Professor He Bingsheng is a faculty member at the Department of Computer Science, School of Computing, National University of Singapore (NUS), where he also serves as Vice-Dean, Research. He holds a Ph.D. in Computer Science from the Hong Kong University of Science & Technology (2008) and dual bachelor’s degrees in Computer Science & Engineering and Business Administration from Shanghai Jiao Tong University (2003). Education: Ph.D. (HKUST, 2008), B.E./B.B.A. (SJTU, 2003) Prior roles: Microsoft Research Asia (2008-2010), Nanyang Technological University (NTU), Singapore His research focuses on Big Data management systems , particularly on cloud computing and emerging hardware architectures (GPU, FPGA, NVM). He has led projects like ThunderGP, a novel FPGA-accelerated graph processing framework achieving 419x speedup for Covid-19 prevalence estimation. His work spans parallel/distributed systems and graph algorithms , with publications in ACM SIGMOD, VLDB, SC, and IEEE Transactions. The selected articles highlight his contributions to GPU/FPGA optimization , LLM applications , and graph analytics . He has received multiple best paper/demo awards, including IEEE/ACM ICCAD (2017), IEEE IC2E (2016), and ACM SIGMOD (2008). As a PC chair and editorial board member for journals like IEEE TPDS and TCC, he actively shapes academic discourse. PhD Students: Chen Xinyu, Tan Hongshi Courses Taught: CS4225/5425 Big Data Systems for Data Science
Dr. Changyou Chen is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York. His research focuses on Multi-Modal Learning Foundation Models Deep Generative Models Large-scale Bayesian Sampling with applications in document understanding, music-AI integration, and molecular representation learning. Research Trends revealed through his recent publications include Optimizing Multimodal Large Language Models Developing Novel Retrieval-Augmented Generation Frameworks Creating Benchmark Datasets for Visual Text Understanding Advancing Diffusion Models with Domain-Specific Constraints across domains from music sheets to biomedical documents. Scientific Contributions : UB Young Investigator Award (2020) Architect of LoCAL Framework for Long Document Understanding Co-developer of MusiXQA Benchmark Pioneering Work in Probability Contrastive Learning Academic Leadership includes mentoring 10+ graduate students and serving as Area Chair for major AI conferences (ICML, NeurIPS, AAAI, IJCAI). His Labs develop scalable solutions for multimodal reasoning, with recent work demonstrating practical GPU memory optimization through LoRA adapter sharing.
Olli Sotamaa is a Professor of Game Culture Studies at Tampere University's Faculty of Information Technology and Communication Sciences, Department of Communication Sciences. He leads the Tampere University Game Research Lab alongside Professor Frans Mäyrä and serves as team leader in the Centre of Excellence in Game Culture Studies. Specializes in game cultural phenomena: online communities, fandom, modding, data-driven game development Co-edited Game Production Studies (Amsterdam University Press, 2021) His research focuses on game industry practices, data analytics impact, and player production cultures. Recent work examines game data labor, industry ethics, and digital preservation challenges. Key trends in his 15 most recent articles include: Game data work and algorithmic culture (2023-2025) Game modding and user-generated content (2021-2022) Game development practices (2019-2021) Game preservation and heritage (2020) Industry sustainability and ethics (2021-2025) Scientific awards: ERC-Advanced-Grant project 'Making Sense of Games (MSG)' Labs/teams: Tampere University Game Research Lab Centre of Excellence in Game Culture Studies
