Find Academic Supervisors

Sarah Masud PreumView profile

Assistant Professor

• Human-AI Interaction
• Natural Language Processing
• Applied Machine Learning
• +4 more

Sarah Masud Preum is an Assistant Professor of Computer Science at Dartmouth College, with adjunct roles in the Department of Biomedical Data Science at Geisel School of Medicine and as Faculty Affiliate at the Center for Technology and Behavioral Health (CTBH). She also serves as Technical Associate Director of the Dartmouth Center for Precision Health and Artificial Intelligence. Her work focuses on machine learning for computational health, including natural language processing, temporal modeling, and human-AI interaction to develop personalized decision support systems in healthcare. Education includes a B.Sc. from Bangladesh University of Engineering and Technology, followed by M.Sc. and Ph.D. degrees from the University of Virginia. Previously, she was a postdoctoral research scholar at Carnegie Mellon University's School of Computer Science, recognized as a Rising Stars in EECS (2020) for her academic excellence and contributions to equity in STEM. Her research interests span Human-AI Interaction, Natural Language Processing, Mobile Health, and Cyber-Physical Systems. Over 2020–2023, her publications emphasize AI-driven solutions for healthcare challenges like conflict detection in health information and cognitive assistants for emergency response. Earlier work includes behavioral prediction models (MAPer) and spatial database optimizations (Maximum Visibility Queries). Awards: Rising Stars in EECS (2020) In teaching, she offers courses like Transforming Healthcare through Machine Learning and Machine Learning and Statistical Data Analysis. Her affiliations with multidisciplinary centers reflect her commitment to bridging technology and healthcare.

• Computer Vision
• 4D Vision
• Machine Learning
• +9 more

Professor Adrian Hilton is a distinguished faculty member at the University of Surrey, serving as Director of the Centre for Vision, Speech and Signal Processing (CVSSP) and Director of the Surrey Institute for People-Centred AI. He is affiliated with the School of Computer Science and Electronic Engineering and leads the Visual Media Research Lab (V-Lab). His research focuses on pioneering next-generation 4D computer vision technologies that enable machines to understand and model dynamic real-world scenes. Key areas include 3D/4D shape capture, computer vision, machine learning, graphics, and animation for applications in sports analysis, film/TV production, virtual reality, and medical imaging. His work bridges the gap between real and computer-generated imagery, with notable contributions in volumetric capture, motion capture, and free-viewpoint video. Hilton's recent publications demonstrate a strong trend toward multimodal integration, particularly combining audio and visual processing for spatial audio applications, while advancing 4D reconstruction techniques for human performance capture. His work increasingly incorporates transformer architectures and neural rendering techniques for improved illumination estimation, shadow modeling, and multi-view consistency. Scientific Awards and Recognition Two EU IST Innovation Prizes Manufacturing Industry Achievement Award Royal Society Industry Fellowship (2008-2011) Royal Society Wolfson Research Merit Award in 4D Vision (2013-2018) Fellow of the Royal Academy of Engineering (FREng) Fellow of the International Association for Pattern Recognition (FIAPR) Fellow of the Institution of Engineering and Technology (FIET) Hilton actively mentors PhD and post-doctoral researchers through his leadership of CVSSP, which has a grant portfolio exceeding £31M and comprises 170 researchers. He has successfully commercialized several technologies, including systems used by the BBC for sports commentary visualization. His research collaborations span major industry partners including BBC, BT, Sony, Framestore, and The Foundry. He co-founded the G3 Games forum and the CVMP Conference on Visual Media Production, demonstrating strong engagement with the creative industries. Current research projects include the S3A Programme Grant in Future Spatial Audio and InnovateUK's ALIVE project for 360 video reconstruction.

