Matthew Price is the George W. Albee Green & Gold Professor of Psychological Science and Director of the Clinical Psychology Training Program at the University of Vermont's College of Arts and Sciences. He holds a B.A. from SUNY Binghamton (2004), an M.A. (2006), and Ph.D. (2011) from Georgia State University. His research focuses on expanding clinical care access for trauma survivors and anxiety disorder patients via technology-driven interventions. Key areas include mobile health applications, wearable sensors, and acute trauma care in Emergency Departments. His interdisciplinary approach involves collaborations with computer science, bioinformatics, and medicine. Current projects explore digital biomarkers (e.g., heart rate variability), technology adoption barriers, and culturally adapted therapies. He leads the Center for Research on Emotion, Stress, and Technology, emphasizing translational frameworks bridging basic research and clinical practice. Recent work includes randomized controlled trials evaluating mobile apps like 'Bounce Back Now' for disaster-related PTSD, and sleep-monitoring studies using wearable devices. Over 150 peer-reviewed articles highlight his focus on trauma mechanisms, symptom networks in veterans, and tech-enabled mental health innovations. His lab actively addresses global mental health disparities through mHealth solutions.
Dr. Michael Stevens is a Senior Lecturer at University of New South Wales (UNSW) Canberra , where he focuses on advanced manufacturing and biomedical device control systems . His work bridges digital manufacturing for SMEs with smart artificial heart technologies , emphasizing industry collaboration and translational research. Specializes in physiological control systems for rotary blood pumps Develops unobtrusive fall detection systems for dementia patients Leads international projects on total artificial heart development Education : B.Eng (Medical - First Class Honours), Queensland University of Technology (2010) PhD in Physiological Control for Biventricular Assist Devices, University of Queensland (2014) Research Trends show consistent focus on: Machine learning for biomedical diagnostics (2018–2025) mmWave radar and thermal sensors in patient monitoring (2021–2024) Computational fluid dynamics in artificial heart modeling (2016–2024) Physiological control algorithms for rotary blood pumps (2011–2025) Scientific Awards : UNSW Scientia Education Award (2021) for contextual teaching Heart Foundation Runner-up for "Smart Artificial Hearts" pitch (2021) ARC PGC Supervisor Award (2017) for mentoring Grants & Supervision : Holds over $6 million in competitive funding including MRFF and ARC grants. Currently supervises 4 PhD students while maintaining industry partnerships with VitalCare and BiVACOR. Labs & Facilities : Works across UNSW Engineering labs and Graduate School of Biomedical Engineering platforms, including mock circulation loops and high-performance computing clusters for CFD simulations.
Jingwei Cheng is an Assistant Professor in the Department of Molecular, Cellular, and Biomedical Sciences at the University of New Hampshire's College of Life Sciences and Agriculture. His research focuses on understanding the molecular mechanisms of DNA tumor viruses, particularly polyomaviruses, and their roles in cancer development. Specifically, his work investigates how Merkel cell polyomavirus (MCV) contributes to Merkel cell carcinoma (MCC) through interactions with tumor suppressors like p53 and RB, and the epigenetic regulation of transcriptional complexes. Cheng completed his B.S. in Biotechnology at Peking University and earned his Ph.D. in Biochemistry from the University of Illinois at Urbana-Champaign. His lab explores viral oncogenesis, MYC-driven cancers, and the interplay between transcriptional activation (via the SLaP complex) and repression (via PRC1.6) in neuroendocrine tumors. He also studies RNA methylation and splicing regulation in cancer cells with MYC overexpression. Cheng's research has identified druggable targets such as PRMT5 and the Tip60-p400 complex, aiming to develop therapies targeting MYC-driven cancers. His work bridges virology and cancer biology, with implications for neuroendocrine tumors like MCC and small cell lung cancer. He teaches courses on virology and cancer biochemistry and mentors students in molecular oncology research. His recent publications focus on viral mechanisms of immune evasion, molecular markers in MCC subtypes, and the therapeutic potential of targeting viral and epigenetic pathways. Cheng collaborates on genome-scale CRISPR screens and omics technologies to uncover cancer dependencies.