Suyi Li is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering, where he leads the Dynamic and Architected Robot and structurE (DARE) Lab. Previously, he served as an Assistant Professor at Clemson University from 2016-2022 after completing postdoctoral research at the University of Michigan. Ph.D. in Mechanical Engineering, University of Michigan, Ann Arbor (2014) M.Sc. in Mechanical Engineering, Pennsylvania State University (2008) B.S. Summa Cum Laude in Mechanical Engineering, University of Michigan, Ann Arbor (2006) Dr. Li's research focuses on pioneering new paradigms of intelligent robots and functional structures by exploiting the interplay between geometry, mechanics, actuation, and computation. His work spans origami-inspired morphing structures, physically computing materials that perform machine learning tasks without traditional electronics, and soft/reconfigurable robots that can move like animals or grow like plants. His innovative approach combines mechanical engineering principles with computational thinking to create systems with 'mechano-intelligence'. Analysis of Dr. Li's recent publications reveals a strong trajectory toward embodied intelligence and mechanical computing, where physical structures themselves perform computational tasks. His work increasingly integrates origami/kirigami principles with advanced materials to create systems that can sense, process information, and actuate without conventional electronics. The research shows progression from fundamental mechanics of adaptive structures to sophisticated applications in robotics and computing. Dean's Awards of Excellence – Faculty Fellow, Virginia Tech (2024) C.D. Mote Jr Early Career Award, ASME Design Engineering Division (2022) Gary Anderson Early Achievement Award, ASME Aerospace Division (2021) Junior Researcher of the Year Award, College of Engineering, Clemson University (2020) CECAS Dean's Faculty Fellow, Clemson University (2018) CAREER Award, National Science Foundation (2018) ASME Freudenstein Young Investigator Award Dr. Li has secured nearly two million dollars in research funding, including the prestigious NSF CAREER award and an NSF EFRI project to build mechano-bio hybrid reservoir computers. He advises multiple Ph.D. and Master's students in the DARE Lab, with recent successes including Vishrut Deshpande's Ph.D. defense. His research has generated close to 80 journal and conference papers, demonstrating significant impact in the fields of adaptive structures and materials systems. Dr. Li also serves on editorial boards for several prominent journals including Journal of Intelligent Material Systems and Structures and Philosophical Transactions of the Royal Society A. The DARE Lab at Virginia Tech comprises a multidisciplinary team of researchers working on origami-inspired meta-structures, physically computing materials, and soft robotics. Current projects include developing electronics-free crawling robots with mechanical central pattern generators, creating kirigami-based wearable medical devices, and engineering metamaterials with programmable mechanical properties. The lab actively collaborates with institutions across the country and has received recognition for its innovative approaches to combining mechanical design with computational capabilities.
Prof. Dr. Dr. Elisabeth Binder is the Director of the Max Planck Institute of Psychiatry and leads the Max Planck Research Group "Genes and Environment" in Munich, Germany. Her research focuses on molecular mechanisms underlying psychiatric disorders, particularly how genetic and environmental factors interact in disease development. Education: Medicine (University of Vienna), Neuroscience (Emory University) Affiliations: Max Planck Institute of Psychiatry, International Max-Planck Research School Translational Psychiatry, Graduate School of Systemic Neuroscience Research Interests: Elisabeth Binder investigates gene-environment interactions in psychiatric disorders, emphasizing early trauma and stress response. Her work employs next-generation sequencing, epigenetic analysis, and induced pluripotent stem cells to identify biological markers for disease prevention and treatment. Scientific Awards: Theodore Reich Young Investigator Award (2010) Max Hamilton Memorial Prize (2012) Eva King-Killam Research Award (2016) Carus Medal (2017) Ron the Kloet Award for Stress Research (2019) Leadership Roles: She is a member of the German National Academy of Sciences (Leopoldina), a Fellow of the American College of Neuropsychopharmacology, and serves on multiple international advisory committees and executive boards in psychiatry and neuroscience.
