H. Jerry Qi is a Professor in the Department of Mechanical Engineering at the Georgia Institute of Technology. He specializes in finite deformation multiphysics modeling of soft active materials, with a focus on shape memory polymers, 4D printing, and material recycling. His research integrates experimental and computational approaches to advance additive manufacturing technologies. Education: Sc.D., Massachusetts Institute of Technology, 2003 Ph.D., Tsinghua University, China, 1999 B.S., Tsinghua University, China, 1994 Research Interests: Dr. Qi's work spans 4D printing of active materials, mechanics in 3D printing, and sustainable polymer processing. His group develops hybrid printing methods and recyclable thermosetting polymers, collaborating with institutions like SUTD and AFRL. Key areas include smart material design, photomechanical experiments, and finite element modeling. Scientific Awards: ASME Fellow (2015) Woodruff Faculty Fellow (2015) J. T. Oden Faculty Fellowship (2012) NSF Career Award (2007) Advising & Grants: Dr. Qi actively seeks undergraduate, PhD, and postdoc researchers. His projects are funded by NSF, AFOSR, and industry partnerships. He leads a research group focused on advancing active materials and sustainable manufacturing. Labs & Teams: His lab integrates computational modeling, experimental mechanics, and additive manufacturing to create innovative materials and structures for applications in aerospace, biomedical, and environmental engineering.
Dr. Imaobong Umoren is an Associate Professor of International History at the London School of Economics (LSE), specializing in race, gender, and political thought in the Caribbean, Britain, and the US. Her research focuses on the intersections of colonialism, imperialism, and activism in the 19th and 20th centuries. She is currently on maternity leave (2025-2026) and has been a Leverhulme Research Fellow (2020/21). Her acclaimed book Race Women Internationalists (2018) won the 2019 Women’s History Network Book Prize and explores Afro-Caribbean and African American women’s roles in global freedom struggles. Her recent work includes Empire Without End (2025), which reinterprets the British Empire’s enduring legacy in the Caribbean, and a political biography of Dominica’s former Prime Minister, Eugenia Charles. Umoren teaches courses such as HY246: The Global Caribbean and coordinates MSc dissertations. She has contributed to media projects like BBC Radio 3’s Essays and appeared on Fake or Fortune . Umoren’s awards include the British Library Eccles Centre/Hay Festival Writer’s Award (2020-2021) and Leverhulme Fellowship. Her research emphasizes systemic racism, decolonization, and the global impact of Caribbean histories.
Dr Fiona Hum is a Senior Lecturer at Monash University's Faculty of Law, where she conducts research and teaches. Admitted as a solicitor and barrister of the Supreme Court of Victoria, she previously practiced commercial litigation, criminal law, and personal injury law while consulting for major insurers and the Victorian police force. Her doctorate from the University of Melbourne focused on Northern Territory euthanasia laws. Education: Doctorate in Law, University of Melbourne (thesis on euthanasia laws) Admitted Solicitor and Barrister, Supreme Court of Victoria Research Focus: Dr Hum's work centers on Evidence Law , Wrongful Convictions , and Gender/Race Relations in Law , with pioneering studies on compassion training for law students now expanding into climate change law. Her research directly supports UN Sustainable Development Goals for justice, equality, and well-being through interdisciplinary approaches connecting legal theory with psychological and social frameworks. Publication Trends: Recent work (2022-2025) analyzes high-profile cases like Kathleen Folbigg and Cardinal Pell while advancing evidence law pedagogy through her Cambridge University Press textbook. Earlier scholarship (2010) established foundational critiques of gender bias in evidentiary processes, particularly regarding women complainants and pregnant patients. Scientific Awards: Faculty Teaching Award for Teaching Excellence (2010) Certificate of Recognition for S1 Unit Performance (2015) Certificate of Recognition for S2 Unit Improvement (2016) Nominee: Inspiring Woman Award (2021) Nominee: Australian Legal Education Award (2023) Advising & Professional Impact: Accepting PhD students, Dr Hum actively shapes legal education through curriculum innovation and peer review for top journals ( University of New South Wales Law Journal , Sydney Law Review ). Her external collaborations include specialist lectures for Monash's Faculty of Medicine and keynotes at national conferences like the Women's Lawyers Conference on 'Justice for All'. Institutional Roles: Current member of the Australasian Law Academics Association (2025-2028) and former Honorary Fellow at the University of Melbourne (2019-2021), she bridges academic rigor with real-world legal practice through ongoing consultancy work.
