Qiang Zhu is a Professor in the Department of Computer and Information Science at the University of Michigan-Dearborn, holding the William E. Stirton Professorship (2017–2024). He founded the Data Science/Management Research Laboratory and is affiliated with the Michigan Institute for Data Science (MIDAS). His research spans data science, data management, and machine learning. Ph.D., University of Waterloo M.S., McMaster University M.Eng., Southeast University B.S., Southeast University Research focuses on advanced data indexing, query optimization, and AI-driven data management, with applications in genomics, network systems, and education. His work integrates machine learning with database systems for scalable solutions. Recent publications include topics in federated learning fairness, digital twin middleware, project-based CS education, and genome data indexing. Scientific contributions recognized through awards like the Wilkes Award (2008), ACM Distinguished Scientist (2013), and Springer Nature Editor of Distinction (2025). 2013–2018: Department Chair NSF, IBM, and Ford grants Over 250 conference committee roles He directs the Data Science/Management Research Lab, focusing on collaborative projects in genome analytics and smart computing infrastructures.
Michael A. Lieberman is a Professor in the Graduate School at the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley. He joined UC Berkeley in 1966 and has received numerous accolades, including the Distinguished Teaching Award (1971) and Guggenheim Fellowship (1972-1973). His research focuses on low-temperature plasma physics and chemistry, particularly plasma-assisted materials processing, capacitive/inductive discharges, and nonlinear plasma dynamics. Education: Ph.D., Electrical Engineering, Massachusetts Institute of Technology (1966) B.S./M.S., Electrical Engineering, Massachusetts Institute of Technology (1962) Research Interests: Prof. Lieberman's work bridges fundamental plasma theory and industrial applications. Key areas include: Modeling of electromagnetic effects in capacitive discharges Hybrid analytical/numerical simulations of plasma processes Nonlinear wave phenomena in RF plasmas Plasma-material interactions for semiconductor fabrication Development of global models for atmospheric-pressure discharges Current projects (2018-2019) involve 2D fluid-analytical simulations, high-pressure discharge modeling, and particle-in-cell methods. Publications Focus: Recent articles emphasize computational plasma physics, including PIC simulations of transport phenomena, sheath dynamics in electronegative plasmas, and resonance effects in RF heating. His work consistently advances predictive modeling for industrial plasma applications. Awards & Honors: AVS Plasma Science Prize (2022) NPSS Marie Curie Award (2020) Will Allis Prize (2006) Von Engel Prize (2005) IEEE Plasma Science Award (1995) Fellowships: APS, AAAS, IEEE, AVS, IPCS, IOP Collaborations & Support: Collaborates extensively with Prof. A.J. Lichtenberg (nonlinear dynamics/plasma textbooks). Research funded by DOE Office of Fusion Energy Sciences and Applied Materials/Display (AKT). Maintains active international partnerships in plasma diagnostics and simulation.
Dr. Alraune Zech is an Assistant Professor at the Department of Earth Science, Utrecht University , and a Guest Scientist at the Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research - UFZ . Her work focuses on Hydrogeology and Groundwater Modeling , particularly in quantifying Aquifer Heterogeneity and Transport Theory . Education: Diploma in Mathematics, University of Leipzig (2009) PhD in Environmental System Science, Friedrich-Schiller-University Jena (2013) Research Interests: Alraune investigates transport experiments , field-scale dispersion , and statistical aquifer parameter estimation from pumping tests. Her projects include groundwater simulations in the Thuringian Basin and revisiting transport theories with modern tools. Publications highlight her contributions to macrodispersivity estimation , geostatistical toolboxes , and heterogeneous aquifer modeling . Recent works in Groundwater and Advances in Water Resources emphasize practical applications and theoretical advancements. Collaborations include projects with the UFZ, Utrecht University, and international institutions. She has contributed to interdisciplinary efforts in groundwater-surface water coupling and contaminant transport analysis .
