Find Academic Supervisors

• Statistical Machine Learning
• Deep Learning
• Computational Biology
• +2 more

Rui Li is an Associate Professor in the Ph.D. program at Rochester Institute of Technology's Golisano College of Computing and Information Sciences. She directs the Lab for Use-inspired Computational Intelligence (LUCI), focusing on AI applications in computational biology and medical imaging. Education includes: B.Sc. in Computer Science, Harbin Institute of Technology M.Sc. in Computer Science, Tianjin University of Technology Ph.D. in Computing and Information Sciences, RIT Research integrates statistical machine learning with computational biology, medical image analysis, and human visual attention modeling. Current projects include deep learning for histopathology, multimodal medical image registration, and gene network inference. Publications demonstrate consistent focus on medical AI applications, with recent advances in unsupervised image registration, interactive segmentation, and multimodal fusion techniques. Key trends include self-supervised learning, uncertainty-aware models, and human-AI collaboration frameworks. Awards include the NSF CAREER Award for developing adaptive machine intelligence systems. Advises multiple PhD students on projects spanning deep learning architectures, biomedical image analysis, and biological network modeling. Leads several NSF-funded projects including human-centered image understanding systems and gene-protein network inference tools. Directs LUCI lab investigating machine learning for healthcare applications and teaches graduate courses in Statistical Machine Learning and Deep Learning.

Chitraleema ChakrabortyView profile

Assistant Professor

• Quantum Emitters
• 2D Materials
• Quantum Optics
• +5 more

Dr. Chitraleema Chakraborty is an Assistant Professor in the Departments of Materials Science and Engineering and Physics and Astronomy at the University of Delaware. Her research focuses on solid-state quantum emitters, 2D materials, and quantum optics, aiming to develop quantum technologies for computing, communication, and sensing. She combines computational and experimental approaches to predict, fabricate, and image quantum emitters integrated with photonic devices. Education: Ph.D. in Materials Science, University of Rochester (2018) Dual MS and MTech in Nanophysics and Nanostructures, University of Delhi and Joseph Fourier University, Grenoble (France) BSc Honors in Physics, Jadavpur University, Kolkata (2009) Research interests include quantum emitters in 2D materials, integrated photonics, and hybrid quantum systems. Her work bridges theoretical predictions and experimental validation to advance applications in quantum information and nanoscale sensing. Publications highlight advancements in strain-tunable quantum emitters, on-chip photonic integration, and room-temperature ferromagnetism in van der Waals materials. Recent trends emphasize scalable synthesis methods and defect engineering for quantum technologies. Awards: Carl E. Anderson Outstanding Doctoral Thesis Finalist (2019) Rising Star in EECS (2019) Outstanding Dissertation Award, University of Rochester (2018) Best Student Speaker at MRS Fall Meeting (2017) Egide Scholar, France (2010-2011) Her research group actively explores nanoscale confinement effects and electrical tuning of quantum systems. Collaborations focus on integrating 2D materials with photonic platforms for scalable quantum devices. Ongoing projects aim to develop robust quantum emitters for real-world applications.

• Game Theory
• Control Systems
• Stochastic Processes
• +5 more

Tamer Başar is a Maybelle Leland Swanlund Endowed Chair Emeritus and Professor Emeritus of Electrical and Computer Engineering at the University of Illinois' College of Engineering. He leads research in game theory, control systems, and networked systems through the Coordinated Science Lab. His work focuses on stochastic processes, multi-agent systems, and optimization under uncertainty. Research interests include Nash equilibrium analysis, mean-field theory, and reinforcement learning applications in dynamic systems. Recent publications explore strategic incentives in large population games, nonstationary reinforcement learning, and coupled bi-virus models. Notable honors include the IEEE Control Systems Award (2014), American Academy of Arts and Sciences Membership (2023), and honorary doctorates from multiple institutions. His work bridges theoretical foundations with practical applications in socio-technical networks and edge computing systems. Basar's contributions span over 900 publications, focusing on distributed control algorithms, network security, and strategic information design. His research lab at Illinois addresses challenges in timely computation, resilient systems, and decentralized decision-making frameworks.