Mahdi Boloursaz MashhadiView profile

Lecturer

• Artificial Intelligence
• Machine Learning
• Wireless Communications
• +6 more

Mahdi Boloursaz Mashhadi is a Lecturer in Communications and AI at the Institute for Communication Systems (ICS), part of the School of Computer Science and Electronic Engineering at the University of Surrey, UK. He is a Surrey AI Fellow and an IEEE Senior Member, with a focus on advancing AI-driven wireless communication systems. He holds B.S., M.S., and Ph.D. degrees in mobile telecommunications from Sharif University of Technology, Tehran, Iran. Prior to joining Surrey, he served as a postdoctoral research associate at Imperial College London’s Intelligent Systems and Networks (ISN) Research Group (2019–2021). His research interests span AI/ML integration with wireless systems, including semantic communications, federated learning, generative AI for telecom, and beamforming optimization in massive MIMO architectures. He also explores edge computing, distributed deep learning frameworks, and energy-efficient communication designs using reconfigurable intelligent surfaces (RIS). Mahdi has been recognized with the IEEE EWDTS Best Paper Award and IEEE ComSoc Exemplary Reviewer Awards (2021–2022). He leads the UKTIN/DSIT 12M£ national project TUDOR and collaborates with industry on cutting-edge 5G/6G innovations. He has contributed to the ITU’s AI/ML in 5G challenge as a panel judge and serves as an editor for Springer’s Wireless Personal Communications Journal. His roles include advising on government/industry projects and advancing interdisciplinary research at the 5G/6G Innovation Centre. He emphasizes practical implementations of AI in telecommunications, aiming to bridge theoretical advancements with real-world applications.

Douglas K. HartmanView profile

Professor

• Educational Technology
• Learning Technologies
• Human Learning
• +3 more

Douglas K. Hartman is a Professor in the Department of Teacher Education at Michigan State University (MSU) , with a joint appointment in Educational Psychology and Educational Technology. He holds a Ph.D. from the University of Illinois Urbana-Champaign. His research focuses on the application of technologies to enhance human learning across diverse contexts, including schools, communities, workplaces, and sports. Hartman’s work bridges educational theory and practice, emphasizing innovation in teaching methodologies and digital literacy. His research interests span educational technology , new literacies , and technology integration in learning environments. He has contributed to understanding how digital tools impact early childhood education, teacher professional development, and global educational policies. His recent studies explore AI applications in literacy assessment and generative AI’s role in artistic disciplines. Key themes in his publications include cross-cultural educational collaboration (e.g., CLIL approaches in EMI contexts), early literacy development, and teacher roles in online learning. While no awards are explicitly noted, his extensive scholarly output reflects sustained contributions to educational innovation. Hartman’s affiliation with MSU’s College of Education positions him at the forefront of interdisciplinary research, though specific grants or labs are not detailed in the provided texts. He maintains an active research agenda addressing 21st-century challenges in education through technology-driven solutions.

Jia WuView profile

Associate Professor

• Artificial Intelligence
• Data Mining
• Deep Learning
• +7 more

Dr. Jia Wu is an Associate Professor and Research Director of the Centre for Applied Artificial Intelligence at Macquarie University. He holds a PhD in Computer Science from the University of Technology Sydney (2009) and is an IEEE Senior Member. His research focuses on artificial intelligence, data mining, graph neural networks, and anomaly detection, with over 200 publications in top-tier journals/conferences like IEEE TPAMI, TKDE, and conferences like KDD, IJCAI, and NeurIPS. He has received awards including the Heidelberg Laureate Forum Fellowship (2019) and multiple best paper awards. Education: PhD in Computer Science (UTS, 2009). Current roles include Director of HDR (Higher Degree Research) and Associate Editor for IEEE TNNLS and ACM TKDD. He leads projects in AI-driven cybersecurity, personalized banking solutions, and disaster response systems. Research interests emphasize graph-based learning, fake news detection, and deep learning applications. His recent work explores hypergraph neural networks for fraud detection and brain graph analysis for neurological disorders. He has pioneered scalable semi-supervised clustering techniques and transformer-based hypergraph models for anomaly detection. Awards include CIKM'22 Best Paper Runner-Up, ICDM'21 Best Student Paper, and the 2023 Faculty of Science and Engineering Collaboration Award. His work spans 13 active research projects, including mitigating AI deepfakes in identity systems and enhancing disaster response networks through graph-based simulations. Labs/Teams: Leads teams in the Data Horizons Research Centre, Future Communications Research Centre, and Hearing Research Centre. Collaborates internationally in AI, data mining, and social network analysis.