Dr. Viola C. Schmid is a postdoctoral researcher in the Quaternary Archaeology research group at the Austrian Academy of Sciences (ÖAI) in Vienna, with additional teaching roles at the University of Tübingen and University of Vienna. She earned her master's degree in 2013 and completed a binational PhD magna cum laude in 2019 through a joint program between the Universities of Tübingen and Paris Nanterre. Her career includes research positions at the University of Geneva (2019), ÖAI (2020-2021), and Leiden University (2021-2022), before returning to ÖAI in October 2022. Her research explores prehistoric archaeology across Africa and Europe, focusing on human evolution during the Pleistocene. Key interests include: Population dynamics and knowledge transfer in hunter-gatherer societies Technological systems development in Paleolithic and Mesolithic contexts Middle and Later Stone Age site excavations Reanalysis of archaeological collections using modern methods Schmid's publications primarily investigate lithic technology evolution, site formation processes, and Middle Stone Age adaptations in Africa and Europe. Her work frequently employs experimental approaches and interdisciplinary methods to analyze raw material sourcing, tool production techniques, and cultural transitions. Research sites span South Africa (Umhlatuzana, Diepkloof), Senegal (Toumboura III), Austria (Csaterberg), and Germany (Swabian Jura caves). While no scientific awards are documented, she actively contributes to international projects like the South African Middle Stone Age research during MIS 5 and the Peuplement humain et paléoenvironnement en Afrique program. Her grants and students are not specified in available materials. At ÖAI, she collaborates within the Quaternary Archaeology research group, focusing on Pleistocene human-environment interactions. She maintains academic networks through co-authorships with researchers across Europe and Africa, particularly in lithic technology and Paleolithic site analysis.
Stuart Hamilton is a part-time Professor and Chair of the Department of Coastal Studies at East Carolina University (ECU) and the UNC Coastal Studies Institute. He holds a Ph.D. in Geography (GIS) from the University of Southern Mississippi (2012), an M.S. in Geography (GIS) from SUNY Buffalo (2003), and a B.S. in Geography and Applied Social Science from Canterbury University (1996). His research focuses on remote sensing and GIS analysis of nearshore environments, particularly mangrove forest change, hurricane impacts, and interactions between environmental degradation and socioeconomic outcomes.
Kate Calder is a Professor and Chair of the Department of Statistics and Data Sciences at the University of Texas at Austin's College of Natural Sciences. She earned her B.A. in Mathematics from Northwestern University, followed by an M.S. and Ph.D. in Statistics from Duke University. Prior to joining UT in 2019, she held faculty positions at The Ohio State University for 16 years. Former co-director of NSF-funded Mathematical Biosciences Institute Associate Director of UT’s Population Research Center Chair of NIH Analytics and Statistics for Population Research Panel B Study Section Area Editor for Annals of Applied Statistics Her research develops statistical methods for complex data, including spatial statistics, Bayesian modeling, and latent space models for networks. Current projects examine: Mobile-tracking data to analyze crime patterns and social ties Youth health impacts from non-residential activity spaces Exposure assessment through hierarchical pathways models She has secured funding from NIH, NSF, and federal foundations, and was elected to leadership roles in the American Statistical Association and International Society for Bayesian Analysis. Her work emphasizes practical applications across public health, ecology, and finance. Notable achievements: Tripled department size after joining UT Launched Online Master’s in Data Science (2021), surpassing 1,000 students Introduced undergraduate major in Data Sciences (2022)
Pablo Warnes is an Assistant Professor at Aalto University's Department of Economics and Helsinki GSE. His research spans Urban Economics, International Trade, Transportation Economics, Development Economics, and Applied Microeconomics. Education: PhD in Economics, Columbia University (2021) Research focuses on urban infrastructure, spatial sorting, commuting behavior, and policy impacts. Recent work includes studies on pedestrianization, bike-friendly cities, and gender differences in commuting. Key trends in publications: Urban mobility and infrastructure Gender disparities in commuting Resilient road networks Public investment in tech clusters Educational policy in Argentina and Ibero-America Contact: pablo.warnes@aalto.fi