Glenda Sluga is a Full-time Professor with a Joint Chair in the Department of History at the European University Institute (EUI) and also holds a concurrent appointment at the Robert Schuman Centre for Advanced Studies. She is a leading scholar in international history, capitalism, and globalization, with a strong focus on 20th-century economic and diplomatic thought. Her research is widely recognized and funded by prestigious grants, including an ERC Advanced Grant and an Australian Research Council Laureate Fellowship. Her research interests span a broad range of fields including: International and Diplomatic History Global and Transnational History Capitalism and Economic History Environmental and Cultural History European Integration and Decolonisation Intellectual and Political History Recent publications highlight her engagement with global economic thinking, climate and capitalism, the history of international organizations, and the construction of international order. Her work often bridges conceptual and empirical analysis, focusing on figures like Barbara Ward and Margaret Mead, as well as major events such as the 1972 UN Conference on the Human Environment. Themes of memory, nationalism, and global publics recur across her recent output, indicating a deepening exploration of the cultural dimensions of internationalism. Her scientific honors include: European Research Council Advanced Grant (2020) Australian Research Council Kathleen Fitzpatrick Laureate Fellowship (2013) Fellow of the Australian Academy of the Humanities Glenda Sluga actively mentors PhD students and serves as second reader for numerous candidates, demonstrating strong commitment to academic training. She leads major research initiatives such as the project on ‘Twentieth Century International Economic Thinking’ and participates in working groups on business history, diplomatic history, and planetary futures. There is no indication of lab-based research, but her leadership in interdisciplinary clusters and grant-funded programs underscores her role in shaping collaborative academic environments.
Bryon Aragam is an Associate Professor of Econometrics and Statistics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research focuses on the intersection of causality, statistical machine learning, and probabilistic modeling, with particular emphasis on applications to artificial intelligence systems including large language models like ChatGPT and generative models like DALL-E. Dr. Aragam completed his PhD in Statistics and a Masters in Applied Mathematics at UCLA, where he was an NSF graduate research fellow. Prior to joining the University of Chicago, he was a project scientist and postdoctoral researcher in the Machine Learning Department at Carnegie Mellon University. Research Focus: Causal structure learning in probabilistic generative models Key Areas: Causal machine learning, deep generative models, latent variable models, statistical learning theory Applications: AI interpretability, ethics, and fairness in artificial intelligence systems Teaching: Business Statistics, Econometrics and Statistics Colloquium His recent publications demonstrate a strong theoretical foundation combined with practical applications, particularly in understanding and improving AI systems. His work spans causal discovery, graphical models, deep learning, and latent variable modeling, with particular attention to the theoretical properties of these methods and their applications to real-world AI challenges. The research shows a progression toward increasingly complex problems in causal representation learning and AI interpretability. Scientific Awards: Robert H. Topel Faculty Scholar NSF Graduate Research Fellow Dr. Aragam's work has been published in top statistics and machine learning venues including the Annals of Statistics, Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the Journal of Machine Learning Research (JMLR). His research group publishes broadly across both statistical and machine learning communities, demonstrating the interdisciplinary nature of his work at the intersection of statistics, machine learning, and causal inference. As a data science consultant for technology and marketing firms, Dr. Aragam has applied his expertise to problems in survey design, customer retention, logistics, and ranking, bridging the gap between theoretical research and practical applications.