Dr. Donald Addington serves as a Clinical Professor in the Department of Psychiatry at the University of Calgary's Cumming School of Medicine, with full memberships at the Hotchkiss Brain Institute and Mathison Centre for Mental Health Research and Education. His academic career spans over 50 years, focusing on transforming mental health service delivery for schizophrenia and early psychosis through evidence-based tools and standards. His educational credentials include: MBBS in Medicine, University of London (1972) MRCPsych in Psychiatry, Royal College of Psychiatrists (1976) FRCPC in Psychiatry, Royal College of Physicians and Surgeons of Canada (1982) Dr. Addington's research integrates clinical psychiatry with health services evaluation to develop practical measurement systems. He pioneered internationally adopted instruments including depression assessment scales for schizophrenia and fidelity metrics for psychosis services, creating bridges between clinical practice, policy development, and funding mechanisms. His work establishes standardized approaches for evaluating mental health service accessibility, quality, and outcomes across diverse healthcare systems. His publication trajectory reveals consistent innovation in measurement science, evolving from the foundational Calgary Depression Scale (1990) to contemporary fidelity scales for early psychosis intervention (FEPS-FS/CHRP-FS). These works establish global benchmarks for service quality assessment, with applications spanning clinical practice guidelines, performance measurement, and cross-system outcome comparison through initiatives like the ICHOM Psychotic Disorders standard set. Dr. Addington's scientific recognition includes: Excellence in Clinical Teaching, PAIRA (1996) Leadership Award, Canadian Alliance on Mental Illness and Mental Health (2000) Gold Medal, Canadian College of Neuropsychopharmacology (2004) Michael Smith Award for Schizophrenia (2006) C.A. Roberts Award for Clinical Leadership (2011) Angelo Cocchi Award for Fidelity Implementation (2016) President’s Commendation, Canadian Psychiatric Association (2022) Dr. John M. Cleghorn Memorial Award (2024) He has secured major research funding from the National Institutes of Health, Canadian Institutes of Health Research, and Alberta Heritage Foundation for Medical Research. His leadership extends through 11 years as Department Chair of Psychiatry and two terms as Canadian Psychiatric Association Board Chair, mentoring generations of clinicians while developing tools implemented across Canadian provinces, US states, and European nations. Dr. Addington leads cross-institutional teams including the ICHOM Psychotic Disorders working group and large-scale implementation projects in Ontario, 32 US states, Czechia, and Italy. His current initiatives expand the FEPS-FS framework to clinical high-risk populations and bipolar disorder services while advancing patient-reported outcome measures for international service comparison.
Sunny Stalter-Pace serves as the Hargis Professor of American Literature in Auburn University's College of Liberal Arts, English Department. A specialist in modernist performance, literature, and urban space, she authored Imitation Artist: Gertrude Hoffmann's Life in Vaudeville and Dance (2020) and is currently completing a cultural history of the New York Hippodrome. Her work bridges academic research with public engagement through blogs, interviews, and collaborations with institutions like the Library of Congress. Her educational foundation includes: Ph.D. in English, Rutgers University (2007) M.A. in English, Rutgers University (2003) B.A. in English and French, Loyola University Chicago (1997), magna cum laude Stalter-Pace's research interrogates intersections of mobility, gender, and performance in 20th-century American culture. She examines how vaudeville, subway systems, and theatrical spectacles shaped public identity, with particular attention to women's experiences and spatial politics. Her methodology combines literary analysis, archival research, and visual studies to reveal how imitation and movement function as cultural forces. Current projects explore aquatic performances at the New York Hippodrome and the legacy of vaudeville producer Gertrude Hoffmann. Her 15 most recent publications demonstrate an evolving trajectory from subway systems ( Underground Movements , 2013) toward aquatic spectacles and vaudeville legacies, consistently centered on New York City's infrastructure. This body of work establishes mobility studies as a critical lens for understanding modernism, revealing how transportation networks and performance venues structured social interactions. Her interdisciplinary approach connects theater history, gender studies, and urban theory to uncover marginalized narratives in American cultural production. Key recognitions include: Harry Ransom Center Fellowship (2020) New York Public Library Short-Term Research Fellowship (2020) Alabama Humanities Foundation Grant (2014) College of Liberal Arts Excellence in Teaching Award nomination (2011) Multiple research fellowships from 2003-2017 Stalter-Pace has secured substantial funding for archival research through fellowships from the NEH, MLA, and university grants. She serves on Biographer’s International Organization's program committee and curated the 'Common Grounds' exhibition at Auburn's Jule Collins Smith Museum. Her teaching innovations include the first-year seminar 'Thinking Through the Arts' and courses on contemporary drama that integrate Hamilton into American literature pedagogy. As Book Review Editor for Transfers: Interdisciplinary Journal of Mobility Studies , she shaped scholarly discourse in mobility studies. Through her Hippodrome research blog and collaborations with the New York Public Library, Stalter-Pace transforms specialized scholarship into accessible public history. Her Library of Congress presentation on Albertina Rasch and the Hippodrome exemplifies her commitment to bridging academic research with community engagement, while ongoing interviews and blog posts extend her work beyond traditional academic boundaries.