Professor George Streftaris is a faculty member at Heriot-Watt University within the Actuarial Mathematics and Statistics department under the School of Mathematical and Computer Sciences . His academic career spans over two decades, including roles as associate professor and lecturer at Heriot-Watt University (2004-2019) and post-doctoral positions at BioSS and Heriot-Watt (2001-2004). He serves on the Board of Examiners for the Institute and Faculty of Actuaries and acts as an external examiner for multiple institutions. Professional memberships include Fellow of the Royal Statistical Society , member of the International Society for Bayesian Analysis , and the Greek Statistical Institute . Education: PhD in Statistics (University of Edinburgh) MSc in Statistics and OR (University of Essex, Distinction) BSc in Statistics and Actuarial Science (University of Piraeus, Greece) Research Interests: Streftaris specializes in Bayesian stochastic modeling , inference, and assessment at the intersection of statistics, epidemiology, and actuarial science. His work addresses critical illness insurance, longevity risk, and health-related insurance through predictive modeling and statistical machine learning. Key themes include disease transmission dynamics, model diagnostics, and uncertainty quantification in epidemic systems. Collaborations extend to life and biomedical sciences. Recent Publications: Recent articles focus on COVID-19 pandemic impacts on breast cancer mortality using semi-Markov models, neural network approaches for admission rate prediction, and Bayesian modeling of epidemic systems. Notable projects involve machine learning for multi-asset strategies, model uncertainty in insurance pricing, and stochastic frameworks for disease spread. Research Projects: Centers of Actuarial Excellence (SOA, 2019-2023): Predictive modeling for medical morbidity risk SCOR Foundation of Science (2022-2024): Breast cancer life insurance impact ARC Project (IFoA, 2016-2022): Longevity and morbidity risk management The Data Lab (2017-2018): Machine learning for multi-asset strategies Advising: Supervises ongoing PhD students in Bayesian and neural network modeling in epidemiology, with completed students working on topics like critical illness insurance, disease transmission, and stochastic mortality. Collaborations include researchers in the UK, USA, and international institutions.
Andrew R. Jamieson is an Assistant Professor in the Lyda Hill Department of Bioinformatics at UT Southwestern Medical Center, where he leads a research team focused on developing advanced AI systems for medical education and clinical performance assessment. He was appointed in 2019 and serves as Principal Investigator of the Jamieson Group. Institution: UT Southwestern Medical Center School: School of Health Professions Department: Lyda Hill Department of Bioinformatics Academic Rank: Assistant Professor Dr. Jamieson earned his B.A. in Physics with honors (2006) and Ph.D. in Medical Physics (2012) from the University of Chicago. His early work in computer-aided diagnosis laid the foundation for his career in AI and machine learning. Education: University of Chicago (B.A., Ph.D.) Prior Experience: GE Healthcare, Big Data Analytics Startup (First Data Scientist) Dr. Jamieson's research lies at the intersection of artificial intelligence, medical education, and bioinformatics. His team leverages multimodal data—including video, audio, and text—from the UTSW Simulation Center to train frontier AI models for automated assessment of medical student performance. His work in computational image analysis spans label-free live-cell imaging, spatial biology, and highly multiplexed immunofluorescence, with applications in cancer biology and diagnostics. He has also made significant contributions to public health through the development of the UTSW COVID-19 forecast model. The most recent publications reflect a strong trend toward AI-driven medical education tools, particularly using large language models and multimodal AI for OSCE assessment. Earlier works focus on deep learning in medical imaging, dimensionality reduction, and computer-aided diagnosis in mammography. The research consistently emphasizes interpretability, automation, and clinical translation. Scientific recognition includes being featured on the cover of Cell Systems (July 2021) for work on melanoma cell analysis. His team's development of the first automatic AI grading system for medical student OSCE notes in 2023 marks a major innovation in educational assessment. Featured on cover of Cell Systems (2021) Developed UTSW COVID-19 forecast model Pioneered AI grading system for OSCE notes (2023) Dr. Jamieson is actively involved in mentoring and graduate education. He serves as Course Director for the Master’s in Health Informatics program and contributes to nanocourses at the Clinical Informatics Center. His team includes multiple advisees and collaborators working on NLP, LLMs, and AI/ML in healthcare. He is expanding his group and seeking researchers in AI, data science, and software development. His leadership in the Bioinformatics Core Facility (2018–2021) and ongoing collaborations with pathologists and radiation oncologists demonstrate strong interdisciplinary grant and project engagement. Course Director: Master’s in Health Informatics Mentor to multiple graduate students and researchers Collaborations: Pathology, Radiation Oncology, Surgery, Clinical Informatics The Jamieson Group is a dynamic, interdisciplinary research team at the forefront of applying cutting-edge AI to medical education and clinical data analysis. The lab focuses on natural language processing, multimodal learning, and computer vision, with strong ties to the UTSW Simulation Center and Clinical Informatics Center. The team develops custom pipelines for spatial biology and imaging data and is actively expanding to meet growing research demands.
