Find Academic Supervisors

Melvyn R.W. HamstraView profile

Professor

• Organizational Behavior
• Leadership
• Human Resource Management
• +6 more

Melvyn R.W. Hamstra is a Full Professor at IÉSEG School of Management in France since 2023. His academic career includes roles as Associate Professor (2021–2023) and Assistant Professor (2020–2021) at IÉSEG, as well as Assistant Professor positions at the University of Maastricht (2015–2020) and the University of Amsterdam (2013–2015). He holds a Ph.D. in Behavioural and Social Sciences from the University of Groningen (2013), preceded by a Master’s (2009) and Bachelor’s (2007) in Psychology from the same institution. Research Interests : His work centers on organizational behavior, leadership, and employee motivation, with a strong emphasis on regulatory focus theory, employee voice dynamics, and knowledge management. Key themes include how leadership styles (e.g., promotion vs. prevention focus) influence team innovation, conflict resolution, and workplace morale. Publication Trends : Recent publications (2025–2024) explore topics such as gender bias in leadership evaluation, financial stress and counterproductive behavior, ethical conflict in teams, and the dual-edged role of humor in workplace negotiations. His longitudinal studies on religious engagement and life satisfaction, as well as theoretical models on knowledge withholding, highlight interdisciplinary breadth. Teaching : He contributes to bachelor and master’s programs at IÉSEG, focusing on leadership development, positive leadership, and organizational learning.

Sascha van SchendelView profile

Assistant Professor

• Data Protection Law
• Privacy Law
• Cybersecurity
• +12 more

Sascha van Schendel is an Assistant Professor in Data Protection & Cybersecurity at the Department of Law & Markets, Erasmus School of Law, Erasmus University Rotterdam. She is affiliated with the Erasmus Centre of Law and Digitalization and contributes to the Sectorplan SSH-Breed research initiative on the influence of digitalization on work, prosperity, and entrepreneurship. Her research lies at the intersection of law, technology, and fundamental rights, with a focus on data protection, privacy, algorithmic governance, and the regulation of emerging technologies in public and environmental domains. She has published widely on topics including GDPR compliance, privacy by design, smart energy systems, AI in criminal justice, and the legal implications of predictive policing. The recent publications reflect a strong trend toward the regulation of data in public infrastructure (e.g., energy grids), algorithmic accountability in law enforcement, and the integration of legal and technical perspectives in privacy-preserving systems. Her work spans environmental law, criminal procedure, and digital constitutionalism, demonstrating interdisciplinary reach. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: While no formal PhD or Master’s students are listed, Dr. van Schendel has been involved in significant research projects such as the NWO-funded Megamind project on smart energy grids, indicating experience with competitive grant funding. She actively collaborates with legal scholars and contributes to public policy debates, including responses to national legislation like the Dutch Cybersecurity Bill. Labs and Teams: She is a core member of the Erasmus Centre of Law and Digitalization, a research hub focusing on the legal challenges of digital transformation. Her work is embedded in interdisciplinary collaborations involving law, technology, and public policy experts.

Xiaoming LiuView profile

Professor

• Computer Vision
• Pattern Recognition
• Image and Video Processing
• +4 more

Xiaoming Liu is the Anil K. and Nandita Jain Endowed Professor of Engineering and MSU Foundation Professor in the Department of Computer Science and Engineering at Michigan State University . Holding a Ph.D. from Carnegie Mellon University (2004), he leads cutting-edge research in computer vision and machine learning. Research Interests : Computer Vision Pattern Recognition Image and Video Processing Machine Learning Medical Image Analysis Multimedia Retrieval Recent Research Trends : Focus on 3D object detection and depth estimation Development of robust biometric recognition systems Integration of radar-camera fusion for autonomous systems Advancements in self-supervised and multimodal learning Exploration of adversarial AI security Creation of interpretable forgery detection frameworks Teaching : Spring 2013: CSE891-006 Computer Vision Seminar Fall 2012-2015: CSE803 Computer Vision Spring 2014-2017: CSE 471 Media Processing and Multimedia Contact Information : Email: liuxm@cse.msu.edu Office: EB 3137, Michigan State University Phone: +1 (517) 355-2359

