Find Academic Supervisors

• Mobile Wireless Networking
• Information and Communication Technologies for Development (ICTD)
• Network Measurement
• +5 more

Elizabeth M. Belding is a Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB). She holds leadership roles as an Associate Dean and Faculty Equity Advisor in the UCSB College of Engineering, and serves as Associate Director of the Center for Information Technology and Society (CITS). Her research focuses on mobile/wireless networking, network measurement, and ICTD, with a focus on improving Internet accessibility in underserved regions globally. She has authored over 180 technical papers and led the development of the AODV routing protocol, foundational to standards like 802.11s and Zigbee. Education: Ph.D./M.S. in Electrical and Computer Engineering from UCSB (2000/1997). Awards include ACM and IEEE Fellowships, the 2018 ACM SIGMOBILE Test-of-Time Award, and mentoring accolades. She directs the MOMENT Lab, exploring broadband measurement, rural connectivity, and satellite networks. Recent projects include the NSF-funded PuebloConnect initiative and analysis of US broadband inequities via the Connect America Fund. Research emphasizes socially impactful solutions, including tribal community internet access, disaster communication (e.g., refugee camps), and combating gender-based violence via social media analysis. She has held leadership roles in the UCSB CS department and campus-wide initiatives, including the Chancellor's Advisory Committee on the Status of Women. Key grants include NSF, Bill & Melinda Gates Foundation, and industry partnerships (e.g., ViaSat). Notable students include Udit Paul (2024 SIGCOMM Dissertation Award) and Jiamo Liu. The MOMENT Lab's work spans technical innovations in mesh networks, cellular coverage, and policy-driven broadband analysis.

Alan RitterView profile

Associate Professor

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +4 more

Alan Ritter is an Associate Professor at the School of Interactive Computing , Georgia Institute of Technology, with additional affiliation to the Machine Learning Center . His research focuses on Natural Language Processing , particularly robust models across domains/languages with fewer labels and efficient resource use, plus data-driven dialogue agents for open-topic conversations. Research Interests : Robust NLP models, cross-lingual transfer, resource-efficient learning, dialogue systems, cultural bias measurement, and privacy-aware language models Students : Mentors Ph.D. students in Georgia Tech's ML and CS programs, including Junmo Kang, Yang Chen, and Duong Minh Le. Alumni include Fan Bai (Ph.D. 2023), Yang Chen (Ph.D. 2024), and Andrew Li (M.S. 2024). Awards : NSF CAREER Award, Amazon Research Award, ACL 2024 Best Social Impact Paper, IUI 2009 Best Student Paper. Recent Work : Studies training budget allocation between supervised and preference-based finetuning, cross-lingual information extraction, cultural bias in LLMs, and privacy risk mitigation in social media disclosures. Service : Served as Program Chair for NAACL 2025, Area Chair for multiple top-tier conferences (COLM, EMNLP, ACL, EACL, AAAI). Email : alan.ritter@cc.gatech.edu

Mathieu SalzmannView profile

Academic

• Computer Vision
• Machine Learning
• Deep Learning
• +7 more

Mathieu Salzmann is a Senior Scientist and Lecturer at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Computer Vision Laboratory (CVLAB) in the School of Computer and Communication Sciences (IC). He also holds a courtesy appointment with the EPFL College of Humanities and serves as Deputy Chief Data Scientist at the Swiss Data Science Center (SDSC). He has held concurrent roles in teaching units including SIN, SODH, and SSC, reflecting his interdisciplinary engagement. His research focuses on the intersection of machine learning and computer vision, particularly in deep learning for 2D and 3D visual scene understanding, efficient and robust models, domain adaptation, and interpretable AI. These interests are evident across his extensive publication record in top-tier venues. His recent publications (2023–2024) show a consistent trend in advancing deep learning methods for visual recognition, with strong representation at CVPR, ICCV, ECCV, ICML, ICLR, and NeurIPS. Topics include domain generalization, 3D understanding, model robustness, and multimodal learning, often with applications in real-world systems. His editorial roles as Associate Editor for IEEE TPAMI and Action Editor for TMLR further highlight his leadership in the field. Area Chair: ICML 2023, CVPR 2023, ICCV 2023, NeurIPS 2023, AAAI 2024, ECCV 2024 Associate Editor: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Action Editor: Transactions on Machine Learning Research (TMLR) Mathieu Salzmann has supervised numerous PhD students at EPFL, both current and past, including Bouquet Yann Yanis, Javed Saqib, Li Shuangqi, and others. He has also been involved in research grants and collaborative projects, such as his work with S. Süsstrunk and R. Baroni on comics reconfiguration. His part-time role as Senior GNC Engineer at ClearSpace (2020–2024) illustrates his applied research engagement in aerospace systems. He is actively involved in EPFL’s data science and AI research ecosystem through SDSC and multiple labs.