Dr David Johnson is an Associate Professor of Entrepreneurship at Durham University Business School, where he serves as Associate Chair for the £9 million Smart & Scale initiative supporting SME innovation in North-East England. He is also a Fellow of the Wolfson Research Institute for Health and Wellbeing and maintains active Visiting Fellow positions at international institutions. Johnson's educational background includes: PhD in Management (Entrepreneurship), University of Edinburgh Business School MSc by Research (Entrepreneurship), University of Edinburgh Business School MBA, Adam Smith Business School, University of Glasgow Master's degree in Science, University of Edinburgh Bachelor's degree in Science, University of Leeds PG Cert in Learning, Teaching, and Assessment Practice His research centers on academic entrepreneurship , life science commercialisation , and university-industry engagement , with particular focus on linguistic approaches and machine learning applications. Johnson examines how institutional practices shape entrepreneurial activities across contexts ranging from regenerative medicine to Freemasonry, emphasizing the built environment's role in ecosystem development. Johnson's publication trajectory reveals evolving methodological sophistication, shifting from early studies on regenerative medicine venturing (2014-2017) toward computational linguistics and machine learning applications (2024-2025). His work consistently bridges theoretical frameworks with practical innovation challenges, spanning entrepreneurial ecosystems, technology transfer, and narrative analysis in resource mobilization. His scientific recognition includes: NASA Innovation and Technology Transfer: Space2Pitch Final Visiting Research Fellow at Interface, Edinburgh Fellow of Wolfson Research Institute for Health and Wellbeing Visiting Research Fellow at Skolkovo Institute Visiting Research Scholar at Wisconsin School of Business Fellow of Higher Education Academy Johnson supervises postgraduate students including Clare Talbot-Jones and Olivia King, supported by over £500,000 in research funding: Science commercialisation activities at university-industry boundary (£390,824) Cardiology-focused point-of-care device development (£38,934) Primary Research Support Fund for Zambian field research (2025) Global Engagement Grant for Dartmouth College knowledge exchange (2024) He actively leads research infrastructure as Co-Director of Durham Enterprise Centre and through his Smart & Scale initiative role, while contributing to interdisciplinary health research via the Wolfson Institute fellowship.
Birgit Öhlinger is a Research Associate and Co-Excavation Director of the Monte Iato Project at the Leopold Franzens University of Innsbruck . Her work focuses on the archaeology of the ancient Mediterranean, particularly social transformation processes in cultural contact zones and identity formation through material culture, with a regional emphasis on Sicily. Education: Doctoral studies in Classical and Provincial Roman Archaeology (2010–2014), University of Innsbruck Master’s in Ancient History and Classical Studies (2005–2009), University of Innsbruck Master’s in Classical and Provincial Roman Archaeology (2002–2008), University of Innsbruck Research Interests: Öhlinger specializes in the archaeology of cultural contact zones, ritual and religious practices, and ceramic studies in the Archaic Mediterranean. Her methodological expertise includes digital excavation documentation, experimental archaeology, and material culture analysis, particularly focusing on Monte Iato in Western Sicily. Recent Publications: Her work examines technological choices in local ceramic production, neutron activation analysis applications in Mediterranean archaeology, and ritual consumption practices. She has contributed to debates on cultural hybridity, social identity, and the role of sanctuaries in elite formation. Awards: Anniversary Prize of Böhlau Verlag Vienna (2015) Prize of the Principality of Liechtenstein (2015) Merit Scholarship (2003–2007), University of Innsbruck Doctoral Scholarship (2013–2014), University of Innsbruck Professional Activities: Öhlinger leads projects like "Monte Iato Pots - Experimental Study on Organic Residue Analysis" and "Crime Scene Monte Iato around 500 BC: Microbiological Forensics" . She organizes international conferences and contributes to public outreach through media appearances and exhibitions.
