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Giacomo CalzolariView profile

Professor

• Industrial Organization
• Competition Policy
• Artificial Intelligence
• +6 more

Giacomo Calzolari is a Full-time Professor of Economics at the European University Institute (EUI) in Florence, Italy, and serves as Provost for Research and External Relations. He holds a Ph.D. from the University of Toulouse. His research focuses on Industrial Organization, Competition Policy, Artificial Intelligence, and Banking Regulation, with notable contributions to understanding algorithmic pricing, collusion, and regulatory frameworks. Education: Ph.D. in Economics from the University of Toulouse. Research Interests: Artificial Intelligence and Market Dynamics Competition Policy and Antitrust Economics Algorithmic Pricing and Collusion Banking Regulation and Supervision Behavioral and Experimental Economics Publications: Recent work includes studies on AI-driven markets, algorithmic collusion, and regulatory policy. His research emphasizes the intersection of technology and competition, with over 50 publications in top-tier journals like the American Economic Review and International Journal of Industrial Organization. Awards: Recognized with the 'Best Paper Award' from the Association of Competition Economics (2013) and the 'Young Economist Award' (2005). Advisory Roles: Advises the European Commission on competition policy and the European Parliament on AI in financial markets. Serves as Editor of the International Journal of Industrial Organization and European Economy - Banks and Regulation. Research Groups: Leads projects on digital transformations, technological change, and AI's impact on competition. Supervises numerous graduate students and collaborates with institutions like the Centre for Economic Policy Research (CEPR).

Bärbel Finkenstädt RandView profile

Tutor

• Statistical Methodology
• Machine Learning
• Bayesian Inference
• +6 more

Bärbel Finkenstädt Rand is a Senior Tutor at the Warwick Medical School , University of Warwick, with extensive research contributions at the intersection of statistics, machine learning, and biomedical sciences. Her work focuses on developing advanced methodologies for analyzing temporal and spatio-temporal data, particularly in circadian rhythms and disease dynamics. Research Themes : Bayesian inference, Hidden Markov Models, circadian rhythm stability, transcriptional bursting, and wearable sensor data analysis. Collaborations : Chronotherapy Group at Warwick, Université Paris-Saclay, and interdisciplinary teams across medicine, genetics, and computational biology. Publications reveal a strong emphasis on circadian health monitoring, gene expression dynamics, and epidemic modeling using stochastic frameworks. Her recent work prioritizes personalized medicine applications through telemonitored biomarkers and IoT platforms . Methodological Innovations include spline-based HMMs, distributed delay systems, and harmonic modeling for nonstationary time series. Applications span oncology, sleep medicine, and population ecology.

Marti G. SubrahmanyamView profile

Professor

• Derivatives Markets
• Corporate Finance
• International Finance
• +6 more

Marti G. Subrahmanyam is the Charles E. Merrill Professor of Finance, Economics and International Business at the Leonard N. Stern School of Business, New York University , and a Global Network Professor of Finance at NYU Shanghai . He holds a PhD in Finance and Economics (MIT, 1974) , a post-graduate diploma from the Indian Institute of Management, Ahmedabad (1969) , and a B.Tech. in Mechanical Engineering from IIT Madras (1967) , where he has also served as a visiting professor. His career spans over five decades, with editorial roles at top journals like Journal of Finance and Review of Financial Studies . Research Focus : Derivatives markets, corporate finance, fixed income, market microstructure, ESG investing, and quantitative easing. Academic Leadership : Founded NYU Stern and NYU Shanghai Undergraduate Honors Programs, served on over 85 doctoral committees, chaired 35. Scientific Awards : New York University Distinguished Teaching Medal (2003) Anneliese Maier Award (2016) - First economist to receive this honor Distinguished Alumnus Awards from IIT Madras (2004) and IIM Ahmedabad (2011)

• Trust and Institutional Economics
• Entrepreneurship in Africa
• Artificial Intelligence in Healthcare
• +5 more

