Hadi Meidani is a Clinical Associate Professor at the Carle Illinois College of Medicine , specifically within the Department of Biomedical and Translational Sciences at the University of Illinois at Urbana-Champaign . He teaches courses in Civil and Environmental Engineering, including topics like Systems Engineering & Economics , Machine Learning in CEE , and Uncertainty Quantification . Ph.D., Civil Engineering, University of Southern California (2012) M.S., Electrical Engineering, University of Southern California (2012) M.S., Structural Engineering, Sharif University of Technology (2005) B.S., Civil Engineering, K.N. Toosi University of Technology (2002) Dr. Meidani's research focuses on uncertainty quantification , scientific machine learning , and optimization under uncertainty for engineering systems. His work spans stochastic multiscale analysis , physics-informed machine learning , and model reduction techniques. His recent publications emphasize machine learning for infrastructure systems , graph neural networks , physics-informed models , and traffic assignment . Key trends include deep learning , multi-fidelity modeling , and neural operator transformers applied to metamaterial design , seismic reliability , and autonomous freight delivery .
Fei Fang is an Associate Professor in the Software and Societal Systems Department at Carnegie Mellon University (CMU) , where she explores the intersection of artificial intelligence and multi-agent systems . Her work integrates machine learning with game theory to address challenges in security , sustainability , and mobility , aligning with the AI for Social Good mission. Ph.D. in Computer Science, University of Southern California (2016) B.Eng. in Electronic Engineering, Tsinghua University (2011) Recent research focuses on reinforcement learning , large language models (LLMs) , and human-AI collaboration . Her team’s work has been recognized with 15+ awards across prestigious venues like IAAI, AAAI, and IJCAI. Notable accolades include the 2023 Allen Newell Award , 2022 Sloan Fellowship , and NSF CAREER Award (2021) . She actively contributes to educational initiatives , including teaching "Demystifying AI for Everyone" at CMU, and has sought part-time teaching assistants for course development. Her research spans 15+ domains , including AI ethics , cyber defense , traffic optimization , and public health .
Abhijit Banerjee is the Ford Foundation International Professor of Economics at MIT and Director of the Abdul Latif Jameel Poverty Action Lab (J-PAL). A 2019 Nobel laureate in Economic Sciences, his research focuses on development economics, political economy, and poverty alleviation. He co-authored influential books like Poor Economics and Good Economics for Hard Times , emphasizing evidence-based policies and randomized controlled trials. Banerjee’s work addresses global challenges such as education, health, and social welfare, with notable contributions to microfinance, public health interventions, and anti-poverty programs. He holds leadership roles in global initiatives like the Global Education Evidence Advisory Panel and has advised governments worldwide. His research spans topics from police resource allocation in India to the impact of information during crises like demonetization and the pandemic. Education: Bachelor’s in Statistics, Presidency College, Kolkata M.A. in Economics, Jawaharlal Nehru University PhD in Economics, Harvard University Key Contributions: Co-founder of J-PAL, promoting evidence-based poverty reduction strategies. Pioneer in using randomized controlled trials (RCTs) for policy evaluation. Research on microfinance, education reforms, and health interventions in developing countries. Awards: Nobel Prize in Economics (2019), Infosys Prize in Social Sciences (2009), Member of the National Academy of Sciences (2020). Grants/Advisory Roles: Collaborations with institutions like the World Bank, UN, and governments on poverty, health, and education policies. Labs/Teams: J-PAL global network, Abdul Latif Jameel Poverty Action Lab.
Professor Rebecca Lawson is a Professor of Neuroscience and Computational Psychiatry at the University of Cambridge, affiliated with the Department of Psychology and Bye-Fellow at Peterhouse College. Her research focuses on understanding how humans learn to make predictions under uncertainty, with applications to mental health conditions such as anxiety and depression. She leads the Prediction and Learning (PaL) Lab, which combines computational modeling, neuroimaging (e.g., 7T MRI), and behavioral experiments to study cognitive processes in typical and atypical populations. Key research interests include computational psychiatry, autism spectrum disorders, neuroimaging techniques, and the neurochemical basis of learning mechanisms. She has received significant funding, including a £4.3m Wellcome Mental Health Award and the Sir Henry Dale Fellowship. Notable contributions include advancing theories of neural gain and sensory expectations in autism, as well as studies on uncertainty processing in anxiety and depression. Professor Lawson holds academic awards such as the BNPA Lishmann Prize and the BAP Psychopharmacology Award. She actively contributes to public engagement, including initiatives like Knit-a-Neuron and involvement with PrideinSTEM. Her lab collaborates internationally, with projects like the CamRAA study investigating autism-anxiety overlaps and the Chemical and Brain Basis of Uncertainty (CBBU) study exploring pharmacological interventions. Education: PhD in Cognitive Neuroscience (University of Cambridge), BA (Hons) Psychology & Philosophy (University of Glasgow). Grants: £4.3m Wellcome Award, Parke-Davis Fellowship, Lister Institute Prize. Labs/Teams: Principal Investigator of the PaL Lab; collaborations with MRC Cognition and Brain Sciences Unit, Yale University, and Brown University.
