Stephen E. Still is a Professor of Practice in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo (UB), affiliated with the Institute for Sustainable Transportation and Logistics. His roles include teaching applied transportation planning and technology courses, advising students, and collaborating across disciplines between the School of Engineering and Applied Sciences and the School of Management. Prior to academia, he served as founder and managing director of Seabury Airline Planning Group and Diio, LLC, specializing in aviation consulting and IT. With over 30 years of industry experience, he held leadership roles at US Airways and United Airlines, focusing on strategic route planning, fleet management, and alliance development. Dr. Still holds a PhD in Civil Engineering and Operations Research from Princeton University, with a focus on transportation systems and economics, and a BS in Engineering (magna cum laude) from UB with a concentration in transportation planning. He has also completed advanced coursework in demand modeling at MIT. His research interests emphasize sustainable transportation systems and logistics, integrating engineering principles with operational efficiency. While his academic contributions primarily reside in transportation engineering, his interdisciplinary work incorporates wearable technology and sensor-based solutions for health monitoring, as evidenced by his extensive publication record in smoking cessation and behavioral health research. Scientific awards and grants are not explicitly mentioned in the provided information. Dr. Still’s advising and teaching focus on fostering student engagement in transportation innovation and real-world problem-solving. His professional experience bridges academia and industry, reflecting a commitment to practical applications of engineering and logistics principles.
David Mosse is Professor of Social Anthropology at SOAS University of London and Director of the Centre for Anthropology and Mental Health Research in Action (CAMHRA). He holds a DPhil from Oxford University and is a Fellow of the British Academy and Academy of Social Sciences. His career integrates academic research with development practice, including roles as Oxfam's South India Representative and advisor to international agencies. Research spans: Anthropology of mental health and cultural psychiatry Caste, Dalit rights, and development activism Environmental history and water resource management Christianity in South Asian society Current work focuses on ethnographic approaches to psychiatric crisis care and suicide prevention. Publications since 2020 predominantly address mental healthcare innovation (particularly Open Dialogue), caste in modern economies, and suicide prevention methodologies, reflecting interdisciplinary engagement across anthropology, psychiatry, and development studies. Awards and honors: Fellow of the British Academy Fellow of the Academy of Social Sciences 2021 Jack Goody Award recipient Supervises doctoral candidates researching caste histories, democratic movements, and mental healthcare innovation. Leads the ESRC-funded 'Anthropology of Peer-Supported Open Dialogue' study and collaborates with NHS Trusts on mental health service design. Directs CAMHRA, coordinating research on culturally responsive mental healthcare models across UK and South Asian contexts.
Donald French is a Full Professor in the Department of Mathematical Sciences at the University of Cincinnati, holding this position since 1999. Additionally, he has been a Contractor/Consultant at Wright-Patterson Air Force Base since 2010. He earned a PhD in Applied Mathematics from Cornell University (1985), an MS in Applied Mathematics from Cornell (1983), and a BA in Mathematics and Physics from the State University of New York at Oswego (1980). His research focuses on interdisciplinary mathematical modeling, particularly in Cellular Physiology and Neuroscience. Key areas include inverse problems in olfactory cilia dynamics, neuronal networks, and biofilms. He has also contributed extensively to numerical analysis, specializing in error analysis for finite element methods, meshfree techniques, and discontinuous Galerkin methods. Research Highlights: Development of energy-preserving numerical schemes for time-dependent PDEs in phase transitions and viscoelasticity. Analysis of meshfree and discontinuous Galerkin methods for diffusion problems. Collaboration with Steven Kleene on olfactory cilia modeling since 2001. His work spans computational neuroscience, fluid dynamics, and aerospace engineering, with recent advancements in trajectory planning for unmanned vehicles using PDE-based models. French has secured over $600,000 in NSF grants for projects like ion channel distribution modeling (2005–2009) and mathematical physiology career development (2002–2004). French has held leadership roles, including Graduate Program Director at UC (2015–2017 and 1999–2001), and served on Taft Research and departmental committees. His teaching includes advanced courses in numerical analysis, PDEs, and mathematical biology, which he helped pioneer at UC.
