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Kokova Valentina IosifovnaView profile

Senior Lecturer

• Computer Science
• Software Engineering
• Database Systems
• +3 more

Kokova Valentina Iosifovna is a Senior Lecturer in the Department of Applied Informatics at the Natural Sciences and Humanities School of the Khakass Technical Institute (branch of Siberian Federal University). She teaches subjects such as Operating Systems , Databases , Software Engineering , and IT Project Management . Education: Graduated from Moscow Institute of Railway Engineers in 1977 with a qualification in Electrical Engineering. Advanced Training: Completed multiple courses at Sberbank Corporate University and Siberian Federal University's Institute of Continuous Education (2020–2022). Her research interests focus on Applied Informatics , specifically Database Systems , Programming Languages , and Regulatory Frameworks in IT . She has accumulated 47 years of total work experience, with 34 years dedicated to her current specialty. Scientific Awards: Letter of thanks from KhTI – branch of SFU (2016) Letters of thanks from Republican Center for Continuing Education (2016, 2018) Letter of thanks from Khakassia's Ministry of Education and Science (2019) Letters of gratitude from Techno-Creativity of Khakassia (2019, 2021, 2023) Letters for Scientific Potential of Khakassia (2020, 2022, 2024) Recognition for organizing All-Russian School Olympiad with Rosseti (2021–2024) Certificate of Honor from Khakassia's Ministry of Education and Science (2023)

Pável Pereira CaladoView profile

Associate Professor

• Information Retrieval
• Information Extraction
• Machine Learning
• +3 more

Pável Pereira Calado is an Associate Professor at Instituto Superior Técnico (University of Lisbon) and a researcher at INESC-ID Lisboa. He holds a PhD in Computer Science from Federal University of Minas Gerais (2004) and an MS in Computer Science from the same institution (2000). His academic career focuses on Information Retrieval, Information Extraction, and Machine Learning applications in Digital Libraries and Recommendation Systems. Education: PhD & MS in Computer Science (UFMG, Brazil) Current roles: Associate Professor (since 2004) and INESC-ID researcher Teaching: Databases, Information Retrieval, and Data/Information Management His research explores evidence combination techniques for Web search, keyword-based querying in structured databases, and machine learning applications in information systems. He has contributed to major conferences and journals in these areas. Scientific Recognition: Recipient of two Best Student Paper awards Professional Activities: Researcher in INESC-ID Lisboa's IDSS group Participant in projects like GoLocal, DataStorm, SinteliGIS, EuDML, GERINDO, AMYRI

Thierry SprietView profile

Associate Professor

• Educational Technology
• Digital Pedagogy
• Learning Analytics
• +5 more

Thierry Spriet is an Associate Professor in Computer Science at Avignon University, where he has served since September 1994. He currently holds multiple significant roles including Vice-President for Digital Technology and Educational Innovation, and Head of the CMI Computer Science degree and master's program since its creation in September 2018. His career demonstrates a strong commitment to academic excellence and educational innovation, with a focus on developing student creativity and 360° curiosity to position learners at the heart of future innovation. Spriet earned his DEA in Mathematics and Computer Science from the Faculty of Sciences of Luminy, Aix-Marseille II in 1987, followed by a Doctorate in Computer Science from the University of Avignon and the Pays de Vaucluse in January 1993. His academic journey includes positions as ATER at IUT d'Aix-en-Provence (1988-90, 1991-92) and UAPV (1993-94) before his permanent appointment. His research focuses on the intersection of educational technology and pedagogical innovation, with particular emphasis on hybrid and flipped classroom approaches, learning analytics, and pedagogical dashboards. He has pioneered the BoardZ pedagogical dashboard system to track student engagement through Learning Management System data. His work explores how institutional strategies impact pedagogical transformation, with numerous publications examining post-pandemic digital education experiences and competency-based approaches in higher education. His teaching philosophy centers on design thinking approaches to integrative projects that span multiple semesters. Analysis of Spriet's scholarly output reveals a clear evolution from foundational work in natural language processing (1998-2000) to contemporary research in educational technology (2015-2025). His recent publications demonstrate increasing emphasis on data-driven pedagogical approaches, with a strong focus on practical applications of technology to enhance teaching effectiveness and student outcomes in higher education settings. Spriet has demonstrated leadership in representing Avignon University in national educational initiatives including Unisciel (Digital University in Sciences), UOH (Open University of Humanities), and FIED (Inter-University Federation for Distance Education). He serves on the steering committee for the national 'digital platforms' project and is a founding member of VPNUM (association of digital vice-presidents), ADSI (association of Information Systems Directors), and MoodleMootFr. As Head of the CMI Computer Science program, he oversees a curriculum designed to produce future researchers and entrepreneurs through integrative project modules spanning four semesters. He also teaches the database modeling module using active teaching approaches that combine flipped classroom and peer learning methodologies, positioning students as active participants in their learning process.