Daniel Cooney is an Assistant Professor in the Department of Mathematics at the University of Illinois Urbana-Champaign. He holds additional affiliations as an Affiliate at the Carl R. Woese Institute for Genomic Biology. His research focuses on applying partial differential equations (PDEs), dynamical systems, and stochastic processes to study evolutionary dynamics, particularly in biological and social systems. Key themes include multilevel selection, evolutionary game theory, and the emergence of cooperative behavior. Cooney earned his PhD in Applied and Computational Mathematics from Princeton University, advised by Simon Levin, and completed a postdoc as a Simons Fellow in Mathematical Biology at the University of Pennsylvania. His work bridges theoretical mathematics with applications in ecology, epidemiology, and social sciences. Recent publications explore topics like altruistic punishment in cultural systems, classroom-turnover dynamics, and protocell evolution. He actively participates in academic outreach, co-organizing conferences such as the AMS Special Session on Mathematics of Infectious Disease and the SIAM Minisymposium on Social-Ecological Systems. His research has been published in high-impact journals including *Proceedings of the National Academy of Sciences* and *Bulletin of Mathematical Biology*.
Jon Singletary serves as Dean and holds the Diana R. Garland Endowed Chair of Child and Family Studies at Baylor University's Diana R. Garland School of Social Work. He joined Baylor in 2003 after earning his PhD in Social Work from Virginia Commonwealth University (VCU), alongside an MSW from VCU and MDiv from Baptist Theological Seminary. His career includes prior roles as Associate Dean (2010–2015) before becoming Dean in 2015. Before academia, Singletary worked as a pastor, community organizer, and social service administrator. His research focuses on strengthening congregational ministries, community development, and advocacy for vulnerable populations. Notable projects include launching the Texas Hunger Initiative and directing the Strengthening Congregational Community Ministries Project. He co-founded the Faith and Service Technical Education Network (FASTENnetwork.org) to bridge faith-based organizations and social service sectors. His publications explore spirituality's role in social work, faith-based program development, and community organizing strategies. Recent work examines career resilience among professionals in aging care and leadership development through Enneagram frameworks. Earlier research addressed child food security, orphan care in Kenya, and rural community capacity building. Singletary's leadership emphasizes integrating faith and practice, evidenced by his edited volumes on Christianity and social work, and his advocacy for competency-based education models. He holds leadership roles in national organizations like the North American Association of Christians in Social Work and has advised global initiatives in Africa.
Therese Nordin is an Assistant Professor at Umeå University's Department of Community Medicine and Rehabilitation, specializing in occupational therapy. Her research focuses on social participation and togetherness among older adults within home care contexts, particularly through the STAY-IN-TOUCH project. Research Themes Gerontological perspectives on loneliness Co-creative methods in home care interventions Relational and transactional models of human activity Power dynamics in health services research Qualitative approaches to social participation Recent Publications Her work explores the interplay between structural care provision and subjective experiences of social connectedness in aging populations, with specific attention to: Gender norms and loneliness in men Home care professionals' conceptualization of social needs Design of participatory care models Quantitative-qualitative integration in aging research Methodological Expertise Therese employs a range of qualitative approaches, including: Scoping reviews Creative co-design methodologies Narrative analysis Transactional perspective frameworks
Elena Agapie is an Assistant Professor in the Department of Informatics at the Donald Bren School of Information & Computer Sciences, University of California, Irvine. Her research lies at the intersection of human-computer interaction (HCI), health, and behavior change, focusing on designing technologies that support individuals in adopting and maintaining healthy behaviors through human-centered approaches. She is affiliated with the Connected Learning Lab and the Institute for Future Health at UCI. Her educational background includes a PhD in Human Centered Design and Engineering from the University of Washington, an MS in Computer Science from Harvard University, and a BS in Computer Science from Jacobs University Bremen in Germany. She has also conducted research at Microsoft Research, FXPAL, Intel Labs, and NASA Jet Propulsion Lab. Elena's research focuses on designing tools that integrate evidence-based behavioral interventions with user needs, particularly in mental health, chronic disease management, and social support systems. She explores how technology can support therapist-client collaboration, enable tailored health interventions, and leverage crowd expertise for personalized behavior change plans. Her work often involves participatory design, qualitative studies, and prototyping of interactive systems for diverse populations, including youth, hospitalized patients, and underserved communities. Her recent publications, primarily in top-tier venues like CHI and CSCW, reflect a strong trend toward social computing in health, longitudinal behavior support, and the design of inclusive digital health tools. Key themes include goal setting, conversational agents, social sharing in health tracking, and cross-disciplinary collaboration in health technology development. Best Paper Award (top 1%) at CHI 2017 Honorable Mention Best Paper Award (top 5%) at CHI 2016 Best Paper Award (top 1%) at HCOMP 2015 Honorable Mention Best Paper Award (top 5%) at CHI 2013 Elena has been funded by the National Science Foundation, National Institutes of Health, and UCI internal grants. She actively mentors PhD students including Bruna Oewel, Meeshu Agnihotri, and Mehreen Masood, and is currently recruiting students interested in HCI, health, and behavior change. She previously led the outreach program in the HCDE department at the University of Washington, creating workshops that introduced K–12 students to engineering and human-centered design, reaching over 2,000 students across public schools and community events. She runs initiatives to broaden participation in computing and advises undergraduate students in outreach and curriculum development. Her lab collaborates with clinical partners and interdisciplinary teams to ensure real-world impact of her research.
