Find Academic Supervisors

• Data-Driven Optimization
• Large-Scale Data Analytics
• Machine Learning
• +4 more

Hai Wang is an Associate Professor at the School of Computing and Information Systems, Singapore Management University, and a Visiting Professor at Carnegie Mellon University's Heinz College. His research bridges data-driven optimization, machine learning, and urban systems, with applications in smart cities, transportation, and shared economies. He holds a PhD in Operations Research from MIT and a BS from Tsinghua University. Research Focus: Wang pioneers methodologies in large-scale data analytics and stochastic optimization to address challenges in ride-sourcing, food delivery logistics, and urban mobility. His work emphasizes practical implementations, including collaborations with industry leaders like Meituan and DiDi. Publications: His recent articles (2023-2025) predominantly explore transportation economics, platform operations, and behavioral analytics in service systems, using advanced computational techniques to model complex urban networks. Honors: World's Top 1% Scientist (2024), Transportation Science Meritorious Service Award (2022-2024), INFORMS Best Paper Award (2024) Grants: Principal Investigator for SG$4M National Research Foundation project on AI-empowered urban systems; collaborations with Tokka Labs (SG$156k) and Mobility21 (US$186k) Students: Advises PhD candidates YANG Jingfeng and Rajiv Ranjan KUMAR on optimization and machine learning applications. Leadership: Serves as Associate Editor for Transportation Science , IISE Transactions , and Service Science , and co-leads INFORMS Transportation Science and Logistics Society initiatives.

Alexander SumichView profile

Professor

• Biopsychology
• Neuroimaging
• Neurobiology of mental health
• +6 more

Alexander Sumich is Professor of Mental Health and Biopsychology at Nottingham Trent University , School of Social Sciences. He co-directs the Centre for Public and Psychosocial Health and co-leads the Affect, Personality and Embodied Brain (APE) Research Group . He also serves as Adjunct Professor in Psychology at Auckland University of Technology, New Zealand , and holds editorial and leadership roles in organizations like the British Society for the Psychology of Individual Differences (Treasurer) and Personality and Individual Differences (Associate Editor). Education: MA in Psychology (First Class Honors), University of Auckland PhD in Psychology as Applied to Medicine, Institute of Psychiatry, London His research spans neuroimaging and electrophysiological methods to investigate the neurobiology of affect-driven behaviors (depression, aggression, hallucinations) and the immune system's role in mental health . He employs virtual reality exposure therapy (VRET) , spiking neural networks , and computational models to enhance mental health interventions. Key areas include gaming disorder , mindfulness effects , and gut-brain axis interactions . Notable research grants include: BIAL Foundation (2023-2024): €58,765 for trauma-paranormal-mental health links MBIE-Catalyst Programme (2020-2024): NZ$2,134,847 for computational neurogenetics UKRI KTP (2021-2024): £204,000 for therapeutic digital displays His external roles include: Treasurer, British Society for the Psychology of Individual Differences Associate Editor, Personality and Individual Differences Co-host, APE2020 Conference

NAOFAL AL-DHAHIRView profile

Professor

• Broadband Wireless Communication
• Machine Learning
• Signal Processing
• +6 more

Dr. Naofal Al-Dhahir is the Erik Jonsson Distinguished Professor of Electrical and Computer Engineering at University of Texas at Dallas , affiliated with the Erik Jonsson School of Engineering and Computer Science . He serves as Associate Department Head for Undergraduate Education and leads the Broadband Information Transmission & Signal Processing (BITS) Laboratory . His research focuses on 6G communications, intelligent reflecting surfaces (IRS), federated learning, integrated sensing and communication (ISAC) , and wireless security. With over 600 publications and 43 US patents, he is an IEEE Fellow (2008), NAI Fellow (2020), and recipient of numerous awards including the 2022 IEEE RCC Technical Recognition Award and 2021 Qualcomm Faculty Award. Educations: PhD (Stanford University, 1994), MSc (Stanford University, 1990) Professional Roles: Editor-in-Chief of IEEE Transactions on Communications (2016-2019), Technical Staff at GE Global Research and AT&T Labs (1994-2003) Research Interests His work spans IRS-based 6G systems, machine learning for communications, vehicular networks, and smart-grid technologies . Recent contributions include secure ISAC designs and low-complexity signal processing algorithms. Collaborations with industry leaders like Qualcomm and Apple highlight his impact on practical applications. Students & Labs Alumni include professionals at Qualcomm, Apple, and NASA. The BITS Lab has hosted researchers from global institutions like KAUST and Xidian University. Current projects explore covert communications, Movable Antenna Systems (MAS), and AI-driven spectrum management .