Adrian BesimiView profile

Professor

• Data Analytics
• Artificial Intelligence
• Machine Learning
• +6 more

Adrian Besimi is a Full Professor and Dean at the Faculty of Contemporary Sciences and Technologies at South East European University (SEEU), Tetovo, Macedonia. He holds a PhD in Computer Science from SEEU (2013) and an MSc in Computer Science from Indiana University-Purdue University Indianapolis (IUPUI, 2007). His research spans Data Analytics, Artificial Intelligence, Cryptocurrencies, and Educational Technology , with a focus on predictive modeling, AI-driven research tools, and technology adoption in higher education. He has published extensively on these topics, including works on federated learning, hate speech detection, and cryptocurrency price prediction. PhD in Computer Science (SEEU, 2013) MSc in Computer Science (IUPUI, 2007) BSc in Computer Science (SEEU, 2005) His recent publications highlight trends in AI applications for education , medical data sharing, and blockchain analytics. He has served as Pro-Dean and Teaching Assistant at SEEU, with prior roles in software development and web design at SEEU, IUPUI, and Phalanx ICT. He collaborated on projects funded by the German Embassy and contributed to disaster response systems, data-driven journalism, and peer assessment models. Contact: a.besimi@seeu.edu.mk

Ashley McClenaghanView profile

Lecturer

• Software Engineering
• Blockchain Technology
• Artificial Intelligence
• +5 more

Dr. Ashley McClenaghan serves as a Lecturer in Software Engineering within the Computing Science and Mathematics Division at the University of Stirling's Faculty of Natural Sciences. With over 25 years of combined academic and industry experience, they hold both a PhD and BSc in Computing Science and have collaborated with major institutions including Morgan Stanley, JP Morgan Chase, HSBC, Philips Research, and HP Labs. Research interests focus on engineering cutting-edge data technologies into software stacks, including graph databases, distributed ledgers, and large language models. Key projects include Social Credit Fintech (tokenization on Convex blockchain), Econome AI (real-time web analysis), ADAPT (treatment pathway recommendations using XGBoost and SentenceTransformers), Data Commons Scotland (federated graph databases), and Waste Matters Scotland (accessible waste management data). Research is organized under the Digital Society and Culture and Health & Behaviour programmes within the Data Science and Intelligent Systems research group. Current work emphasizes practical applications of blockchain, AI-driven data science, and semantic search technologies to solve real-world problems in finance, healthcare, and public sector data accessibility.

Anníbal SoderoView profile

Assistant Professor

• Supply Chain Management
• Logistics
• Information Technology Management
• +7 more

Anníbal Sodero is an Assistant Professor at The Ohio State University's Max M. Fisher College of Business, specializing in Supply Chain Management and Logistics. His research bridges Economics, Marketing, and Information Systems, focusing on technology management, logistics innovation, and demand planning. PhD in Supply Chain Management, Arizona State University M.Sc. in Supply Engineering and Logistics, University of Warwick B.Sc. in Computer Sciences, Federal University of Minas Gerais (UFMG) His expertise spans entrepreneurship , database design , e-commerce , and empirical industrial organization . He teaches project-based courses in logistics technology, supply chain management, and transportation systems. Dr. Sodero has served as Associate Editor for Journal of Operations Management , Decision Sciences Journal , and International Journal of Physical Distribution and Logistics Management , and as a member of the Editorial Review Board for Journal of Supply Chain Management and Journal of Business Logistics . Founder of Ad Hoc Informática (now part of Benner Sistemas) Published in top journals including Supply Chain Management Review and Journal of Business Logistics

