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Prof. Dr. Kiril Anguelov
Management and Business Information Systems, Technical University of Sofia, Sofia, Sofia-Grad, Bulgaria
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Academic Career Length
11Years (2016-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications27 May 2021
Conference Paper
KAKiril Anguelov
Kiril AnguelovThis paper outlines the main opportunities for implementing the methods and developed ICT solutions of an artificial intelligence (AI) in the field of Enterprise Resource Planning Systems. The author explores different possible implementations of AI in the ERP such as: process of Implementation of ERP; Customer relationship management; Supply Chain Management; Production; Product Lifecycle Management; Human Resources; Financial Management, etc.
13 November 2019 in AIP Conference Proceedings
Conference Paper
Speaking for artificial intelligence and mathematics, some will say that they are two different fields. But we can assure you that mathematical models are its foundations, especially the main subset machine learning. Investigating these models and algorithms, we have the possibility to predict the abilities and limitations of artificial intelligence. Utilization of super-recursive algorithms for proving theorems, makes many such systems complete and decidable. Here we will discuss the main differences of recursive and super-recursive algorithm in particular Turing machine and inductive Turing machine. Our main statement is that artificial intelligent based on inductive Turing machine is much more powerful and will greatly enhance machine learning capabilities. As theorem proving and logic used commonly in artificial intelligence, these results will have a very important role in its implications.
15 August 2016
Conference Paper
KAKiril Anguelov
Kiril Anguelov
Dimo Georgiev StoilovThe paper presents methodological approach for asset management of electric distribution company through a policy, built upon the Risk based asset management. Here are shown the indicators by which the reliability of a distribution network is estimated and consequent cost of failure of equipment and missed benefits are determined. Using the described methodology the distribution companies could perform: qualitative and quantitative assessment of the risk, determination of measures to reduce the risk, and asset management based on the wise policy of the maximum acceptable risk.
15 August 2016
Conference Paper
KAKiril Anguelov
Kiril AnguelovMAMiglena Dimitrova Angelova
Miglena Dimitrova AngelovaThe present paper represents methodological approach for effectiveness and efficiency of IT project management, part of a comprehensive research in Bulgarian high-tech companies. Traditional and Agile methods are explored on the base of different developed indicators establishing wasted time and increased costs for the final product and result, due to the imperfection in IT project management of the companies.
30 March 2020 in Entrepreneurship and Sustainability Issues
Journal Article
KAKiril Anguelov
Kiril AnguelovTSTsvetana Stoyanova
Tsvetana Stoyanova
Rima TamošiūnienėEntrepreneurship and Sustainability Issues is a peer-reviewed journal which publishes original research papers and case studies
1 June 2018
Conference Paper
The concept decision-making AI Bots is introduced. The modern Agile systems and structures are analyzed. A methodological approach of the study using the concept of Cynefin Framework in agile decision making of AI bots is proposed. The Cynefin transitions between the different domains are illustrated through the rotated Snowdon's v45° unfolded cylindric overlapping version. The cycle of adaptive change is used to analyze the effect of Cynefin Framework in the agile decision-making system of AI Bots. Analysis of the results, as well as relevant discussion and conclusions are proposed.
About Me
My research interests include digital transformation, business process reengineering, artificial intelligence in management, algorithmic management, organizational change, innovation management, and strategic management. I am particularly interested in the impact of intelligent technologies on managerial decision-making, organizational governance, and the future of work.
My work explores how AI-driven systems, algorithms, and digital platforms are transforming managerial practices, organizational structures, employee autonomy, performance management, and workplace relations. A significant part of my research focuses on the opportunities and challenges associated with the implementation of algorithmic management and data-driven decision-making systems in contemporary organizations.
At the intersection of engineering, management, and digital technologies, I investigate business process modeling and reengineering, intelligent management systems, digital transformation strategies, and the application of artificial intelligence to organizational and managerial challenges. I examine how advanced technologies, data-driven approaches, and process innovations can improve organizational effectiveness, support managerial decision-making, and facilitate sustainable organizational development in increasingly complex and technology-intensive environments.