Roles & Affiliations: King Omeihe is a Senior Lecturer at the School of Business and Creative Industries, University of the West of Scotland, and serves as UoA 17 Associate Research Lead for People, Culture, and Environment. He holds external roles including Chair of African Studies at the British Academy of Management and Chair of Entrepreneurship in Minority Groups at the Institute for Small Business and Entrepreneurship (ISBE). He advises on African economic policy and chairs several parliamentary groups in Scotland. Education: PhD from University of the West of Scotland, MBA from University of Aberdeen, and a diploma from University of Cambridge. Research Interests: Focuses on trust institutions, entrepreneurship in Africa, and the intersection of AI with societal challenges. Recent works include Trust and Market Institutions in Africa (2023), Qualitative Research Methods for Business Students (2024), and Handbook of African Studies (2025). Explores institutional economics, ethical AI applications, and decolonizing business education. Articles Trends: Recent publications emphasize AI ethics in healthcare, institutional resilience in developing economies, and leadership in complex systems. Key themes include sustainable development goals (SDGs), cross-cultural entrepreneurship, and policy interventions for minority entrepreneurs. Awards: Includes the 2025 UWS Innovation Teaching Award, 2022 Entrepreneurial Supporter of the Year, and multiple recognitions for teaching excellence. His work has been highlighted by Bright Red Spark for shaping enterprise education. Grants & Advising: Advises startups, policymakers, and global bodies like UNCTAD. Leads initiatives such as the MSc Entrepreneurship programme and collaborates with organizations like Marcel Advisory and the West African Transitional Justice Centre. Active in cross-party policy groups addressing social enterprise and racial equality. Labs & Teams: Co-leads the Centre for African Research on Enterprise and Economic Development (CAREED) and contributes to Emerald’s African Context of Business and Society as Editor-in-Chief. Oversees the UWS BME Staff Network and Academic Integrity Panel.

Christian KrupitzerView profile

Professor

• Food Informatics
• Self-adaptive Software Systems
• Machine Learning
• +4 more

Jun.-Prof. Dr. Christian Krupitzer is a Tenure Track Professor in Food Informatics at the University of Hohenheim's Institute of Food Science and Biotechnology, part of the Faculty of Natural Sciences. He leads the Department of Food Informatics and is a member of the Computational Science Hub (CSH). His research focuses on self-adaptive software systems, machine learning (especially edge computing), IoT technologies, and software engineering applied to food processing and agricultural systems. Education: PhD in Business Information Systems (Dr. rer. pol.), University of Mannheim (2018) M.Sc. and B.Sc. in Business Information Systems, University of Mannheim (2010–2012) High School Diploma (Abitur) from Wilhelmi-Gymnasium Sinsheim (2007) Research Interests: Krupitzer’s work integrates computational methods with food science, emphasizing adaptive systems for food quality monitoring, IoT in agriculture, and machine learning for predictive analytics. He explores edge computing’s role in real-time decision-making and secure group communication schemes for IoT networks. Publications: His recent work spans predictive maintenance in Industry 4.0, digital twins in food systems, and blockchain applications in supply chain authentication. The articles highlight trends in interdisciplinary approaches combining AI, IoT, and domain-specific challenges in food production and logistics. Awards: No scientific awards explicitly listed in the provided materials. Grants & Advising: While specific grants are unmentioned, his roles as department head and tenure-track professor suggest involvement in research funding. No formal advisee list provided, though his team includes postgraduate researchers like Dana Jox, Daniel Einsiedel, and others. Labs & Teams: Leads the Food Informatics department and collaborates with the Computational Science Hub. His team focuses on developing innovative solutions for food systems through computational methods.

John LeahyView profile

Professor

• Macroeconomics
• Monetary Economics
• Economic Theory
• +3 more

John Leahy is the Allen Sinai Professor of Macroeconomics and Public Policy at the University of Michigan, holding dual appointments in the Department of Economics (College of Literature, Science, and the Arts) and the Gerald R. Ford School of Public Policy. As Chair of the Economics Department, he focuses on macroeconomic theory, monetary policy, and behavioral economics, particularly rational inattention models. His research emphasizes how cognitive limitations and information processing affect economic decisions, contrasting classical economic assumptions. Leahy has held positions at Harvard, NYU, and Boston University, and served as Coeditor of the American Economic Review and Editor of the American Economic Journal: Macroeconomics. He consults with Federal Reserve Banks, advocating for data-driven, question-first research methodologies. His work bridges theoretical rigor and practical applications, influencing policy analysis and academic discourse. Education: PhD in Macroeconomics from Princeton University; MSFS from Georgetown University; BA in Math and History. His research spans macroeconomic policy, structural change, and behavioral models of decision-making, with recent focus on wishful thinking and imperfect information processing. He collaborates widely, emphasizing interdisciplinary approaches and creative problem-solving. Key contributions include modeling rational inattention, analyzing age structure impacts on monetary policy, and exploring North-South economic disparities. His editorial leadership and academic mentorship reflect his commitment to advancing innovative economic inquiry.