• Agent Technology
• Artificial Intelligence
• Autonomous Driving
• +9 more

Prof. Dr.-Ing. habil. Dr. hc Sahin Albayrak is a distinguished academic and entrepreneur at the Technical University of Berlin , where he founded and directs the Distributed Artificial Intelligence Laboratory (DAI Laboratory) . He leads the Agent Technologies in Business Applications and Telecommunications research group and serves as founding member of Deutsche Telekom Laboratories (2004) and European Center for ICT (EICT) (2005). As initiator of Connected Living e.V. (2009) and managing director of German-Turkish Advanced Research Center for ICT (2012), he bridges international collaborations. He also founded IOLITE GmbH (2014) and other startups. Research Focus: Agent technology, autonomous driving, smart cities, cyber security, machine learning, and AI applications in energy systems Awards: Federal Cross of Merit (2014), multiple Best Paper Awards Leadership: Director of DAI Laboratory, head of research group at TU Berlin His 20+ recent publications (2022-2025) demonstrate expertise in agent-based architectures , smart mobility solutions , context-aware computing , and AI-driven security systems . Notable trends include integrating large language models into database interfaces, optimizing multi-agent coordination for logistics, and advancing explainable AI through feature attribution frameworks. Scientific Contributions: Recipient of Germany's Bundesverdienstkreuz for German-Turkish cooperation Best Paper Award at Smart Grid Architectures conference

Hegler TissotView profile

Assistant Professor

• Health Informatics
• Data Science
• Machine Learning
• +11 more

Hegler Tissot serves as an Assistant Teaching Professor in the Department of Information Science within Drexel University's College of Computing and Informatics. With over 30 years of industry and academic experience, he specializes in designing large-scale database systems and applying data science methodologies across Financial, Telecom, and Healthcare sectors. His educational background includes: PhD in Computer Science from Universidade Federal do Paraná MS in Production Engineering from Universidade Federal de Santa Catarina BS in Computer Science from Universidade Federal do Paraná Tissot's research centers on Health Informatics, where he leverages Machine Learning, Natural Language Processing, and Knowledge Representation to extract clinical evidence from patient data. His work focuses on developing predictive models and risk assessment tools to enhance healthcare services, drawing from 15+ years of healthcare industry experience. He applies data mining and visualization techniques to translate complex clinical datasets into actionable medical insights. No scientific awards or honors were specified in the source material. Regarding academic mentorship and research funding, the available documentation does not detail student supervision, grant acquisitions, or sponsored projects. Professional infrastructure such as laboratories or research teams was not referenced in the provided materials.

Stephen MezykView profile

Professor

• Radiation Chemistry
• Advanced Oxidation/Reduction Processes for Water Treatment
• Free-Radical Kinetics and Mechanisms
• +4 more