Andrew Currie is a Professor and Associate Dean (Research & Innovation) at Murdoch University's School of Medical, Molecular and Forensic Sciences, within the College of Environmental and Life Sciences. He leads the Sepsis Diagnostics Research Group at the Centre for Molecular Medicine and Innovative Therapeutics and co-heads the Neonatal Infection and Immunity Team with Clinical Professor Tobias Strunk at the Wesfarmers Centre of Vaccine & Infectious Diseases at Telethon Kids Institute. His research focuses on immunology and infectious diseases in pediatric populations, particularly sepsis diagnostics and neonatal immunity. Education: PhD (Immunology, University of Western Australia, 2001); BSc (Biotechnology with Honors, Murdoch University, 1997). Research Interests: Sepsis diagnostics, innate immunity mechanisms in neonates, medical biotechnology for diagnostics (e.g., biosensors), and translational research in pediatric infections. Collaborates internationally with institutions in Canada, Denmark, the UK, US, and China. Aims to reduce sepsis burden in vulnerable populations through advanced molecular methods and interdisciplinary partnerships. Key Affiliations: Lead of Sepsis Diagnostics Research Group (Murdoch University), Senior Lecturer in Immunology, Honorary Associate at Kids Research Institute Australia. Past roles include leadership in the Centre for Molecular Medicine and Innovative Therapeutics. Scientific Contributions: Over 100 peer-reviewed articles focusing on sepsis biomarkers, neonatal immunity, tick-borne diseases, and clinical trials for interventions like vitamin C and probiotics in critical illness. Active in developing precision medicine approaches for neonatal sepsis. Grants & Funding: Co-leads major projects on sepsis diagnostics and neonatal infection, supported by national and international grants. Collaborates on multi-institutional initiatives. Labs/Teams: Sepsis Diagnostics Research Group (Murdoch) and Neonatal Infection and Immunity Team (Telethon Kids Institute). Works closely with the Personalised Medicine Centre and Health Futures Institute.
Stephen Pankavich is a Professor and Department Head in the Department of Applied Mathematics and Statistics at the Colorado School of Mines. He holds a PhD in Mathematical Sciences from Carnegie Mellon University, with research focused on partial differential equations, kinetic theory, and mathematical biology. His work bridges theoretical analysis and computational methods, addressing challenges in plasma dynamics, epidemiological modeling, and multiscale systems. Education: PhD, Mathematical Sciences, Carnegie Mellon University (2005) MS, Mathematical Sciences, Carnegie Mellon University (2001) BS, Mathematical Sciences, Carnegie Mellon University (2000) Research interests include the analytical and numerical study of collisionless plasmas, HIV dynamics, and epidemiological models. He has received awards such as the W.M. Keck Mentorship Award and the Colorado School of Mines Alumni Teaching Award. His articles explore topics like plasma decay rates, HIV therapy models, and particle-tracking algorithms. He has advised over 20 graduate and undergraduate students, contributing to impactful research in applied mathematics and computational science.
Lei Liu, PhD, is a Professor of Biostatistics, Medicine, and Statistics and Data Science at Washington University in St. Louis. He holds positions in the Roy and Diana Vagelos Division of Biology & Biomedical Sciences (DBBS), the Institute for Informatics, Data Science and Biostatistics (I2DB), and the Center for Biostatistics and Data Science (CBDS). His research focuses on biostatistical and data science methods, including survival analysis, longitudinal data modeling, and machine learning applications in healthcare. He collaborates with clinicians across disciplines like cardiology, ophthalmology, and addiction medicine. Dr. Liu’s work emphasizes high-dimensional omics data analysis, medical cost modeling, and joint multi-outcome models. He is an Associate Editor of Biometrics and a former member of the NIH Biostatistical Methods and Research Design Study Section. He mentors underrepresented minority researchers through the NHLBI PRIDE program.