Luc Anselin is the Stein-Freiler Distinguished Service Professor of Sociology and the College at the University of Chicago. He serves as Director of the Center for Spatial Data Science and Senior Fellow at NORC, with affiliations in the Department of Sociology and the Committee on Quantitative Research Methods in Social, Behavioral, and Health Sciences. B.S., Vrije Universiteit Brussel, 1975 M.S., Vrije Universiteit Brussel, 1976 M.A., Cornell University, 1979 Ph.D., Cornell University, 1980 Anselin is a pioneer in spatial data science, spatial econometrics, and computational social science. His work bridges quantitative geography, regional science, and computer science, with applications in urban studies, economic analysis, and health research. His recent publications focus on spatial regimes, software ecosystems like GeoDa and PySAL, stigma analysis in public health, and computational methods for urban equity. These reflect interdisciplinary trends in spatial statistical modeling, open-source development, and geospatial policy evaluation. Scientific recognition includes: Fellow, Regional Science Association International (2004) Walter Isard Prize (2005) William Alonso Memorial Prize (2006) National Academy of Sciences (2008) American Academy of Arts and Sciences (2011) Anselin has led major grants and directed institutions like the GeoDa Center for Geospatial Analysis and Computation at Arizona State University. He has mentored interdisciplinary collaborations across sociology, economics, and data science. His laboratories and teams include the Center for Spatial Data Science at the University of Chicago and the GeoDa Center at Arizona State University, fostering innovation in geospatial computation and open-source spatial analytics.
Emmett Witchel is a Professor of Computer Science at the University of Texas at Austin , with research spanning computer architecture, systems, networking, security, and privacy . His work focuses on low-level systems optimization and secure concurrent execution. Research Interests: Concurrent systems, secure execution environments, GPU integration, distributed systems. Teaching: CS 380L (Advanced Operating Systems), CS 371M (Mobile Computing). Scientific Awards: Runner-up Best Paper, ASPLOS 2013 Runner-up Award for Outstanding Research, USENIX Symposium 2012 IEEE Micro Top Pick Award 2007 ACM Honorable Mention 2004 George M. Sprowls Award, MIT EECS 2004 Recent Publications demonstrate leadership in CXL pod databases ( Tigon ), stateful serverless computing ( Boki ), SmartNIC-accelerated file systems ( LineFS ), and GPU security ( Telekine ). His work bridges hardware-software co-design and practical systems implementation.
Brett Laursen is a Professor of Psychology at Florida Atlantic University's Charles E. Schmidt College of Science, with additional Docent Professor appointments in Educational Psychology at the University of Helsinki and in Social Developmental Psychology at the University of Jyväskylä in Finland. His research focuses on developmental psychology, particularly adolescent development, peer relationships, and social dynamics. Dr. Laursen earned his Ph.D. and M.A. in Child Psychology from the Institute of Child Development at the University of Minnesota and his B.A. in Psychology from Nebraska Wesleyan University. He also holds an Honorary Ph.D. from Örebro University in Sweden. His research program examines influence within close relationships, with particular focus on peer relationships during childhood and adolescence. Current projects include longitudinal studies of elementary and middle school children in Florida, Lithuanian youth transitioning from middle to secondary school, and child characteristics affecting parent engagement in literacy activities. His work consistently explores how social dynamics shape development, with special attention to friendship formation, dissolution, and influence processes. Analysis of his recent publications reveals a strong focus on peer relationships, social status, and developmental transitions. His research employs sophisticated longitudinal and genetically informed designs to examine how social contexts shape development across childhood and adolescence, with particular emphasis on the mechanisms through which peer influence operates. Fellow, American Psychological Association (Division 7, Developmental; Division 8, Social) Fellow and Charter Member, Association for Psychological Science Fellow, International Society for the Study of Behavioural Development Distinguished Alumnus, College of Education and Human Development, University of Minnesota Florida Atlantic University Scholar of the Year (2023-24 and 2016-17) Dr. Laursen has mentored numerous doctoral and master's students who have gone on to successful careers in academia and research. His research has been supported by major funding sources including the US National Institute of Child Health and Human Development, the US National Institute of Mental Health, the US National Science Foundation, Trygfonden, the Jacobs Foundation, and the European Social Fund. As Editor-in-Chief of Merrill Palmer Quarterly and Founding Editor of Cambridge Elements in Research Methods for Developmental Science, he plays a significant role in shaping the field's scholarly discourse. The Laursen Lab operates as a collaborative research team involving current students, alumni, and international collaborators including Professors Goda Kaniušonytė and Rita Žukauskienė of Mykolas Romeris University in Lithuania. The lab regularly presents research at major conferences including the Society for Research on Child Development.