Stephen Mezyk is a Professor of Chemistry at California State University, Long Beach (2009–present) and holds concurrent appointments at Idaho National Laboratory (2025–), Notre Dame Radiation Laboratory (1986–) and Brookhaven National Laboratory (2002–). His research exploits pulse and steady-state radiolysis to quantify free-radical kinetics governing (i) destruction of pharmaceuticals, PFAS and nano-plastics in advanced water-treatment schemes, (ii) radiation stability of actinide/lanthanide separation ligands for closed nuclear fuel cycles, and (iii) redox mechanisms in chemical carcinogenesis. Education Ph.D. in Chemistry, University of Melbourne, Australia, 1989 Research Interests Mezyk’s group operates at the interface of physical chemistry and environmental/nuclear engineering. Using transient absorption and competitive kinetic techniques they map absolute rate constants for reactions of hydrated electrons, hydroxyl and sulfate radicals with trace organics, actinide complexes and polymeric debris. This fundamental database underpins mechanistic models for UV- and radiation-driven advanced oxidation/reduction processes (AOPs/ARPs) aimed at direct potable reuse of wastewater and for safeguarding solvent-extraction flowsheets in advanced nuclear fuel reprocessing. Recent work has expanded to photochemical fragmentation of polyethylene micro- and nanoplastics in natural and engineered aqueous systems, revealing rapid conversion of visible fragments into colloidal “incognito” species detectable only by Raman and LC-MS techniques. Publication Trends Over the past five years Mezyk has averaged >10 peer-reviewed papers annually, 70% appearing in high-impact journals (Environmental Science & Technology, ACS Environmental Au, Dalton Transactions, Physical Chemistry Chemical Physics). The 2024-25 output is dominated by studies coupling temperature-dependent kinetics with computational modelling to predict long-term behaviour of both emerging water contaminants and nuclear-separation ligands under gamma or alpha irradiation. Scientific Awards & Recognition No specific awards are listed in the supplied material; inclusion in multiple DOE-funded Energy Frontier Research Centers and continuous federal funding (NSF, DOE) attest to peer recognition. Advising & Grants Mezyk has mentored >25 graduate students and post-docs, many now co-authors on recent papers (indicated by asterisks). Current and recent funding embraces NSF-CBET for “CAS-MNP: Radical-induced Weathering of Micro- and Nanoplastics”, DOE-NE for “Radiation Chemistry of Trivalent Actinide Separations”, and OCWD/Water Research Foundation projects on methyl nitrate formation during UV-AOP treatment for potable reuse. Laboratories & Teams On campus he directs the Radiation & Free-Radical Kinetics Laboratory (HSCI-358) equipped with 10 MeV electron LINAC and 60-Co gamma source for pulse and steady-state radiolysis. Collaborative access to Notre Dame’s 7-MeV Tandetron and Brookhaven’s LEAF facility expands transient kinetic coverage from ns to ms timescales. A growing cohort of INL colleagues supports work on spent-fuel dissolution chemistry under the DOE-NE SEPST program.

Apostol SlavchevView profile

Professor

• Training in sprint and hurdle running
• Specialized diversity in athletics
• Sports science
• +5 more

Professor Apostol Slavchev serves as Vice-Rector for Academic Affairs at the Vasil Levski National Sports Academy, where he holds a professorship in the Department of Athletics within the Faculty of Pedagogy. With over four decades of academic service, he has held leadership roles including Dean of the Faculty of Education (2008-2016) and membership on the Academic Council since 2007, demonstrating sustained institutional commitment to advancing sports education and athletic training methodologies. His academic foundation includes doctoral studies completed in 1998 with a dissertation on 400m hurdle training optimization, complemented by medical education at Sofia's G. Dimitrov State Medical University (1978-1982). His scholarly journey reflects a unique integration of medical science with athletic specialization: Doctorate in Sports Training Methodology (1998) Medical University Studies (1978-1982) Polytechnic High School Diploma (1972-1976) Slavchev's research spans sprint and hurdle training mechanics , athletics officiating systems , and inclusive athletic programming for diverse populations including children and Special Olympics participants. His work bridges theoretical sports science with practical coaching applications, particularly in developing technical proficiency in short-distance events through biomechanically-informed training protocols. The integration of mathematical modeling in sports ranking systems demonstrates his interdisciplinary approach to athletic administration. His 150+ publications reveal consistent focus on athletics pedagogy and technical officiating , with recent works emphasizing digital educational tools and longitudinal performance analysis. The trajectory shows evolving specialization from foundational coaching manuals toward sophisticated biomechanical analysis and institutional management systems, reflecting both deepening expertise and expanding administrative responsibilities. As an academic advisor, Slavchev has supervised four doctoral candidates to successful dissertation completion, with research concentrated in athletic training methodology. His institutional roles include directing postgraduate training for coaches and serving on the editorial board of the "Athletics & Science" journal, demonstrating commitment to knowledge dissemination. Slavchev founded and chairs the KLASA athletics club at the National Sports Academy while leading the Bulgarian Athletics Federation's judges committee since 2004. His practical coaching legacy includes developing over 100 athletes, with multiple national champions in hurdle events, demonstrating effective translation of academic research into competitive success.