Andrew McArthur is a Professor in the Department of Biochemistry & Biomedical Sciences at McMaster University, where he leads the McArthur Laboratory. His research focuses on bioinformatics , genomics , and computational biology with a specialization in genomic surveillance of antimicrobial resistance (AMR) . He spearheads the Comprehensive Antibiotic Resistance Database (CARD) and collaborates with the Canadian Anti-Infective Innovation Network (CAIN) , GenEpio Consortium , and IRIDA Platform for pathogen genomics. Education : PhD in Biochemistry (University of Victoria, 1996), Postdoctoral work at Marine Biological Laboratory (1998-1999) and National Museum of Natural History (1996-1998) His research spans antimicrobial resistance surveillance , machine learning applications , viral genomics (including SARS-CoV-2), and pathogen evolution . He has developed tools like CARD and IRIDA to standardize AMR data and enable rapid infectious disease analysis. Recent work includes machine learning models for predicting AMR, cloud-based pathogen detection , and resistome profiling in clinical and environmental contexts. He has mentored graduate students including Jalees Nasir (HSGSA Impact Award 2025), Dirk Hackenberger , Autumn Arnold , and Emily Bordeleau , as well as postdoctoral fellows like Sheridan Baker . His teaching includes courses in practical bioinformatics and biomedical consulting at McMaster University.
Li Liu is the Sir Robert Ho Tung Professor in the Department of East Asian Languages and Cultures at Stanford University. She joined the Stanford faculty in 2010, following 14 years at La Trobe University in Melbourne, Australia, where she taught archaeology and was elected a Fellow of the Academy of Humanities in Australia. Her research focuses on early China's archaeology, encompassing the Neolithic and Bronze Ages, ritual practices, cultural interactions with the Old World, domestication processes, state formation, and urban development. She holds a B.A. in Archaeology from Northwestern University (Xi'an), an M.A. in Anthropology from Temple University (Philadelphia), and a Ph.D. in Anthropology from Harvard University (1994). Dr. Liu's educational background includes degrees from prestigious institutions across multiple countries, reflecting her global academic engagement. Her work bridges archaeological methods with interdisciplinary approaches to understand societal complexity and environmental adaptation in ancient China. Notably, her contributions to understanding cultural exchanges between China and neighboring regions have been influential in East Asian Studies. Her research interests emphasize material culture analysis, settlement patterns, and the socio-political dynamics underlying early state formations. This includes investigations into ritual landscapes, agricultural practices, and urbanization processes in ancient China. Her studies often involve collaborative projects that integrate archaeological data with historical and anthropological perspectives. Dr. Liu has been recognized for her scholarly contributions, including her Fellowship in the Australian Academy of Humanities. Though her primary role is in archaeology, her Google Scholar publications reflect interdisciplinary collaborations in medical research, audio engineering, and environmental science, suggesting diverse academic engagements. In advising, she mentors students in archaeological and anthropological studies, though specific advisee names are not listed here. Her grants and funding history, while not detailed in the text, would likely support her archaeological fieldwork and interdisciplinary projects. She has contributed to the Stanford Center for East Asian Studies and affiliated programs, fostering cross-cultural research initiatives.
Daniel Almirall is a Research Associate Professor at the University of Michigan's Institute for Social Research (ISR) and holds a courtesy appointment in the Department of Statistics. He co-directs the Data Science for Dynamic Intervention Decision-making Center (d3c), focusing on developing statistical methods for adaptive interventions in healthcare and education. With a Ph.D. in Statistics from the University of Michigan (2007), his career includes roles at Duke University and the Durham VA Center for Health Services Research. His research emphasizes adaptive interventions—dynamic treatment strategies optimized via Sequential Multiple Assignment Randomized Trials (SMARTs)—to address chronic health conditions, mental health (e.g., autism, depression), and substance abuse. Key contributions include methodological frameworks for causal inference, longitudinal data analysis, and implementation science. Notable recognition includes a Top 20 Autism Article (2016) and a US Department of Education-recognized methodology publication (2020). Almirall advises students across statistics, biostatistics, and education, mentoring over a dozen PhD, master’s, and undergraduate researchers. His work bridges theory and practice, collaborating with clinicians and educators to deploy evidence-based interventions. Ongoing efforts focus on scalable strategies for schools and clinics to adopt adaptive interventions, leveraging d3c's collaborative environment.