Tal Ezer is a Professor in the Department of Ocean & Earth Sciences at Old Dominion University (ODU), part of the College of Sciences. His expertise lies in physical oceanography, climate change, and sea level dynamics. He holds a Ph.D. from Florida State University (1989), M.Sc. and B.Sc. from Hebrew University of Jerusalem (1984 and 1981). Education: Ph.D. in Physical Oceanography, Florida State University (1989) M.Sc. in Atmospheric Sciences, Hebrew University of Jerusalem (1984) B.Sc. in Physics (major) and Mathematics (minor), Hebrew University of Jerusalem (1981) Research Interests: Physical oceanography, including Gulf Stream dynamics and coastal processes Climate change impacts on sea level rise and coastal flooding Numerical modeling of ocean circulation and environmental interactions Applications of ocean models to ecological and societal challenges Grant Highlights: "A Tool to Measure Community Stress and Social Capital to Support Disaster Resilience Planning" ($270,000, 2016–2017) "Modeling sea ice-ocean ecosystem responses to climate changes in the Bering-Chukchi-Beaufort Seas" ($108,000, 2008–2012) "Red Sea - Dead Sea conveyance feasibility study" ($98,540, 2008–2010) Key Awards: 2018 MIT SOLVE Competition Winning Team 2017 Distinguished Research Award (ODU) 2016 Highly Cited Paper, Thomson-Reuters 2002 NOPP Excellence in Partnering Award Labs & Teams: Center for Coastal Physical Oceanography (CCPO), ODU Collaborations with NASA, NOAA, and international institutions
Dr. Michael Hiley is a Senior Lecturer in Sports Biomechanics and Motor Control at Loughborough University, part of the School of Sport and Exercise Science. He serves as the Programme Director for Joint Honours programmes involving Sport Science and leads the Centre for Gymnastics Research. His roles include teaching and research in biomechanics and motor control. Michael holds a Joint Honours degree in Sport Science and Mathematics from Loughborough University (1993) and a PhD in the computer simulation of gymnastics skills from the same institution. His research interests are centered around sports biomechanics and motor control , with a focus on optimizing athletic performance and understanding movement strategies. Key areas include: Biomechanical analysis of gymnastics skills and equipment Optimization of techniques in golf, basketball, and badminton Functional variability in whole-body coordinated movements Control strategies under uncertain conditions, such as deceptive actions in sports His publications explore biomechanical analysis across various sports, emphasizing optimal technique optimization, sensor technology comparisons (e.g., IMUs vs optical systems), and the impact of environmental factors like slopes on performance. Recent work highlights strategies for controlling movements under uncertainty and the biomechanics of deceptive actions in sports. Michael is actively involved in the Sports Biomechanics and Motor Control Research Group and directs the Centre for Gymnastics Research , fostering collaborative projects in sports science and technology.
John Rowan is a Professor of Physical Geography and Director of the UNESCO Centre for Water Law, Policy & Science at the University of Dundee. His roles include advancing sustainable development, particularly SDG6 (water and sanitation), and leading interdisciplinary initiatives. Previously, he served as Vice Principal for Research and inaugural Dean of the School of Social Sciences. His research focuses on environmental change, climate impacts on water resources, and policy-driven solutions, with global collaborations in Bangladesh, India, and Kenya. He has held advisory roles in Scottish Government’s Centres of Expertise and chairs UNESCO’s UK International Hydrological Committee. Research Interests: Environmental change, climate-water-food nexus, river basin management, sediment dynamics, and policy integration. His work bridges academic and applied domains, emphasizing governance and sustainable practices. Key projects include enhancing water security under climate uncertainty, developing risk frameworks for drinking water, and addressing the water-food-energy nexus. Publications: Over 111 articles, focusing on climate adaptation, water resource vulnerabilities, and ecohydrological modeling. Recent highlights include studies on the Karakoram Anomaly’s hydrological tipping points and frameworks for climate-resilient water safety plans. Awards: Gold Engage Watermark Award (2020), United Nations Risk Award (2019). Projects span international collaborations and policy advisory roles. He has supervised 12 students and led over 33 research projects, including the Hydro Nation Scholars Programme. Labs/Teams: UNESCO Centre for Water Law, Policy & Science; Centre for Environmental Change and Human Resilience (CECHR), collaborating with the James Hutton Institute. Active in global forums like the UNFCCC Climate Assembly and World Water Forum.