Lin CaiView profile

Associate Professor

• Wireless Communication
• Networking
• Green Radio Communication Networks
• +5 more

Lin Cai is an Associate Professor in the Department of Electrical and Computer Engineering at Illinois Institute of Technology, serving as Director of Graduate Affairs. She holds a Ph.D. in Electrical and Computer Engineering from the University of Waterloo, Canada (2010). Her research focuses on sustainable wireless communication and networking, particularly in energy harvesting, IoT, and deep reinforcement learning for resource management. Key research projects include energy sustainability in renewable-energy-powered networks, energy-efficient 5G protocols, and radio resource management over unlicensed bands. She has received the NSF CAREER Award (2016-2020), Best Paper Awards, and NSERC Postdoctoral Fellowship. Her work spans theoretical frameworks and practical implementations in HetNets, MIMO, and UAV-based systems. Education: Ph.D., E&CE, University of Waterloo, Canada (2010) Affiliations: Executive Editorial Committee member, IEEE Transactions on Wireless Communications (2021–present); Associate Editor for multiple IEEE journals Teaching: Courses include ECE 407/408 (Computer Networks) and ECE 517 (Modern Wireless Network Protocols) Her research emphasizes cross-layer protocol design, sustainable capacity planning, and topology control. Notable contributions include frameworks for energy sustainable radio resource management and optimization in dense HetNets. She actively contributes to conference organization and technical program committees for IEEE INFOCOM, GLOBECOM, and ICC.

Chung-Hsing YehView profile

Associate Professor

• Multicriteria Decision Analysis
• Applied Artificial Intelligence
• Intelligent Decision Support Systems
• +6 more

Chung-Hsing Yeh is an Associate Professor at Monash University's Faculty of Information Technology, Department of Data Science & AI. He holds a visiting professorship at National Cheng Kung University, Taiwan, and has extensive experience in academic roles including Chief Examiner and Lecturer for numerous IT and business-related courses. His research focuses on multicriteria decision analysis, applied artificial intelligence, fuzzy logic, neural networks, and sustainable operations management. He has led collaborative projects on e-waste recycling, supply chain optimization, and public health policy, funded by organizations like the Ministry of Science and Technology (Taiwan) and the Australian Research Council. Education: PhD in Operations Research/Information Systems, Monash University (1988) MSc in Management Science, National Cheng Kung University (1982) BSc (Engineering) in Industrial Design, National Cheng Kung University (1977) Research Interests: His work spans decision support systems, optimization modeling, transport research, and recycling operations. Notable contributions include algorithms for production scheduling, AI-driven solutions for healthcare, and sustainable e-waste management strategies. Awards: Listed in Marquis Who's Who in the World Listed in Who's Who in Finance and Industry Listed in Who's Who in Science and Engineering Grants & Projects: Led 6 major projects, including 'Maximizing E-waste Recycling Profitability' (2019–2020) and 'Smoke-Free Policy Effectiveness' (2007–2010). Active in grant review roles for ARC and the Netherlands Organisation for Scientific Research. Teaching: Overseeing courses such as Fundamentals of Artificial Intelligence, Business Intelligence Modelling, and Management Information Systems.

Richard BellamyView profile

Professor

• Democratic Theory
• Comparative Politics
• EU Studies
• +11 more

Professor Richard Bellamy is a leading scholar in political science and constitutional theory at University College London (UCL) and serves as a Senior Fellow at the Hertie School, Berlin. He holds a PhD from the University of Cambridge and has held visiting positions across Europe and Australia. Doctor of Philosophy , University of Cambridge (1983) MA Cantab , University of Cambridge (1979) His research spans democratic theory , republicanism , constitutionalism , and EU studies , with a focus on Italian political thought and global ethics . His recent articles explore rule of law , data ethics , and EU differentiated integration . He has authored over 150 publications and 11 monographs, including the acclaimed Political Constitutionalism . Key awards include: Fellow of the British Academy (2022) 2016 PADEMIA Research Award Serena Medal (2012) David and Elaine Spitz Prize (2009) Fellow of the Academy of Social Sciences (2008) Member, Academia Europaea (2024) Bellamy has supervised 24 PhD students and led major Leverhulme , ESRC , and European Commission projects. His current work includes Defending the Political Constitution (Oxford UP) and The Democratic Prince (political leadership study). He co-edits The Cambridge Companion to Constitutional Theory and The Cambridge Dictionary of Political Thought .