Catherine LaiView profile

Associate Professor

• Speech and Language Processing
• Computational Linguistics
• Prosody
• +17 more

Catherine Lai is a Reader (~Associate Professor) in the Department of Linguistics and English Language at the University of Edinburgh, with strong affiliations to the Centre for Speech Technology Research (CSTR) and the Institute for Language, Cognition and Computation (ILCC) in the School of Informatics. She is based in the School of Philosophy, Psychology and Language Sciences and is actively involved in research, teaching, and academic service. Department: Department of Linguistics and English Language School: School of Philosophy, Psychology and Language Sciences Research Institutes: Centre for Speech Technology Research, Institute for Language, Cognition and Computation Email: C.Lai@ed.ac.uk Her research centers on the role of prosody—non-lexical aspects of speech—in spoken communication. She investigates how prosody contributes to discourse structure, information structure, and affect in dialogue, using interdisciplinary methods from linguistics and machine learning. Her work bridges theoretical linguistics and practical speech technology, aiming to improve spoken language understanding and synthesis systems. She is particularly interested in how prosody shapes listener expectations and how affect and topic are expressed and perceived in conversation. Her recent publications reflect a strong focus on self-supervised learning in speech models, emotion recognition, ASR error correction using large language models, cognitive state classification, and ethical considerations in language technology. She explores topics such as the uncanny valley in synthetic speech, gender expression through voice, and community-centered development of language technologies. Prize from Scopus Profile Catherine Lai has supervised several PhD students, including Leimin Tian and Yuanchao Li, and has been involved in significant research projects, such as a Toyota-funded initiative on spoken dialogue for robot companions. She has secured multiple grants and leads a research agenda that integrates theoretical inquiry with real-world applications in assistive technologies and social science. Her academic service includes organizing major conferences like Interspeech and UK and Ireland Speech. She is a key member of research teams at CSTR and ILCC, collaborating across disciplines to advance the understanding of spoken communication and the development of robust, ethical speech technologies.

• Uncertainty Reasoning and Decision Making in Artificial Intelligence
• Electronic Business
• Systems Analysis and Design
• +7 more

Liping Liu is a Professor in the Department of Management at The University of Akron's College of Business. He holds a Ph.D. in Business from the University of Kansas (1995), Master of Engineering in Systems Engineering (1991), and dual bachelor's degrees in Applied Mathematics (1986) and River Dynamics (1987). Ph.D., University of Kansas MS, Huazhong University of Science and Technology B.E., Wuhan University BS, Huazhong University of Science and Technology His research spans Artificial Intelligence , Electronic Business , Systems Analysis , Data Quality , and Belief Function Theory . He pioneered coarse utility theory and linear belief functions , now taught in top Ph.D. programs across multiple disciplines. Key trends in his publications include Belief Function Applications (2012-2024), Medical Data Systems (2003-2015), and Decision Theory (2004-2014). Recent works focus on Gamma Belief Functions (2024) and computational improvements in linear belief function operations (2019-2016). Scientific contributions recognized via: Microsoft Azure Educator Grant (2014-2016) Inclusion in Who's Who in America (2010-2013) and Who's Who in the World (2011-2013) As an editor and committee member for major conferences (INFORMS, AMCIS, Belief Functions conferences), he bridges academic research with practical systems implementation in e-business and healthcare domains.