Parinaz NaghizadehView profile

Assistant Professor

• Network Economics
• Game Theory
• Ethics and Economics of AI
• +3 more

Parinaz Naghizadeh is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California San Diego (UCSD), affiliated with the Design Lab. She holds a PhD from the University of Michigan and has prior roles at Ohio State University and postdoctoral positions at Purdue and Princeton. Her research focuses on network economics, game theory, AI ethics, optimization, and cybersecurity. She received the NSF CAREER Award (2022), Rising Stars in EECS (2017), and Barbour Scholarship (2014). Education: PhD in Electrical Engineering (University of Michigan), M.Sc. in Mathematics and Electrical Engineering (University of Michigan), B.Sc. in Electrical Engineering (Sharif University of Technology, Iran). Research Interests: She develops mathematical models to analyze decision-making in complex networks, with emphasis on AI ethics, multi-agent systems, and cybersecurity. Recent work explores biases in AI, strategic classification, and incentive mechanisms for security investments. Article Trends: Her recent publications (2023-2025) address strategic classification challenges, multiplex network equilibria, federated learning fairness, and robust control in cyber-physical systems. Themes include ethical AI, game-theoretic security design, and optimization under uncertainty. Awards: NSF CAREER Award (2022), Rising Stars in EECS (2017), Barbour Scholarship (2014) Advising & Grants: No student advisees listed, but active in securing research grants (e.g., NSF CAREER). Works with interdisciplinary teams in UCSD's Design Lab. Labs/Teams: Affiliated with UCSD's Design Lab, focusing on innovative engineering solutions for societal challenges.

Binil StarlyView profile

Adjunct Professor

• Digital Manufacturing
• Additive Manufacturing
• Tissue Biofabrication
• +5 more

Binil Starly is an Adjunct Professor at North Carolina State University's Edward P. Fitts Department of Industrial and Systems Engineering, part of the College of Engineering. He leads the Data Intensive Manufacturing Laboratory (DIME Lab), focusing on digital-physical integration in manufacturing, additive manufacturing, and biofabrication. His work emphasizes democratizing manufacturing access through machine learning and smart systems. Starly holds a B.S. in Mechanical Engineering from the University of Kerala (2001) and a Ph.D. from Drexel University (2006). He previously worked at the University of Oklahoma on tissue engineering platforms. His research spans digital factories, smart manufacturing, and biometrology, with over 45 journal publications. His awards include the NSF CAREER Award (2009), SME Young Manufacturing Engineer Award (2011), and multiple teaching/research recognitions at NC State. He teaches courses on product development, additive manufacturing, and Python for industrial engineers. Starly’s research trends emphasize blockchain in manufacturing ecosystems, cybersecurity for IoT devices, and knowledge graphs for service discovery. He co-leads the Functional Tissue Engineering (FTE) Program, integrating regenerative medicine with scalable manufacturing processes. His grants focus on smart manufacturing innovation, blockchain platforms, and real-time bioprinting monitoring. He advises 7 graduate and 3 undergraduate students, having guided 22 M.S. and 6 Ph.D. students. His outreach includes online courses on smart manufacturing and Python programming through NC State’s Wolfware Outreach. The DIME Lab develops advanced manufacturing technologies, including digital twins for industrial metaverse applications and machine authentication systems. Collaborations span academia, industry, and government to advance personalized manufacturing solutions.