Sarath Chandar ANBIL PARTHIPANView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +7 more

Sarath Chandar is an Associate Professor at Polytechnique Montréal and Core Faculty Member at Mila, the Quebec AI Institute. He holds a Canada CIFAR AI Chair and Canada Research Chair in Lifelong Machine Learning. His research focuses on developing interactive learning algorithms for continual and lifelong learning, with expertise in deep learning, reinforcement learning, and natural language processing. Education: Ph.D. in Computer Science, University of Montreal (advisor: Yoshua Bengio) M.S. in Computer Science, Indian Institute of Technology Madras (advisor: Balaraman Ravindran) Research Themes: Continual Learning and Lifelong Learning Deep Reinforcement Learning Optimization for Deep Networks Natural Language Processing AI for Scientific Discovery Notable Contributions: Founder of the Conference on Lifelong Learning Agents (CoLLAs) Developed Chandar Research Lab (CRL), focusing on adaptive learning algorithms Contributions to model-based reinforcement learning and bias mitigation in AI systems Awards & Grants: Canada CIFAR AI Chair Canada Research Chair Tier 2 MITACS-funded projects on reinforcement learning applications Lab & Collaboration: CRL collaborates with academic/industrial partners (e.g., IBM, Samsung) Hosts annual symposium showcasing research in AI, optimization, and multi-agent systems

Dimitrios TsarapatsanisView profile

Senior Lecturer

• EU Law
• Human Rights
• Legal Theory
• +7 more

Dr Dimitrios Tsarapatsanis is a Senior Lecturer at York Law School, University of York. Previously, he served as a Lecturer in Law at the University of Sheffield. He holds an LLB from the University of Athens, an LLM in EU and International Law, and a PhD from Université Paris X-Nanterre. His research focuses on legal theory, human rights, AI ethics, and European law. Education: LLB, University of Athens LLM in EU and International Law, University of Athens DEA in Legal Theory, Université Paris X-Nanterre PhD (summa cum laude), Université Paris X-Nanterre Research Interests: Legal realism, administrative law, judicial decision-making, AI ethics in law, human rights jurisprudence, and bioethical legal issues. His work bridges theoretical jurisprudence with practical legal challenges, particularly in European contexts. Recent work explores the application of natural language processing to predict judicial outcomes and the ethical implications of AI in legal systems. He has also contributed to debates on the European Court of Human Rights' strategies and the legal status of prenatal life. Recipient of the Paul Ricoeur Prize (2009) for his doctoral thesis on prenatal legal personhood. Collaborations: Active in interdisciplinary projects, including the 'AI Law and Ethics: The Challenge of AI Wrongdoing' initiative. His research often intersects with political theory and institutional analysis. Professional Contributions: Fellow of the Higher Education Academy (2018). Previously practiced law in Greece, focusing on EU law and human rights cases.

Camellia ZakariaView profile

Assistant Professor

• Mobile Health
• Applied Machine Learning
• Human-Computer Interaction
• +3 more

Camellia Zakaria is an Assistant Professor at the University of Toronto, holding appointments in the Biostatistics Division and Institute of Health Policy, Management, and Evaluation (IHPME) at the Dalla Lana School of Public Health (DLSPH), and the Faculty of Information (FoI). She was recently named Canada Research Chair (Tier 2) for mobile health solutions. Her research focuses on integrating mobile technologies and machine learning to develop equitable health monitoring systems. Education: University of Toronto (Present) University of Massachusetts Amherst (2020–2023) Singapore Management University (2014–2019) Research interests span mobile health, applied machine learning, and human-computer interaction, with a focus on creating inclusive health applications. Her work addresses challenges in environmental sensing, sleep monitoring, and mental health tracking through innovative sensor technologies and data analytics. Key articles (2024–2016) explore medical decision-making, aerosol emissions, and group behavior modeling. Her work has been recognized in venues like BMJ , IMWUT , and CHI . Awards : Canada Research Chair (Tier 2, 2024) Projects like StressMon and WATCHME highlight her commitment to scalable health monitoring systems. She collaborates on lab initiatives such as sensAILabs, advancing interdisciplinary health technology solutions.

