as a shortcut for transcription, or being dependent on AI for primary writings, researchers should develop his/her drafts and engage deliberately and critically with AI. AI-generated content can include errors, outdated information, or biases, so it is vital to corroborate its outputs against trusted sources, research archives, and maintain vigilance in interpretation. At every stage of the research process—whether it is crafting hypotheses, reviewing literature, conducting statistical and data analyses, or drafting manuscripts—AI is becoming an indispensable tool. When used judiciously with common sense, it can streamline workflows, surface novel insights, and elevate the precision of scholarly output. However, its effectiveness rests on the researcher’s ability to blend AI’s capabilities with sound methodology, rigorous fact-checking, and editorial judgment. People should form concepts and hypotheses, while AI assists in research. Academic researchers across disciplines are beginning to recognize that integrating AI into the research cycle can yield more profound insights, foster innovation, and reduce workload—when used thoughtfully. Supporting the research lifecycle AI technologies now help at virtually every stage of the process, irrespective of the type of research. Natural language processing (NLP) algorithms and large language models, or LLMs (like ChatGPT and Copilot), can help researchers to formulate more meaningful research questions, refine arguments, and organize thoughts. Tools like semantic search engines, citation managers, and content summarizers help streamline literature reviews by rapidly identifying relevant publications, extracting key themes, and organizing references. These are becoming more advanced. Accelerating interdisciplinary discovery Generative AI supports interdisciplinary exploration by scanning massive repositories of scholarly literature and revealing patterns, relationships, and knowledge gaps that might otherwise go unnoticed. These tools can generate new research questions or hypotheses by connecting seemingly unrelated domains. For example, AI can suggest how a method in computational linguistics might be applied to biological data analysis or link behavioral economics to environmental policy. Interdisciplinary collaborations One of the most profound impacts of AI is its facilitation of interdisciplinary collaboration. By swiftly processing and synthesizing information from disparate fields, AI enables scholars to uncover novel connections and propose innovative solutions to complex questions. This technology empowers teams to break down traditional academic silos, fostering dialogue between disciplines such as medicine, engineering, social sciences, and the humanities. Computational tools can discern emerging trends and knowledge gaps, helping researchers focus their efforts more strategically and encouraging fresh perspectives. Enhancing academic writing and communication AI-based writing assistants improve the clarity, tone, and technical quality of academic writing. These tools provide feedback on sentence structure, eliminate verbosity, improve readability, and ensure consistent formatting. For non-native English speakers, AI offers real-time language translation and grammatical correction, making academic publishing more inclusive and globally accessible. Besides, AI also supports visual communication by generating graphs, data visualizations, and graphical abstracts, allowing researchers to communicate findings more effectively. AI developments in medicine AI already demonstrates superior diagnostic power in complex, image-driven cases and delivers faster, more cost-effective diagnostics. Shortly, the combination of AI and physicians—when workflows are optimized—can yield the best outcomes, with AI supporting rapid triage and test selection. At the same time, doctors serve as validators, communicators, and caregivers. The physician’s evolving role will be to integrate AI insights with human nuance, ensuring that technology enhances rather than replaces clinical judgment. Current barriers include workflow integration, trust, and regulatory challenges, while the future demands improved user experience, targeted training, rigorous clinical trials, and robust ethical oversight. Capabilities of AI to transform academic and healthcare AI’s capacity to integrate and analyze large-scale data offers a transformative opportunity for uncovering patterns and connections that remain hidden in vast datasets. By concurrently querying multiple databases, AI dramatically reduces the time needed to extract pertinent information—soaring beyond the limitations of manual review. This expedited access not only accelerates the pace of discovery but also enables dynamic, data-driven hypothesis testing across fields, highlighting the importance of methodological rigor at every stage of research. Moreover, AI tools are increasingly indispensable in conducting meta-analyses, systematic reviews, and evidence mapping—cornerstones of evidence-based research. For instance, AI systems like “Elicit” can assist with repeatable and reliable systematic reviews, while platforms such as “Paperguide” automate key workflows from search to statistical synthesis. “Elicit” is an AI research assistant that helps users find relevant academic papers, generate literature reviews, and structure research questions using natural language queries. “Paperguide” streamlines the writing process by offering AI-powered support for manuscript organization, clarity improvements, and journal-specific formatting guidance. AI tools like these would make the content more tangible and helpful for a researcher, but writers should not depend on them. Emerging innovations—like explainable AI frameworks that adhere to PRISMA guidelines—offer even faster, transparent review processes, shrinking timelines from months to days. These advancements not only foster innovation but also elevate collaboration, enabling researchers to pivot from information gathering to analysis and insight generation with unprecedented efficiency. AI developments in patient care AI already demonstrates superior diagnostic power in complex, data and image-driven cases and delivers faster, more cost-effective diagnostics. Shortly, the combination of AI and physicians—when workflows are optimized—can yield the best outcomes, with AI supporting rapid triage, compiling and summarizing patients’ electronic medical records, as well as the selection (prompt) of the most optimal and cost-effective investigations. At the same time, doctors serve as validators, communicators, and caregivers. The physician’s evolving role will be to integrate AI insights with human nuance, ensuring that technology enhances rather than replaces clinical judgment. Current barriers include workflow integration, trust, and regulatory challenges, while the future demands improved user experience, targeted training, rigorous clinical trials, and robust ethical oversight. Potentials of AI in healthcare AI holds transformative promises in healthcare by effectively bridging theoretical knowledge and clinical practice. When applied judiciously, it elevates understanding from foundational principles to advanced applications in patient care. AI-driven tools can inspire innovation, sharpen diagnostics, forecast recovery paths, guide cost-effective investigations, and optimize treatment plans. However, it is essential not to lose sight of the trajectory of findings and data—and to apply common sense when interpreting conclusions. Presently, the application of this prudent, contextual judgment remains noticeably lacking. When applied wisely, it enhances understanding from foundational principles to advanced clinical applications. AI can drive innovation, improve diagnostics, predict recovery paths, guide cost-effective investigations, and optimize treatment strategies. However, one should not lose the path of common sense in validating and understanding data, and apply commensurate judgment in interpretations and conclusions. To realize AI’s full potential, academics and healthcare professionals must approach its adoption with open-mindedness, holistic perspectives, and a sense of responsibility. Only by pairing technological capability with sound methodology and critical oversight can AI meaningfully enhance medicine rather than merely augmenting its pitfalls. AI can greatly enhance research and collaboration, but its impact relies on human guidance, rigorous methodology, and critical judgment. In the next blog, we will discuss the limitations and responsibilities of using AI. Disclaimer The views, thoughts, and opinions expressed in this article belong solely to the author, and do not necessarily reflect the position or opinions of MDPI or its employees. MDPI takes no responsibility for the content or ideas expressed in this article. Last updated on: July 25, 2026
Sunil J. WimalawansaSunil J. Wimalawansa
Sunil J. Wimalawansa