• Human-Computer Interaction
• Virtual Reality
• Social Virtual Reality
• +4 more

Giulio Jacucci is a Professor in the Department of Computer Science at the University of Helsinki, affiliated with the Helsinki Information Technology Research Institute. He serves as a Supervisor in the Doctoral Programme in Computer Science, mentoring PhD candidates in human-computer interaction and related fields. His academic career spans over two decades with continuous research productivity from 2006 through 2025. Professor Jacucci's research interests center on Human-Computer Interaction , particularly focusing on Virtual Reality , Brain-Computer Interfaces , and Neuroadaptive Systems . His work explores how technology can adapt to users' cognitive and physiological states, with significant contributions to social virtual reality environments, embodied agents, and information retrieval systems. He investigates how virtual representations affect social behavior, time perception, and communication in digital spaces. His publication record shows a clear evolution from foundational work in information retrieval toward increasingly sophisticated neuroadaptive systems. Recent publications (2024-2025) demonstrate his leadership in examining social dynamics within virtual reality platforms, including votekicking mechanisms, mirror watching behaviors, and communication tools like mutes. His work bridges technical innovation with deep understanding of human social behavior in digital environments. Professor Jacucci currently leads multiple research projects funded by the Academy of Finland, including DataLit: Datalukutaito ja vastuullinen päätöksenteko (2023-2026) and MyModel: Selitettävyys suositusten hallinnassa (2023-2027). These projects focus on data literacy, responsible decision-making, and explainability in recommendation systems, reflecting his commitment to ethical and user-centered technology development. His research has received media attention, particularly around brain-computer interfaces and virtual reality applications, with coverage in outlets discussing how deep learning transforms mobile applications and sensor landscapes. He has presented his work at major conferences including CHI 2017 and continues to be an active contributor to the international research community.

Niels HenzeView profile

Professor

• Human-Computer Interaction
• Predictive Models in Interactive Systems
• Mobile Human-Computer Interaction
• +5 more

Niels Henze is a Professor at the Chair of Media Informatics within the Faculty of Languages, Literature and Cultural Studies at the University of Regensburg, where he has been serving since May 2018. His research centers on human-computer interaction, with a strong focus on predictive models in interactive systems, mobile interaction, augmented and virtual reality, and attention-aware computing. His research interests include: Human-Computer Interaction (HCI) Predictive modeling for runtime adaptation Mobile and wearable interaction Augmented and Virtual Reality (AR/VR) Attention-aware and context-sensitive systems Sociocognitive aspects of interactive technologies The analysis of his recent publications reveals a consistent focus on leveraging user behavior and contextual cues to build intelligent, adaptive interfaces. His work integrates machine learning with interaction design, emphasizing real-time model updates, implicit feedback, and cognitive load awareness to improve usability and user experience across mobile and immersive platforms. Scientific awards: No awards mentioned in the provided text. Niels Henze leads research in adaptive interactive systems and advises students in the field of media informatics. He has previously held a junior professorship at the University of Stuttgart and completed his doctorate at the University of Oldenburg under Susanne Boll. He is actively involved in advancing the theoretical and practical foundations of predictive and attention-aware computing. Grants and funding sources are not specified in the text. He is associated with the Institute for Information and Media, Language and Culture (I:IMSK) at the University of Regensburg, contributing to a multidisciplinary environment that bridges informatics with cultural and linguistic studies.