• Digital Technology in Organizations
• Public Sector Transformation
• Institutional Actors and Structures
• +7 more

Dr. Amizan Omar is an Associate Professor in Strategic Management at the School of Management, University of Bradford, where she also serves as the Director of Accreditation for the Faculty of Management, Law and Social Sciences. With over 15 years of government experience in Malaysia, including roles as Assistant Director of Talent Management and Chief Assistant Director of Business Development, she brings practical insights to her academic work. Her interdisciplinary research focuses on the institutionalization of digital technology in organizations, particularly within the public sector. She examines how digital technologies interact with institutional actors and structures to drive public service transformation toward sustainable societies. Her work spans digital government, AI ethics in HRM, talent management in the circular economy, and public sector innovation. Dr. Omar has published over 30 scientific articles in leading peer-reviewed journals and conferences, including 12 journal articles, 6 conference publications, and 1 book chapter. Her research demonstrates consistent exploration of how digital transformation reshapes public sector institutions and service delivery, with recent work increasingly focusing on ethical implications of emerging technologies. Fellow of the UK Higher Education Academy (FHEA) Associate Member of the Chartered Institute of Personnel and Development (CIPD) Editorial advisory board member of Journal of Information Technology (JIT) Editorial advisory board member of Journal of Electronic Government Research (IJEGR) Chair of digital government mini-track for the 2022 Americas Conference on Information Systems As a Co-Investigator on multi-million-pound research projects funded by the European Commission (FP7 and H2020) and UK Local Government, Dr. Omar has secured significant research funding. She is an active member of the British Academy of Management (BAM) and the Association for Information Systems (AIS), contributing to the academic community through leadership roles and editorial work.

Kevin SchneiderView profile

Professor

• Software Architecture and Design
• Software Evolution and Maintenance
• Software Analysis and Navigation
• +6 more

Dr. Kevin Schneider is a Professor in the Department of Computer Science at the University of Saskatchewan. His research focuses on software architecture, evolution, analysis, and visualization, with notable work in quantum computing applications and machine learning. He also explores collaborative software teams and domain-specific languages to enhance development processes. Education: Ph.D., Computing and Information Science, Queen’s University (2000) Research Associate, Computing and Information Science, Queen’s University (1991–94) M.Sc., Computing and Information Science, Queen’s University (1990) B.Sc.(Hon), Computational Science, University of Saskatchewan (1980) Research interests include software design principles, maintenance strategies, and the integration of AI/quantum computing into software engineering. He emphasizes reproducibility in scientific workflows and tools like VizSciFlow. His work often bridges theory and practice, addressing challenges in code clone stability, user feedback management, and healthcare-related machine learning frameworks. Scientific Awards: Most Influential Paper at SCAM 2001 for his work on software engineering via source transformation. Advising and grants: While no specific advisees are listed, his research involves large-scale projects such as the Nutrient App and automated polyp segmentation tools. He collaborates on grants related to quantum computing applications and cloud-based software systems. Labs and teams: His work centers on collaborative scientific data analysis groups and developing tools for real-time groupware systems in complex workflows. He contributes to projects like CloneCognition and FSECAM, aiming to improve software design and maintenance through advanced analytics.

Burhaneddin İzgiView profile

Associate Professor

• Game Theory
• Stochastic Differential Equations
• Numerical Analysis
• +3 more

Burhaneddin İzgi serves as an Associate Professor in the Department of Mathematics Engineering at Istanbul Technical University, where he maintains an active research profile with projects extending through 2025. His work bridges theoretical mathematics with computational applications, particularly in game-theoretic problem solving. Research interests center on Game Theory and Stochastic Differential Equations, with specialized focus on matrix norm-based solution methods for zero-sum, fuzzy, and stochastic matrix games. Recent work integrates Artificial Intelligence techniques to address large-scale game complexity, reflecting interdisciplinary innovation across Numerical Analysis and Fuzzy Mathematics. Article trends (2022-2025) reveal consistent advancement of matrix norm methodologies across diverse game types, increasingly incorporating machine learning for computational efficiency. Publications demonstrate strong theoretical grounding in Mathematics while addressing practical applications in finance (e.g., IPO modeling) and decision systems. Scientific recognition includes: 2210 - Yurt İçi Yüksek Lisans Burs Programı (2008) 2211 - Yurt İçi Doktora Burs Programı (2010) Matematik Bölüm Birinciliği (2008) Üniversite İkinciliği ödülü (2008) Research funding includes TUBITAK-supported projects such as 'Stokastik Oyunlar İçin Matris Norm Tabanli Yeni Çözüm Yöntemleri Ve Yapay Zeka Uygulamalari' (2021-2023) and current grants developing chaos theory approaches for stochastic matrix games (2024-2025), demonstrating sustained external validation of his research program.