Naseem ChoudhuryView profile

Professor

• Neuroscience
• Developmental Psychology
• Infant Information Processing
• +3 more

Dr. Naseem Choudhury is a Professor of Psychology and Neuroscience at Ramapo College of New Jersey, affiliated with the School of Social Science and Human Services (SSHS). She holds a Ph.D. in Experimental Psychology from the University of Vermont. Her research focuses on the neural basis of infant information processing, particularly how perceptual abilities influence typical and atypical development, with an emphasis on familial and sociocultural factors. Her work spans auditory processing in infants at risk for developmental language disorders, electrophysiological studies in children with autism, and cross-cultural analyses of artistic perception. She directs the Palestroni Integrated Neuroscience Lab, exploring neural mechanisms underlying cognitive development. Dr. Choudhury has published extensively in journals like Journal of Neuroscience and Developmental Cognitive Neuroscience , with over 50 peer-reviewed articles since 2002. Her studies often involve ERP and EEG methodologies to track developmental milestones and intervention efficacy in high-risk populations. Her research demonstrates that early auditory experiences shape prelinguistic acoustic mapping and that neuroplasticity interventions improve outcomes for language-impaired children. She collaborates internationally on projects linking sensory perception to linguistic outcomes, particularly in Italian and bilingual populations. Dr. Choudhury’s contributions bridge basic neuroscience and clinical applications, emphasizing early screening and preventive strategies for developmental disorders.

Huazheng WangView profile

Assistant Professor

• Reinforcement Learning
• Information Retrieval
• Machine Learning
• +4 more

Huazheng Wang is an Assistant Professor in the School of Electrical Engineering and Computer Science at Oregon State University. His research focuses on reinforcement learning, information retrieval, and trustworthy AI. He received his Ph.D. from the University of Virginia (2021) and B.E. from the University of Science and Technology of China (2015). He holds awards including the 2025 EECS Fabulous Teacher Recognition and SIGIR 2019 Best Paper Award. His work addresses challenges in robust reinforcement learning, adversarial attacks on bandit systems, and applications in scientific discovery. Education: Ph.D., Computer Science, University of Virginia (2021) B.E., Computer Science and Technology, University of Science and Technology of China (2015) Research interests emphasize developing efficient algorithms for reinforcement learning, multi-armed bandits, and their applications in recommendation systems, protein optimization, and security. Notable contributions include provably efficient risk-aware reinforcement learning frameworks and adversarial attack analysis on bandit systems. Recent work includes NSF-funded research on neural bandits (IIS-2403401) and publications in top venues like ICML, NeurIPS, and AAAI. His lab explores embodied LLM agents for team cooperation and federated collaborative online monitoring frameworks.

Amalia FokaView profile

Assistant Professor

• Artificial Intelligence Applications in Arts
• Computer Science for Creative Practices
• Digital Interaction
• +4 more

Amalia Foka is an Assistant Professor in Computer Science Applications for the Arts at the Department of Fine Arts & Art Sciences , School of Fine Arts , University of Ioannina , Greece. She has held academic positions at the University of Patras (2005-2013), University of Ioannina (2005-2008), and Computer Technology Institute & Press "Diophantus" (2014-2015). Her research bridges Artificial Intelligence with Digital Art , focusing on Generative AI , Social Media Mining , and Human-Computer Interaction within artistic contexts. Education: BEng in Computer Systems Engineering (1998) from the University of Manchester Institute of Science & Technology (UMIST) , UK MSc in Advanced Control (1999) from UMIST PhD in Robotics (2005) from the Department of Computer Science , University of Crete Her artistic research includes projects like Bushwalking (StyleGAN2 landscape generation), Breaking the Silence (NLP analysis of taboo topics), and The Invisible Structures of the Artworld (social media-driven network visualization). She leads the Multimedia Lab at the University of Ioannina, focusing on AI in Creative Processes and Digital Interaction methodologies.

Rozenn DahyotView profile

Professor

• Computer Vision
• Machine Learning
• Digital Signal Processing
• +4 more

Rozenn Dahyot is a Professor of Computer Science at Maynooth University within the Faculty of Science & Engineering. She previously held roles as Assistant and Associate Professor in Statistics at Trinity College Dublin (2008-2021) and Lecturer in Computer Science (2005-2008). Her research interests bridge Digital Signal Processing, Computer Vision, Machine Learning, and Statistical Analysis. She organized the European Signal Processing Conference (EUSIPCO2021) in Dublin and served as President of the Irish Pattern Recognition and Classification Society (IPRCS) from 2014-2020. Her work spans topics like semantic scene understanding, CNN compression, and medical image segmentation. Key contributions include advancements in graph-based image analysis, reinforcement learning optimization, and AI-driven systems for disaster management. Dahyot is a member of IEEE, ACM, and EURASIP, contributing to both academic and industrial collaborations.

