Find Academic Supervisors

Joi L. MooreView profile

Professor

• Educational Technology
• Usability Design
• E-Learning
• +5 more

Dr. Joi L. Moore serves as Associate Dean for Engagement & Outreach in the College of Education & Human Development and holds a Professorship in the School of Information Science & Learning Technologies at the University of Missouri. She is also affiliated with the MU Institute for Data Science & Informatics and the Black Studies Department. With a B.S. and M.S. from North Carolina State University and a Ph.D. in Instructional Technology from the University of Georgia, her expertise spans Learning Design, E-Learning, and Usability. Over 25 years of experience in instructional materials and digital media development underscores her contributions to educational technology. Her professional service includes presidential roles in the Minorities in Media Affiliate and the Association for Educational Communications and Technology (AECT). Research focuses on Electronic Performance Support Systems, Interactive Learning Environments, and Human-Computer Interaction in web application design. Notable projects include health informatics initiatives like medication timeline visualization and patient-centered clinical documentation. Educations: B.S. Computer Science, North Carolina State University M.S. Management (MIS), North Carolina State University Ph.D. Instructional Technology, University of Georgia Research Themes: Educational Technology & Usability Patient-Centered Health IT Cultural Competency in Digital Spaces Adult Learning & Professional Development Awards: Her leadership roles in national associations reflect her impact on educational technology policy and practice. Advising/Grants: Extensive mentorship and project management experience in educational technology projects, including agile methodologies for mobile applications. Labs/Teams: Active in MU’s Data Science Institute and interdisciplinary health informatics collaborations.

• Artificial Intelligence and Data Science
• Decision Making & Optimization
• Information Systems & Technology
• +5 more

Dan MA is an Associate Professor of Information Systems at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU). He holds a PhD from the University of Rochester (2006). His research focuses on Artificial Intelligence, Data Science, Cybersecurity, and Digital Transformation, with particular emphasis on software reliability, payment systems design, and cloud computing strategies. He advises PhD candidates in SMU-ZJU and SJTU-SMU DBA programs. Research interests include optimizing retail payment systems, analyzing bug bounty programs for software security, and evaluating cloud computing adoption readiness. His work bridges economic theory and technology management, addressing challenges in SaaS models, mobile payment ecosystems, and real-time financial infrastructure. Recent articles highlight trends in competitive content platform strategies, cybersecurity through crowd-sourced bug bounty programs, and the design of innovative payment systems. His contributions span over 40 peer-reviewed publications since 2002, with notable focus areas in fintech innovation and IT-enabled service economies. Teaching responsibilities include courses on advanced IS management and technology strategy. He has supervised three doctoral students and maintains active collaborations in cybersecurity and digital transformation research.

Kyle J. HuntView profile

Assistant Professor

• Computational Research and Modeling
• Finance, Business and Management
• Healthcare Analytics
• +5 more

Kyle J. Hunt is an Assistant Professor in Management Science and Systems at the School of Management, University at Buffalo. He is affiliated with the Institute for Artificial Intelligence and Data Science and focuses on interdisciplinary research bridging academia and industry. Education: PhD in Industrial Engineering (Operations Research), University at Buffalo BS in Industrial Engineering, University at Buffalo His research integrates operations research, machine learning, and empirical methods to address challenges in security and defense, healthcare analytics, information management, and technology management. Key areas include attacker-defender games, pandemic decision-making, and misinformation detection during crises. Recent publications analyze adversarial belief formation, counterterrorism technology signaling, and open-set recognition algorithms. Research trends highlight interdisciplinary approaches combining game theory, machine learning, and policy analysis in security and public health contexts. Grants: STTR Phase 2: Machine Learning Detection and Response for Space Force Ground Systems ($540,000, Air Force Research Lab, 2024–2025) AMiRA: Assessing and Mitigating Risks in the Arctic ($460,000, Department of Homeland Security, 2024–2025) NSF DDRIG: Multi-target Technology Deployment in Attacker-Defender Settings ($15,325, 2022–2023) Professional affiliations include INFORMS, Association for Information Systems, INFORMS Information Systems Society, and INFORMS Decision Analysis Society.