Brice Kuhl is a Professor in the Department of Psychology at the University of Oregon , where he leads the Kuhl Lab. His research focuses on the cognitive neuroscience of memory formation, retrieval, and forgetting , utilizing advanced neuroimaging techniques like fMRI and EEG combined with machine learning algorithms to analyze distributed neural activity patterns. His work explores mechanisms of memory interference resolution , forgetting , and neural representation transformation . Recent publications emphasize spaced learning , temporal memory dynamics , and memory-cognitive control interactions . The lab has received attention for decoding perceptual content from neural activity and reconstructing face images based on brain states. Current lab members include graduate students Anisha Babu , Tongle Cai , and America Romero , alongside postdocs like Soroush Mirjalili and Yoonjung Lee . The lab frequently presents at conferences like CNS and SFN , and maintains active collaborations in memory research and neuroimaging methodology . Notable projects include investigations into hippocampal pattern differentiation and parietal cortex roles in memory . The lab also contributes to open science initiatives with publicly available experimental codes and data .
Professor Brian Z. Tamanaha is a distinguished scholar in jurisprudence and law and society at Washington University School of Law. With over 75 publications, his work spans legal realism, rule of law, and legal pluralism, earning international acclaim. Education: Doctorate of Juridical Science (Harvard Law School), Juris Doctor (Boston University), Bachelor of Science (University of Oregon) Research Interests: Focused on the intersection of legal theory, historical analysis, and societal impacts, Tamanaha’s scholarship critiques formalist approaches while exploring the evolution of legal systems across cultures. Scientific Awards: 2019 IVR Book Prize 2018 Prose Awards Honorable Mention Dennis Leslie Mahoney Prize in Legal Theory (2006) Herbert Jacob Book Prize (2002) Special Recognition Award (1998, Law and Society Association) Key Speaking Engagements: Cotterrell Lecture (2015), Kobe Memorial Lecture (2014), Julius Stone Address (2008), and multiple international keynote addresses. Grants & Fellowships: Ferdinand Braudel Senior Fellowship (European University Institute), Institute for Advanced Study Membership (Princeton), and Visiting Professor Fellowship (Queen Mary University).
Alan Zaoxing Liu is an Assistant Professor of Computer Science at the University of Maryland, College Park , with appointments at the University of Maryland Institute for Advanced Computer Studies (UMIACS) and Maryland Cybersecurity Center (MC2) . His research bridges systems, networking, and cybersecurity to design scalable, trustworthy approximate computing systems. Ph.D. in Computer Science from Johns Hopkins University (2018) Postdoctoral research at Carnegie Mellon CyLab (2018–2020) Research Interests : Networked and data-intensive systems Telemetry/analytics for heterogeneous networks Machine learning for network optimization Security in programmable networks Recent Publications include work on future-proof telemetry (PromSketch, VLDB’25), scalable caching (OctoCache, ASPLOS’25), and secure network analytics (TrustSketch, NDSS’24). His NSF-funded projects focus on optics-enabled DDoS defense and data-driven network management. Scientific Awards : USENIX FAST Best Paper (2019) USENIX ATC 'Best of Rest' (2021) Red Hat Collaboratory Research Awards (2022, 2023) Teaching : Leads Cloud Computing at Boston University , emphasizing agile development, open-source collaboration, and cloud infrastructure.
Leslie Valiant is the T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics in Harvard University's School of Engineering and Applied Sciences, where he has held a faculty position since 1982. A foundational figure in theoretical computer science, his work bridges artificial and natural computational phenomena across multiple disciplines. His academic background includes education at: King's College, Cambridge Imperial College, London Ph.D. in Computer Science from Warwick University (1974) Valiant's research spans computational complexity , machine learning theory , parallel systems , and computational neuroscience . He pioneered the PAC (Probably Approximately Correct) learning framework that established computational learning theory as a rigorous field. His holographic algorithms work revealed deep connections between computational complexity and statistical physics, while his neuroidal model and evolvability theory provide computational explanations for cognitive processes and biological evolution. Current investigations focus on cortical computation primitives and knowledge infusion architectures. His publication trends show increasing integration of neuroscience with computational theory since 2010, with dominant themes in holographic computation (2006-2018), cortical modeling (2012-2018), and evolvability (2009-2017). The work consistently applies computational complexity analysis to biological and cognitive systems. Major recognitions include: Nevanlinna Prize (1986) for mathematical aspects of computer science Knuth Award (1997) for foundational algorithms contributions EATCS Award (2008) for theoretical computer science impact Turing Award (2010) for computational learning theory and complexity Fellowship in the Royal Society and National Academy of Sciences Valiant's research has been supported by NSF and international grants enabling cross-disciplinary work in computational neuroscience and evolutionary algorithms. While specific advisees aren't documented in source materials, his theoretical frameworks have shaped generations of researchers in machine learning and complexity theory. His current research group explores neuroidal architectures for cognitive computation, investigating how cortical circuits achieve robust information processing through in-circuit testing methodologies. Ongoing projects aim to identify fundamental computational primitives in neural systems and develop biologically inspired AI frameworks.