Ananth GramaView profile

Professor

• Parallel Computing
• Distributed Systems
• Machine Learning
• +7 more

Ananth Grama is the Samuel D. Conte Distinguished Professor of Computer Science and Associate Director of the Center for Science of Information at Purdue University. He holds a faculty position in the Department of Computer Science, College of Science. His research focuses on parallel computing, distributed systems, machine learning, and their applications in complex systems such as materials modeling and clinical analytics. He teaches advanced courses like CS525 (Parallel Computing) and CS314 (Numerical Methods). Research interests span parallel algorithms, fault-tolerant learning, quantum machine learning, and data-driven healthcare analytics. Recent work addresses fundamental limits of generative models, online learning under noisy conditions, and clinical outcome predictions. His projects include DOE-funded research on critical element recovery and NIH grants for hearing assessment technologies. Notable contributions include over 50 peer-reviewed publications since 2022, with recent papers appearing at ICLR, NeurIPS, and ICML. Current postdocs include Changlong Wu (collaborating with Wojciech Szpankowski) and Luopin Wang (with Nadia Atallah). He advises seven graduate students and oversees multidisciplinary research teams.

• Computational Design
• Architectural Education
• Artificial Intelligence in Architecture
• +9 more

Assoc. Prof. Dr. Sema Alaçam Doğan has been affiliated with Istanbul Technical University since 2014, serving as an Associate Professor in the Department of Architecture . She has held administrative roles including Deputy Head of Department and Erasmus Coordinator. Education : PhD in Informatics in Architectural Design (2008-2014), MS in Informatics in Architectural Design (2005-2008), and BS in Architecture (1999-2005) from Istanbul Technical University. Her research explores Computational Design , Artificial Intelligence in Architecture , and Sustainable Material Innovation . She investigates digital tools for heritage preservation, daylight optimization in BIM, and cognitive development in architecture students. Recent publications analyze AI-assisted design literacy , machine learning for Sinan mosques , and environmental comfort in Harran houses . Her work integrates algorithmic frameworks with sustainable practices. Scientific awards include multiple ITU Publication and Performance Awards (2021-2024), FABFEST Prizes , and the 2024 Artemis Educator Award from NASA. Active projects like "Physical Computation in Architectural Drawing" and "Robotic Fabrication with Recycled Wind Turbine Blades" demonstrate her leadership in computational and sustainable research.

Sascha StruweView profile

Research Fellow

• Service Innovation
• Service Design
• Value Co-Creation
• +4 more

Sascha Struwe serves as a Postdoctoral Researcher at Aalborg University Business School within the Faculty of Social Sciences and Humanities, actively contributing to the International Business Research Group. Based at Fibigerstræde 11 in Aalborg Øst, Denmark, Struwe operates at the intersection of service innovation theory and business practice with international focus. Research expertise centers on service innovation , value co-creation , and digital servitization , particularly examining B2B contexts and open banking ecosystems. Work consistently explores institutional influences through German-Chinese case studies, addressing how cultural and regulatory frameworks shape service design. Recent trajectories reveal evolution from foundational service design challenges (2019-2021) toward digital transformation implications (2022-2023), with emphasis on value co-destruction mechanisms in financial ecosystems. Struwe led the PhD project Innovating the Invisible and Intangible: Value Creation in B2B service (2018-2021) investigating co-creation capabilities across industrial sectors. Academic engagement includes conference participation at EIBA and CICALICS events, plus a visiting researcher appointment at Fudan University's Nordic Centre (2019-2020). Current work continues through the International Business Research Group, focusing on digital literacies and service ecosystem resilience.