Handan Kulan serves as Assistant Professor at Yeditepe University's Faculty of Computer and Information Sciences, Department of Information Systems and Technologies since 2024. Previously, she held faculty positions at Istinye University (2023), Uskudar University (2022), and Beykoz University (2020) across computer engineering and software engineering departments. Education: Ph.D. in Computer Engineering, Kadir Has University (2016-2020): Thesis on critical proteins in Down syndrome learning processes M.S. in Computer Science and Engineering, Sabanci University (2013-2014): Thesis analyzing protein residue networks B.S. in Genetics and Bioengineering, Yeditepe University (2007-2013) Second Major in Computer Engineering, Yeditepe University (2009-2013) Her research integrates machine learning with biomedical challenges, specializing in Down syndrome proteomics, neural network analysis of brain aging, and immune system disorders. She develops computational models for protein identification and applies gradient boosting algorithms to biological datasets, bridging AI with healthcare decision systems as demonstrated in her 2023 Springer book. Publications reveal consistent focus on computational approaches to Down syndrome, with recent conference presentations expanding into statistical clustering of biological data and gene ontology analysis for drug discovery. Her work demonstrates methodological evolution from protein network analysis to advanced predictive analytics. Awards: No specific scientific awards documented in source materials. Dr. Kulan actively supervises graduate theses while teaching core computer science courses including Deep Learning, Artificial Intelligence, and Data Structures at both undergraduate and graduate levels across multiple institutions. Her teaching portfolio reflects direct alignment with her research in AI-driven biomedical analysis.
Y. N. Singh is a Professor in the Department of Electrical Engineering at Indian Institute of Technology Kanpur . He holds a PhD and M.Tech from IIT Delhi and a B.Tech from REC Hamirpur . Education PhD, IIT Delhi (1997) M.Tech, IIT Delhi (1992) B.Tech, REC Hamirpur (1991) His research focuses on telecom networks , optical networks , complex networks , and wireless sensor networks , with significant contributions to network protection protocols, rumor propagation modeling, and optical memory design. His work on p-cycles has advanced telecom network survivability techniques. Selected publications include key papers in IEEE/OSA Journal of Lightwave Technology and Acta Physica Polonica B . He has received the AICTE Young Teacher Award (2002) and the Dr. M.N. Saha Memorial Award (2006). Contact details Office: EE/ACES, IIT Kanpur, UP, India-208016 Phone: 0512-[679/392/259]-7944 (O) Lab: 0512-[679/392/259]-7841, 7070 Fax: 0512-259-0063
Guy Dove is a Professor in the School of Arts & Sciences Humanities at the University of Louisville. His research bridges philosophy, cognitive science, neuroscience, linguistics, and artificial intelligence, focusing on the philosophy of psychology and abstract concept formation. PhD in Philosophy from the University of Chicago His work explores how language shapes cognition, advocating for a multimodal and flexible framework to understand abstract concepts. Recent publications address the implications of large language models for human cognition and the role of linguistic scaffolding in semantic memory. Key journals include Philosophical Transactions of the Royal Society B , Cognitive Neuropsychology , and Topics in Cognitive Science . He co-authored the book Consciousness and Physicalism: A Defense of a Research Program . Prior to his current role, Dove worked in the Developmental Neuropsychology and Electrophysiology Lab (2002-2003) and taught in the Department of Psychological and Brain Sciences (2004-2008).