• Human-Computer Interaction (HCI)
• Health Informatics
• Personal Informatics
• +3 more

Christina Chung is an Assistant Professor in the Department of Computational Media at the University of California, Santa Cruz (UCSC). Her research focuses on personal informatics, health & wellbeing in interpersonal contexts, and human-computer interaction (HCI). She has previously been affiliated with the University of Washington (UW) and Indiana University, evidenced by her emails at those institutions. Her work explores topics such as goal-setting behaviors in technology-mediated environments, dining-out challenges for individuals with food hypersensitivities, and collaborative health practices between patients and healthcare providers. Key research interests include behavioral design, user experience (UX) in healthcare systems, and the intersection of technology with social behavior. She has published in journals like the International Journal of Human-Computer Studies and the ACM CHI Conference proceedings. Her studies often involve participatory design approaches to address real-world challenges, such as improving restaurant safety protocols for allergy sufferers or enhancing patient-doctor data-sharing practices. Chung collaborates with interdisciplinary teams, including the Design Use Build group at UW and the Proactive Health Lab at Indiana University. Her research bridges academic and applied contexts, aiming to create technologies that support long-term health behaviors and interpersonal well-being.

• Machine Learning
• Artificial Intelligence
• Distributed Systems
• +3 more

Ameet Talwalkar is an Associate Professor in the Machine Learning Department at Carnegie Mellon University and Chief Scientist at Datadog. He holds a PhD from the Courant Institute at NYU (2010) where he received the Janet Fabri Prize for Best Thesis. His professional achievements include co-founding Determined AI (acquired by HPE), creating MLlib in Apache Spark, co-authoring the textbook 'Foundations of Machine Learning,' and spearheading the MLSys conference. Talwalkar's research focuses on fundamental challenges in machine learning systems, including distributed ML, federated learning, neural architecture search, and human-AI interaction. His work bridges theoretical foundations with practical applications across domains like computational biology, PDE solving, and code generation. Current interests include AI for science, specialized model development, and agent-based systems. His publications demonstrate strong focus on ML systems optimization, foundation model evaluation, and interpretable AI. Recent works investigate specialized foundation models, PDE-solving frameworks, code generation tools, and human-AI interaction paradigms. The research consistently targets efficiency, scalability, and practical deployment challenges. Best Paper Award at EAAMO 2023 Best Student Paper at NYAS ML Symposium 2009 Runner-up for Best Real-world Application at Socal ML Symposium 2017 Janet Fabri Prize for Best PhD Thesis (2010) Talwalkar leads the CMU MLSys Lab focused on scalable ML systems and has served as Board President for the MLSys conference series. His educational contributions include developing courses like 'Machine Learning with Large Datasets' and creating the LEAF benchmark for federated learning and NAS-Bench-360 for neural architecture search.

Min ChiView profile

Professor

• Artificial Intelligence
• Deep Learning
• Reinforcement Learning
• +5 more

Dr. Min Chi is a Professor in the Department of Computer Science at North Carolina State University, where she joined in 2013 as a Chancellor's Faculty Excellence Program cluster hire in the Digital Transformation of Education. Her academic journey includes a Ph.D. and M.S. in Intelligent Systems from the University of Pittsburgh and a B.E. in Information Science and Technology from Xi'an Jiaotong University, China. She completed postdoctoral fellowships at Carnegie Mellon University's Machine Learning Department and Stanford University's Human Sciences and Technologies Advanced Research Institute. Dr. Chi's research focuses on the development and empirical evaluation of cutting-edge Artificial Intelligence, Deep Learning, and Reinforcement Learning frameworks tailored for addressing human-centric challenges. Her work spans multiple domains including advanced learning technologies, AI and intelligent agents, data sciences and analytics, and human-computer interaction. She has made significant contributions to intelligent tutoring systems, healthcare applications, nuclear power systems, and humanitarian efforts such as food distribution and disaster relief. Her publication record demonstrates a strong focus on applying AI techniques to real-world educational challenges, with recent work examining metacognitive knowledge transfer, reinforcement learning for pedagogical policy induction, and deep learning approaches for proactive help in educational settings. Her research also extends to healthcare applications, food distribution systems, and other socially impactful domains. 10 Best Paper, Best Student Paper, and Outstanding Paper Awards Prestigious Alcoa Foundation Engineering Research Achievement Award NSF CAREER Award Dr. Chi leads multiple significant research projects funded by the National Science Foundation, National Institutes of Health, and the Department of Energy, with a total funding exceeding $7 million. Her work bridges theoretical advances in AI with practical applications that address critical societal challenges in education, healthcare, and humanitarian operations.