3241

How Should Junior Researchers Design a Sustainable Career Path?

10 December 2025

NetworkingNavigating Your Career

How Should Junior Researchers Design a Sustainable Career Path?

Designing a fulfilling research career often gets lost in the daily grind of experiments, papers, and grant deadlines. Without strategic planning, even talented researchers risk burnout and career instability. Here, we offer practical and strategic discussions for building a sustainable, values-driven research career that adapts to changing circumstances. Start with purpose, not just outputs Publications and citations matter, but they don’t guarantee career satisfaction. What truly drives your scientific curiosity? Which societal challenges resonate with you? A clear sense of purpose helps you make better decisions and stay motivated during tough times. It is even more important to set realistic goals and plan strategies to achieve them. Furthermore, an early-career researcher must be ready to reschedule his objectives and change the timeframes required to accomplish them. Build core competencies A sustainable academic trajectory requires balancing deep specialization with a broad set of transferable competencies. First, researchers should cultivate advanced expertise within a clearly defined scientific niche, allowing them to contribute original insights and develop a recognizable scholarly identity. However, specialization alone is insufficient in contemporary research ecosystems. Cross-disciplinary skills, particularly data literacy, scientific communication, and project management, are increasingly essential to navigate complex research workflows, collaborate effectively, and translate findings into meaningful impact. In parallel, early-career investigators must demonstrate familiarity with modern research tools, including fundamental statistical methods, introductory concepts in artificial intelligence and machine learning, and the use of collaborative digital platforms that support transparent, reproducible science. This integrated skillset enhances academic adaptability, competitiveness, and long-term professional resilience. Build a mentorship network No single mentor can adequately address the full spectrum of professional needs encountered in an academic career. Developing a diversified mentoring network is therefore essential. Scientific mentors provide methodological and analytical guidance, career mentors offer strategic advice and long-term planning, peer mentors contribute practical support and shared experience, and external mentors introduce industry-oriented perspectives. These complementary relationships can enhance professional growth, broaden opportunities, and promote more balanced and resilient career development. Practice sustainable work habits Research is inherently a long-term, endurance-driven endeavor, requiring sustained concentration rather than constant acceleration. It is a marathon. Protecting uninterrupted focus time, establishing clear professional boundaries, and declining non-essential commitments are essential practices for maintaining productivity and preserving cognitive resources. Systematic weekly planning further supports stable progress across complex projects. Importantly, burnout should not be viewed as an indicator of dedication; it represents a significant threat to creativity, performance, and long-term career sustainability. Diversify funding and career options Relying on a single funding source or a narrowly defined career trajectory introduces substantial professional vulnerability. Early-career researchers should actively pursue diverse funding opportunities and engage in interdisciplinary projects that broaden their expertise and collaborative networks. Maintaining openness to multiple career pathways, including academia, industry, policy, data science, and science communication, enhances long-term adaptability and resilience. This kind of strategic diversification mitigates risk, expands professional opportunities, and supports sustained contributions to the scientific enterprise. Invest in your professional identity Reputation constitutes a critical, non-technical asset in academic and scientific advancement. Beyond methodological proficiency, researchers benefit substantially from being visible, reliable, and actively engaged within their scholarly communities. Participation in conferences and professional meetings facilitates networking, fosters collaborations, and exposes investigators to emerging research opportunities. Maintaining an updated and coherent digital presence (through platforms such as ORCID, ResearchGate, SciProfiles, and even professionally curated social media profiles) enhances discoverability and reinforces credibility. Demonstrating integrity, consistency, and timely communication builds trust among collaborators, reviewers, and potential mentors. Collectively, these elements generate opportunities that technical skills alone cannot secure, shaping long-term