Siamak F. ShahandashtiView profile

Senior Lecturer

• Cyber Security
• Privacy
• Cryptography
• +3 more

Siamak F. Shahandashti is a Senior Lecturer (Associate Professor) in the Department of Computer Science at the University of York, UK. He leads the Cyber Security and Privacy Research Group and is involved in academic leadership roles such as Programme Lead for the MSc Cyber Security. His research focuses on cyber security, privacy, cryptography, and blockchain technology, with notable contributions to post-quantum cryptography, secure authentication frameworks, and privacy-preserving systems. Education: PhD in Computer Science, MSc and BSc in Electrical Engineering. His work integrates technical innovation with human-centered design, addressing challenges in user privacy, secure protocols, and resilient systems. Key research areas include: Cryptography and Post-Quantum Security Blockchain and Distributed Ledger Technology User-Centric Privacy Solutions Cyber Security Resilience in IoT and Edge Computing Current projects include PRIME (protecting minority ethnic communities online) and PHAWM (participatory harm auditing methodologies). He has been recognized for collaborative achievements, including a best paper award for work on DoS-resilient Bitcoin mempools and contributions to password manager governance frameworks. Teaching includes the MSc module 'Cryptography Theory and Practice', emphasizing both theoretical foundations and real-world applications.

Rik WehrensView profile

Assistant Professor

• Health Policy
• Health Care Governance
• Qualitative Research
• +13 more

Rik Wehrens is an Assistant Professor at Erasmus MC in the Department of Dermatology and Associate Professor in the Health Care Governance (HCG) group at the Erasmus School of Health Policy & Management. His work bridges health policy, qualitative research, and science and technology studies (STS), focusing on collaborative structures in public health and healthcare innovation. Assistant Professor, Erasmus MC – Dermatology Associate Professor, Erasmus School of Health Policy & Management – Health Care Governance Education: Bachelor of Arts and Culture, University of Maastricht Research Master in Cultures of Arts, Science and Technology (CAST), Maastricht University PhD, defended March 1, 2013, on Academic Collaborative Centers for Public Health Rik Wehrens’ research focuses on the coordination between researchers, policymakers, and healthcare professionals in collaborative settings. He employs theoretical frameworks such as boundary organizations, Mode 2 science, communities of practice, and Goffman’s front-stage/back-stage dynamics. His work contributes to understanding how evidence is translated into practice and how values are negotiated in healthcare governance. He has a strong emphasis on qualitative methodologies and interdisciplinary approaches. His recent publications explore themes such as value complexity in healthcare, legitimacy in health technology, scaling eHealth innovations, patient waiting experiences in breast cancer care, and methodological reflections on qualitative research. These works demonstrate a consistent focus on the social, ethical, and organizational dimensions of healthcare, particularly in the Dutch context. Scientific Contributions: Extensive research on Academic Collaborative Centers for Public Health (ACCs) Development and application of the Imitation Game method to understand patient experiences Analysis of policy experiments and value conflicts in healthcare Contributions to knowledge translation and epistemic practices in health Rik Wehrens has supervised several academic projects and contributed to key datasets on policy experiments and elderly care perspectives. His work aligns with UN Sustainable Development Goals related to health and well-being, emphasizing equity, innovation, and governance in healthcare systems.

• Computer Science
• Artificial Intelligence
• Robotics

Gonzalo Esteban Costales is a researcher affiliated with the University of Leon from 2012 to 2025, specializing in Computer Science and Artificial Intelligence within the Robotics research group. His work bridges haptic simulation, robotics, and educational technology. Education: Ph.D. in Computer Science (2020), University of Leon, with a thesis on haptic simulators for expert knowledge transfer . Research Interests: Haptic simulation for surgical training and rehabilitation Robotics security in industrial environments Educational technology frameworks Version control analytics for student performance Open-source vulnerability detection tools Key Article Trends: Recent publications focus on haptic workspace optimization, threat modeling for robotic production plants, and security enhancements in continuous integration workflows. His work spans simulation design, cybersecurity, and educational applications of robotics.

Daniël LakensView profile

Associate Professor

• Meta-Science
• Research Methods
• Applied Statistics
• +10 more

Daniël Lakens is an Associate Professor in the Human Technology Interaction group at Eindhoven University of Technology (TU/e), with expertise in meta-science, research methods, and applied statistics. His empirical research focuses on conceptual thought, similarity, meaning, study design, and reward structures in science. He has contributed to replication research and open science initiatives. Academic Background: PhD in Experimental Psychology (2010) from Utrecht University Grants: NWO VIDI grant (2017), pilot project for replication research grants Teaching: MOOC on 'Improving Your Statistical Inferences', TU/e Teacher of the Year (2014), over 40 workshops on open science His research spans methodologies to optimize study structures, meta-statistics, and interdisciplinary collaborations. Recent publications include datasets and interventions in esports, behavioral modeling, and methodological frameworks. Scientific Awards: Ammodo Science Award for Fundamental Research (2023) Leamer-Rosenthal Prize for Open Social Science (2017) NWO Vidi Award (2017) Datasets and projects highlight reproducibility in psychology, computational models for goal-directed behavior, and open data practices. He serves on editorial boards and has supervised 23 students, with current courses in advanced research methods and ethics.

