Carlos Mario Meléndez, Ph.D., is a Professor at Universidad del Atlántico (Colombia), where he leads the Laboratory of Molecular Biology (LIBM) and the Research Group in Organic and Biomedical Chemistry. He earned his B.Sc. and Ph.D. in Chemistry from the Industrial University of Santander (UIS), Colombia. His research spans medicinal chemistry, organic synthesis, biological and analytical chemistry, computational chemistry, and AI applied to biomedical research. His current interests include antibacterial agent discovery, quorum sensing inhibition, antimicrobial resistance, FTIR-based bacterial characterization, molecular docking and dynamics simulations, cheminformatics, and AI-driven models for resistance prediction and target identification. Dr. Meléndez has extensive experience designing, synthesizing, and biologically evaluating bioactive molecules, and integrating experimental and computational approaches for drug discovery. He has led multidisciplinary projects involving natural products, antimicrobial compounds, spectroscopy, and machine learning. He serves as principal investigator and supervisor of undergraduate, master's, and doctoral research, and has authored numerous peer-reviewed publications in medicinal, analytical, and computational chemistry, published internationally and presented at scientific conferences worldwide.
Carlos Mario Meléndez, Ph.D., is a Professor at Universidad del Atlántico (Colombia), where he leads the Laboratory of Molecular Biology (LIBM) and the Research Group in Organic and Biomedical Chemistry. He earned his B.Sc. and Ph.D. in Chemistry from the Industrial University of Santander (UIS), Colombia. His research spans medicinal chemistry, organic synthesis, biological and analytical chemistry, computational chemistry, and AI applied to biomedical research. His current interests include antibacterial agent discovery, quorum sensing inhibition, antimicrobial resistance, FTIR-based bacterial characterization, molecular docking and dynamics simulations, cheminformatics, and AI-driven models for resistance prediction and target identification. Dr. Meléndez has extensive experience designing, synthesizing, and biologically evaluating bioactive molecules, and integrating experimental and computational approaches for drug discovery. He has led multidisciplinary projects involving natural products, antimicrobial compounds, spectroscopy, and machine learning. He serves as principal investigator and supervisor of undergraduate, master's, and doctoral research, and has authored numerous peer-reviewed publications in medicinal, analytical, and computational chemistry, published internationally and presented at scientific conferences worldwide.