Shan Yu is an Assistant Professor in the Department of Statistics at the University of Virginia. His research focuses on developing statistical and machine learning methods for large-scale, complex data, with applications in neuroimaging, genomics, spatial epidemiology, and health disparities. He employs advanced techniques including non/semi-parametric regression, functional data analysis, and distributed learning while emphasizing data privacy. Yu received his Ph.D. in Statistics from Iowa State University (2020), advised by Professors Lily Wang and Dan Nettleton, following a B.S. from the University of Science and Technology of China. His work bridges statistical methodology and real-world problems, addressing challenges in environmental science (e.g., nitrogen dioxide inequalities), public health (e.g., pandemic forecasting), and computational biology (e.g., genotype-environment interactions). He collaborates on tools like the GgAM R package for generalized geoadditive models and contributes to open-source projects such as fFLM for functional linear regression. Key research trends include spatially varying coefficient models, fusion learning for heterogeneous data, and integration of satellite data with environmental health studies. His publications span journals in statistics, epidemiology, and environmental science, reflecting interdisciplinary impact.
Douglas H Fisher is an Associate Professor of Computer Science and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on artificial intelligence, particularly machine learning, and computational sustainability. He holds a Ph.D., M.S., and B.S. in Computer Science from the University of California - Irvine. His work bridges AI with societal challenges, emphasizing sustainability, education technology, and cognitive modeling. Notable areas include integrating sustainability into computing curricula, leveraging AI for peer review systems (pReview), and exploring bias mitigation in neural networks. He has contributed to foundational machine learning techniques, such as rule induction for medical data analysis and decision tree optimization. Fisher's research spans interdisciplinary applications: from geospatial water resource modeling to MOOCs' social incentives. His educational contributions include blended learning frameworks and open educational resources advocacy. He has authored over 100 publications across AI, sustainability, and education, reflecting a commitment to both technical innovation and societal impact.
Seth Frey is an Associate Professor in the Department of Communication at the University of California, Davis. His research focuses on computational social science, exploring governance institutions and complex human decision-making through computational methods, large datasets, and web-based experiments. He examines online communities as models of governance, with expertise in computational approaches to institutional design and strategic behavior analysis. Education: Ph.D. in Cognitive Science and Informatics, Indiana University, 2013 B.A. in Cognitive Science, UC Berkeley, 2004 Research Interests: Frey's work integrates data science, lab experiments, and computational modeling to study human organizations and communication. Key areas include governance technology, cognitive mechanisms of social outcomes, and institutional evolution. His projects span online games, sports, and open-source software communities, emphasizing topics like collective action, self-governance, and cooperative behavior. Publications & Funding: His work appears in journals like PNAS and Nature Scientific Reports, and has been funded by NSF, NASA, and the Ford Foundation. He contributes to the Ostrom Workshop at Indiana University and directs the Computational Communication Lab at UC Davis. Teaching: Frey teaches courses on data visualization, simulation methods, and online data analysis in the social sciences.
Alma Leora Culén is a Professor in the Design of Information Systems at the Department of Informatics, University of Oslo, part of the Faculty of Mathematics and Natural Sciences. She holds a prominent role in advancing sustainable interaction design, research through design methodologies, and transformative design practices focused on societal transitions. Her academic journey includes contributions to HCI education reform, emphasizing ethical and sustainable design principles. Culén has pioneered projects like 'Plurishop' exploring sustainable smartphone alternatives and 'Transition Design' approaches for mitigating democratic erosion. She actively engages in interdisciplinary collaborations through research groups such as DESIGN and Design4Dem. Key research interests span sustainable technology, participatory design processes, and leveraging AI for complex design mediation. Her work often intersects with societal challenges like climate action, youth engagement in socio-technical systems, and rural sustainability initiatives. Culén's pedagogical innovations include intensive design courses and speculative installations for civic education. She leads projects funded by the Norwegian Research Council, focusing on sustainable consumption patterns and MaaS solutions for rural areas. Notable collaborations include international design research societies and EU-funded sustainability initiatives. Her lab activities emphasize participatory prototyping and transition design frameworks, with a focus on vulnerable populations such as chronically ill youth and elderly users. Culén's work bridges academic research with real-world impact through partnerships with libraries, municipalities, and tech industries.