academic trajectories and strengthening professional influence. Navigate the data analysis evolution Integrating traditional statistical principles with emerging AI and machine-learning methodologies enhances analytical precision and adaptability. Maintaining statistical rigor while acquiring foundational skills in Python or R, basic machine-learning techniques, and reproducible research practices ensures that researchers can critically evaluate and apply modern tools without abandoning methodological soundness. The aim is not to become a data scientist, but to remain scientifically agile and responsive to evolving research standards, thereby expanding opportunities for high-impact investigation. Build resilience for rejection Rejection is an inherent and structural component of academic life. It reflects competitive processes rather than personal inadequacy. Developing deliberate strategies to navigate these setbacks is essential for long-term success. For manuscripts, authors should systematically analyze reviewers’ comments, extract constructive elements, and implement revisions that strengthen methodological clarity and scientific coherence. In the context of grant applications, diversifying funding targets and soliciting post-mortem feedback from reviewers or program officers can illuminate weaknesses and guide future submissions. Similarly, negative or null results should be rigorously documented and, when scientifically sound, considered for publication, as such evidence contributes to transparency, reduces publication bias, and advances cumulative knowledge. Plan financial stability Financial precarity is a tangible and often under-recognized challenge in early academic careers. Addressing it proactively is essential for long-term stability. Researchers should systematically budget for predictable professional expenses, including open-access publication fees, conference travel, and society memberships, which are integral to maintaining scientific visibility and career progression. Establishing a personal emergency fund covering three to six months of living costs provides a buffer against contract gaps, delayed funding, or transitional periods between positions. Equally important is developing a clear understanding of compensation structures across sectors, recognizing the trade-offs between academic and industry roles in terms of salary, security, benefits, and scientific autonomy. A strategic financial plan enhances resilience and supports sustained scholarly engagement. Young researchers in low-resources countries Early-career researchers working in medium- and low-resource environments must intentionally cultivate deep scientific literacy to remain competitive within the global research landscape. This requires allocating dedicated time for the systematic study of high-quality scientific models, including exemplary trial designs, robust observational studies, and methodologically sound reviews. Equally important is strict adherence to international reporting frameworks, such as CONSORT for randomized trials, STROBE for observational research, and PRISMA for systematic reviews, which ensures transparency, reproducibility, and methodological credibility. Given the limitations of local laboratory or clinical infrastructure, developing proficiency in secondary data analysis, bioinformatics tools, and the exploitation of publicly available datasets represents a highly resource-efficient strategy for producing impactful research. By integrating rigorous methodological practices with data-driven approaches, early-career investigators can enhance scholarly visibility and strengthen their prospects for publication in high-quality international journals. Join the conversation We’re ready to hear from you. What is your biggest career challenge right now? Which strategy resonates most with you, and what advice would you offer to junior researchers? Authors This blog was collaboratively developed by an international team of researchers and clinicians that are passionate about supporting early-career scientists. Van Y Tran and Van Phong Phan Department of Anesthesiology and Pain Medicine, Binh Dan Hospital, Ho Chi Minh City, Vietnam Giacomo Farì Department of Experimental Medicine, University of Salento, Lecce, Italy Matteo Luigi Giuseppe Leoni Department of Medical and Surgical Sciences and Translational Medicine, Sapienza University of Roma, Italy Ameen A. Al Alwany College of Medicine, University of Baghdad, Iraq Annalisa Caruso Department of Surgery, ASST Lodi, Italy Giustino Varrassi Fondazione Paolo Procacci, Roma, Italy; College of Medicine, University of Baghdad, Iraq Disclaimer The views, thoughts, and opinions expressed in this article belong solely to the author, and do not necessarily reflect the position or opinions of MDPI or its employees. MDPI takes no responsibility for the content or ideas expressed in this article. Last updated on: July 25, 2026
Giustino VarrassiGiustino Varrassi
Giustino Varrassi