• Strategy
• Management
• Organisational Behaviour
• +10 more

Sam Yam is a Professor and Head of the Management & Organisation Department at the National University of Singapore's (NUS) Business School. He holds the Jardine Cycle & Carriage Professorship and serves as Associate Dean. His research spans strategy, organisational behaviour, applied psychology, ethics, and human-technology interaction. Yam has contributed to over 125 publications, focusing on AI ethics, workplace dynamics, and cross-cultural management. He explores topics like robot replacement effects, abusive supervision, and financial anxiety's intergenerational impacts. His work bridges psychology, ethics, and organisational theory, addressing contemporary challenges in automation, leadership, and human-AI collaboration. Appointments: Head of Management & Organisation (2022–present), Joint Appointment in Arts & Social Sciences (2023–present). Key Research Themes: Future of work, human-technology interaction, ethical leadership, and Machiavellian dynamics. Notable Contributions: Multimodal ADHD diagnostics, leader biases toward robot-using employees, and cultural impacts on team performance. Yam’s interdisciplinary approach integrates psychology, technology, and management, addressing societal issues like AI ethics and workplace automation. His research frequently appears in top journals like the Journal of Management and Annual Review of Organizational Psychology .

• Operations Management
• Supply Chain Management
• Sharing Economy
• +6 more

Ming Hu is a Professor and University of Toronto Distinguished Professor of Business Operations and Analytics at Rotman School of Management, University of Toronto. He serves as Area Coordinator for the Operations Management & Statistics Area and holds editorial leadership roles including Editor-in-Chief of Naval Research Logistics and Associate Editor for multiple top journals. MS in Applied Mathematics, Brown University (2003) PhD in Operations Research, Columbia University (2009) His research focuses on sharing economy , social operations , and platform economics , examining how operational decisions can maximize societal benefit. Key areas include crowdfunding , two-sided markets , crowdsourcing , and group buying , with applications to DEI , sustainability , and AI-empowered operations . Recent work analyzes spatial operations in delivery systems, algorithmic fairness , and climate change adaptation in agricultural supply chains. His publications span top journals like Management Science and Operations Research , covering topics from blockchain traceability to quantum-inspired optimization . Scientific recognitions include: Wickham Skinner Early-Career Research Award (2016) Best Operations Management Paper in Management Science (2017) 2018 Poets & Quants Best 40 Under 40 MBA Professors As an Amazon Scholar (2022–) and Chair of Chain Analytics Institute (2023–), he bridges academic research with industry applications in AI-driven logistics and sustainable operations.

Arvind KarunakaranView profile

Assistant Professor

• Sociology of Work and Occupations/Professions
• Organization Theory
• Technological/Organizational Change
• +4 more

Arvind Karunakaran is an Assistant Professor at Stanford University in the Department of Management Science and Engineering. He holds affiliations with the Center for Work, Technology, and Organization (WTO) , Stanford Technology Ventures Program (STVP) , Stanford Institute for Human-centered Artificial Intelligence (HAI) , and the Digital Economy Lab (DEL) . His research focuses on authority and accountability in the workplace , particularly under technological change and human-AI augmentation. Education: Ph.D. from MIT Sloan School of Management (2018) His work employs ethnographic and field-based methods to study empirical puzzles in workplace dynamics, complemented by comparative-historical analysis and quantitative/textual data analysis . Key research areas include social/algorithmic evaluation of workers , human-AI reskilling , and conflicts in symmetrical relations . Recent publications analyze AI's impact on workplace inequality , platform governance , and crowd-based accountability . His findings are published in top journals like Administrative Science Quarterly and Organization Science . Scientific Awards & Recognitions: Best Published Paper Award (ASA, 2025) Gerard J. Tellis Best Junior Faculty Paper Award (AIM Conference, 2025) W. Richard Scott Article Award (ASA, 2024) Responsible Research in Management Award (RRBM, 2024) Future of Organizations Fellowship (2024) Professor Karunakaran advises doctoral and master's students in areas related to technology and organizations , and teaches courses on organizational behavior , organizational theory , and innovation management .