Susanne IwarssonView profile

Professor

• Gerontology
• Occupational Therapy
• Public Health
• +6 more

Susanne Iwarsson is a Professor in Gerontology and Care for Older People at Lund University's Faculty of Medicine, holding the Mary and Seved Ribbing Professorship since 2005. She also serves as Director of the Centre for Ageing and Supportive Environments (CASE) and Coordinator of the Swedish National Graduate School for Competitive Science on Ageing and Health (SWEAH). Her academic journey includes a PhD in Medical Science (1997) and promotions to Associate Professor (1999) and Professor (2003). She has held leadership roles such as Pro-dean of the Faculty of Medicine (2006-2011) and Coordinator of the strategic research area MultiPark (2012-2014). Her research focuses on environmental gerontology, housing accessibility, and proactive ageing strategies. Key contributions include the Housing Enabler assessment tool and studies on ageing populations' participation in society. She has supervised 18 PhD students and 6 licentiates, with ongoing supervision of 4 current PhD candidates. Major projects include the Home, Health and Disability longitudinal study (2002-present) and the UserAge program exploring user participation in ageing research. Awards include the Excellent Teaching Practitioner title (2010) and Doctor Honoris Causa. Her work addresses UN Sustainable Development Goals related to health, sustainable cities, and reduced inequalities. Collaborations span universities in Sweden, Finland, Latvia, and the U.S., with partnerships in healthcare and municipal sectors.

Mikael B. SkovView profile

Professor

• Human-Computer Interaction
• Artificial Intelligence
• Robotics
• +6 more

Mikael B. Skov is a Vice Dean and Professor at the Technical Faculty of IT and Design of Aalborg University , Denmark. His research spans human-AI interaction, robotics, and user experience, with a focus on trust signaling in clinical AI, swarm robotics, and sound zones for domestic environments. Role: Vice Dean for Research Department: Computer Science Research Interests: Skov investigates how humans interact with AI and robots in healthcare and domestic settings, emphasizing trust calibration, alert design, and acoustic comfort. His work includes developing frameworks for UX maturity in robotics organizations and studying long-term adoption of sound zone systems. Recent Projects: As principal/co-investigator, he leads the HERD project on human-AI collaboration in robot swarms (2021–2025) and supervises Data og Bæredygtig Mad (2020–2023), an HCI perspective on sustainable food systems. Publications: His 2024 work includes studies on AI explanations in clinical training, music applications with intermittent interactions, and multi-robot supervision. Earlier projects (2001–2020) focused on mobile device usability, UX practices, and context-aware computing.

Grace LimView profile

Assistant Professor

• Organizational Behavior
• Diversity and Inclusion
• Social Class in Organizations
• +5 more

Grace Lim is an Assistant Professor in the Department of Management at the Nanyang Business School, Nanyang Technological University, Singapore. Her research focuses on inclusion, diversity, and the empowerment of disadvantaged employees in organizations, particularly those from lower social class backgrounds and women. Education: Ph.D. in Business (Organizational Behavior and Human Resources), Singapore Management University B.Sc. in Psychology, National University of Singapore Her research employs a range of methodologies, including field surveys, experiments, archival data, and qualitative methods, to ensure robust and generalizable findings. She investigates how individuals can exercise agency to overcome structural disadvantages in the workplace, contributing to the fields of organizational behavior, human resources, and social psychology. Her recent publications reflect a strong trend in studying diversity, inclusion, and equity, with a focus on social class, gender, leadership, and employee well-being. The research spans interdisciplinary themes, integrating insights from psychology, management, and sociology to understand workplace dynamics. Scientific Contributions: Published in top-tier journals such as Organizational Behavior and Human Decision Processes and Academy of Management Annals Research on social class, gender, inclusion, and leadership has been influential in shaping organizational practices Dr. Lim is actively involved in advancing knowledge in organizational behavior and human resources. She has not supervised any listed students yet but continues to contribute through impactful research and academic engagement. She is a member of the Centre for Leadership and Cultural Intelligence at NTU, collaborating on initiatives related to cultural intelligence and inclusive leadership.