Matthew DuvallView profile

Lecturer

• Technology-Enhanced Learning
• Game-Based Learning
• Computational Thinking
• +4 more

Matthew Duvall is a Lecturer at the University of Pennsylvania’s Graduate School of Education. His career spans roles as a computer programmer, high school teacher, instructional designer, and writer. His research focuses on leveraging technology to create inclusive learning experiences, particularly for underserved populations. He specializes in game-based learning, computational thinking, teacher professional development, and corporate training. Dr. Duvall’s work includes directing the Skyscraper Games project at Drexel University’s ExCITe Center, where middle school students designed video games displayed on Philadelphia’s Cira Centre. His dissertation explored using Goodreads to engage high school students in English language arts. He has also designed corporate training programs informed by learning science frameworks. His research trends emphasize bridging educational technology with practical applications, such as evaluating serious games, refining teacher feedback models, and integrating literacy tools like Goodreads into classrooms. His articles reflect a focus on equity, innovative pedagogy, and technology’s role in fostering authentic learning experiences. While no specific awards are listed, Dr. Duvall’s projects highlight impactful contributions to educational equity and technology integration. He collaborates with teams like the ExCITe Center and organizations serving individuals with autism, emphasizing collaborative approaches to educational innovation.

Arianne TeheraniView profile

Professor

• Health Professions Education
• Educational Equity and Social Justice
• Climate Change and Health
• +12 more

Arianne Teherani, PhD, is Professor in Residence in the Department of Medicine at the University of California, San Francisco (UCSF) School of Medicine. She serves as Founding Co-Director of the UC Center for Climate, Health and Equity and Director for Program Evaluation and Education Continuous Quality Improvement at the UCSF School of Medicine. She earned her undergraduate degree in Social Ecology from the University of California, Irvine, her master's and doctorate in Education from the University of Southern California, and completed a fellowship in Higher Education at the University of British Columbia. Dr. Teherani’s research advances equity, social justice, and climate solutions in health professions education. Her work identifies and dismantles practices that perpetuate educational disparities. She leads initiatives in equitable clinical assessment, climate-health education, and sustainable healthcare training. Her scholarship focuses on educational reform, faculty development, and community-engaged learning. She has published extensively on topics including clerkship equity, professionalism, longitudinal integrated clerkships, and the integration of climate change into medical education. Her recent publications demonstrate a strong trend toward climate-health education, healthcare decarbonization, and equity in assessment. She frequently collaborates with national and UC-system-wide teams on sustainability and educational innovation. Her work emphasizes systems-level change and the translation of research into policy and practice. UCSF Faculty Sustainability Award UC Sustainability Champion Award Faculty Climate Action Champion (University of California system) Dr. Teherani mentors students, residents, fellows, and faculty in health professions education. She has led numerous educational initiatives, including the Aspiring Physicians Program and the Academic Leadership Academy, aimed at supporting underrepresented students. She has also driven continuous quality improvement in medical education through rigorous evaluation of innovative programs. Her leadership extends to national organizations including the Association of American Medical Colleges, the American Educational Research Association, and the National Academies of Science, Engineering, and Medicine. She leads the Equity and Justice in Education initiative and is deeply involved in antiracism and DEI efforts. She co-leads faculty development programs focused on sustainable healthcare and climate education across the UC system.