Jonathan Winawer is an Associate Professor of Psychology and Neural Science at New York University (NYU). He leads the Winawer Laboratory for Human Visual Perception and Neuroscience, which is affiliated with the NYU Psychology Department, NYU Center for Neural Science, NYU Neuroscience Institute, and collaborates with the NYU Comprehensive Epilepsy Center and Stanford University's Human Intracranial Cognitive Program. Ph.D., Massachusetts Institute of Technology (2007) M.S., City College of the City University of New York (2005) A.B., Columbia University (1995) His research focuses on the biological basis of visual perception, including computational models of the visual pathways using fMRI, EEG, ECoG, and psychophysics. Key areas include: Encoding of visual stimuli in neural pathways Perceptual memory's influence on cognition Neural circuit properties underlying imaging signals Individual differences in visual perception Publications highlight interdisciplinary approaches spanning computational neuroscience, neuroimaging, and psychophysics, with recent work on population receptive fields, spatial frequency tuning, and memory-related cortical dynamics. He has mentored numerous students and postdocs, many of whom have advanced to academic and research roles at institutions like Stanford, Columbia, and the University of Amsterdam. Department of Psychology, NYU Center for Neural Science, NYU Neuroscience Institute, NYU Comprehensive Epilepsy Center, NYU Stanford University collaborations
Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.
Brett Welch is an Assistant Professor and Biostatistician at the University of Houston with dual appointments in the Department of Communication Sciences and Disorders and the Department of Psychological, Health, and Learning Sciences within the College of Liberal Arts and Social Sciences. Dr. Welch's educational background includes: Ph.D. in Communication Science and Disorders from the University of Pittsburgh M.S. in Communication Sciences and Disorders from the University of Texas Rio Grande Valley B.S. in Linguistics from the University of Texas at Austin B.A. in Communication Sciences and Disorders – Speech-Language Pathology from the University of Texas at Austin Dr. Welch's research sits at the intersection of psychology and communication. He seeks to understand how psychological processes like personality and psychopathology influence communication behaviors, and conversely, how communication behaviors impact psycho-social well-being. His work leverages quantitative methods, cross-sectional studies, and intensive longitudinal designs to interrogate the dynamic interplay between psychological processes and voice and communication behaviors. This research aims to advance understanding of functional voice disorders, improve assessment of psychopathology, and promote well-being for people with and without communication disorders. Dr. Welch has received several notable awards: Honors Council of Academic Programs in Communication Sciences and Disorders PhD Scholarship (2024) New Century Scholars Doctoral Scholarship from the American Speech-Language-Hearing Foundation (2023) New Investigator Forum from The Voice Foundation (2021) As an academic, Dr. Welch serves as an ad hoc peer reviewer for various scientific journals in speech-language pathology and psychology. He is also a mentor in the Students to Empowered Professional Mentoring Program and a member of the American Speech-Language-Hearing Association. His teaching includes Special Problems: Introduction to Quantitative Modeling (COMD 8398). Dr. Welch maintains an active research program focused on the intersection of psychology and communication, with particular emphasis on voice disorders and their psychological correlates. His work combines biostatistical approaches with clinical insights to advance understanding in this specialized field.