3238

Why Traditional Publishing Continues to Flourish

13 November 2025

The Latest in Global Science

Why Traditional Publishing Continues to Flourish

A consistent record of academic publishing is a crucial part of being a successful scholar. In order to accomplish this, authors can be strategic and take into consideration the best publishing model to pursue. Traditional academic publishing continues to flourish even as options are expanded. In order to help you make an informed decision, this article will explore the continued success of the traditional publishing process. It will consider: What is traditional publishing exactly? Why do scholars continue to choose traditional models for their work? We will also explain how traditional publishing offers both advantages and disadvantages versus open access academic publishing. What is traditional publishing? The academic publishing landscape has been significantly altered by cultural shifts towards inclusivity, diversity, and accessibility. This has resulted in widespread adoption of open access publishing as part of the broader open science movement. Even though the advent of open access models, the traditional publishing process continues to flourish. This model involves a closed access subscription publishing-based model of peer-reviewed academic work. An important aspect of traditional publishing is that readers do not pay a fee. The responsibility for paying to access paywalled research falls to the individual or their affiliated institution. In general, the traditional publishing process is made up of several different steps. These include doing research, preparing a manuscript, submission to a journal, peer review, revisions, copy edits, and final publication. Journals using this model produce high-quality publications through a lengthy and rigorous process. Advantages of traditional publishing Now that we have a sense of what traditional publishing is, what are the key benefits of choosing this model? Getting your academic work published requires consistent work, dedication, and patience. What and where you publish can have a significant impact on your career advancement. There are different aspects of the traditional publishing model that are discipline- or journal-specific. But a few key factors keep traditional publishing as a top choice for scholars. Historically, traditional publications have been more likely to be highly ranked, have a high impact factor, and have a strong reputation. Many of the most well-regarded and prestigious journals in the relevant field(s) publish under traditional models. This is in large part due to these journals maintaining the highest ethical standards and quality control practices. Rigorous peer review and an established readership and wide reach for their publications are also key. In addition, subscription publishing journals do not require authors to pay an article processing charge (APC) to publish. This means that scholars don’t have to be funded or pay out of pocket in order to have a chance to share their work. Limitations of traditional publishing While there are many advantages to the traditional publishing process, there are also some disadvantages to consider. One disadvantage is that this process typically follows a much longer timeline than open access publishing. Rather than taking months, it can take years to move through peer review and revisions to final publication and distribution. An important limitation that remains is the financial barriers associated with a subscription publishing-based system. This is because, while subscription publishing doesn’t charge authors to publish, they do charge for access. For those affiliated with an institution that covers the subscription cost, being able to read and share academic work is easy. But paying for each article individually from journals can quickly become very costly, and is completely prohibitive for many. Economic status and institutional affiliation (or lack thereof) limit who can actually access, use, and share scientific research. This has significant consequences globally, with various marginalized communities unable to fully participate in academic discourse. This only widens the research and publication gaps due to a lack of community-driven programs. The academic publishing landscape has been significantly altered by cultural shifts towards inclusivity, diversity, and accessibility. This has resulted in widespread adoption of open access publishing as part of the broader open science movement. Balancing your publishing program Both traditional and open access models offer advantages to authors, readers, and academia more broadly. As you do your research, keep in mind things like high impact factor, reputation, accessibility and reach, and readership. There may be times when certain advantages or disadvantages matter more than others. For example, if you are doing research that is particularly timely or cutting-edge, you may want to try to publish as quickly and widely as possible. In this instance, publishing open access may be the best option to disseminate your research findings within academia and to the public. At other times, as scholars are looking toward tenure or promotion opportunities, pursuing academic publication with a subscription publishing-based journal, particularly one with a high impact factor and a notable reputation in your field, may be a better option. As the academic publishing world continues to open up, there are plenty of options to pursue for publication. If you keep working hard and demonstrating your commitment to the work, you can build a strong and impactful publishing portfolio. Last updated on: July 25, 2026
Zoë GrossZoë Gross
Zoë Gross