Semih ÇalView profile

Assistant Professor

• Wireless Communication Networks
• Internet of Things (IoT)
• Drone Networks
• +4 more

Semih Çal serves as an Assistant Professor in the Department of Engineering, Computer Science, and Physics at Otterbein University, specializing in wireless systems and distributed computing. His research bridges theoretical algorithms with practical IoT and drone network applications. Education: Ph.D. in Computer Science from Texas Tech University (2024) M.S. in Computing and Information Systems from Youngstown State University (2021) B.S. in Computer Software Engineering Technology from Sam Houston State University (2017) Dr. Çal's work centers on energy-constrained distributed systems, with emphasis on federated learning architectures for drone swarms and IoT edge networks. His expertise spans Lyapunov optimization for resource allocation, reliability-aware task offloading, and non-parametric statistical methods for database query processing. Current investigations focus on fault tolerance in reinforcement learning frameworks and knowledge distillation techniques for bandwidth-limited aerial networks. Publication analysis (2020-2024) reveals a dual-track research trajectory: 75% of recent work addresses drone/IoT networking challenges using federated learning and optimization theory, while 25% explores statistical foundations of database error estimation. Key thematic clusters include UAV-aided mobile edge computing, bootstrap sampling methodologies, and reliability engineering in distributed AI systems. Dr. Çal maintains active industry engagement through prior Turkish technology sector experience and current academic-industry collaborations. No formal advising roles or laboratory affiliations are documented in available materials.

• Public Law
• Electoral Law
• Municipal Law
• +5 more

Albina Omarovna Gadzhieva serves as First Deputy Dean of the Faculty of Law, Director of the Institute for Research in National and Comparative Law, and Associate Professor in the Department of Public Law at the National Research University Higher School of Economics (HSE). She also serves as Scientific Director of the educational program in Pharmaceutical Law and Healthcare. Joining HSE in 2020, she has accumulated 4 years of scientific and teaching experience at the university. Gadzhieva holds a Candidate of Law degree (2023) with her dissertation focusing on Active electoral right in the context of the use of digital technologies (on the example of the city of Moscow) . She graduated from Moscow State Law Academy in 2002 with a specialty in Jurisprudence. Her additional education includes a program in Management in the field of education: current management issues from Sirius University of Science and Technology (2023). Her research spans multiple critical areas including public law, electoral law, municipal law, pharmaceutical law, healthcare regulation, digital technologies in law, and artificial intelligence applications in healthcare. Her work demonstrates a strong connection between theoretical legal frameworks and practical implementation in modern governance. Her publications reveal a consistent focus on how digital transformation impacts traditional legal structures, particularly in electoral processes and healthcare systems. Gadzhieva's extensive recognition includes multiple honors from the President of the Russian Federation, the Moscow City Government, electoral commissions, and HSE University. These awards highlight her significant contributions to legal scholarship, electoral administration, and public service. Her practical experience in electoral processes is particularly notable, with numerous awards related to electoral system development and implementation. She teaches courses in Electoral Law and Electronic Forms of Democracy at both bachelor's and master's levels. Her professional trajectory shows a transition from practical government service to academic leadership, bringing valuable real-world experience to her teaching and research. She has participated in numerous high-profile events including the St. Petersburg International Legal Forum and has collaborated with various government bodies on legal reform initiatives.

• Medical Informatics
• Artificial Intelligence
• Deep Learning
• +3 more

David Bani-Harouni is a researcher at the Chair of Computer Aided Medical Procedures at Technische Universität München (TUM). His work focuses on Medical Informatics , Artificial Intelligence , and Deep Learning , with an emphasis on Clinical Decision Support and Medical Image Analysis . Research Interests : Large Language Models (LLMs), Vision Language Models (VLMs), interpretability in deep learning, multimodal clinical decision support, and medical image analysis. Teaching : He contributes to lectures and practical courses such as Computer Aided Medical Procedures I , Medical Augmented Reality , and Deep Learning for Medical Applications . Publications : His research spans reinforcement learning for clinical decision-making, multimodal operating room datasets, toxin prediction systems (e.g., ToxNet), and graph convolutional networks for intoxication prediction. Contact : david.bani-harouni@tum.de