Wijnand IJsselsteijnView profile

Professor

• Human-Technology Interaction
• Cognitive Psychology
• Affective Computing
• +7 more

Wijnand IJsselsteijn is a Full Professor at the Eindhoven University of Technology in the Department of Industrial Engineering and Innovation Sciences , affiliated with the Human Technology Interaction group and the Eindhoven AI Systems Institute (EAISI). His research bridges psychology and technology design, focusing on digital environments' impact on human learning, health, and wellbeing. Academic background in Artificial Intelligence and Cognitive Neuropsychology (MSc, Utrecht University), PhD in Telepresence (2004). Leadership roles: Scientific Director of the Center for Humans and Technology, board member of EAISI . Research interests include: Measuring human experiences in immersive media and serious games . Integrating data science and AI into psychological frameworks. Designing sensor-enabled mobile technologies and virtual environments for behavior tracking. Recent publications highlight: Human-robot interaction strategies for health behavior change (2025). Emotional bonding with robots through caregiving (2025). Machine Ethics challenges in aligning computer scientists and ethicists (2025). Cybersecurity breach responses in domestic IoT contexts (2024). Grants & Awards: NWO Gravitation grant "Ethics of Socially Disruptive Technologies" (co-PI). Support from EU FP6, FP7 , and H2020 grants. Additional affiliations include part-time professorship at the Jheronimus Academy of Data Science (JADS).

• Educational Technology
• Virtual Reality in Education
• Game-Based Learning
• +7 more

Morris Siu-Yung Jong is a Professor at The Chinese University of Hong Kong's Faculty of Education, Department of Educational Administration and Policy. With over 100 publications from 2006 to 2025, he has established himself as a leading researcher in educational technology, particularly focusing on innovative applications of virtual reality, artificial intelligence, and game-based learning in formal education settings. His work bridges theoretical frameworks with practical classroom implementations, making significant contributions to how technology enhances teaching and learning experiences. Professor Jong's research interests span multiple cutting-edge domains in educational technology. He has pioneered work in spherical video-based virtual reality (SVVR) applications for education, developing frameworks for immersive learning experiences that transform traditional classroom instruction. His research on AI in education, particularly examining ChatGPT's impact on student engagement and language learning, positions him at the forefront of understanding how emerging technologies reshape educational practices. Additionally, his extensive work on game-based learning, flipped classroom methodologies, and STEM education integration demonstrates a comprehensive approach to technology-enhanced learning across multiple educational contexts and age groups. Analysis of Professor Jong's recent publications reveals a clear progression from foundational work in game-based learning to more sophisticated applications of immersive technologies. His research increasingly focuses on AI integration in educational settings, with a significant portion of his 2023-2025 publications examining ChatGPT's educational applications. The methodological approaches in his work have evolved from basic implementation studies to more sophisticated designs incorporating hierarchical linear modeling, longitudinal analyses, and systematic reviews, demonstrating growing methodological rigor and impact across the educational technology field. Professor Jong has made substantial contributions to educational research through his extensive publication record in top-tier journals including Computers & Education, British Journal of Educational Technology, and Educational Technology & Society. His work has significantly influenced how educators implement virtual reality, AI, and game-based approaches in classrooms worldwide. His research on teacher concerns, implementation challenges, and pedagogical frameworks provides crucial insights for successful technology integration in formal educational settings. Through his supervision of numerous research projects and collaborations with scholars worldwide, Professor Jong has fostered a robust research ecosystem focused on advancing educational technology. His work on design-based research approaches has provided valuable methodological frameworks for studying technology implementation in authentic educational contexts. His recent focus on AI in education positions him as a key contributor to understanding how emerging technologies can be effectively integrated into teaching and learning processes. Professor Jong's research laboratory focuses on immersive learning environments, with particular emphasis on spherical video-based virtual reality applications. His team has developed several innovative frameworks for implementing VR in educational settings, addressing both technical and pedagogical challenges. Current projects appear to focus on AI integration with immersive technologies, exploring how generative AI can enhance virtual learning experiences and support student engagement across various subject areas.