Muhammad Intizar AliView profile

Assistant Professor

• Data Analytics
• Internet of Things (IoT)
• Machine Learning & AI for IoT
• +8 more

Dr. Muhammad Intizar Ali is an Assistant Professor in the School of Electronic Engineering at Dublin City University (DCU). He holds a PhD (with distinction) from Vienna University of Technology, Austria (2011) and has held roles including Adjunct Lecturer and Research Fellow at the Insight Centre for Data Analytics, NUI Galway. His primary research focuses on IoT, Data Analytics, Machine Learning, and Knowledge Graphs with applications in Smart Cities, Manufacturing, Farming, and Healthcare. Education: PhD in Computer Science, Vienna University of Technology (2007-2011) Research Interests: IoT and Edge Analytics Federated and Distributed Machine Learning Semantic Web and Knowledge Graphs Smart Manufacturing and Industry 4.0 Stream Processing and Real-Time Systems Recent Work Trends: His publications emphasize federated learning frameworks, IoT-enabled adaptive intelligence, and knowledge graph applications in industrial contexts. Recent projects include digital twin systems for predictive maintenance and ontology-driven manufacturing solutions. Grants & Projects: Lead Investigator in SFI-funded projects like MultiRoof (2025-2029) and Neuro-Symbolic AI for Building Management EU/Industry collaborations including Terrain-AI and Bentley-funded initiatives Labs & Teams: Active in DCU's Data Analysis and Machine Learning research groups, leading projects like Smart DCU Digital Twin for campus optimization.

Dan S JurafskyView profile

Professor

• Computational Linguistics
• Natural Language Processing
• Social and Behavioral Sciences
• +5 more

Dan S. Jurafsky is the Jackson Eli Reynolds Professor in Humanities and Professor of Computer Science at Stanford University. He holds joint appointments in the Department of Linguistics and Department of Computer Science. His academic journey includes a B.A. in Linguistics (UC Berkeley, 1983), Ph.D. in Computer Science (UC Berkeley, 1992), and postdoctoral work at the International Computer Science Institute (Berkeley, 1995-1998). Prior to Stanford, he was on the faculty at the University of Colorado, Boulder (1996-2003). Jurafsky's research bridges computational linguistics, natural language processing, and sociocultural studies. Notable works include The Language of Food (2014) and co-authorship of the seminal textbook Speech and Language Processing (2009, 2022). His work applies NLP to domains like policing interactions, healthcare communication, and historical discourse analysis. His awards include the MacArthur "Genius" Fellowship (2003), American Academy of Arts and Sciences membership (2020), and multiple ACL/IJCAI best paper recognitions. He co-created one of the first MOOCs on NLP with Chris Manning and has advised over 50 students, many of whom won top awards like the Arthur Samuel Thesis Prize. Current projects include studying dialect bias in AI systems, linguistic analysis of police interactions, and ethical foundations of large language models. He leads interdisciplinary teams at Stanford's Center for East Asian Studies and collaborates with researchers in sociology, psychology, and computer science.

Kieron O'HaraView profile

Associate Professor

• Privacy
• Trust
• Digital Modernity
• +4 more

Kieron O'Hara is an Associate Professor in Electronics and Computer Science at the University of Southampton. He is a founding contributor to Web Science, focusing on digital modernity's societal, economic, and political impacts. His work explores privacy preservation in AI/ML contexts, trust dynamics in networked societies, and internet governance. He co-authored seminal works like A Framework for Web Science (2006) and Four Internets (2021), and chairs UKAN's anonymisation network. He has held roles at the Ministry of Justice's transparency panel and serves as editor of Foundations and Trends in Web Science . Research Groups: Web and Internet Science, Centre for Democratic Futures External Roles: Speaker for 'Four Internets: The Ethics and Geopolitics of the Internet' (2019) His research interests include anonymisation techniques, data geopolitics, and the ethical implications of emerging technologies. Notable awards include Best Paper prizes at ACM Web Science (2016) and Best Oral Presentation at Sensecam (2012). Current projects focus on provenance/anonymization frameworks and national identity system analysis, funded by the Alan Turing Institute.