Cecilie Schou AndreassenView profile

Professor

• Behavioral Addictions
• Social Media Psychology
• Workaholism
• +3 more

Cecilie Schou Andreassen is a Professor at the Department of Clinical Psychology, University of Bergen . She specializes in behavioral addictions , including workaholism, social media addiction, and substance use interactions. Email: cecilie.andreassen@uib.no Visitor Address: Alrek Health Cluster, Årstadveien 17, 5009 Bergen Research Focus: Andreassen's work examines the psychosocial antecedents of addictive behaviors, with emphasis on personality traits , workplace dynamics , and digital platform interactions . Her research spans cross-cultural validation studies and longitudinal health outcomes related to technology and substance misuse. Article Trends (2017-2022): Analyzing 15 recent publications reveals a consistent focus on addiction scale validation , social media epidemiology , and workaholism's health impacts . Key themes include measurement invariance , digital-chemical addiction comorbidity , and psychological withdrawal mechanisms . Scientific Contributions: Co-developer of Bergen Work Addiction Scale Creator of Bergen-Yale Sex Addiction Scale Leadership in behavioral addiction epidemiology Recipient of Norwegian Research Council grants Advising & Collaborations: While no direct advisees are listed, Andreassen collaborates extensively with international researchers in work psychology , social media studies , and public health . Her work involves partnerships with Nottingham Trent University , Yale University , and National Competence Service for Sleep Disorders . Labs & Teams: Affiliated with the Department of Clinical Psychology and previously with the Department of Social Psychology at University of Bergen, she contributes to national health registry studies and cross-occupational research on addiction patterns.

Nagi GebraeelView profile

Professor

• Predictive Analytics
• Machine Learning
• Prognostics and Health Management
• +5 more

Professor Nagi Gebraeel serves as the Georgia Power Early Career Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology, where his research integrates predictive analytics, machine learning, and optimization for industrial IoT applications. His work focuses on real-time equipment diagnostics, prognostics, and operational decision-making in critical infrastructure systems. Education: Ph.D. in Industrial Engineering (2003), Purdue University M.S. in Industrial Engineering (1998), Purdue University Research Focus: Dr. Gebraeel develops statistical learning algorithms for IoT-enabled maintenance, repair, and operations (MRO), with emphasis on federated learning frameworks for distributed fault diagnosis and cybersecurity protection against Industrial Control System (ICS) attacks. His research spans manufacturing, power generation, and deep space habitats through NASA's HOME Space Technology Research Institute, where he pioneers self-aware habitat systems. Recent work addresses data heterogeneity in high-consequence industrial environments using causal-informed analytics. Publication Trends: His 2024-2025 publications demonstrate a strong trajectory toward distributionally robust optimization for maintenance logistics, federated learning architectures for distributed fault diagnosis, and prognostics for complex systems like offshore wind farms and industrial robots. Key themes include handling imbalanced data in fault diagnosis, state-space representations for interdependent systems, and cybersecurity integration in manufacturing networks. Awards and Recognition: NSF CAREER Award (2007) SAE Aircraft Electrical Power System Recognition Award (2008) SAE Materials Modeling and Testing Recognition Award (2006) IEEE-AUTOTESTCON Certificate (2006) Fellow of the Institute of Industrial and Systems Engineers Advising and Funding: Dr. Gebraeel mentors doctoral students including Michael Ibrahim (2025 IISE Best Student Paper winner), Heraldo Rozas (now Assistant Professor at University of Chile), Ayush Mohanty, and Nazal Mohamed. He secured a $500,000 NSF grant in August 2025 for AI-driven cybersecurity in distributed manufacturing networks and leads NASA-funded research on deep space habitat systems. His work bridges academic research with industry applications through Georgia Tech's Strategic Energy Institute collaborations. Research Infrastructure: He directs the Analytics and Prognostics Systems laboratory at Georgia Tech's Manufacturing Institute and leads the Predictive Analytics and Intelligent Systems (PAIS) research group. Previously, he served as associate director of Georgia Tech's Strategic Energy Institute (2014-2019), fostering data science applications in energy systems.