Mike KirbyView profile

Professor

• Scientific Computing
• Physics-Informed Machine Learning
• Computational Science and Engineering
• +4 more

Mike Kirby is a Professor at the Kahlert School of Computing, University of Utah. He also holds adjunct professorships in the Department of Bioengineering and the Department of Mathematics. His current roles include leadership in scientific computing and informatics initiatives, including former directorships of the Utah Informatics Initiative (2019-2023) and the Multi-Scale Multidisciplinary Modeling of Electronic Materials (MSME) Collaborative Research Alliance (2016-2022). He has extensive experience in strategic research initiatives, including serving as Assistant Vice President for Research (2024-2025). Education: Dr. Kirby earned a PhD in Applied Mathematics (2002) and MS in Computer Science (2001) from Brown University, and a BS in Applied Mathematics and Computer Science from Florida State University (1997). Research Interests: Focus on large-scale scientific computing, physics-informed machine learning, computational science and engineering, high-order numerical methods, and visualization. His work bridges applied mathematics and computer science to address real-world engineering challenges. Publications: Over 150 peer-reviewed articles, including high-impact contributions in journals like Journal of Computational Physics and SIAM Journal on Scientific Computing . Recent work emphasizes machine learning for differential equations, topology optimization under uncertainty, and multi-fidelity modeling. Awards: Recognized for leadership in computational science and informatics, including contributions to University of Utah’s Clery Compliance Program. Advising & Grants: Supervised over 50 graduate students and postdocs. Secured funding from NSF, DOE, and industry partnerships, totaling millions in research grants. Active in interdisciplinary collaborations across engineering, materials science, and medicine. Labs/Teams: Scientific Computing and Imaging (SCI) Institute, Utah Informatics Initiative, and the Center for Multiscale Modeling of Electronic Materials (MSME).

Beth St. JeanView profile

Associate Professor

• Health Informatics
• Health Justice
• Consumer Health Information Behavior
• +3 more

Beth St. Jean is an Associate Professor and Faculty Director of the Carillon Community in Health Justice at the University of Maryland’s College of Information Studies (College Park). She holds a PhD and MS in Information from the University of Michigan School of Information and a BA in Mathematics from Smith College. Her research focuses on improving health outcomes through understanding health-related information behaviors, health literacy, and self-efficacy. She co-authored Understanding Human Information Behavior (2021) and leads projects like HackHealth to enhance youth health literacy. Education: PhD in Information, University of Michigan School of Information (2012) MS in Information (LIS), University of Michigan School of Information (2006) BA in Mathematics, Smith College (1988) Research Interests: Health informatics, health justice, consumer health information behavior, health literacy, youth digital practices, and information literacy. Her work emphasizes addressing health disparities through information access and education. Recent Research Trends: Her publications explore topics like long-haulers’ information needs (2024), pandemic-era health justice (2023), and social media’s role in predicting health disparities (2022). She also investigates patient-generated health data challenges (2022) and library roles in promoting health equity (2020). Awards and Recognition: ASIS&T SIG-USE Innovation Award (2017) ACM SIGCHI Excellent Reviewer (2017) ALISE/LMC Paper Award (2015) Beta Phi Mu/LRRT Research Award (2014) Teaching and Grants: Teaches courses on information behavior, research methods, and consumer health informatics. Co-PI on grants like HackHealth 2.0 (NIH, $123K) and youth health literacy initiatives ($68.5K). Also serves as Assistant Director of the Information Policy & Access Center and Senior Fellow at CASCI. Labs and Initiatives: Leads the Carillon Community in Health Justice and collaborates on projects like the HackHealth after-school program to engage disadvantaged youth in health entrepreneurship.

• Movement Disorders
• Cognitive Behavioral Neurology
• Parkinson's Disease
• +7 more

Ana Vives-Rodriguez, MD is an Assistant Professor of Neurology at Yale School of Medicine. She specializes in movement disorders and cognitive-behavioral neurology, caring for patients with Parkinson's disease, tremor, tics, dystonia, Alzheimer's disease, Dementia with Lewy bodies, and frontotemporal dementias. Based at Yale Physicians Building in New Haven, Connecticut, she provides both in-person and telehealth services to adult patients, accepting new patients without requiring referrals. Dr. Vives-Rodriguez's educational background includes: BS and MD from University of Costa Rica (2009), graduating Magna Cum Laude Residency at University Costa Rica/Calderon Guardia Hospital (2014) Clinical Fellowship in Movement Disorders at Yale New Haven Hospital (2018) Advanced Fellowship in Cognitive Behavioral Neurology at Boston University/VA Medical Center (2022) Her primary research interests focus on the behavioral and cognitive aspects of movement disorders and the early diagnosis of neurodegenerative disorders . Dr. Vives-Rodriguez examines structural and functional brain changes in conditions like Parkinson's disease, Wilson's disease, and Alzheimer's disease and their relation to clinical manifestations. Her work bridges clinical practice with translational neuroscience to improve diagnostic approaches and patient outcomes in complex neurological conditions. Analysis of her publications from 2017-2021 reveals a strong focus on movement disorders, cognitive impairment, and neuroimaging. Her research spans clinical observations of movement phenomena like index finger pointing and writing tremor, structural and functional brain changes in Wilson's disease, and innovative approaches to medical education in movement disorders. A recurring theme is the intersection between movement disorders and cognitive function, highlighting her dual expertise in both specialties. Dr. Vives-Rodriguez serves as a Sub Investigator for the Cognitive Training in Parkinson's Disease clinical trial (HIC ID 2000033352), which is recruiting participants aged 40+ through 2027. While specific grant funding isn't detailed in the available information, her active research program suggests ongoing support for her work in neurodegenerative disorders. She is affiliated with Yale's Movement Disorders and Neurodegenerative Disorders divisions, working within the Department of Neurology at Yale School of Medicine. Her clinical work at Yale Physicians Building integrates the latest research findings into patient care while contributing to the academic mission through teaching and scholarly activities.