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5 Simple Tips for Young Researchers

28 October 2025

Navigating Your Career

5 Simple Tips for Young Researchers

Starting your academic research journey can be both exciting and confusing. You may have many ideas but wonder how to turn them into something real and useful. That’s completely normal. In this blog post, I want to share some simple advice to help young or early-career researchers get started and grow with confidence. Building a solid research foundation The first challenge many students face is organizing their ideas into a clear research plan. The best way to begin is by asking yourself a simple question: What do I want to study, and why is it important? Once you have your topic in mind, read a few academic papers on the subject to see what other researchers have already done. This will help you find your place in the conversation. After that, you can break your project into steps, such as doing background reading, collecting data, analyzing it, and, finally, writing about your results. It’s also a good idea to make a schedule to manage your time and speak with your teacher or supervisor regularly to get feedback and stay on the right track. Integrating AI as a strategic research tool Today, many researchers use artificial intelligence (AI) tools to help with their work. Tools like ChatGPT can help you improve your writing, find articles faster, or even give you ideas for analysing data. AI is very helpful, especially when you are short on time. However, it’s important to remember that AI should be used as a support tool, not as a replacement for your own thinking. Always double-check the information and be honest about using AI in your research process. Maximizing research visibility and outreach Once your paper is written, you may wonder how to share it with others. Publishing your research is a great start, but if you want more people to read it, you need to make it visible. You can upload your paper to research websites like Google Scholar or ResearchGate. You can also talk about your work on social media, especially LinkedIn, where many academics and professionals connect. If possible, try to present your research at student conferences or write a short summary in simple words so people outside your field can also understand your work. Perfecting academic writing through practice and feedback Writing a good academic paper takes practice. Start by writing clearly and simply. You don’t need to use complicated words to sound smart. Focus on explaining what is new or interesting about your research, and support your points with real data or references. After writing, take time to review and improve your draft. Ask classmates, friends, or your supervisor to read it and give you feedback. Don’t be afraid of rewriting—it makes your work stronger. Strategizing your academic career and personal growth Lastly, as a young researcher, you might be wondering how to plan your academic career. Start by thinking about what you enjoy doing and where you want to go in the future. Try different academic activities, like writing papers, presenting your work, or joining group projects. Finding a mentor—someone more experienced who can give advice—is also a great help. Most importantly, take care of yourself. Research is important, but so is your health and balance in life. Stay open to learning new things, even outside your main subject, and don’t be afraid to adjust your path along the way. In conclusion, research is a journey. It doesn’t require perfection—it requires curiosity, effort, and patience. Keep learning, stay motivated, and enjoy the small steps along the way. Every great researcher started where you are now. Disclaimer The views, thoughts, and opinions expressed in this article belong solely to the author, and do not necessarily reflect the position or opinions of MDPI or its employees. MDPI takes no responsibility for the content or ideas expressed in this article. Last updated on: July 25, 2026
Atour TaghipourAtour Taghipour
Atour Taghipour

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Boosting Research Visibility with Academic Video Abstracts