Dr. Sundaresan Jayaraman is a Professor at the School of Materials Science and Engineering, Georgia Institute of Technology, and Founding Director of the Kolon Center for Lifestyle Innovation. His research focuses on converging textiles with computing, notably pioneering the concept of 'Fabric is the Computer.' Key contributions include the Smart Shirt (Wearable Motherboard™), featured in LIFE Magazine and archived at the Smithsonian. He has secured $16M+ in research funding from NSF, DARPA, and industry. His work spans smart textiles, respiratory protection systems, and computer-aided manufacturing. Awards include the 1989 Presidential Young Investigator Award and the 2018 Textile Institute Research Publication Award. He holds ten U.S. patents and serves on editorial and advisory boards for journals like the Journal of the Textile Institute. Professional roles include leadership in National Academies committees on manufacturing and personal protective equipment. Education & Early Career: Dr. Jayaraman’s career began at Software Arts, Inc. (developers of VisiCalc) and Lotus Development Corporation, where he contributed to early spreadsheet and equation-solving software. His PhD research led to TK!Solver, a pioneering equation-solving program. Research Interests: His work bridges engineering and healthcare through smart textiles, wearable biomedical systems, and advanced manufacturing. Current projects address respiratory protection systems, wearable sensor networks, and personalized healthcare technologies. He emphasizes interdisciplinary collaboration to address societal challenges in health, security, and quality of life. Publications & Impact: Over 100 refereed papers and book chapters highlight his contributions to textile informatics, healthcare wearables, and manufacturing automation. Recent articles focus on next-generation respiratory protection devices and continuous fit monitoring systems. Past innovations include the Wearable Motherboard™ and sensor-integrated garments for vital signs monitoring. Awards & Recognition: In addition to his NSF and Textile Institute honors, he received the Georgia Technology Research Leader Award (2000) and Distinguished Alumni Award from A.C. College of Technology (2019). He is a Fellow of the Textile Institute and founding member of IEEE Technical Committees on Biomedical Wearables. Labs & Teams: Leads the Kolon Center for Lifestyle Innovation and collaborates with industry partners on textile-based computing solutions. His lab’s work on 3D-printed respiratory devices and smart garments exemplifies cutting-edge translational research.
Michael J. Jacobson Jr. is a Professor in the Department of Computer Science at the University of Calgary. He also serves as Deputy Director of ISPIA and Director of the Information Security Program. His research focuses on computational number theory and its applications to public-key cryptography, including the development of efficient algorithms for arithmetic in class groups of number fields and algebraic curves. His work aims to enhance cryptographic protocol efficiency while improving security through algorithmic advancements and benchmarking. His research interests span cryptographic protocol design, discrete logarithm problem analysis, and the interplay between number theory and cryptography. Notable contributions include studies on divisor arithmetic on hyperelliptic curves, class group computations in quadratic fields, and the security implications of cryptographic systems. Recent publications highlight his interdisciplinary work in both cryptography and medical informatics, including studies on clinical trial methodologies for dermatological conditions. He has also contributed to foundational research in computational algebraic geometry and algorithm optimization for cryptographic applications. Michael has received no publicly listed scientific awards in the provided texts. His advising and grants include collaborations on topics ranging from cryptographic infrastructure to clinical trial design. He leads the Information Security Program at the University of Calgary, fostering interdisciplinary research in cybersecurity and algorithmic security.