Peng Ding is an Associate Professor in the Department of Statistics at the University of California, Berkeley. He holds a B.S. in Mathematics and B.A. in Economics from Peking University, followed by an M.S. in Statistics from the same institution. He earned his Ph.D. in Statistics from Harvard University in 2015 and completed a postdoctoral fellowship at Harvard T.H. Chan School of Public Health. His research focuses on causal inference, missing data, Bayesian statistics, and applied statistical methods in biomedical and social sciences. Ding is particularly known for his work on improving the robustness of causal inference in observational studies and randomized experiments through sensitivity analysis and design-based approaches. His research interests include methodologies to address contaminated data (e.g., missing values, measurement errors), factorial experiments, and sensitivity analysis for unmeasured confounding. He has contributed to theoretical advancements in rerandomization, regression adjustment, and instrumental variable techniques. His work emphasizes practical applications in fields such as epidemiology, social sciences, and public health. Peng Ding teaches courses on causal inference, statistical theory, and linear models. His most recent courses include Data, Inference, and Decisions and Linear Models . He actively mentors graduate and undergraduate students through directed study programs. His research has been published in top-tier statistical journals and presented at international conferences.
Lexin Li is a Professor in the Department of Biostatistics and Epidemiology at the University of California, Berkeley School of Public Health, with additional affiliations at the Helen Wills Neuroscience Institute, the UC Berkeley-UCSF Joint Program on Computational Precision Health, and the Center for the Theoretical Foundations of Learning, Inference, Information, Intelligence, Mathematics and Microeconomics at Berkeley (CLIMB). He received his BE in Electrical Engineering from Zhejiang University (1998) and PhD in Statistics from the University of Minnesota (2003), followed by postdoctoral training at UC Davis School of Medicine. He joined North Carolina State University as Assistant Professor in 2005, was promoted to Associate Professor in 2011, and served as visiting faculty at Stanford University and Yahoo Research Labs (2011-2013) before joining UC Berkeley as Associate Professor in 2014, where he was promoted to Full Professor in 2018. Dr. Li's research spans statistical methodology development for neuroimaging data analysis, tensor statistics, and machine learning applications to biomedical problems. His work focuses on brain connectivity and network analysis, imaging causal inference, tensor regression, dimension reduction, and statistical machine learning with applications to Alzheimer's disease, Parkinson's disease, and other neurological disorders. His methodological innovations bridge theoretical statistics with practical neuroscience applications, particularly in multimodal neuroimaging analysis and brain network modeling. His recent publications demonstrate a strong trajectory in integrating deep learning with classical statistical inference, particularly in tensor analysis, functional data modeling, and causal inference. The research shows increasing sophistication in handling high-dimensional, complex neuroimaging data while developing rigorous statistical frameworks for inference. His work increasingly focuses on multimodal data integration and developing methods that can handle the complexity of real-world neurological data. Dr. Li has received numerous prestigious honors including being elected as a Fellow of the American Statistical Association (2017), Fellow of the Institute of Mathematical Statistics (2021), Elected Member of the International Statistical Institute, and Fellow of the American Association for the Advancement of Science (2024). Fellow, American Statistical Association (2017) Fellow, Institute of Mathematical Statistics (2021) Elected Member, International Statistical Institute Fellow, American Association for the Advancement of Science (2024) Editor-in-Chief, Annals of Applied Statistics (2025-2027) As an academic leader, Dr. Li serves as Co-Director of the Biostatistics Program (2019-) and Director of Graduate Admissions (2015-) at UC Berkeley. He is an active editor, currently serving as Editor-in-Chief of the Annals of Applied Statistics (2025-2027), and has held associate editor positions at multiple top statistical journals including the Journal of the American Statistical Association and Journal of Computational and Graphical Statistics. He also serves as a Standing Member of the NIH Emerging Imaging Technologies in Neuroscience Study Section (2023-2027). His research has been supported by various NIH grants focused on statistical methodology for neuroimaging analysis. Dr. Li leads a vibrant research group focused on statistical neuroimaging and machine learning methodology, with strong connections to the Helen Wills Neuroscience Institute and collaborations across multiple departments at UC Berkeley. His team develops innovative statistical methods that address real challenges in neuroscience research while maintaining rigorous theoretical foundations. The group maintains active collaborations with neuroscientists and clinicians working on Alzheimer's disease, Parkinson's disease, and other neurological conditions.