• Human-Computer Interaction (HCI)
• Game Design
• Educational Technology
• +4 more

Prof. Peter Purgathofer is an Associate Professor at TU Wien's Department of Human Computer Interaction within the Faculty of Informatics. His work focuses on interdisciplinary research at the intersection of technology, design, and society. He leads projects such as 'Gesture controlled computer game for dementia prevention' and 'Haptic e-learning instrument for handicapped pupils,' demonstrating expertise in healthcare technologies and inclusive design. His research emphasizes ethical AI, game design for education, and human-centered interaction paradigms. Education background includes advanced degrees in engineering and informatics, reflected in his dual role as educator and researcher. Notable contributions include co-creating flipped classroom models for large cohorts, integrating adversarial chatbots into AI ethics curricula, and developing peer-review frameworks for large university courses. Over 20 student theses supervised span topics from AI ethics to gamified health interventions. Publications highlight his work in design-based research, educational technology, and healthcare applications. Projects often involve co-creation with students and end-users, emphasizing participatory design principles. Ongoing interests include responsible innovation in technology and bridging societal challenges through interactive systems.

• Game Development
• Serious Games
• Game Analytics
• +7 more

Henrik Engström is a Professor of Informatics at the University of Skövde, affiliated with the School of Informatics and Department of Information Technology. He holds a PhD in Computer Science from the University of Exeter. His research focuses on game development processes, serious games, and interdisciplinary collaboration in game design. Engström has led multiple projects, including the Game Tech Academy and Sweden Game Arena initiative, aiming to leverage game technology for societal challenges in health, education, and industry. He coordinates the Game Development Master's Programme and has published extensively on topics like game analytics, inclusive design, and mobile game publishing strategies. His work often bridges academia and industry, emphasizing practical applications in training simulations and healthcare. Education: PhD in Computer Science (University of Exeter) Key Projects: Sweden Game Arena, Game Hub Scandinavia, Digital Parental Support Tools Research Interests: Game design processes, serious games for health, inclusive game development, and mobile game business models Engström’s research outputs span over two decades, with notable contributions to understanding game development challenges, stress detection in games, and the application of AI in game narratives. His book Game Development Research (2020) synthesizes empirical insights from industry practices. He collaborates internationally, including with Japanese and Scandinavian institutions, to advance educational game models and industry-academia partnerships. His articles highlight trends in data-driven decision-making for indie game publishers, the psychological impact of game design on player experiences, and leveraging game jams for addressing heavy societal topics. Engström also leads grants focused on digital health tools for expecting parents and sustainable urban planning via game-based participation. Labs/Teams: Key contributor to the Sweden Game Conference and collaborator with Game Tech Academy, fostering innovation in game-based solutions for societal challenges.

• Energy Systems
• Electricity Markets
• Energy Storage
• +12 more

Ramteen Sioshansi is a Professor in the Department of Engineering and Public Policy, the Department of Electrical and Computer Engineering, and Heinz College at Carnegie Mellon University, where he also serves as Associate Department Head for Graduate Affairs and Director of the Carnegie Mellon Electricity Industry Center. He is additionally an Adjunct Professor at The Ohio State University’s Department of Integrated Systems Engineering. His work bridges engineering, economics, and policy with a focus on energy systems and market design. His research interests include energy storage, electricity market design, renewable integration, decarbonization, grid resilience, and energy justice. He employs advanced optimization and modeling techniques to analyze how energy systems can be operated and regulated more efficiently and equitably. His work often addresses the economic and policy challenges of integrating low-carbon technologies and distributed energy resources. Ramteen's recent publications highlight a strong trend in analyzing the role of energy storage in providing multiple grid services, reforming market designs to accommodate long-duration storage, and ensuring equitable access to resilient energy. His work spans technical modeling, economic analysis, and policy implications, frequently appearing in high-impact journals such as Current Sustainable/Renewable Energy Reports and The Energy Journal . Energy Justice Through Energy Storage Long-Duration Energy Storage (LDES) Policy Electric Vehicle Integration Demand Flexibility and Aggregators Hydrogen and Carbon Removal Economics Small Modular Reactors and Nuclear Policy Ramteen has received recognition as a top researcher in energy and energy storage domains. He actively contributes to the academic community through INFORMS, particularly in the Energy, Natural Resources, and the Environment (ENRE) section, and encourages nominations for prestigious awards like the Harold Hotelling Medal. He advises graduate students, including recent PhD graduate Dr. Hyeong Jun Kim and former student Joe Duggan. His research is supported by collaborations across academia, national labs (e.g., Argonne), and industry. He frequently engages with media on topics such as natural gas supply risks, EV integration, and the future of nuclear energy. Ramteen leads the Carnegie Mellon Electricity Industry Center, a hub for interdisciplinary research on electricity markets and policy. He is also a Faculty Affiliate at the Wilton E. Scott Institute for Energy Innovation, where he contributes to CMU’s broader energy innovation ecosystem.