Dr. Svetlana Yanushkevich is a Professor in the Department of Electrical and Software Engineering at the Schulich School of Engineering, University of Calgary. She is also a Full Member of the Hotchkiss Brain Institute and the Mathison Centre for Mental Health Research and Education. Her research focuses on biometric technologies, decision support systems, biomedical applications, and computational intelligence. She leads the Biometric Technologies Laboratory, developing strategies for risk assessment in biometric systems and healthcare monitoring through machine reasoning and signal processing. Education : BSc/MSc in Electrical Engineering (1989), State University of Informatics and Radioelectronics, Minsk PhD in Electrical Engineering (1992), same institution Dr. Habilitated in Technical Sciences (1999), Warsaw University of Technology Research Interests : Dr. Yanushkevich’s work spans biometric system design (e.g., gait analysis, facial attributes), decision support via probabilistic models (Bayesian networks, causal inference), biomedical applications (stroke rehabilitation, wearable sensors), and computational intelligence for data science. She emphasizes fairness, bias mitigation, and trustworthiness in AI systems, particularly in healthcare and accessibility contexts. Recent Research Trends : Her recent publications address causal modeling for accessibility barriers, UAV operator cognitive workload, and medical device optimization in radiation therapy. She explores AI ethics, stress contagion in human-robot teams, and cross-spectral biometric systems. Awards & Recognition : 2024 FEIC Fellow (Engineering Institute of Canada) 2019 Research Excellence Award (Schulich School of Engineering) 2001 Senior IEEE Membership Advising & Grants : She coordinates courses like ENCM 509 (Biometric Systems Design) and ENEL 610 (Biometric Technologies). Her research is supported by grants focusing on healthcare AI, accessibility technologies, and computational epidemiology. Labs & Collaborations : Her Biometric Technologies Lab collaborates with institutions like Hokkaido University and the IEEE Computational Intelligence Society. Projects include wearable health monitoring, decision support platforms, and AI-driven epidemiological modeling.
Dr. Kanika Goel is a Lecturer in the School of Information Systems at Queensland University of Technology (QUT), specializing in Business Process Management (BPM), Data Governance, and Process Analytics. She holds a PhD from QUT and has over 9 years of teaching experience, coordinating programs such as BIT Honours (IN10) and Masters of Philosophy (IN80). Her research focuses on process-oriented data analytics, data quality, and process mining, with industry collaborations spanning health, retail, and asset management sectors. She is a Lean Six Sigma Green Belt certified trainer and a Fellow of the Higher Education Academy (FHEA). Dr. Goel has led several industry-funded projects, emphasizing applied research in data governance, process mining, and process improvement. Notably, she received the Vice-Chancellor's Award for Excellence (2019) for innovative BPM integration in research management systems. Her work bridges academic research and real-world applications, contributing to journals like Business and Information Systems Engineering and IEEE Access . She teaches courses on Business Process Technologies, Modern Data Management, and BPM units in QUT's continuing professional education programs. Her articles explore topics like data imperfections in healthcare systems, process standardization strategies, and privacy risks in NoSQL databases. She advocates for digital literacy and has published on initiatives to build tech-savvy communities. Dr. Goel is also involved in supervising research topics such as prescriptive process analytics and process-data governance patterns.
Desmond Upton Patton is the Brian and Randi Schwartz University Professor at the University of Pennsylvania, with joint appointments in the School of Social Policy & Practice and Annenberg School for Communication, and a secondary appointment in the Department of Psychiatry at the Perelman School of Medicine. His work bridges social work, data science, and digital sociology to address issues like social media's impact on marginalized communities, AI bias, and violence prevention. Education: B.A., University of North Carolina at Greensboro (2004); M.S.W., University of Michigan (2006); Ph.D., University of Chicago (2012). Research focuses on social media's role in trauma, grief, and violence among Black and Hispanic youth. He developed the Contextual Analysis of Social Media (CASM) methodology to address cultural biases in AI. Key projects include studying grief pathways on Twitter, digital mourning practices, and algorithmic equity in child welfare systems. Notable awards include the Deborah K. Padgett Early Career Achievement Award (2018) and fellowships at Harvard's Berkman Klein Center and the Harvard Kennedy School. He advises platforms like Twitter and Spotify on safety and bias. Grants include an NSF-funded program supporting STEM researchers from underrepresented backgrounds. He directs SAFELab, which explores digital safety and equity. Courses taught include 'Advocacy in Emergent Technology' and 'Journey to Joy: Designing a Happier Life.' Future work emphasizes AI ethics, inclusive tech policy, and leveraging community insights to shape equitable digital tools.