David Porter is a Professor of English and Comparative Literature at the University of Michigan's LSA (Literature, Science, and the Arts). He holds a MA from Cambridge University (1990) and a PhD from Stanford University (1996). His research focuses on transcultural translation, early modern China-Europe exchanges, and Great Lakes environmental humanities. Key projects include the Detroit River Story Lab and the Great Lakes Theme Semester. He has authored works such as The Chinese Taste in Eighteenth-Century England and edited Comparative Early Modernities: 1100-1800 . His recent work bridges environmental stewardship with community engagement in the Great Lakes region. Research interests span seventeenth/eighteenth-century British literature, postcolonial studies, material culture, and environmental humanities. His publications analyze cross-cultural aesthetics, global early modernity, and anarchist political thought. He teaches courses on literary journalism and research methodologies. Porter's interdisciplinary projects engage public audiences through initiatives like the Great Lakes Writers Corps and the Great Lakes Arts, Cultures, and Environments Summer Program. His scholarship integrates literary analysis with ecological and historical frameworks, emphasizing interconnected global histories.
Dr. Andrew Curtis is a Professor in the Department of Population and Quantitative Health Sciences at Case Western Reserve University's School of Medicine. He also holds a joint appointment in the Department of Anthropology, College of Arts and Sciences. His research focuses on spatial epidemiology, context-driven spatial data collection, and spatial confidentiality, with methodological expertise in geospatial data collection and analysis. He previously directed the WHO Collaborating Center for Remote Sensing and Public Health and has advised numerous public health agencies internationally. His work addresses health disparities at neighborhood scales, disaster response, and spatial syndromic surveillance. Dr. Curtis has mentored 10 PhD graduates now working in academia and public health sectors globally. Education includes a PhD in Geography from SUNY Buffalo (1995), MA in Geography from SUNY Buffalo (1991), and a BA from Portsmouth Polytechnic (1987). He has taught courses in GIS for health, medical geography, and global health. His advisory roles include collaborations with the CDC, Red Cross, and public health departments in Ohio and internationally. His research has been applied to cholera outbreaks, opioid overdose patterns, and pandemic response strategies. He co-edited a special issue on health geography and serves on the editorial board of the Annals of the Association of American Geographers. Dr. Curtis' spatial video methodologies have enabled fine-scale mapping in informal settlements, disaster zones, and conflict-affected areas. His recent work includes geospatial support for Ohio hospitals during the pandemic and energy vulnerability analysis. He emphasizes participatory research and context-enriched data collection to bridge gaps between health research and actionable policy.
Xiaogang Wu is a Professor of Sociology and Yufeng Global Professor of Social Science at New York University, affiliated with the College of Arts & Science and the Department of Sociology. He holds a Ph.D. from UCLA, an M.A. from Peking University, and a B.A. from Renmin University of China. His research focuses on China's social stratification, education policy, inequality dynamics, urban studies, and quantitative methodologies. Key interests include social cohesion, housing policy impacts, migrant labor outcomes, and the interplay between education and socioeconomic status. His recent work analyzes pandemic vulnerability, educational expansion effects on earnings, and gender dynamics in reform-era China. He has contributed to major publications like Research in Social Stratification and Mobility and Demographic Research .
Catherine Bolten is a Professor of Anthropology and Peace Studies at the University of Notre Dame's Keough School of Global Affairs, holding concurrent appointments in Africana Studies and Poverty Studies. Her primary affiliation is the Kroc Institute for International Peace Studies, where she also served as Director of Doctoral Studies (2018–2023). She is affiliated with multiple interdisciplinary initiatives including the Eck Institute for Global Health and the Initiative on Race and Resilience. Bolten holds a PhD in Anthropology from the University of Michigan (2008), an MPhil from the University of Cambridge (2000), and a BA from Williams College (1998). Her research focuses on Sierra Leone, examining themes such as youth agency, structural violence, food security, and climate change through long-term ethnographic engagement. She has conducted fieldwork on primate-human coexistence, Ebola crisis response, and post-conflict development since 2003. Her research interests bridge anthropology, peacebuilding, and environmental studies. Recent work explores climate change impacts in rural Sierra Leone, youth participation in peace processes, and the intersections of ecology and violence. She has authored three books and over 40 peer-reviewed articles, with ongoing projects funded by the NEH and ND Institute for Advanced Studies. Bolten has advised over 30 doctoral and master’s students in anthropology, peace studies, and global health. Her awards include the Undergraduate Mentoring Award (2013, 2022) and the UC Press Public Anthropology Prize. She serves on editorial boards for African Conflict and Peacebuilding Review and Studies in Comparative International Development , and has held leadership roles in professional organizations like the American Anthropological Association.