Michael Ferdman is an Associate Professor in the Department of Computer Science at Stony Brook University, where he leads research in computer architecture and systems. His office is located in Room 343 at Stony Brook, NY 11794-2424, and he can be contacted via phone (631-632-8449) or email. Ferdman directs the Computer Architecture and Systems Laboratory (compas.cs.stonybrook.edu), focusing on next-generation server infrastructure. Ferdman's research spans the entire computing stack with emphasis on: FPGA integration for server environments (Intel HARP, Microsoft Catapult) Machine learning accelerators for convolutional neural networks Server systems optimization in the post-Moore era Network processing and software-defined networking Programming models for emerging memory technologies (HBM, 3D XPoint) Reconfigurable hardware and high-level synthesis His work addresses both performance and security challenges in modern computing infrastructure. Analysis of his 15 most recent publications (2022-2025) reveals consistent focus on: Hardware acceleration techniques (FPGAs, specialized processors) Memory hierarchy optimization and cache management Security vulnerabilities in web applications and systems Post-Moore computing architectures Parallel processing and distributed systems His research shows strong emphasis on practical implementations bridging hardware and software layers. Awards recognizing his contributions include: Graduate Teaching Award (2014) Best Paper Award at ASPLOS XVII Best Paper Finalist at HPCA XVII Three IEEE Micro Top Picks selections (2009, 2012) He teaches advanced courses including CSE 502, CSE 602, and CSE 506 at Stony Brook University.
Rishidev Chaudhuri is an Associate Professor at the University of California, Davis in the Department of Neurobiology, Physiology and Behavior within the College of Biological Sciences. His research focuses on computational neuroscience and neural dynamics, employing mathematical models to investigate how neural circuits generate cognitive processes such as memory, perception, and decision-making. His work explores neural dynamics through models of memory systems, attentional mechanisms, and probabilistic inference. Recent publications highlight advances in understanding hippocampal memory scaffolds, parietal-frontal interactions, and neuromorphic computing inspired by brain architecture. Education: BA in Physics (Amherst College), PhD in Applied Mathematics (Yale University) Centers: Center for Neuroscience; affiliated with Applied Mathematics and Neuroscience Graduate Groups Scientific awards and honors are not explicitly mentioned in the provided materials.
Matt Nassar is an Associate Professor of Neuroscience and Assistant Professor of Cognitive and Psychological Sciences at Brown University. He leads the Learning, Memory and Decision Lab, which is part of the Department of Neuroscience and the Robert J. & Nancy D. Carney Institute for Brain Science. His research focuses on understanding how the brain flexibly processes information to achieve complex and adaptive behaviors through computational approaches that bridge cognitive psychology and neuroscience. Education: PhD, University of Pennsylvania (2012) BA, Colgate University (2004) Nassar's research examines how different cognitive systems—learning, memory, and perception—leverage common computational principles to optimize decision-making. His work particularly focuses on how the brain balances stability and flexibility in processing information, how uncertainty is represented and utilized in learning, and how neural computations underlie complex behaviors. Through computational modeling and empirical research, he investigates how modular information-processing systems impact decisions and complex behavior in dynamic environments. His research integrates methods from cognitive psychology, neuroscience, and computational modeling to address fundamental questions about human cognition. Analysis of Nassar's recent publications (2020-2024) reveals a strong focus on computational neuroscience applied to decision-making, learning, and psychiatric conditions. His work frequently employs Bayesian modeling approaches to understand belief updating, uncertainty processing, and structure learning. Key themes include the neural basis of flexibility in learning, computational mechanisms underlying psychiatric symptoms, and age-related changes in cognitive processing. His research bridges cognitive psychology, neuroscience, and computational modeling to provide insights into both healthy cognition and disorders such as depression and schizophrenia. Scientific Contributions: Developed computational models of belief updating and learning under uncertainty Investigated neural mechanisms of stability-flexibility tradeoffs in cognition Examined age-related differences in learning and memory processes Explored computational mechanisms underlying psychiatric conditions Studied the role of noise correlations in neural learning systems Investigated how prefrontal cortex representations shape decision processes Nassar actively mentors researchers in his lab, with recent announcements highlighting postdocs joining from prestigious institutions like Max Planck UCL and Freie Universität Berlin. His lab appears to receive significant research funding, supporting multiple postdoctoral positions and research projects. Collaborations span multiple departments at Brown University, particularly with researchers in Cognitive and Psychological Sciences, Neurology, and Psychiatry. The lab has produced numerous high-impact publications in top journals including Nature Human Behaviour, Brain, and eLife. The Learning, Memory and Decision Lab, led by Nassar, is an active research group that uses computational models to understand how the brain represents and stores information for effective decision making. Recent lab announcements (as of February 2025) indicate the lab is expanding with new postdoctoral researchers joining from Harvard, Max Planck UCL, and Freie Universität Berlin, suggesting strong research momentum and funding support. The lab appears to be well-integrated within Brown's neuroscience community, with collaborations spanning multiple departments and research centers.