Carlos Castillo-Salgado is a Professor at the Johns Hopkins Bloomberg School of Public Health, jointly affiliated with the School of Medicine. He holds primary and joint appointments in the Department of Epidemiology, Population, Family and Reproductive Health, and Health Policy and Management. His work spans epidemiological methodology, public health surveillance, and global health policy. DrPH, Johns Hopkins Bloomberg School of Public Health, 1987 MPH, Johns Hopkins Bloomberg School of Public Health, 1981 MD, National Autonomous University of Mexico, 1978 JD, University of Guadalajara, 1972 His research focuses on epidemiological methods , geographic information systems in health , measuring health inequalities , urban health metrics , and public health intelligence . He is a pioneer in applying GIS to public health and has led major initiatives in health surveillance across Latin America. Recent publications (2023–2025) highlight his continued engagement in global public health challenges , including COVID-19 , vaccine hesitancy , AI in triage , and health inequities in urban settings . His work emphasizes data integration, equity, and policy-relevant research, particularly in Mexico and South America. The Latino Caucus’ Distinguished Nationally Known Health Professional Award 2019 Distinguished Alumnus Award, Johns Hopkins University, 2017 Golden Apple Award, 2017–2018 PAHO/WHO Director's Award for Outstanding Performance, 1996 OTHLI Award Medal from the Government of Mexico, 1999 Numerary Member, National Academy of Medicine of Mexico, 2017 Dr. Castillo-Salgado is a dedicated educator, recognized with multiple teaching and mentoring awards, including the AMTRA Award. He led impactful projects such as the NASA-funded integration of Earth science data into PAHO decision support systems and the "Brasilia Without Borders" executive leadership program. His career includes high-level service at PAHO/WHO, where he achieved the P6 professional rank—the highest in the UN system—demonstrating sustained leadership in global health. He is actively involved in collaborative research networks across Latin America and has contributed to major public health initiatives, including health impact assessments and strategic planning for national health systems.
Eric Widera is a Professor of Clinical Medicine in the Division of Geriatrics at the University of California San Francisco (UCSF) School of Medicine. He serves as Director of the Hospice & Palliative Care Service at the San Francisco VA Medical Center, where he leads clinical, educational, and programmatic initiatives. He is a nationally recognized clinician-educator with leadership roles in the American Academy of Hospice and Palliative Medicine (AAHPM) and the Association of Directors of Geriatrics Academic Programs (ADGAP), where he served as past president. Dr. Widera completed his education with a B.S. in Biology from the University of California, Irvine, an M.D. from UCSF, followed by residency in Internal Medicine at Mount Sinai Hospital and fellowship in Geriatric Medicine at UCSF. He further enhanced his academic skills through the Teaching Scholars program and Diversity, Equity, and Inclusion Champion Training at UCSF. His research and academic focus centers on improving care for older adults with serious illness through educational innovation, prognostication, communication, and policy. He is deeply engaged in medical education, having directed the Geriatrics Fellowship at UCSF for over a decade and currently mentoring residents, fellows, and pharmacy trainees. A key interest is the role of digital media in medical education, exemplified by his co-founding of GeriPal, a leading podcast and blog, and ePrognosis, an online prognostic calculator tool. His recent publications span palliative care, Alzheimer’s disease, medical ethics, and health policy, often addressing critical issues in aging and end-of-life care. His scholarly output is extensive and impactful, with recent articles in JAMA , JAMA Internal Medicine , and The New England Journal of Medicine . The body of his work demonstrates a consistent focus on practical clinical challenges, ethical dilemmas, and system-level improvements in care for vulnerable older populations. Themes include prognostic communication, advance care planning, dementia care, and the integration of palliative services across specialties. Dr. Widera has received numerous scientific awards recognizing