25 September 2025

The Latest in Global Science

Boosting Research Visibility with Academic Video Abstracts

Academic spaces are a place of constant evolution, and one such evolution was the creation of video abstracts. A relatively new part of academic publishing, here we’ll address what a video abstract is and why you’d want one for your research. What is a video abstract? As scholarly communication moves toward digital, open access, and multimedia formats, traditional text-based dissemination is being complemented by more dynamic and accessible methods. A video abstract is a concise, visually engaging multimedia presentation that summarizes the core findings of a scholarly article. By combining narration with visuals such as animations, infographics, real-world footage, or data visualizations, it makes complex research easier to understand for both academic and non-specialist audiences. Video abstracts are often shared through multiple channels, including academic publishers’ platforms (e.g., MDPI, Elsevier, Springer Nature), where they appear alongside the original article, as well as open access repositories, academic networks like ResearchGate, video platforms such as YouTube, and social media channels including LinkedIn and X. Read the paper that this video abstract is based on here Why create a video abstract? In the evolving landscape of scholarly communication, video abstracts are becoming an essential tool for increasing research visibility, enhancing impact, and improving discoverability in a competitive research environment. Enhancing views Research consistently shows that video abstracts can significantly improve visibility. A 2014 study in the Journal of Librarianship and Scholarly Communication found that although only 5% of articles included a video abstract, 25–30% of the most-read articles featured one. More recently, a 2023 Scientometrics study reported a 35% increase in article views for papers with video abstracts, even after controlling for other factors. Boosting citations Research indicates that video abstracts can significantly increase citation rates. A 2009 study published in Scientometrics found that articles accompanied by video abstracts received 20% more citations than those without. This statistically significant increase highlights the role of video abstracts in enhancing a work’s academic reach. Amplifying altmetrics scores Video abstracts can also enhance attention beyond scholarly circles. The Scientometrics study showed that articles with video abstracts have been shown to achieve a 25% higher Altmetric Attention Score (AAS), a metric that reflects attention across X , blogs, news outlets, and other digital media. A well-produced video abstract can: Demonstrate experiments or fieldwork visually Clarify theoretical concepts with illustrations or examples Present tools, equipment, or datasets used in the study Highlight simulations or animations that reinforce findings Engage audiences in a more informal and memorable way Therefore, video abstracts support scholars when used in academic presentations, lectures, and instructional settings. In an era where research is increasingly evaluated by both scholarly impact and public relevance, video abstracts offer a compelling tool to bridge the gap between academia and broader societal engagement. Which publishers encourage video abstracts? Publishers encourage researchers to create and share video abstracts by offering comprehensive support and showcasing their measurable impact. Some publishers integrate video abstract submission options into manuscript submission systems, provide detailed guidelines and templates, and occasionally collaborate with third-party platforms to assist with production. Most leading academic publishers now support or encourage the use of video abstracts as part of their publishing strategy, recognizing their value in enhancing research visibility and engagement. Publishers such as MDPI, Elsevier, Wiley, ACS Publications, Cell Press, Taylor & Francis, and IOP Science offer dedicated platforms or guidelines for submitting video content alongside written articles. The video abstract “How Do Sex Hormones Control Behavior?” has received over 1.9 million views on YouTube, and the related article has been cited more than 290 times, reflecting both its broad public impact and substantial academic influence. How to produce a good video abstract A video abstract is a short, engaging video summary that condenses key elements of a study. Keep It Brief: Aim for under 5 minutes. Focus on the research question, methodology, key findings, and implications. Write a Clear and Engaging Script: Ensure clarity and accessibility. Avoid jargon, keeping the language simple and engaging for a broad audience. Use Visuals: Use professional video editing software and animation tools to present charts, graphs, and animations that simplify complex data and highlight key points. Ensure Quality Audio and Video: Record in a quiet environment with a good microphone. Proper lighting enhances professionalism. Adopt a Conversational Tone: Speak naturally to engage viewers, avoiding reading directly from the script. However, creating video abstracts remains a significant challenge for most researchers. As such, many are turning to commercial services for assistance. Some video services offer one-stop solutions, helping researchers produce polished video abstracts. Sample video abstract Flavonoid-Based Nanoparticles for Osteoarthritis and Rheumatoid Arthritis This review has shed light on the potential of flavonoids and flavonoid-based nanoparticles as promising avenues for the management of osteoarthritis and rheumatoid arthritis. The video abstract was produced by MDPI’s Encyclopedia Academic Video Service. It has helped broaden its reach, garnering significant attention with 24 academic citations, 5.8k article views, and 3.4k video views. MDPI Academic Video Service The MDPI Academic Video Service is dedicated to helping researchers communicate their work through engaging visual media. The services was officially launched in April 2025. It offers comprehensive support, including one-on-one video assistance, scriptwriting and editing. Not only that, but also high-quality animations, voice actor or AI voiceovers, multiple revision rounds, custom infographics, and social media promotion. This service includes the production of Video Abstracts, Short Takes, and Scholar Interviews. These are designed to complement traditional academic publications and enhance the reach of research. Encyclopedia has collaborated with more than 40 SCI-indexed journals. Nutrients, Foods, Sustainability, Cancers, Entropy, Remote Sensing, Nanomaterials, Animals, and Encyclopediaare some examples. These collaborations aim to support the dissemination of research findings, facilitate viewer engagement, and contribute to broader scholarly communication efforts. For more information about video abstracts or assistance with video production, feel free to contact office@encyclopedia.pub.
SciProfiles OfficialSciProfiles Official
SciProfiles Official

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AI in My Research: Practical Lessons Every Academic Should Know