Inga ProkopenkoView profile

Professor

• Genetic Epidemiology
• Multi-Omics Analysis
• Type 2 Diabetes
• +5 more

Professor Inga Prokopenko is a faculty member at the University of Surrey's School of Biosciences (Faculty of Health and Medical Sciences), specializing in e-One Health and leading the Statistical Multi-Omics group. Her research focuses on genetic epidemiology, multi-omics approaches, and the comorbidity between metabolic disorders like type 2 diabetes and conditions such as cardiovascular disease, cancer, and mental health disorders. She leads studies on genetic determinants of blood glucose regulation, obesity-related risks, and shared pathophysiological pathways between diseases. Key research areas include: Genetic links between type 2 diabetes and cancers (breast, pancreatic, etc.) Mechanisms of GLP-1 receptor signaling in diabetes treatment Causal relationships between depression and diabetes using Mendelian randomization Role of abdominal obesity in cancer susceptibility She supervises PhD/MSc students in biosciences and medicine programs and develops computational tools like comorbidPRS for polygenic risk score analysis. Her work integrates large-scale genomic data from cohorts like the UK Biobank and EPIC studies to uncover shared genetic mechanisms across diseases. Recent work highlights include: Systematic reviews on flavan-3-ols and cardiovascular health Meta-analyses of trans-ethnic diabetes GWAS data Epigenetic studies linking blood metabolites to cancer risk Her research bridges statistical genetics with clinical applications, emphasizing precision medicine strategies for complex diseases.

Judith VerstegenView profile

Assistant Professor

• Geographic Information Science
• Spatial Modelling
• Agent-Based Modelling
• +4 more

Dr. Judith Verstegen is an Assistant Professor in the Department of Human Geography and Spatial Planning at Utrecht University's Faculty of Geosciences. Her research focuses on geosimulation modeling and spatial optimization, with applications in urban planning, environmental vulnerability assessment, and policy analysis. She leads projects such as HEADS 4 Health (2023-2024), which integrates agent-based models into urban digital twins, and coordinates the GeoSIM research group. Her work emphasizes interdisciplinary collaboration, including projects analyzing linguistic diversity in South America and environmental threats to Amazonian indigenous lands. She is the Program Chair of the MSc Geographical Information Management and Applications (GIMA) program and serves as Editor-in-Chief of the Journal of Spatial Information Science. Notable contributions include methodologies for spatial optimization under uncertainty and agent-based modeling of pedestrian behavior in urban environments. Key research areas include applied data science, complex systems analysis, and the PtS - Transforming Cities initiative. She has advised PhD students on topics ranging from fire prevention optimization to indigenous land vulnerability. Her lab at the University of Münster previously focused on spatial modeling frameworks, and she collaborates internationally with institutions like Leiden University and the PBL Netherlands Environmental Assessment Agency. Recent projects highlight innovation in computational methods, such as Python-based open-source tools for land-use modeling (IMAGE-land) and immersive video experiments for behavioral studies. Her work bridges theoretical modeling with practical policy applications, addressing challenges in sustainable urban development and environmental conservation.

Anthony ConstantinouView profile

Senior Lecturer

• Causal Machine Learning
• Decision Systems
• Bayesian Networks
• +6 more

Anthony Constantinou is a Senior Lecturer at Queen Mary University of London, part of the School of Electronic Engineering and Computer Science. He leads the MInDS Research Group and the Bayesian AI Lab, focusing on causal machine learning for decision-making under uncertainty. His research spans healthcare, defense, sports, economics, and gaming, with a strong emphasis on Bayesian networks and causal inference. Research Interests: Causal machine learning, decision systems, Bayesian networks, uncertainty quantification, and their applications in healthcare, military defense, sports analytics, and economics. He collaborates with academia and industry to advance AI-driven decision-making systems. Grants: Noted for securing funding such as the Engineering and Physical Sciences Research Council grant (EP/S001646/1) for Bayesian AI research. His work emphasizes practical applications in diverse fields through collaborative projects. Labs & Teams: Head of the MInDS Research Group and Bayesian AI Lab, fostering interdisciplinary research in AI and decision systems.

