Jonathan Pila is a Reader in Mathematical Logic at the University of Oxford's Mathematical Institute, with a focus on model theory and number theory. He is affiliated with the Mathematical Logic and Number Theory research groups. BScHons (University of Melbourne, 1984) PhD (Stanford University, 1988) His research explores intersections of mathematical logic with number theory, particularly via o-minimality, addressing problems like the Andre-Oort conjecture, Zilber-Pink conjecture, and Ax-Schanuel theorems in algebraic and Diophantine geometry. Recent work includes advancements on functional transcendence, canonical heights in Shimura varieties, and uniform parameterization techniques with applications to Diophantine problems. Leverhulme Trust Research Fellowship (2008-2010) Clay Research Award (2011) LMS Senior Whitehead Prize (2011) ASL Karp Prize (2013) Elected FRS (2015) Rolf Schock Prize (2022) Frontiers of Science Award (2023)
Jon Russ is a Professor of Chemistry at Rhodes University , specializing in the chemical analysis of archaeological and environmental materials. His research integrates advanced analytical techniques such as XRF, SEM-EDS, LA-ICP-MS, and GC-MS to investigate rock coatings, ancient rock art, and prehistoric smoking pipes. Education: B.S. in Chemistry (1987), Corpus Christi State University (now TAMU-CC) Ph.D. in Analytical/Physical Chemistry (1991), Texas A&M University Research Interests: His work focuses on understanding the formation of calcium oxalate rock coatings that preserve prehistoric rock art globally, using trace organic compounds to date these coatings. He also explores the chemical residue in archaeological smoking pipes to trace the historical use of tobacco and other plants in North America, employing radiocarbon dating and compound detection methods. Publications: Recent studies include analyses of rock coatings in the Lower Pecos Canyonlands, organic residues in Mississippian-era pipes, and pioneering work identifying nicotine in a 3500-year-old smoking tube from Georgia—the earliest evidence of tobacco in North America. His interdisciplinary approach bridges chemistry, archaeology, and environmental science.
Gizem Karaali is a Professor of Mathematics and Statistics and Chair of the Mathematics Department at Pomona College, part of The Claremont Colleges. She holds a Ph.D. in Mathematics from UC Berkeley (2004) and a B.S. in Electrical Engineering and Mathematics from Boğaziçi University. Her research spans algebraic structures like Lie algebras, representation theory, and humanistic mathematics, with a focus on integrating social justice into mathematics education. She co-founded the Journal of Humanistic Mathematics and created innovative courses such as the first-year seminar Can Zombies Do Math? to explore mathematics’ humanistic dimensions. Research Interests: Representation Theory, Algebraic Combinatorics, Quantitative Literacy, Mathematics Education, and the intersection of math with social justice. She has published widely in journals like Advances in Mathematics , Ramanujan Journal , and Journal of Humanistic Mathematics . Awards: NSA Young Investigator Award (2011-2013), NEH Enduring Questions Grant (2014-2016), AMS Project NExT Fellow. Active in editorial roles for Journal of Humanistic Mathematics and Numeracy . Teaching: Courses include Calculus, Linear Algebra, Abstract Algebra, and interdisciplinary topics like Mathematics, Philosophy, and the Real World. Advised senior theses in diverse areas including ethnomathematics and quantitative literacy.
Ivan Lee is an Associate Professor and Informatics Program Director in the College of Information and Computer Sciences at the University of Massachusetts Amherst. His research focuses on mobile and personalized health, leveraging digital technologies to support individuals with motor and cognitive impairments such as stroke, Parkinson's disease, and traumatic brain injuries. He leads the Advanced Human & Health Analytics (AHHA) Laboratory and is actively engaged in interdisciplinary health technology research. Education: B.A.Sc. in Computer Engineering, Simon Fraser University (2008) M.S. in Electrical Engineering, University of California, Los Angeles (2010) M.S. in Computer Science, University of California, Los Angeles (2013) Ph.D. in Computer Science, University of California, Los Angeles (2014) His research interests lie at the intersection of mobile computing, sensor systems, and health informatics. He emphasizes human-centered design, developing novel sensors and remote monitoring tools grounded in clinical needs, conducting rigorous human studies, and evaluating solutions through both quantitative and qualitative methods. His work promotes health behavior change through personalized, technology-driven interventions. Ivan Lee has received significant recognition for his research, including the NSF CRII Award (2018) and the NIH Trailblazer Award (2018). His publications have earned best paper, best demo, and featured article honors at premier venues such as IEEE TNSRE, IEEE JBHI, ACM SenSys, and ACM MobiSys. He serves as an Academic Editor for PLOS ONE and an Associate Editor for the IEEE Open Journal of Engineering in Medicine and Biology (OJEMB) . He is an elected Standing Member of the IEEE EMBS Technical Committee on Wearable Biomedical Sensors and Systems and has served on technical program committees and as workshop chair for major conferences. He regularly participates in scientific review panels for the NSF, NIH, and DARPA. He previously held a postdoctoral fellowship at Harvard Medical School in the Department of Physical Medicine & Rehabilitation (2014–2016). Lee leads the Advanced Human & Health Analytics (AHHA) Laboratory, where his team develops and evaluates innovative health technologies through interdisciplinary collaboration with clinicians and engineers.