29 August 2025

The Latest in Global Science

AI in My Research: Practical Lessons Every Academic Should Know

Enhancing Efficiency Without Replacing Expertise Here, I share practical lessons from my research, where Artificial Intelligence (AI) has become an essential productivity tool. AI enhances efficiency, improves data-driven decision-making, and simplifies the management of complex technical workflows. In research areas like energy systems, hydrogen economy, and decarbonization, AI has become indispensable in supporting design optimization, techno-economic assessments, and policy-related studies. The Growing Role of AI in Technical Research Research demands in engineering and sustainability are increasing. The volume of data, the complexity of multidisciplinary systems, and the expectation for actionable and impactful results make it clear that traditional methods, while foundational, require intelligent support. AI has emerged as a practical solution to address these demands by assisting researchers in managing large datasets, improving analytical workflows, and enhancing research efficiency. To me, it feels like AI is no longer a luxury or an optional add-on. For researchers working in technical fields, it is becoming an essential tool that supports rigorous analysis and process optimization. AI allows people to focus on high-level problem-solving while automating data-heavy and repetitive processes. AI as a Technical Enabler in Modeling, Design, and Analysis In my research, AI functions as a supportive tool that enhances technical workflows, particularly in design optimization, data management, and analytical assessments. In a recent carbon capture project, an AI-driven data generation framework boosted the accuracy of solvent screening for rotating packed beds from 40% to over 92%, reducing the time and cost needed to identify optimal candidates and accelerating deployment of advanced CO₂ capture systems. However, the core scientific thinking, critical analysis, and decision-making remain entirely driven by human expertise. AI assists in improving efficiency, but intellectual leadership and scientific rigor always come from the researcher. Optimizing Design Configurations and Scenario Assessments Design optimization tasks often involve multiple design variables, complex trade-offs, and scenario evaluations. AI supports these workflows by organizing variable sets and assisting in identifying efficient configurations within defined technical boundaries. For example, in one liquefied natural gas (LNG) study, an AI-based surrogate model paired with advanced optimization algorithms cut the computational time of process design by over 90 percent, while maintaining near-perfect accuracy in predicting energy use. This approach not only sped up decision-making but also revealed operating conditions that could meaningfully lower greenhouse gas emissions. AI helps in managing optimization parameters and providing structured comparisons of alternative configurations. However, the final selection of the optimal design, assessment of trade-offs, and alignment with project objectives are determined through in-depth analysis by the researcher. Enhancing Data Handling and Techno-Economic Evaluations Techno-economic studies demand managing extensive technical and economic data, modeling various policy scenarios, and evaluating the financial viability of technologies. AI assists in organizing datasets, automating trend analysis, and visualizing results for better clarity. In my research, AI-driven analytics streamline the handling of complex datasets, helping structure the evaluation process more efficiently. However, the interpretation of economic impacts, policy implications, and formulation of strategic conclusions is a process that depends entirely on the researcher’s expertise and critical assessment. Streamlining Documentation and Review Processes Research documentation, reporting, and preparation of policy briefs require meticulous attention to detail. AI tools assist in managing references, ensuring formatting consistency, and organizing large documents efficiently. These tools help reduce the time spent on routine documentation tasks, allowing me to dedicate more focus to in-depth content development and technical analysis. However, the creation of research content, the development of arguments, and the final quality review remain the responsibility of the researcher. Supporting Communication and Ethical Compliance Communicating research findings effectively, whether in academic publications, policy discussions, or industry engagements, requires clarity, accuracy, and contextual understanding. AI tools support by organizing supporting materials, managing citations, and preparing visual summaries. However, crafting the message, ensuring factual precision, and maintaining ethical standards in communication are tasks that require human oversight and intellectual responsibility. AI organizes information, but the integrity and depth of communication are led by the researcher. Key Lessons and Guidance for Researchers AI enhances workflow efficiency in data handling, optimization processes, and analytical documentation, but does not influence the intellectual direction of research. The researcher’s expertise, critical thinking, and domain knowledge are central to every decision-making and analysis process. AI assists in managing technical tasks, allowing researchers to focus on addressing complex challenges and delivering meaningful research outcomes. How to maximize benefits To maximize the benefits of AI while maintaining academic rigor and scientific leadership, researchers should consider the following practical guidelines: Apply AI tools to streamline data-heavy workflows, such as managing datasets and organizing scenario comparisons. Use AI to assist in optimizing workflow efficiency, but retain full ownership of analysis and conclusions. Collaborate with AI experts to adapt tools effectively for specific research applications. Engage in interdisciplinary collaborations where AI applications intersect with engineering, data science, and policy research to develop comprehensive, real-world solutions to complex energy and sustainability challenges. Maintain a clear distinction between AI-assisted processes and core research activities that require human expertise. Continuously evaluate AI’s role as a productivity enhancer, ensuring that academic rigor and research integrity are never compromised. Stay informed about advancements in AI methodologies relevant to your research domain to leverage emerging tools that can further enhance analytical efficiency. Document AI-assisted methodologies in your research publications to demonstrate transparency, reproducibility, and the thoughtful integration of AI into technical workflows. The Future of AI in Research Excellence AI will continue to play an important role in improving research workflows, especially in technical disciplines that involve complex data structures, design optimization, and techno-economic evaluations. It will enhance research capacity and streamline analytical processes. However, AI will not replace the human expertise and scientific judgment necessary for high-quality research. Institutions that integrate AI strategically will benefit from improved efficiency, but the leadership in innovation and research excellence will always remain with the researchers. Conclusion It is important to recognize that AI cannot replace researchers and scientists. The formulation of research ideas, critical evaluations, analytical reasoning, and strategic conclusions will always require human intellect, domain expertise, and scientific judgment. AI assists in improving workflows, but it does not possess the creativity, contextual understanding, or scientific rigor needed to drive research innovation. AI is a powerful productivity tool, but it is the researcher who defines the direction, ensures the quality, and leads the journey from data to impactful outcomes. By embracing AI with a clear understanding of its role as a supportive enabler, researchers can amplify their capabilities, enhance their efficiency, and maintain the integrity and depth that define academic and scientific excellence. Disclaimer The views, thoughts, and opinions expressed in this article belong solely to the author, and do not necessarily reflect the position or opinions of MDPI or its employees. MDPI takes no responsibility for the content or ideas expressed in this article. Last updated on: July 25, 2026
Muhammad Abdul QyyumMuhammad Abdul Qyyum
Muhammad Abdul Qyyum