Alenda Y. ChangView profile

Assistant Professor

• Environmental Media
• Game Studies
• Ecocritical Theory
• +3 more

Alenda Y. Chang serves as an Assistant Professor in Film and Media Studies at the University of California, Santa Barbara. With a multidisciplinary background spanning biology, literature, and film, she integrates ecocritical theory with contemporary media analysis. Her scholarly work appears in journals including Interdisciplinary Studies in Literature and Environment , Qui Parle , and electronic book review , focusing on sustainable media practices and ecological frameworks for digital engagement. Her educational background includes: M.A. and Ph.D. in Rhetoric from the University of California, Berkeley M.A. in English Language and Literature from the University of Maryland Chang specializes in environmental media and game studies, developing theoretical frameworks for ecological game design. Her research examines how digital games model environmental systems and foster player engagement with climate change through concepts like "slow violence" and "rambunctious play." She advocates for sustainable design patterns that address gaming's carbon footprint while creating immersive ecological narratives. Analysis of her 15 most recent publications reveals a consistent trajectory from foundational ecological game theory (2013-2018) to current work on thermal contexts of play and sustainable infrastructure (2022-2024). Her scholarship increasingly bridges data-driven activism with critical game design, emphasizing multispecies entanglements and infrastructural play as tools for environmental awareness. As co-founder of Wireframe—a collaborative media studio at UCSB—Chang cultivates critical game design practices through initiatives like growinggames.net . The studio supports data-driven global media art, environmental activism, and experimental pedagogy, serving as a hub for translating ecological theory into tangible digital interventions that challenge anthropocentric perspectives in gaming.

Bernadka DubickaView profile

Clinical Professor

• Mood Disorders
• Adolescent Mental Health
• Depression Treatment
• +3 more

Bernadka Dubicka is a Clinical Professor and Honorary Clinical Chair in the Division of Neuroscience at the University of Manchester. She holds dual roles as a research lead at Pennine Care NHS Foundation Trust and as the child and adolescent mental health research lead for Health Innovation Manchester. She is the Editor-in-Chief of the Journal of Child and Adolescent Mental Health and previously served as Chair of the Child and Adolescent Faculty at the Royal College of Psychiatrists (2017–2021). Her academic qualifications include a BSc in Psychology and MBBs from University College London, followed by FRCPsych accreditation in child psychiatry. She earned a gold medal for her MD thesis on behavioral disorder implications in depression. Dubicka’s research focuses on adolescent depression, mood disorders, and brief interventions, including the IMPACT and STADIA trials evaluating psychological treatments and standardized diagnostic assessments. Her work also addresses technology’s role in youth mental health and the eco-crisis’s mental health impacts. Education: BSc Psychology, University College London MBBs, University of London MD Thesis (Gold Medal), University College London FRCPsych, Royal College of Psychiatrists Her research spans depression treatment efficacy, behavioral activation, and cross-national studies on pediatric bipolar disorder. She collaborates internationally and has led over 49 publications. Awards include a gold medal for her thesis and recognition as an RCPsych Fellow. Her work also emphasizes policy advocacy, such as addressing digital rights for children and mental health responses to climate change (e.g., COP26 contributions). She trains clinicians in brief psychosocial interventions and behavioral activation through academic programs and national courses. Grants & Funding: Co-investigator on the £1.1M HTA-funded STADIA trial evaluating remote mental health assessments. Principal investigator on the IMPACT trial, one of the largest adolescent depression trials globally. Labs/Teams: Collaborations include the University of Cambridge (IMPACT trial), University of Nottingham (STADIA), and international taskforces on treatment-resistant depression.