Professor Alan Penn is a leading academic at University College London's The Bartlett School of Architecture , where he holds the title of Professor in Architectural and Urban Computing. He previously served as Dean of the Bartlett Faculty of the Built Environment from 2009 to 2019 and has been instrumental in establishing Space Syntax Ltd , a UCL knowledge transfer spin-out company. His affiliations include membership in the Space Syntax Laboratory, board membership of UCL Consultants Ltd, and trustee status at Shakespeare North Trust. Education: BSc (1978), Dip Arch (1980), MSc (1983) - all from University College London Alan Penn’s research investigates how spatial design influences social and economic behaviors through innovative space syntax methodologies . Key areas include: Agent-based simulations of human behavior Spatio-temporal representations of built environments Urban spatial network analysis Urban sustainability across multiple dimensions Cognitive markers in architectural design Historical urban growth modeling His recent publications demonstrate a strong focus on computational urbanism, evolutionary city patterns, and behavioral architecture. Research trends show interdisciplinary approaches combining architectural theory with: Machine learning applications Network science analysis Behavioral psychology insights Historical GIS techniques Complex systems modeling Public health considerations Scientific recognition includes: HEFCE Business Fellowship (2001-2005) KTP SE Region Award (2010) Multiple UCL Enterprise awards ‘Spirit of Enterprise’ Award (2008) As Principal Investigator he leads the £5m EPSRC-funded Urban Dynamics Lab , demonstrating sustained research excellence. His work extends to public engagement through: Shakespeare North Trust educational theatre development Media appearances (New Scientist, Slashdot) Public policy contributions
Robert Clements is an Assistant Professor in the Master of Science in Data Science (MSDS) program at the University of San Francisco (USF) and serves as Director of the Center for AI and Data Ethics. After nearly ten years in industry as a data scientist and senior director of data science across Bay-Area companies including Optum, Walmart Labs, UnitedHealthcare, GE Digital, and Verisk Analytics, he returned to academia to focus on education and ethical issues surrounding AI and data. Education PhD in Statistics, University of California, Los Angeles, 2011 MS in Statistics, University of California, Los Angeles, 2009 BA in Mathematics, Humboldt State University, 2006 Research Interests Dr. Clements focuses on data science education , exploring innovative pedagogies that equip students with practical and ethical data skills. He studies the societal impacts of AI and datafication , seeking frameworks to ensure responsible deployment of machine-learning systems. Additional interests include MLOps (the engineering practices that support reliable machine-learning workflows) and applied statistics across diverse domains. His peer-reviewed work to date concentrates on statistical seismology, where he developed advanced residual-analysis and model-evaluation techniques for earthquake-forecast models. These contributions provide rigorous methods for assessing space-time point processes and improve the reliability of seismic hazard assessments. Academic & Professional Service As Director of the Center for AI and Data Ethics, Dr. Clements leads initiatives that create open educational resources, case studies, and student practicum projects centered on ethical AI. He co-hosts the USF Data Science Podcast alongside faculty colleague Cody Carroll, offering guidance to prospective and current MSDS students on program insights, learning strategies, and career development.
Dr. Sander Kramer is an Assistant Professor at Utrecht University's Faculty of Law, Economics and Governance , specifically within the Department of Public Administration and Organizational Science . His work bridges organizational theory, mental health ethics, and migration studies, with a focus on transformative education and data-driven governance. Research Interests: Kramer investigates the intersection of organizational practices and social impact , particularly in contexts involving asylum seekers and refugee mental health . He explores ethical dilemmas in healthcare, cultural adaptation in Western societies, and data-intensive public health through projects like GECCO's exposome studies. Publication Trends: His recent work includes critical praxis in education ( 2024 ), cross-cultural mental health diagnosis ( 2022 ), and data analytics for health geographics ( 2020 ). Earlier studies focus on refugee coping mechanisms ( 2004 ), ethical challenges ( 2018 ), and veterinary biomarkers ( 2012 ).
Denny Yu is an Associate Professor at the Edwardson School of Industrial Engineering, Purdue University. His work bridges human factors, neuroergonomics, and healthcare safety through advanced sensor systems and AI. Primary Affiliation : Edwardson School of Industrial Engineering, Purdue University Research Themes : Surgical ergonomics, autonomous vehicle human factors, cognitive workload assessment, multimodal physiological sensing Dr. Yu's research focuses on neuroergonomics and human-robot interaction , particularly in surgical and transportation contexts. His team develops sensor-based systems for workload monitoring, including: EEG-eye tracking fusion for situation awareness Wearable exoskeletons for surgical posture support Computer vision tools for lifting task risk analysis Smart infusion pump usability frameworks AI-driven surgical coaching systems Recent publications emphasize deep learning applications in soft tissue deformation estimation and real-time adaptive systems for robotic surgery augmentation. His work spans both occupational health (veterinary surgeons, airport workers) and medical device innovation domains.