Federico BecattiniView profile

Assistant Professor

• Computer Vision
• Deep Learning
• Artificial Intelligence
• +7 more

Federico Becattini is a Tenure-Track Assistant Professor at the Department of Information Engineering and Mathematics (DIISM), University of Siena, Italy. He is an active member of the Siena Artificial Intelligence Lab (SAILab), where he contributes to cutting-edge research in computer vision, deep learning, and artificial intelligence. His work spans multiple interdisciplinary domains, including autonomous driving, human behavior understanding, cultural heritage, neuromorphic vision, and fashion recommendation. His research interests center on memory-based neural networks , which he has applied in numerous publications at top-tier venues such as CVPR, ECCV, IEEE TPAMI, and ACM TOMM. He has also delivered tutorials on this topic at international conferences including ICIAP 2022 and ACM MM 2022, and taught a Ph.D. course at the University of Florence. His recent work is aligned with the Collectionless AI paradigm, which emphasizes continual learning and interaction with dynamic environments. The recent publications highlight a strong trend in human-centric AI , focusing on understanding people through multimodal analysis of face, body, and clothing, as well as generating 3D virtual avatars. There is also a clear emphasis on memory-augmented architectures for temporal reasoning, explainability, and adaptive learning. His editorial role as Associate Editor of the International Journal of Multimedia Information Retrieval further underscores his standing in the research community. Associate Editor, International Journal of Multimedia Information Retrieval (IJMIR) Organizer, Workshop on Facial and Body Expressions (ICPR2020) Co-organizer, T-CAP Workshop (ICIAP2021, ICPR2022) Co-organizer, MCFR Workshop (ACM MM 2022) Co-organizer, WCPA Workshop and Challenge (ECCV 2022) Federico Becattini actively advises students and researchers within SAILab, particularly in the context of Ph.D. theses and research projects related to Collectionless AI and memory-based models. While specific grants are not mentioned, his extensive publication record and leadership in workshops and editorial roles suggest involvement in funded research initiatives. He collaborates with both academic and international research communities, serving as a reviewer for top-tier conferences and journals. He is a core member of the SAILab research group, which is pioneering the Collectionless AI initiative—a framework for continual learning over time, interacting with humans and agents without relying on pre-built static datasets. This lab serves as a hub for innovation in adaptive and sustainable AI systems.

• Civil Law
• Succession Law
• Family Law
• +10 more

Maria Elena Cobas Cobiella is an Associate Professor in the Department of Civil Law at the Faculty of Law, University of Valencia. Her academic work is deeply rooted in civil and private law, with significant contributions to inheritance, family, mediation, and European private law. She is an active member of two research groups: the GPF Research Group on Person and Family and the GEDPED Study Group on European Private and Digital Law. Research Interests: Her research spans civil law, succession law, bio-law, legal mediation, reproductive rights, and legal education. She has explored the legal implications of posthumous reproduction, European succession instruments, Cuban property law, and innovative teaching methods such as concept mapping and cooperative learning in legal education. Her work often bridges doctrinal analysis with practical and ethical considerations. The trends in her scholarly publications from 2001 to 2017 reflect a sustained focus on succession law and legal modernization, with increasing attention to European harmonization, digital law, and interdisciplinary issues in bio-law. Her articles also reveal a strong commitment to pedagogical innovation and comparative legal analysis, particularly between Spanish and U.S. legal systems. Scientific Contributions: PhD from the University of Valencia (2001) on testamentary executorship. Active researcher in European private and digital law. Prolific author on mediation, inheritance, and legal education. Advising and Grants: While no specific grants are listed, she has supervised PhD research, as evidenced by her role as advisor to Dr. Lorenzo Prats Albentosa’s thesis. She actively contributes to academic discourse through publications and research group leadership. Her work in legal education suggests involvement in curriculum development and pedagogical projects. Labs and Teams: She collaborates with the GPF Research Group on Person and Family and the GEDPED Study Group on European Private and Digital Law, indicating active participation in team-based legal research focused on contemporary civil law challenges.

Jennifer M MortonView profile

Professor

• Poverty
• Social Class
• Agency and Rationality
• +5 more

Jennifer M Morton is the Presidential Penn Compact Professor of Philosophy at the University of Pennsylvania with a secondary appointment at the Graduate School of Education. As Graduate Chair of the Philosophy Department, she bridges philosophical theory with empirical research on poverty, social class, and upward mobility. Her work interrogates the ethical sacrifices of first-generation and low-income students, earning her the Grawemeyer Award in Education (2023) and the Frederic W. Ness Book Award for Moving Up Without Losing Your Way (2019). A Guggenheim Fellow (2023-2024), she integrates social psychology, policy analysis, and ethics to address structural inequities in education. Key Themes: Pessimism traps, cultural mismatch, and non-cognitive skill development. Awards: Grawemeyer Award, Scheffler Prize, Philosopher’s Annual Best Paper (2019). Media: Featured in The New York Times , The Atlantic , and Hidden Brain podcast. Her recent articles analyze poverty’s impact on prospective agency, planning capacity, and decision-making under uncertainty. She critiques online education’s limitations for marginalized students and explores the educator’s dual role in ideal vs. non-ideal contexts. As a senior fellow at Wisconsin’s Center for Ethics and Education, she advocates for inclusive institutional design, balancing pragmatic success with systemic critique.