Karen PanettaView profile

Professor

• Signal Processing
• Image Processing
• Simulation Modeling
• +6 more

Karen Panetta is a Professor at Tufts University School of Engineering with appointments in Electrical and Computer Engineering, Computer Science, Mechanical Engineering, and Academic Services. She currently serves as Dean of Graduate Education for the School of Engineering and holds the title of Distinguished Professor. Ph.D. in Electrical Engineering, Northeastern University M.S. in Electrical Engineering, Northeastern University B.S. in Computer Engineering, Boston University Dr. Panetta's research focuses on developing efficient algorithms for simulation, modeling, and signal and image processing for security and biomedical applications. Her work brings together artificial intelligence, machine learning, and visual sensing systems to create solutions for robot vision and biomedical imaging. She develops algorithms inspired by the human visual system to enable machines to 'see' like humans, with applications in homeland security, biomedicine, facial recognition, and search and rescue operations. Her research has significant humanitarian applications, addressing global challenges facing women and children. Dr. Panetta has received numerous prestigious awards including induction into the National Academy of Engineering (2023), the Presidential Award for Science and Engineering Education and Mentoring (2011), and the IEEE Award for Distinguished Ethical Practices (2013). She is a fellow of multiple prestigious academies including the National Academy of Inventors, European Academy of Sciences and the Arts, and IEEE. Member, National Academy of Engineering (2023) Presidential Award for Science and Engineering Education and Mentoring (2011) IEEE Award for Distinguished Ethical Practices (2013) Fellow, National Academy of Inventors Fellow, European Academy of Sciences and the Arts Fellow, Asia-Pacific Artificial Intelligence Association As an educator and mentor, Dr. Panetta founded the nationally acclaimed Nerd Girls program to promote engineering to young students, particularly women. She previously served as worldwide director for IEEE Women in Engineering and editor-in-chief of the IEEE Women in Engineering magazine. Her approach to graduate education emphasizes the importance of building strong collaborative relationships between faculty and students, with a focus on proactive communication and documentation of research progress. Dr. Panetta's humanitarian research applies engineering solutions to global challenges, including developing technology to help doctors find cancerous tumors, security screeners find concealed weapons, and law enforcement agencies find criminals and missing children. Her work demonstrates a commitment to 'Doing The Right Thing' by addressing issues affecting populations with limited resources or 'voice' in society.

• Entrepreneurship
• Psychology of Entrepreneurship
• Entrepreneurial Well-being
• +17 more

Professor Ute Stephan is a Professor of Entrepreneurship at King's Business School, King’s College London, where she is affiliated with the Strategy, International Management & Entrepreneurship department. She is a globally recognized scholar in the psychology of entrepreneurship, with a focus on entrepreneurial well-being, mental health, social entrepreneurship, and the role of culture and institutions. Research Interests: Entrepreneurial well-being, stress, and mental health Social and inclusive entrepreneurship Cross-cultural innovation and national culture Family business and women entrepreneurs Entrepreneurial resilience during crises (e.g., Covid-19) Feedback-seeking and social networks Her recent publications reveal a strong trend toward understanding the psychological and social dimensions of entrepreneurship, particularly how entrepreneurs navigate uncertainty, maintain well-being, and create inclusive impact. Her work integrates insights from organizational behavior, psychology, and management, often using cross-national data and meta-analytic methods. Scientific Awards and Recognition: 2025 JIBS Decade Award Fellow, International Association of Applied Psychology (IAAP) 21st Century Entrepreneurship Fellow Winner, 2016 GLOBE Robert J. House Best Research Paper Award Highly Commended, 2015 GLOBE Robert J. House Best Research Paper Award Nominee, 2021 Journal of Management Scholarly Impact Award She has secured over £3 million in research funding from the European Commission, UK Government, UK research councils, and German institutions. She serves as Associate Editor at Journal of Management and Entrepreneurship Theory & Practice , and previously held editorial leadership roles at Applied Psychology and Journal of International Business Studies . She is an elected board member of the IAAP and chairs its publication committee. She also advises the Founder Mental Health Pledge and is an IfM Research Fellow at IfM Bonn. Labs and Research Teams: Lead investigator of the 25-country study on Entrepreneurship & COVID-19 Principal investigator of the WEWell project on women entrepreneurs’ well-being Lead investigator of the SEFORIS and SELUSI projects on social enterprises Team member in large-scale international collaborations across Europe, Asia, and the Americas