Li Azinovic-YangView profile

Assistant Professor

• Corporate Disclosure
• Financial Accounting
• Firm Innovation
• +3 more

Li Azinovic-Yang serves as an Assistant Professor of Accounting and IBM Faculty Fellow at the University of Chicago Booth School of Business. Her research examines corporate disclosure dynamics through analytical modeling and data analysis, focusing on intersections with firm innovation, competition structures, and labor practices. Education: PhD in Accounting, Columbia Business School Master in Banking and Finance, University of Zurich Bachelor in Finance, Shanghai University of Finance and Economics Her research spans corporate disclosure antecedents and consequences, particularly investigating how information transparency affects firm innovation strategies, competitive market structures, and labor policy implementation. Current work analyzes disclosure regulation's welfare impacts and strategic communication in corporate experimentation contexts through rigorous analytical frameworks. Recent publications demonstrate strong focus on accounting standard evolution and diversity initiatives, revealing how regulatory stability shifts impact financial reporting and how diversity targets transform organizational behavior. Her work bridges theoretical accounting models with real-world corporate practices. Scientific Recognition: IBM Faculty Fellow As an active researcher, Azinovic-Yang maintains significant industry engagement through media coverage in outlets like Forbes and CBS Newsroom. Her work on innovation disclosure regulation generated podcast interviews on The Finance Bro, while diversity research received mainstream news attention. She contributes to academic discourse through Booth School publications and maintains an active research pipeline examining capital rationing incentives and strategic communication.

Anil SethView profile

Professor

• Cognitive Neuroscience
• Computational Neuroscience
• Consciousness Science
• +12 more

Professor Anil Seth is a leading cognitive and computational neuroscientist at the University of Sussex, where he holds a professorship in the School of Engineering and Informatics. He is Director of the Sussex Centre for Consciousness Science and Co-Director of the CIFAR Program on Brain, Mind, and Consciousness and the Leverhulme Doctoral Scholarship Programme. His research bridges neuroscience, psychology, philosophy, and AI to investigate the biological basis of consciousness and selfhood. His research interests include: Predictive processing approaches to perception Virtual and augmented reality in self-experience studies Mathematical modeling of perception and emergence Machine learning applications in subjective perception modeling Interoception and selfhood Neural mechanisms of conscious experience The recent publications reflect a strong focus on consciousness, neural dynamics, predictive models, and interdisciplinary approaches. Trends include the use of computational modeling, neurophenomenology, causal analysis, and the ethical implications of emerging neurotechnologies. His work increasingly integrates large language models and data-driven methods for analyzing subjective experience. His scientific awards include: Segerfalk Award Perspectives Award Highly Cited Researcher (Web of Science, 2019–2022) Royal Society Michael Faraday Prize (2023) Seth has secured substantial research funding from the European Research Council (ERC), EPSRC, Wellcome Trust, CIFAR, and the Sackler Foundation. He has supervised numerous research projects and doctoral students through interdisciplinary programs. He leads the Dreamachine project and has been an Engagement Fellow with the Wellcome Trust. He serves on editorial boards including Philosophical Transactions of the Royal Society B and is Editor-in-Chief of Neuroscience of Consciousness . He leads a multidisciplinary research group at the Sackler Centre, bringing together psychologists, mathematicians, neuroscientists, computer scientists, and philosophers. His team conducts innovative research using virtual reality, neuroimaging, and computational modeling to explore the nature of consciousness and self.