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What Is An Editorial Board and Why Is It Important?

21 August 2025

Networking

What Is An Editorial Board and Why Is It Important?

Editorial boards in academic publishing are crucial to the process of running a peer-reviewed journal. Board members bring their expertise and experience to the journal to guide its content and direction in line with its mission statement. This article introduces the idea of editorial board and answers some questions you might have: What does an advisory board do? What is their role in academic publishing? We provide an overview of key responsibilities, including oversight and management of quality control and peer review. We will also provide some ideas for those interested in joining an editorial board, as well as active board members looking to recruit new people. What is an editorial board? In the context of academic publishing, an editorial board is a group of scholars responsible for overseeing the direction and production of a journal. Essentially, it is an advisory board that helps with decision-making and implementation of the journal’s policies and practices. A committed and engaged advisory board can help to guide a journal towards increased reach and impact. Ideally, scientific advisory board members should represent diverse perspectives and backgrounds within the field(s) of study. In addition to bringing knowledge and passion about the field of study, those with backgrounds in other areas are also desirable candidates. For example, skills in logistics, finance, business, marketing, or graphic design can offer significant support to different sides of the journal. In addition, bringing on scholars who are well-established with strong reputations can help to elevate the journal’s visibility. What does an editorial board do? The work that editorial boards do varies depending on the needs and goals of the journal and the expertise of board members. There are, however, some standard roles and responsibilities for board members across most journals. In general, alongside the editor, board members help to shape the direction of the journal in terms of the focus of the subject matter. In addition to editorial decisions, they are responsible for both day-to-day decisions and long-term vision planning. Recruitment of board members, promotion of the journal to readership, and networking with other scholars to increase the visibility of the journal. They also provide oversight for general operations and publishing workflows. This includes quality control in terms of screening, peer review, revisions, copy edits, and production. Managing ethical concerns and ensuring the implementation of ethical practices within the journal and its publications is also a significant aspect of running a journal. Joining an editorial board Developing professional associations is an important part of any academic’s career. Sitting on the editorial board of a journal can be a particularly useful and illuminating experience. Joining an editorial board enables scholars to see the “other side” of publishing. As with every aspect of academic life, start by doing your research on the different opportunities that exist. What is it about being a board member that interests you? What would you like to do and learn during your tenure? In turn, what can you bring to the role in terms of experience? Although board members do have obligations to fulfill in their position, each individual usually decides how involved they actually are. Levels of engagement can vary a lot depending on the context of your own work and where you are in your career. Appealing to board members If you currently sit on a journal’s editorial board, you likely know a bit about maintaining an engaged and well-rounded board. Building a positive reputation for your journal and its working environment helps with both recruitment and retention of board members. Academia is a demanding and time-consuming profession. Scholars have many different responsibilities and a limited number of hours they can work. At the same time, sitting on an editorial board is an important role that many take on because of the experience and opportunities it brings with it. It’s thus important to build an advisory board that is well-managed and effective. Encouraging open discussion and fostering a collegial environment where people’s ideas are valued allows scholars to bring their best selves to the work. Create a collegial atmosphere that encourages board members to contribute ideas.  Current board members can help with recruitment by connecting with their own networks when opportunities are available. If members enjoy the work they are doing, they are more likely to stay on, as well as recommend others to join. Last updated on: July 25, 2026
Zoë GrossZoë Gross
Zoë Gross

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