Ferrante NeriView profile

Professor

• Machine Learning
• Artificial Intelligence
• Optimization
• +5 more

Professor Ferrante Neri is a faculty member at the University of Surrey, holding the positions of Professor of Machine Learning and Artificial Intelligence and Associate Dean (International) for the Faculty of Engineering and Physical Sciences (FEPS). He is affiliated with the Nature Inspired Computing and Engineering Research Group, Surrey Institute for People-Centred AI (PAI), and the Computer Science Research Centre within the School of Computer Science and Electronic Engineering. His research focuses on optimization, explainable AI, and machine learning, with contributions to memetic computing and differential evolution. Since 2010, he has chaired the IEEE Task Force on Memetic Computing. He advises PhD students in topics like dynamic multi-objective optimization and AI-driven applications. His teaching expertise includes mathematical foundations for computer science. He has supervised students such as Aisha E S E Saeid and Pengjin Wu. Notable research areas include evolutionary algorithms, neural architecture search, and applications in robotics and environmental monitoring. Labs and teams include the Nature Inspired Computing group, which explores AI-driven solutions for complex problems. His work bridges theoretical advancements and practical applications in fields like autonomous systems and deep learning.

Erlend LavikView profile

Professor

• Television Studies
• Film History
• Film and TV Analysis
• +3 more

Erlend Lavik is Professor at the Department of Information Science and Media Studies, University of Bergen, Norway. Specialising in television studies, film history, and digital criticism, he leads research on cinematic television, narrative complexity, and the scholarly video essay. He is a key figure in the study of HBO’s The Wire , which he frames as emblematic of the medium’s “third golden age.” Education 2008 – PhD, Changing Narratives. Five Essays on Hollywood History , University of Bergen 2001 – MA (hovedoppgave), Kjærlighet i seriemonogamiets tidsalder. Romantiske komedier i Hollywood , University of Bergen Research Interests Lavik’s work interrogates the intersection of aesthetics, narrative theory, and media policy. Core themes include: Serial television and long-form storytelling Film and television authorship (showrunner model, copyright aesthetics) Digital criticism and the video essay as scholarly genre Hollywood historiography from classical to post-classical cinema Documentary ethics and truth claims in factual media Publication Trends Across more than 60 publications, Lavik moves fluidly between peer-reviewed journals, academic monographs, trade-press essays, and experimental video essays. Recurrent case studies include The Wire , The Sopranos , Succession , and blockbuster cinema, examined through lenses of narrative complexity, intertextuality, and cultural memory. Selected Public Engagement & Service Chairman of the jury, Best Norwegian Documentary, Bergen International Film Festival 2012 Keynote speaker, Nordic Media Conference, Akureiri 2011; NTNU seminar on video essays 2012 Public lectures at NRK Drama, University of Tromsø, Bergen Public Library, and numerous film clubs Labs, Teams, Collaborations Lavik is affiliated with the research group Film, Television, and Visual Culture at the University of Bergen, where he collaborates on projects concerning production studies, visual aesthetics, and digital distribution. While specific grant numbers are not listed, his sustained output and conference presence indicate ongoing funded research within Norwegian and European media-studies networks.

Margarida CARVALHOView profile

Associate Professor

• Algorithmic Game Theory
• Operations Research
• Combinatorial Optimization
• +4 more

Margarida Carvalho is an Associate Professor in the Department of Computer Science and Operations Research at Université de Montréal. She holds the FRQ–IVADO Research Chair in Data Science for Combinatorial Game Theory and was awarded the 2018 EURO Doctoral Dissertation Award. Her research integrates algorithmic game theory and integer programming to address strategic decision-making challenges in healthcare, urban planning, and sustainability. Education: Bachelor's and Master's in Mathematics PhD in Computer Science (Universidade do Porto, 2016) Postdoctoral Fellow at Polytechnique Montréal (2017) Research Interests: Algorithmic Game Theory and Combinatorial Optimization Applications in Kidney Exchange Programs, EV Infrastructure, and Urban Decision-Making Development of fair and scalable optimization frameworks Awards & Grants: FRQ–IVADO Research Chair (2018–present) Teaching Excellence Award (2024) Lead on projects funded by CRSNG, MITACS, and Fonds de recherche du Québec Lab & Collaborations: Member of CIRRELT, CRM, Mila, and the AI Cybersecurity Lab (talents). Her team focuses on interdisciplinary solutions for complex socio-economic systems.