Bing Yan is an Assistant Professor in the Department of Electrical and Microelectronic Engineering at Rochester Institute of Technology (RIT), affiliated with the Kate Gleason College of Engineering. She holds a B.S. in Information Management from Renmin University of China (2010), and M.S. and Ph.D. degrees in Electrical Engineering and Statistics from the University of Connecticut (2012–2017). Prior to RIT, she was an Assistant Research Professor at the University of Connecticut. Dr. Yan’s research focuses on power system optimization , including grid integration of renewables (wind/solar), microgrid operations, distributed energy systems, and manufacturing scheduling. She has published over 30 peer-reviewed articles and secured grants from the National Science Foundation (including a CAREER Award), Department of Energy, and industry partners like Brookhaven National Laboratory and ABB. Her work emphasizes mixed-integer linear programming and machine learning applications in energy systems. Notable contributions include stochastic unit commitment models for wind farms, voltage control via deep reinforcement learning, and multi-layer weather models for PV prediction. She advises on projects involving grid resilience, smart manufacturing, and data-driven optimization. Awards: National Science Foundation Faculty Early Career Development (CAREER) Award Multiple NSF grants, DOE grants, and industry contracts Teaching: Courses include Circuits I , Electric Power Transmission & Distribution , and Advanced Power Systems . She also mentors students through co-op programs and independent studies. Labs/Teams: Leads the Intelligent Lab of Power and Manufacturing (ILPM), focusing on multidisciplinary solutions for energy and manufacturing systems. The lab emphasizes hands-on training and innovation in smart grid technologies and sustainable energy systems.
Raymond T. Ng is a Professor of Computer Science at the University of British Columbia (UBC) and serves as Director of the Data Science Institute . In addition, he is the part-time Chief Informatics Officer at the PROOF Centre of Excellence for the Prevention of Organ Failures located at St Paul’s Hospital. Since 2016 he has held the prestigious Canada Research Chair in Data Science and Analytics. Education B.Sc. (Hons.) Computer Science, University of British Columbia, 1986 M.Math. Computer Science, University of Waterloo, 1988 Ph.D. Computer Science, University of Maryland, College Park, 1992 Research Interests Professor Ng’s research lies at the intersection of data mining , text mining , health informatics , sensor analytics , and databases . Over the past decade he has focused on two major domains: Genomics & Biomarker Discovery: Developing multi-omics biomarker panels for heart, lung and kidney transplant rejection and COPD exacerbations using transcriptomics, proteomics and metabolomics data. Natural Language Processing: Mining and summarizing conversational text such as emails, blogs and meeting transcripts to generate structured metadata and actionable insights. Scientific Awards Canada Research Chair in Data Science and Analytics (2016-2026) Best Paper Award, ACM SIGMOD 2004 Best Paper Award, ACM SIGKDD 2001 Selected among Best Papers of VLDB ’99 & ’98 Governor General’s Gold Medal, UBC (1986) Research Funding & Leadership Since joining UBC in 1992, Professor Ng has continuously secured major peer-reviewed funding from NSERC, CIHR, Genome Canada, CFI, MITACS and industry partners (Google, IBM, SAP). He leads or co-leads several large-scale initiatives: HEARTBiT multi-marker blood test for cardiac transplant rejection (CIHR 2018-2021) MERIDIAN ocean acoustic data infrastructure (CFI 2018-2021) Pan-Canadian Early Detection of Lung Cancer (Terry Fox 2018-2021) Business Intelligence Network (NSERC 2009-2014) Multiple Genome Canada programs on biomarker translation (2004-2018) Laboratories & Teams Professor Ng directs the Data Science Institute and works closely with the Natural Language Processing Research Group . At the PROOF Centre he heads a multidisciplinary team of statisticians, computer scientists and clinicians advancing computational biomarker pipelines from discovery to clinical implementation.
Sara Wade is a Lecturer in Statistics and Machine Learning at the University of Edinburgh , within the School of Mathematics . Her research focuses on Bayesian statistics, machine learning, and their applications in health sciences, particularly in dementia diagnosis and predictive modeling. She holds a PhD from the University of Milan and has held academic positions at the University of Cambridge and University of Warwick before joining Edinburgh. She teaches a popular Machine Learning and Python course for Master’s and final-year undergraduate students, attracting nearly 200 enrollments annually. Her work integrates Bayesian methods with modern machine learning, emphasizing interdisciplinary applications such as scalar-on-image regression and biomarker analysis. Notable contributions include developing hierarchical Dirichlet processes for clustering and uncertainty quantification in RNA velocity studies. She secured a Royal Society of Edinburgh grant for her dementia research project, which aims to improve early diagnosis through statistical modeling. Education: PhD in Statistics, University of Milan Bachelor’s in Mathematics, University of Maryland Wade advocates for diversity in STEM, actively participating in the Women in Machine Learning community. Her research bridges statistical rigor and computational tools, fostering collaborations across academia and healthcare sectors.