Anita Hubley is a Professor at the University of British Columbia's Faculty of Education, Department of Educational and Counselling Psychology, and Special Education (ECPS). She serves as MERM Program Coordinator and directs the Adult Development and Psychometrics Lab. Her work focuses on psychometric test development/validation and quality of life research across adult populations. Education: Ph.D. in Psychology (Human Assessment specialization), Carleton University (1995) M.A. in Psychology (Lifespan Development and Aging), University of Victoria (1991) Pre-doctoral training at Geriatric Assessment Unit (Ottawa) and Neuropsychological Assessment Unit (Ottawa) Her research integrates psychometric theory with practical applications in aging populations, homeless/vulnerably housed individuals, and neuropsychological assessment tools. Key contributions include developing the Memory Test for Older Adults (MTOA), Hubley Depression Scale for Older Adults (HDS-OA), Quality of Life in Homeless and Hard-to-House Individuals (QoLHHI), and Subjective Age Identity Scale (SAIS). Scientific Awards: Killam Teaching Prize (2017) Distinguished Reviewer, Buros Institute of Mental Measurements (2013) She has taught graduate courses in Psychological Assessment, Measurement Principles, Scale Development, and Applied Neuropsychology, emphasizing ethical testing practices and response process research. Her lab's work on test adaptation for marginalized populations has informed international measurement standards.
Jiaxin Lin is an Assistant Professor in the Department of Electrical and Computer Engineering at Cornell University , affiliated with the Computer Systems Laboratory . She earned her Ph.D. in Computer Science from UT Austin (2025) , preceded by an M.S. from University of Wisconsin-Madison and a B.S. from ShenYuan Honors College at Beihang University. Her research focuses on co-designing software and hardware systems to enable high-performance data center communication, particularly through: Programmable network interface controllers (SmartNICs) Terabit network system stacks Cache/memory interconnects Compilers for in-network computing Chip-to-chip interconnects Her work addresses challenges in portability across heterogeneous SmartNICs, demonstrated through the development of the Alkali compiler framework (NSDI '25). Key themes include hardware abstraction, data center scalability, and network-compute co-design. Scientific Awards: Google Junior Faculty Award (2025) MIT EECS Rising Star (2024) Google Ph.D. Fellowship (2021) Meta Ph.D. Fellowship (2021)
Zsolt Kira serves as an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology's College of Computing, with additional affiliations at the Georgia Tech Research Institute and as Associate Director of ML@GT. He leads the Robotics Perception and Learning (RIPL) Lab, driving research at the intersection of machine learning and robotics. Dr. Kira earned his Ph.D. in 2010 under Professor Ron Arkin, establishing foundational expertise in robotics and AI before transitioning to his current academic role after industry experience at SRI International Sarnoff. His research pioneers beyond supervised learning through unsupervised, semi-supervised, self-supervised, and continual/lifelong learning frameworks, while advancing distributed perception via multi-modal fusion and cross-robot information integration. This dual focus addresses core challenges in robotic autonomy and sensor processing. Analysis of his 15 most recent publications reveals dominant trends in embodied AI systems, robust foundation model adaptation, and multimodal learning architectures. Key themes include neural radiance field applications, reinforcement learning for locomotion, and novel benchmarks for memory evaluation in agents. While specific advisees and grants aren't documented in the source material, his RIPL Lab leadership implies active graduate mentorship and research funding acquisition. The lab's work directly enables next-generation robotic systems through algorithmic innovation in perception and learning. The RIPL Lab operates as a hub for developing machine learning techniques that solve difficult perception problems in robotics, with particular emphasis on unsupervised learning paradigms and distributed multi-robot systems that push the boundaries of autonomous operation.