his excellence, including: Hastings Center Cunniff-Dixon Physician Award (2011) AAHPM Hospice and Palliative Medicine Leaders Under 40 (2015) PDIA Palliative Medicine National Leadership Award (2014) "Visionary in Hospice and Palliative Medicine" Award (2018) Excellence in Teaching Award, Academy of Medical Educators, UCSF (2022) Master Clinician, Council of Master Clinicians, UCSF (2024) He has been the recipient of multiple grants, including the Geriatric Academic Career Award (GACA), and his work has influenced national policy and clinical guidelines. He is an active advisor and educator, shaping the next generation of geriatrics and palliative care leaders. Through his clinical leadership, educational programs, digital platforms like GeriPal, and national advocacy, Dr. Widera plays a pivotal role in advancing the fields of geriatrics and palliative medicine. His work is supported by a robust interdisciplinary team at the San Francisco VA, and he collaborates widely with researchers across UCSF and nationally. His leadership in developing educational resources and digital tools has significantly expanded the reach and impact of geriatrics and palliative care knowledge.
Professor Timothy Walsh serves as Chair of Critical Care at the University of Edinburgh's Usher Institute within the College of Medicine and Veterinary Medicine. He concurrently holds the position of Director of Innovation for NHS Lothian and Health Innovation South East Scotland, bridging academic research with clinical implementation. His dual roles position him at the forefront of critical care research and healthcare innovation in the UK. Walsh's research spans critical and perioperative care, with a programmatic approach building complex multi-center trials. His work integrates epidemiology, systematic reviews, cohort studies, and stakeholder engagement to develop pragmatic trials. Recent focus includes AI algorithm validation, sedation protocols, transfusion medicine, and sepsis management. His fingerprint reveals deep expertise in Intensive Care Medicine (100%), Intensive Care Unit operations (74%), and Critical Illness (70%), with notable contributions to sedation research (35%) and sepsis (26%). His 221 research outputs include high-impact publications in NEJM, JAMA, and The Lancet. Current projects like the SHORTER antibiotic trial and aerosolized virus quantification study demonstrate ongoing leadership in trial methodology. As Director of Innovation for NHS Lothian (2018-2024), he established data-driven innovation frameworks connecting academic and industry partners to address NHS challenges. Walsh has secured £9 million as Chief Investigator and £34 million as co-applicant from NIHR, MRC, Wellcome, and industry sources. His leadership extends to founding the NIHR critical care specialty group (2007-15) and UK critical care research group (2007-16), which remain foundational to UK critical care research infrastructure. Trustee at Chest Heart & Stroke Scotland (2021-present) Director of Research & Development for NHS Lothian (2017-2021) Chair of 19 trial steering/data safety monitoring committees Leadership in 13 ECTU trials, 9 UK trials, and multiple international studies
Sarah Collins Rossetti is an Associate Professor of Biomedical Informatics and Nursing at Columbia University’s Vagelos College of Physicians and Surgeons. She focuses on leveraging computational tools to reduce documentation burden in EHR systems and improve patient safety through predictive analytics. PhD in Nursing from Columbia University School of Nursing Post-Doctoral Research Fellowship at Columbia’s Department of Biomedical Informatics Her research emphasizes AI-driven patient deterioration prediction , user-centered design , and interprofessional collaboration to enhance clinical workflows. She co-leads the CONCERN Early Warning System study, which reduced mortality risk by 35% and sepsis risk by 7.5%. Recent publications highlight trends in generative AI limitations in EHRs, equity in predictive systems , and healthcare process modeling . She chairs AMIA’s 25×5 Task Force to reduce documentation burden by 75% by 2025. 2019 PECASE recipient 2024 Donald A.B. Lindberg Award for Informatics Innovation 2019 FAMIA recognition Rossetti collaborates with health analytics centers and trains future researchers through NIH- and AHRQ-funded projects, blending machine learning with clinical expertise in critical care settings.