Anne Margriet PotView profile

Professor

• Geropsychology
• Long-Term Care
• Mental Health of Older Adults
• +7 more

Anne Margriet Pot is an endowed professor at the Erasmus School of Health Policy & Management (ESHPM), Erasmus University Rotterdam, with a focus on Health Care Governance. She also holds the position of extraordinary professor at Optentia, North West University, South Africa. Additionally, she serves as a strategic advisor for Long-Term Care at the Health and Youth Care Inspectorate, Ministry of Health, the Netherlands, and is President-elect of the International Psychogeriatric Association. She co-chairs the Lancet Commission on Long-Term Care for Older Persons and has advised the World Health Organization (2014–2018). Her research is deeply rooted in improving the mental health and quality of life of older adults, particularly through innovations in long-term care. Key areas include the measurement of care quality, development of technology-based interventions for mental well-being, and the use of narrative methods in care regulation. Her work significantly contributes to the UN Sustainable Development Goals, especially those related to health and well-being. The most recent publications highlight a strong trend toward meta-analytic and scoping review methodologies, focusing on subthreshold depression interventions, narrative approaches in youth and elderly care, and inclusive regulatory frameworks. These works reflect a shift toward evidence synthesis and policy-oriented research with global applicability. President-elect, International Psychogeriatric Association Co-chair, The Lancet Commission on Long-Term Care for Older Persons Strategic Advisor, Long-Term Care, Health and Youth Care Inspectorate, Netherlands Former Advisor, World Health Organization (2014–2018) She has authored over 235 publications, including the influential Dutch Manual on Geropsychology and a recent book on caregiver dilemmas. She is currently establishing a research program on person-centred and integrated long-term care regulation at ESHPM. Her work bridges clinical psychology, health policy, and public governance, with strong international collaborations, particularly in Africa and through global health initiatives. While no formal students are listed, her leadership in large-scale research projects suggests mentorship and team-based research training. She is actively involved in multiple research networks and has contributed to policy development at national and international levels. Her interdisciplinary approach integrates psychology, public health, and narrative ethics to transform long-term care systems.

• Artificial Intelligence
• Data Science
• Machine Learning
• +5 more

Lizi Liao is an Assistant Professor at the School of Computing and Information Systems , Singapore Management University (SMU) , specializing in Artificial Intelligence and Conversational AI . Her research bridges Machine Learning , Natural Language Processing , and Multimodal Systems , focusing on proactive dialogue systems, multimodal conversational search, and task-oriented interactions. Education : PhD in Computer Science (2019) from the National University of Singapore (NUS) , advised by Professor Tat-Seng Chua . Research Interests center on principles of human conversational understanding and machine implementation, particularly in proactive conversational agents , multimodal dialogue systems , and target-driven conversation planning . Key applications include emotional support systems , intelligent shopping assistants , and learning companions . Recent Publications (2024-2025) highlight her work on LLM-based proactive dialogue , multimodal emotion recognition , and dynamic graph modeling , often integrating NLP , Multimedia , and Knowledge Graphs . Collaborative projects with her CoAgent Lab team emphasize human-AI interaction and ethical response generation . Scientific Awards : Google South Asia & Southeast Asia Research Award 2023 Lee Kong Chian Fellow Teaching includes Visual Analytics for Business Intelligence (undergraduate) and Text Analytics and Application (graduate). She also serves as Associate Editor for TOIS and TOMM , and organizes tutorials at ACL , SIGIR , and WSDM .