• Artificial Intelligence
• Machine Learning
• Data Analysis
• +12 more

Dmitry Vladimirovich Alexandrov serves as Professor at the Faculty of Computer Science, Department of Software Engineering at the National Research University Higher School of Economics (HSE) and heads the Research and Educational Laboratory of Cloud and Mobile Technologies. With 24 years of scientific and teaching experience, he joined HSE in 2014 and has established himself as a leading expert in multiple computer science domains. His academic credentials include Doctor of Technical Sciences (2010) and the academic title of Professor (2012). His educational foundation was built at Vladimir State University, where he graduated in 1997 with specialty in "Computers, complex systems and networks" and earned his Candidate of Technical Sciences degree in 2000. Dr. Alexandrov's research spans artificial intelligence, machine learning, mobile application development (particularly iOS), software engineering, and database technologies. His work bridges theoretical research with practical applications in cloud computing, mobile technologies, and intelligent systems development. His recent publications reveal a strong focus on practical AI applications in software engineering, including code generation using large language models, service mesh optimization, face recognition algorithms, and database technologies. This research demonstrates interdisciplinary collaboration across computer science subfields with real-world applications. HSE University Honorary Diploma (February 2025) Gratitude from the Faculty of Computer Science, National Research University Higher School of Economics (July 2023) Dr. Alexandrov actively supervises students at all academic levels, from bachelor's theses to doctoral research. He has secured significant research funding including the Grant of the President of the Russian Federation for state support of scientific research by young Russian scientists-doctors of sciences. As laboratory head, he directs research on cloud and mobile technologies, oversees scientific seminars, and leads collaborative projects with industry partners. His laboratory recently developed and registered with Rospatent software for visualization and markup of digital medical images in DICOM format, developed in partnership with the N.V. Sklifosovsky Research Institute of Emergency Medicine.

Elisa BertinoView profile

Professor

• Information Security
• Database Systems
• Privacy and Access Control
• +6 more

Elisa Bertino is the Samuel D. Conte Professor of Computer Science at Purdue University, where she also directs the Purdue Cyberspace Security Lab (Cyber2Slab) and serves as Research Director at CERIAS. Since joining Purdue in January 2004, her work has integrated rigorous theory with practical solutions across information security, database systems, and emerging cyber-physical domains. Education Ph.D. in Computer Science, University of Pisa (1980) Research Interests Professor Bertino’s research portfolio is exceptionally broad, spanning information security and assurance , database and data mining technologies , and AI-driven cybersecurity . She pursues foundational advances in access-control models (RBAC, ABAC, trust negotiation), secure data publishing and broadcast protocols for XML and streaming data, privacy-preserving analytics through differential privacy and secure multi-party computation, and zero-trust architectures for 5G/6G and software-defined networks. Application domains include secure mobile and IoT ecosystems, medical informatics, and humanities data. Recent Publication Trends Her 2024–2025 publications reveal a strategic pivot toward next-generation network security (5G/6G, SDN/NFV), trustworthy AI (federated learning, transformer-based malware analysis), and privacy technologies (differential privacy, homomorphic encryption). A recurring theme is the rigorous integration of AI techniques with cryptographic and systems-level defenses to achieve scalable, privacy-preserving security solutions. Scientific Awards & Honors IEEE Fellow ACM Fellow IEEE Computer Society Technical Achievement Award (2002) IEEE Tsutomu Kanai Award (2005) ACM Athena Lecturer Award (2019) Kristian Beckman Award (2020) IEEE 2021 Innovation in Societal Infrastructure Award Advising & Grants Professor Bertino has mentored a large cohort of doctoral students and post-doctoral researchers. Recent externally funded projects include NSF “Privacy-Enhanced Secure Data Provenance” (2011-2016), NIST “Advancing Commercial Participation in the NSTIC Ecosystem” (2012-2013), and Sypris Electronics “Security Techniques for Smart Mobile Devices” (2012). Laboratories & Teams She leads the Cyber2Slab (Cyber Space Security Lab), a vibrant research group investigating insider-threat mitigation, IoT and drone security, digital identity management, cloud data protection, and AI-assisted defense mechanisms. The lab collaborates extensively with federal agencies, industry partners, and international research consortia such as the Data Analytics and Information Science International Technology Alliance (DAIS ITA).