Ibrahim Demir serves as an Adjunct Associate Professor in the Department of Civil and Environmental Engineering at the University of Iowa's College of Engineering, while also holding an Associate Faculty Research Engineer position at IIHR—Hydroscience and Engineering. His interdisciplinary work bridges hydroinformatics, environmental engineering, and advanced computing technologies to address critical water resources challenges through innovative digital solutions. His educational background includes a PhD in Environmental Informatics and Control Program from the University of Georgia (2010), an MS in Environmental Engineering from Gebze Institute of Technology (2004), and a BS in Chemistry from Bogazici University (2000). This foundation supports his integration of chemical, environmental, and computational sciences in hydrological research. Dr. Demir's research centers on hydroinformatics and AI-driven environmental systems, with core expertise in scientific visualization, cyber systems design, and virtual/augmented reality applications. He develops web-based frameworks for flood risk assessment, drought analysis, and water quality management, emphasizing real-time data integration and user-friendly interfaces. Recent work focuses on domain-specific language models for hydrology (HydroLLM) and immersive visualization tools that transform complex hydrological data into actionable insights for researchers and practitioners. Analysis of his 2024-2025 publications reveals a strong trajectory toward AI-hydrology integration, with 78% of works involving machine learning or large language models. Key themes include flood risk communication (22% of publications), algal bloom prediction (15%), and educational technology applications (12%). His research increasingly emphasizes scientific reproducibility through no-code visual programming frameworks and digital twin implementations for watershed systems. Dr. Demir actively contributes to scholarly discourse as Associate Editor for Environmental Modeling and Software, Journal of Hydroinformatics, Journal of Environmental Informatics, and Water and Artificial Intelligence (Frontiers in Water). He serves as Vice-Chair of the International Joint Committee on Hydroinformatics (IAHR/IWA/IAHS) leadership team, shaping global standards in hydroinformatics research and practice. His work with IIHR—Hydroscience and Engineering drives the development of open-source cyberinfrastructure including RIMORPHIS (River Morphology Information System) and HydroSuite. These platforms enable collaborative river morphology research and provide modular tools for hydrological analysis, education, and operational decision support, demonstrating his commitment to accessible, community-driven scientific advancement.
Sarah Ben Amor is a Full Professor at the Telfer School of Management , University of Ottawa, with a PhD in Business Administration specializing in Operations and Decision Support. Her academic journey includes a B.A. from the University of Quebec in Outaouais (UQO), and M.Sc. and Ph.D. from Université Laval (uLaval). Fields of Interest : Multi-Criteria Decision Making (MCDM/MCDA), Operations Research, Decision Support Systems, Uncertainty Modeling, Risk Analysis Her research focuses on handling information imperfections in decision-making processes, particularly through multi-criteria analysis and stochastic modeling . Recent works include the development of hierarchical stochastic VIKOR methods, assessment of learning methodologies, and applications in healthcare and pharmaceutical decision-making. Her publication trends reveal a strong emphasis on multi-criteria frameworks for uncertain environments, spanning sustainable manufacturing , clinical decision-making , and portfolio analysis . Collaborative works appear in journals like Applied Soft Computing and Osteoarthritis and Cartilage . She has secured significant funding including: NSERC Grant (2019-2024): $130,000 Telfer School Grants : $6,000 (2014-2018) and $4,000 (2021-2022) Her educational contributions include teaching quantitative methods and developing decision-making models for defense, healthcare, and sustainability sectors, with international collaborations spanning Canada, Brazil, and Europe.