Helen KennedyView profile

Professor

• Digital Society
• Datafication
• Big Data
• +12 more

Professor Helen Kennedy is a leading scholar in digital society at the School of Sociological Studies, Politics and International Relations , University of Sheffield . She holds the title of Professor of Digital Society and is Director of the £4 million ESRC Digital Good Network. A Fellow of the British Academy (FBA) and the Academy of Social Sciences (FacSS), her work bridges academia and public policy through collaborations with the BBC, DWP, and international media organizations. Her educational background includes a BA in English and American Studies from the University of Birmingham, an MA in Cultural Studies from the Birmingham Centre for Contemporary Cultural Studies (CCCS), and a PhD from the University of East London (2002) on digital identity and multimedia. Helen's research centers on digital inequality, datafication, algorithmic culture, data ethics, and public engagement with data . She investigates how non-expert publics experience and interpret data, visualizations, and AI, with a focus on fairness, transparency, and resistance. Her work also examines data visualization in society , particularly in news media, and the emotional and cultural dimensions of data engagement. Her recent publications reveal a consistent trend in exploring public perceptions of data practices , the politics of data visualization , and ethical dimensions of data use across journalism, public services, and digital platforms. Themes include trust, fairness, emotion, and the socio-political shaping of data systems. Fellow of the British Academy (FBA) Fellow of the Academy of Social Sciences (FacSS) Helen has led numerous major grants from the ESRC, AHRC, Nuffield Foundation, and EPSRC , including projects like Living With Data , Generic Visuals in the News , and Seeing Data . She supervises PhD students on topics ranging from algorithmic bias to digital self-tracking and has completed 13 PhD supervisions. She actively collaborates with policy makers (DWP, BBC, DCMS) , media organizations (Financial Times, Reach PLC) , and NGOs to translate research into impact, particularly in web accessibility and data governance. She leads the Living With Data research programme and is involved in the Everyday Life and Critical Diversities and Science, Technology and Medicine in Society research groups. Her work with the ESRC Digital Good Network brings together academics, practitioners, and civil society to envision equitable digital futures.

Emily WallView profile

Assistant Professor

• Data Visualization
• Visual Analytics
• Cognitive Psychology
• +3 more

Dr. Emily Wall is an Assistant Professor in the Department of Computer Science at Emory University, leading the CAV Lab (Cognition and Visualization). She earned her Ph.D. in Computer Science from Georgia Tech (2020) and completed a postdoctoral fellowship at Northwestern University before joining Emory. Ph.D., Computer Science, Georgia Tech (2020) Postdoctoral Researcher, Northwestern University Current: Assistant Professor, Emory University Her research focuses on enhancing human decision-making through data visualization and visual analytics by addressing cognitive limitations and biases. Key areas include metacognition promotion, computational strategies for bias mitigation, and human-AI collaboration in data analysis. She combines cognitive psychology principles with technical implementation using tools like D3.js and Tableau. Recent publications highlight her work on LLM applications in visual analytics, cognitive bias interventions, and trust calibration in AI systems. Current students like Mengyu Chen, Shiyao Li, and Zhongzheng Xu are presenting at top conferences such as CHI and IEEE VIS. She also explores educational applications through interactive visualization pedagogy and innovative assessment methods. Dr. Wall actively engages in academic service through graduate mentorship, conference judging, and diversity initiatives. Her lab emphasizes both technical proficiency and social justice implications in visualization design, reflected in course projects that merge artistic expression with data-driven storytelling.

• Public Health
• Health Promotion
• Behavioral Science
• +10 more

Rik Crutzen is a Full Professor at the Faculty of Health, Medicine and Life Sciences, Maastricht University, specializing in health promotion and digital interventions. His research focuses on leveraging technology to improve health behaviors across diverse populations, including adolescents, older adults, and immigrant communities. He leads projects in the CAPHRI research group for Promoting Health & Personalised Care. Research trends include: Digital health innovations (e.g., helplines, apps, algorithms) Chronic disease management (post-COVID-19, dementia risk) Health equity in immigrant populations (cervical cancer, maternal care) Behavioral interventions (physical activity, sleep, STI prevention) Systematic reviews and mixed-methods studies He has supervised 22 academic works and contributed to datasets on activity patterns and sleep-activity correlations. His work spans public health policy, health education, and technology integration.