Liping Liu is a Professor in the Department of Management at The University of Akron's College of Business. He holds a Ph.D. in Business from the University of Kansas (1995), Master of Engineering in Systems Engineering (1991), and dual bachelor's degrees in Applied Mathematics (1986) and River Dynamics (1987). Ph.D., University of Kansas MS, Huazhong University of Science and Technology B.E., Wuhan University BS, Huazhong University of Science and Technology His research spans Artificial Intelligence , Electronic Business , Systems Analysis , Data Quality , and Belief Function Theory . He pioneered coarse utility theory and linear belief functions , now taught in top Ph.D. programs across multiple disciplines. Key trends in his publications include Belief Function Applications (2012-2024), Medical Data Systems (2003-2015), and Decision Theory (2004-2014). Recent works focus on Gamma Belief Functions (2024) and computational improvements in linear belief function operations (2019-2016). Scientific contributions recognized via: Microsoft Azure Educator Grant (2014-2016) Inclusion in Who's Who in America (2010-2013) and Who's Who in the World (2011-2013) As an editor and committee member for major conferences (INFORMS, AMCIS, Belief Functions conferences), he bridges academic research with practical systems implementation in e-business and healthcare domains.
Flavio Vasconcellos Comim is a Full Professor at IQS School of Management in Barcelona, Spain, holding the Chair of Ethics and Christian Thought (intercenter). His research focuses on the intersections of Sustainability, Economics, and Ethics. Fields of Interest : Human Development, Capability Approach, Social Exclusion, Regional Development, AI Ethics, Poverty Stigma (Aporophobia), Sustainable Development, Social Welfare, Justice, and Happiness. Recent research includes publications on youth HDI in Spain (2025), AI bias against the poor (2024), and critiques of Sen's social choice theory (2024). He leads projects like Big data applied to the study of aporophobia and Population Medicine and Sustainable Development collaborations with China. His academic output spans journals like Regional Studies , AI and Society , and Cambridge Journal of Regions, Economy and Society , with keywords spanning Economics, Machine Learning, Human Development, and Social Justice. No formal students or awards are listed in available records.
Adriana Tapus is a Full Professor at ENSTA Paris, affiliated with Institut Polytechnique de Paris, leading the Autonomous Systems and Robotics Laboratory (SAR) within the Computer Science and Systems Engineering Unit (U2IS). She holds an HDR (Habilitation) and a PhD from EPFL, Switzerland, with postdoctoral experience at USC. Her research focuses on socially assistive robotics, human-robot interaction (HRI), and personalized therapy for individuals with physical/cognitive impairments. She directs the IP Paris Doctoral School and coordinates national/international projects like the EU-funded ENRICHME and SWEET. Education: PhD in Mobile Robotics, EPFL (2005) Habilitation (HDR), ENSTA Paris (2011) M.S. Computer Science, University Joseph Fourier Engineer, Politehnica University of Bucharest Research Interests: Tapus pioneers socially assistive robotics, integrating machine learning, human modeling, and multimodal communication (verbal/non-verbal/para-verbal). Her work addresses adaptive therapies for vulnerable populations using robotics, physiological data interpretation, and context-aware interaction. Key themes include: Human-robot cooperation and trust Emotion recognition and expression Personalized rehabilitation systems AI ethics and human-centered design Publications: Over 150 articles, with recent work exploring humor in HRI, teleoperation trust models, and cross-cultural intelligent vehicles. Notable 2025 contributions include studies on robot laughter efficacy and multimodal facial expression frameworks. Awards: 2025: 4 IROS papers accepted 2016: 25 Women in Robotics recognition 2010: Romanian Academy Award Multiple conference best paper awards (RO-MAN, ICRA, etc.) Advising & Grants: Supervised over 20 PhD students and led projects like EU Horizon 2020 ENRICHME. Current students focus on teleoperation dynamics, robot humor, and haptic interfaces. Active in editorial roles (IJSR, THRI) and conference organization (HRI General Chair 2019). Labs/Teams: Founder of RoboticsByDesign lab and co-initiator of the Hi! Paris interdisciplinary AI center. The SAR lab develops systems for healthcare, education, and human-robot collaboration.
Ewain Gwynne is a Professor of Mathematics at the University of Chicago, affiliated with the Committee on Computational and Applied Mathematics (CCAM) and the Statistics Department. He previously held postdoctoral positions at the University of Cambridge and earned his Ph.D. from MIT in 2018 under Scott Sheffield. His research focuses on probability theory, particularly random geometric structures in statistical mechanics, including Schramm-Loewner evolution (SLE), Liouville quantum gravity (LQG), and random planar maps. Education: Ph.D. in Mathematics, MIT (2018); M.Sc., MIT (2015); B.Sc., Northwestern University (2013). Research Interests: Random geometric objects in statistical mechanics Liouville quantum gravity and its metric properties Random planar maps and their scaling limits SLE and its relationship with LQG Random walks on random planar maps Percolation and permutons His recent articles explore topics such as supercritical LQG, Gaussian curvature on random maps, and harmonic balls in LQG. He has advised multiple Ph.D. students and serves as an associate editor for Probability and Mathematical Physics . His work bridges probability theory, geometry, and mathematical physics, with applications to understanding critical phenomena in random systems.