Snigdha ChaturvediView profile

Associate Professor

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +8 more

Snigdha Chaturvedi is an Associate Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. She previously held faculty positions at the University of California, Santa Cruz, and has conducted postdoctoral research at the University of Pennsylvania and University of Illinois, Urbana-Champaign. PhD in Computer Science from University of Maryland, College Park Bachelor's degree in Computer Science and Engineering from Indian Institute of Technology (IIT) Kanpur Her research spans Natural Language Processing with emphasis on Narrative Understanding , Text Summarization , and Socially Aware Language Generation . She advances Fairness in AI through ethical NLP applications in Mental Health and Educational Technology . Recent work focuses on 2025 publications in ACL and NAACL journals, alongside 2024 contributions to EMNLP Findings and ICLR . Earlier projects include the NarraSum dataset (2022) and MOOC forum analysis (2020). Scientific recognitions include: ACM Student Research Competition First Place (2014) IBM PhD Fellowship (2014-2015, renewed in 2015) Kulkarni Summer Research Fellowship (2015) WPI STEM Faculty Launch Program Participant (2015) Her team has advised 13 PhD and Master's students with notable placements at Bloomberg, AI2, and University of Southern California. Research integrates Accessibility challenges through collaborations with Google and IBM labs.

Kristy RobinsonView profile

Associate Professor

• Educational Psychology
• Student Motivation
• Classroom Environment
• +4 more

Kristy Robinson is an Associate Professor in the Department of Educational and Counselling Psychology at McGill University , where she investigates classroom teaching practices and contextual factors that enhance student motivation and wellbeing. Her research program focuses on creating theoretical and empirical frameworks to support equitable instructional strategies for students' goal achievement. SSHRC-funded researcher FQRSC grant recipient Key Research Areas Motivational climate theory Expectancy-value-cost models STEM education equity Self-determination theory Emotion dynamics in learning Awards & Recognition Canadian Psychological Society President's New Researcher Award AERA Division C Outstanding Early Career Scholar AERA Motivation SIG Wilbert C. McKeachie Early Career Award Top-Producing Educational Psychology Scholar (2024) Research Platforms Director of MILES Lab (Motivation, Instructional, and Learning Experience Study) Developer of "mFlip" flipped classroom framework

Abigail JohnsonView profile

Assistant Professor

• Microbiome
• Nutrition
• Obesity
• +6 more

Abigail Johnson, PhD, RD is an Assistant Professor in the Division of Epidemiology & Community Health at the University of Minnesota. She also serves as the Associate Director of the Nutrition Coordinating Center (NCC) and is a Member of the Masonic Cancer Center (MCC). Dr. Johnson earned her PhD in Nutrition and completed her Registered Dietitian (RD) training at the University of Minnesota, where she also obtained her BS in Nutrition Science and Biology. Her research explores the relationships between diet and the human gut microbiome in health and disease using novel computational methods for dietary data. Her current focus areas include: analysis of diet and microbiome after dietary interventions, methods development for dietary data analysis and visualization, and understanding the interactions between foods, microbes, and fungi during different stages of development. She is particularly interested in how diet and the microbiome interact to influence chronic diseases including prediabetes, diabetes, and cancer. Dr. Johnson's research demonstrates significant trends in microbiome analysis, dietary assessment, and computational methods. Her work increasingly focuses on personalized nutrition approaches, longitudinal microbiome dynamics, and the integration of multi-omics data to understand diet-microbe-host interactions in disease contexts. Her scientific contributions include: Development of methods for dietary data analysis and visualization Research on diet-microbiome interactions in chronic diseases Studies on how immigration and dietary changes affect the gut microbiome Investigations into personalized diet-microbiome associations Dr. Johnson actively mentors students and researchers in the fields of nutritional science, microbiome research, and computational biology. Her work has been supported by various research grants focused on understanding the complex relationships between diet, the microbiome, and human health.