Frank E. Garcea, Ph.D., is a Research Assistant Professor in the Department of Neurosurgery and Neuroscience at the University of Rochester School of Medicine and Dentistry. His research focuses on the cognitive and neural mechanisms underlying tool use, apraxia, and stroke recovery. He employs neuropsychological testing, fMRI, and lesion-symptom mapping to study brain injury effects on functional connectivity and action knowledge. Education: Bachelor of Science in Psychology, St. John Fisher College (2006–2010) PhD in Brain and Cognitive Sciences, University of Rochester (2012–2017) Research Interests: Dr. Garcea investigates how brain regions like the parietal cortex and dorsal/ventral streams mediate object manipulation and tool use. His work explores stroke-related disconnection syndromes, motor speech coordination networks, and translational brain mapping to preserve neural function during surgery. He collaborates on projects involving epilepsy patients undergoing electrocorticography to study action-related neural pathways. Labs & Affiliations: Principal Investigator of the Garcea Lab at URMC, focusing on tool use deficits in brain tumor/stroke survivors. Affiliated with the Del Monte Institute for Neuroscience and the Neurobiology & Anatomy Program. His lab integrates neuroimaging, lesion analysis, and clinical care to advance personalized brain mapping strategies.
Edward Muir is the Clarence L. Ver Steeg Professor in the Arts and Sciences and Charles Deering McCormick Professor of Teaching Excellence at Northwestern University, with joint appointments in the Department of History and Italian Studies at Weinberg College of Arts and Sciences. His academic journey includes a B.A. from the University of Utah (1969), an M.A. (1970), and Ph.D. (1975) in Modern European History from Rutgers University, including a Semester in Italy Program at Syracuse University (1967). Muir's research explores the intersection of ritual, violence, and power in Renaissance Europe, with emphases on Italian history, microhistory, and cultural anthropology. His work examines civic ceremonies, gender exclusion, and the sociopolitical underpinnings of early opera. Key themes include the anthropology of Venice, religious processions, and community formation in pre-modern societies. His scholarly publications reveal a consistent focus on Renaissance cultural practices, Venetian society, and methodological innovations in microhistory. Recent works analyze opera's emergence in 17th-century Venice, anti-war movements, and gendered public spaces, blending archival rigor with interdisciplinary theory. Awards and Honors: Herbert Baxter Adams Prize (1982) Two-time Howard R. Marraro Prize winner (1982, 1993) Andrew W. Mellon Foundation Distinguished Achievement Award (2010, $1.5 million) Fellow, American Academy of Arts and Sciences (2014) Charles Deering McCormick Professorship for Teaching Excellence (2006) Muir has held major administrative roles including Department Chair at Northwestern and LSU, co-directed the Graduate Program in Italian Studies, and served on editorial boards for journals like the American Historical Review . He mentors through graduate programs but no specific student advisees are listed.