Ellen VitercikView profile

Assistant Professor

• Machine Learning
• Algorithm Design
• Discrete Optimization
• +3 more

Ellen Vitercik is an Assistant Professor at Stanford University with joint appointments in the Management Science and Engineering and Computer Science departments. She holds a PhD from Carnegie Mellon University, advised by Nina Balcan and Tuomas Sandholm, and was a Miller Fellow at UC Berkeley under Michael Jordan and Jennifer Chayes. Her research focuses on machine learning, algorithm design, discrete optimization, and the intersection of economics and computation. She explores how machine learning can enhance discrete optimization and algorithmic reasoning, with applications to fairness, efficiency, and decision-making systems. Her work has garnered prestigious awards including the Schmidt Sciences AI2050 Early Career Fellowship and the NSF CAREER Award. Her doctoral thesis received multiple accolades, including the SIGecom Doctoral Dissertation Award and the CMU School of Computer Science Distinguished Dissertation Award. Notable research contributions include developing neural algorithmic reasoning frameworks, evaluating LLMs' structural reasoning abilities, and advancing techniques for optimization formulation equivalence checking. Her academic contributions span algorithm design, learning-augmented optimization, and mechanism design. She has pioneered methods for offline tuning in online decision-making systems and explored data-driven approaches for algorithm selection and configuration. Her research often bridges theoretical foundations with practical applications, addressing challenges in marketing, resource allocation, and social network dynamics. Ellen's interdisciplinary work integrates computer science, economics, and operations research, with a focus on creating scalable, fair, and efficient systems. Her current projects include investigating cold-start algorithm configuration using LLMs, optimizing decision-making under uncertainty, and designing robust systems resilient to data limitations.

Richard JoinerView profile

Professor

• Digital Technology and Learning
• Computer Supported Collaborative Learning
• Digital Games and Learning
• +5 more

Richard Joiner is a Professor in the Department of Psychology at the University of Bath, where he serves as Deputy Head of Department for Education and Student Experience. He leads research at the intersection of digital technology and education within the Cognition, Affective Science & Technology Laboratories (CASTL). Academic appointment: Professor (since 2015) Administrative role: Deputy Head (Education & Student Experience) Research group: CASTL Research interests center on technology-enhanced learning: Digital technology for physics education Game-based engineering learning with 'Racing Academy' Conflict resolution in collaborative digital environments Gender dynamics in ICT adoption Immersive technology applications Extended mind theory in healthcare education Recent publications demonstrate: AI and VR integration in medical training ITEM framework validation for immersive tech Digital learning equity research Psychological impacts of technology mediation Curriculum innovation through tech Cross-disciplinary educational technology

Padmini SrinivasanView profile

Professor

• Information Retrieval
• Natural Language Processing
• Text Mining
• +12 more

Padmini Srinivasan is a Professor in the Department of Computer Science at the University of Iowa, affiliated with the College of Engineering. Her work bridges computer science, informatics, and social applications through advanced research in information retrieval, natural language processing, and data mining. Research Interests: Her research focuses on Information Retrieval & NLP , Text and Web Mining , Biomedical Text Mining , Privacy/Security & Censorship , Social Media Analytics (particularly in political and health belief contexts), and Crowdsourcing & Games . She leads the Text Retrieval & Text Mining Group , fostering interdisciplinary research involving machine learning, human computation, and real-world data challenges. Publication Trends: Her recent work appears in top-tier venues such as SIG-IR, KDD, WSDM, ICWSM, EMNLP, JASIST, and PLOS One, reflecting sustained contributions to both foundational and applied aspects of data science. These publications span topics from ranking optimization and query modeling to social dynamics, health informatics, and ethical AI. Scientific Awards: No specific awards were mentioned in the provided text. Advising and Grants: She has advised numerous graduate students including Osama Khalid, Ingroj Shrestha, Asad Mahmood, Jonathan Rusert, and others. While grant details are not listed, her publication record in premier venues suggests consistent external funding and collaborative research activity. Labs and Teams: She leads the Text Retrieval & Text Mining Group , which conducts cutting-edge research in search technologies, text analysis, and social media understanding, often integrating crowdsourcing and game-based methods for data collection and evaluation.