William Balch, PhD, is a Professor in the Department of Molecular and Cellular Biology at Scripps Research. His research focuses on linking genetic variation in human populations to protein function using machine learning tools like Gaussian Process (GP) modeling. He pioneered concepts in proteostasis and spatial covariance, exploring how genetic and environmental factors influence protein folding and disease. Education: Ph.D. in Microbiology from University of Illinois (1979) Research interests include inherited diseases (e.g., CFTR, AATD, NPC1), aging-related proteostasis collapse, and host-pathogen interactions in SARS-CoV-2. His lab develops computational platforms to model protein design and discover therapeutic interventions. Key projects involve GP-based analysis of genetic diversity, small molecule therapeutics targeting chaperone systems, and understanding viral evolution via spatial covariance. His work bridges genomics and phenomics to address disease mechanisms at atomic resolution. Grants and collaborations focus on protein-folding correction, with applications in precision medicine and climate change mitigation through RuBisCo optimization in plants.
Rich Walker is an Assistant Professor in the Department of Biology, Geology, and Environmental Science at the University of Tennessee at Chattanooga (UTC). His research focuses on freshwater ecosystems, particularly understanding how stressors affect stream biodiversity and ecological processes. He leads the Freshwater Ecology and Conservation Lab, emphasizing interdisciplinary approaches to environmental challenges. Education: PhD in Ecology (University of Wyoming, 2019), MS in Biology (University of Central Arkansas, 2011), and BS in Environmental Science (University of Central Arkansas, 2008). Research interests include freshwater salinization, non-perennial stream dynamics, and fisheries conservation. His work bridges basic and applied questions, such as how climate change and human activities alter water quality and habitat availability. Recent studies explore predictive modeling of conductivity in the Chesapeake Bay watershed and biogeochemical responses in intermittent streams. Publications span Environmental Science & Technology Water , Nature Water , and Science of the Total Environment . His 2024 studies address conductivity trends and non-perennial stream management. Key findings include global gaps in salinization research and crayfish population dynamics under climate variability. Service roles include membership in UTC’s Curriculum Committee, Izaak Walton League’s Save Our Streams, and the Hartman Nature Reserve Board. Teaching covers ecology, limnology, and fisheries management.
Daniel Powell is a Senior Lecturer in Health Psychology and Programme Director of the MSc Health Psychology at the University of Aberdeen, School of Medicine, Medical Sciences and Nutrition. He is a core member of the Aberdeen Health Psychology Group and the interdisciplinary Centre for Labour Market Research. He holds a PhD from the University of Southampton and became a Fellow of the Higher Education Academy in 2019. His educational background includes: BSc (Hons) Psychology – University of the West of England, 2007 MSc Health Psychology – University of Southampton, 2009 PhD Psychology – University of Southampton, 2014 Daniel's research focuses on health psychology, particularly using intensive longitudinal methods such as ecological momentary assessment (EMA) to study stress, fatigue, self-regulation, and decision-making in real-world contexts. His work spans chronic illness (e.g., multiple sclerosis, diabetes), healthcare professionals (e.g., doctors, nurses), and occupational settings (e.g., fly-in fly-out workers). He leads the Stress and Health Research Theme and convenes regular workshops to support health psychology researchers. His methodological expertise includes real-time data collection, psychophysiology (e.g., heart rate variability, cortisol), and interdisciplinary collaboration with health economics, primary care, and bioengineering. His recent publications (2024–2025) reveal a strong trend in investigating decision fatigue in healthcare, stress and recovery patterns in medical professionals using biometric monitoring, and the psychosocial impact of shift and rotation work. He frequently employs EMA and systematic reviews to explore behavioral patterns in context. His work also extends to sustainable clinical research and digital health tools for pandemic response. His scientific recognition includes: Stan Maes Early Career Award, European Health Psychology Society (2019) Rosemary Anne Price Student Award, MS Society (2013) Daniel actively supervises five PhD students on topics including decision fatigue in healthcare, quality of life after limb loss, stress in medical and dental students, and low-carbon clinical trials. He teaches across postgraduate programs, coordinates the PU5053 course on Stress, Personality & Health, and co-founded an annual Summer School in Intensive Longitudinal Methods. He has no indication of part-time status and is actively engaged in research, teaching, and leadership. He is affiliated with several professional organizations, including the British Psychological Society (Chartered Psychologist), Division of Health Psychology, European Health Psychology Society, and UK Society for Behavioural Medicine. His research lab is embedded within the Aberdeen Health Psychology Group, which fosters interdisciplinary collaboration and methodological innovation in health behavior research.