Nicole MegowView profile

Professor

• Combinatorial optimization
• Discrete optimization
• Mathematical optimization
• +11 more

Nicole Megow is a Professor holding the chair for Combinatorial Optimization in the Faculty of Mathematics and Computer Science at the University of Bremen since 2016. She is affiliated with several research clusters including Humans on Mars Initiative, Minds, Media, Machines, and Dynamics in Logistics. Her academic journey includes positions at TU Berlin, Max Planck Institute for Informatics, TU Darmstadt, and TU Munich. Professor Megow's research focuses on mathematical optimization, algorithm design and analysis, and operations research. Her specific interests span combinatorial and discrete optimization, efficient algorithms, scheduling theory, resource allocation, packing problems, network design, routing, and uncertainty models including online, stochastic, robust, and explorable approaches. Her work bridges theoretical foundations with practical applications in logistics and decision-making systems. Her recent publications demonstrate a strong trend toward integrating prediction models with traditional optimization frameworks, particularly in scheduling and matching problems. She has made significant contributions to understanding the role of uncertainty in optimization problems, developing algorithms that work effectively with incomplete or uncertain information. Her work spans multiple prestigious venues including Mathematical Programming, Algorithmica, SODA, STACS, and NeurIPS. Dissertation Award by the German Operations Research Society (2007) Berlin Science Award for Young Researchers (2013) Heinz Maier-Leibnitz Prize (2013) Listed among Germany's top 40 researchers below 40 (Capital, 2014, 2015) Professor Megow actively supervises PhD students and postdocs, including Max Stahlberg, Joes Biburger, Sarah Morell, Bart Zondervan, Zhenwei Liu, and Alexander Lindermayr. She serves on numerous program committees for major conferences including SODA, IPCO, and STOC, and holds editorial positions for several prestigious journals. Her current research projects include Optimization under Explorable Uncertainty (DFG funded), How robots learn how to use structure (seed grant from MMM research cluster), and Scheduling Invasive Multicore Programs Under Uncertainty (within TCRC 89).

Tamás KoltaiView profile

Professor

• Production Management
• Operations Research
• Data Envelopment Analysis (DEA)
• +3 more

Dr. Tamás Koltai is a Professor and Dean at the Faculty of Economics and Social Sciences of Budapest University of Technology and Economics (BME). He leads the doctoral school's Specialization Group in Production Management. His roles include overseeing academic programs and research in production management, operations research, and efficiency analysis. Education: Doctor of the Hungarian Academy of Sciences (2016) Dr. habil. (2000), Budapest University of Technology and Economics Candidate of Technical Sciences (1987), Hungarian Academy of Sciences M.Sc. in Mechanical Engineering (1983), BME Faculty of Mechanical Engineering Research Interests: Dr. Koltai focuses on production management optimization, including the application of Data Envelopment Analysis (DEA), sensitivity analysis in mathematical models, and the integration of robotics in assembly lines. His work bridges theoretical models (e.g., MILP/CP optimization) with practical industrial challenges, particularly in healthcare efficiency and educational management. Notable Awards: IEOM Society Teaching Excellence Award (2021) BME GTK Faculty Memorial Medal (2016) János Susánszki Award (2013) Széchenyi Professorship Scholarship (1999–) Teaching & Leadership: He has held visiting roles at the University of Seville (1990–1992) and the University of Michigan (1988/89). His teaching excellence is recognized through awards and his contributions to business simulation education. His research often collaborates with industry partners to address real-world operational challenges. Labs/Teams: Leads the Production Management Specialization Group and contributes to interdisciplinary teams focusing on manufacturing efficiency and healthcare operations within BME.

Jeffrey D MarrView profile

Assistant Professor

• Health Economics
• Health Policy
• Health Care Markets
• +5 more

Jeffrey D Marr is an Assistant Professor of Health Services, Policy, and Practice at Brown University’s School of Public Health. His research focuses on health care markets using quasi-experimental methods and administrative data, with current work emphasizing Medicare, private insurance, and AI applications in healthcare decision-making. Marr holds a PhD in Health Economics and Policy from Johns Hopkins University (2025) and a BA in Economics from Colgate University (2018). Key Affiliations: Brown University School of Public Health Research Themes: Algorithmic healthcare decision-making, Medicare Advantage networks, insurer market power, and post-acute care economics His research demonstrates how predictive algorithms reduce skilled nursing facility stays without compromising health outcomes, and how Medicare Advantage expansion impacts hospital pricing and provider networks. Marr’s work has been published in prestigious journals like Health Affairs , Health Services Research , and Journal of the American Geriatrics Society . His studies on Medicaid managed care reveal hospital pricing disparities linked to insurer bargaining power, while analyses of Medicare Advantage enrollment trends highlight shifts in supplemental insurance usage among elderly patients. Marr’s research also addresses critical issues like dialysis facility choice constraints and home-based care utilization differences between Medicare programs.