Thomas Smucker is a Professor and Graduate Chair in the Department of Geography at Ohio University's College of Arts and Sciences. He is based in Clippinger Hall on the Athens Campus and is affiliated with International Studies, African Studies, and International Development Studies programs. His research centers on human-environment interactions in East Africa, with a focus on climate change adaptation, food security, rural livelihoods, and environmental governance. He integrates local knowledge systems and political economy frameworks to understand vulnerability and resilience in African drylands. His interdisciplinary work is supported by NSF-funded projects including EACLIPSE and LKCCAP. Dr. Smucker teaches courses in human geography, development, food security, and environmental change. His recent publications reflect a strong emphasis on gender, governance, and community-based adaptation. He has contributed to the IPCC's Sixth Assessment Report as a Contributing Author and currently serves as Editor of the Research in International Studies, Africa Series at Ohio University Press. Advising and Mentoring Award, Center for International Studies, 2021 Grasselli Brown Outstanding Teacher Award, College of Arts and Sciences, 2021 He mentors master’s students conducting field research in Ghana, the Gambia, Kenya, Tanzania, India, and Brazil. His advising emphasizes field-based, interdisciplinary inquiry into development and environmental challenges. He has been involved in projects supported by the National Science Foundation and other international research initiatives. Dr. Smucker’s research is deeply collaborative, often involving multi-institutional teams and local stakeholders. His work on the convergence of climate adaptation, disaster risk reduction, and land restoration highlights institutional innovation under devolved governance in Kenya. He is committed to centering non-climatic drivers in vulnerability analysis and advancing social justice in environmental policy.
Andrei Khrennikov is Professor of Mathematics at the Department of Mathematics, Linnaeus University, where he also serves as director of the International Center for Mathematical Modeling (ICMM) . He leads a vibrant research group focused on interdisciplinary modeling in physics, biology, cognition, and social systems. Research Interests: His work spans a vast interdisciplinary landscape, including mathematical physics, p-adic and non-Archimedean analysis, quantum foundations, quantum-like modeling of cognition and decision-making, econophysics, and biological dynamics . He is a pioneer in applying quantum probability and formalism outside quantum physics, especially in psychology and social sciences. The Växjö series of quantum theory conferences , which he organizes, is the longest-running continuous conference series on quantum foundations, fostering dialogue between theorists, experimentalists, and philosophers. His recent publications (2021–2025) show a strong focus on quantum cognition, p-adic biology, entanglement models, and social laser theory , often leveraging generalized probability and open quantum systems frameworks. Scientific Contributions: Developed quantum-like models for cognition, decision-making, and biological processes. Pioneered use of p-adic and ultrametric analysis in genetics and brain dynamics. Advanced classical random field models as alternatives to quantum interpretations. Introduced the social laser model for collective emotional amplification in societies. He is actively involved in major research projects such as QUARTZ (Quantum Information Access and Retrieval Theory) and DYNALIFE (Information, Coding, and Biological Function) . His work bridges mathematics, physics, and cognitive science, promoting a unified framework for understanding complex systems through quantum-inspired tools.
Yang Liu is an Assistant Professor in the Department of Electrical and Computer Engineering at the Baskin School of Engineering, University of California, Santa Cruz. Previously, they were affiliated with Harvard University and earned their PhD in 2015 from the Department of EECS at the University of Michigan, Ann Arbor. Their research lies at the intersection of machine learning, fairness, and trustworthy AI, with a strong focus on large language models, federated learning, and causal reasoning. Their research interests include: Machine Learning and Fairness Federated and Privacy-Preserving Learning Large Language Model Safety and Unlearning Causal Inference and Counterfactual Reasoning Anomaly Detection and Robust Forecasting Human-AI Interaction and Ethical AI Recent publications (2024–2025) demonstrate a strong trend in developing methods for machine unlearning, fairness in LLMs, and robustness under label noise and distribution shifts. Their work frequently appears in top-tier venues such as NeurIPS, ICLR, ICML, AAAI, and KDD, often in collaboration with researchers like Zhaowei Zhu, Mingyan Liu, Jiaheng Wei, and Kun Zhang. Themes include algorithmic fairness, model accountability, and human-aligned AI systems. Scientific contributions include: Frameworks for LLM unlearning and model editing Methods for fair classification and recourse Robust time series forecasting under anomalies Test-time adaptation in multimodal models Causal approaches to debiasing and policy learning While no formal advising list is provided, the depth and volume of collaborative work suggest active mentorship of graduate students and postdocs. Their research program is highly active, with numerous ongoing projects in trustworthy and socially responsible AI.