Joel Greenhouse is a Professor of Statistics at Carnegie Mellon University (CMU), affiliated with the Department of Statistics & Data Science. He has been on the faculty since 1983 and held leadership roles, including serving as Associate Dean of the College of Humanities and Social Sciences from 1997 to 2002. He also holds an adjunct appointment as Professor of Epidemiology and Psychiatry at the University of Pittsburgh. His expertise spans statistical methodology, clinical trial design, and meta-analysis, with a focus on integrating data from multiple sources to address complex healthcare and public health challenges. Greenhouse earned his Ph.D. in Biostatistics from the University of Michigan and completed a postdoctoral fellowship at CMU. His research emphasizes developing statistical tools for observational studies, clinical trials, and meta-analytic frameworks, particularly in neurology, mental health, and public policy contexts. Notable contributions include analyzing the impact of media on youth suicide rates, improving aphasia classification through automated speech analysis, and evaluating highway safety through driver health data. Education: Ph.D. in Biostatistics, University of Michigan Affiliations: Adjunct Professor at University of Pittsburgh, Member of National Academy of Sciences’ committees Professional Service: Data and safety monitoring boards for NIH/VA studies, co-chair of Federal Motor Carrier Safety Administration review panels His awards include CMU’s Doherty Award for Education, Ryan Teaching Award, and E. Dunlop Smith Award for teaching excellence. His work bridges theoretical statistics with real-world applications, particularly in interdisciplinary collaborations across medicine, psychology, and public policy. Greenhouse’s recent articles highlight trends in leveraging large datasets for clinical insights (e.g., aphasiaBank), re-evaluating environmental and behavioral health associations, and advancing causal inference methods. His interdisciplinary approach ensures statistical rigor addresses societal challenges, from suicide prevention to highway safety.
Emma Mercier is an Associate Professor and Associate Head & Director of Graduate Programs in the Department of Curriculum & Instruction at the University of Illinois, Urbana-Champaign's College of Education. She also holds a secondary appointment in the Department of Educational Psychology, demonstrating her interdisciplinary approach to educational research. Dr. Mercier's research focuses on the relationship between social interaction and learning, with particular emphasis on collaboration and computer-supported collaborative learning (CSCL) in classroom settings. Her work examines how technology influences group interactions and learning, especially through the use of multi-touch tables in classrooms. She investigates between-group and whole-class interactions, device ecologies, teacher tools, and classroom contexts that shape learning opportunities in technology-enhanced environments. Her research spans K-12 and higher education settings, with significant contributions to engineering education and the design of collaborative learning spaces. Analysis of Dr. Mercier's recent publications reveals a strong focus on orchestration tools that support instructors in facilitating collaborative learning, the role of technology (particularly augmented and virtual reality) in collaborative problem solving, and the design of effective collaborative tasks in engineering education. Her work bridges educational theory with practical classroom applications, often employing design-based implementation research methodologies. A notable trend is her increasing focus on machine learning applications to analyze and support collaborative interactions in real-time classroom settings. Dr. Mercier has been actively involved in mentoring graduate students and teaching courses related to educational research methods, child development and technology, and advanced study of education. Her work has involved significant collaboration with researchers across institutions and disciplines, particularly in the fields of educational technology, learning sciences, and engineering education. Her research has been supported through various projects, including the CSTEPS (Collaborative Support Tools for Engineering Problem Solving) initiative, which has developed and evaluated tools to support collaborative learning in engineering classrooms. This work has involved partnerships with teaching assistants, course assistants, and faculty to implement and refine collaborative learning approaches in undergraduate engineering courses.
Bo Xiong is a researcher at the University of Stuttgart in the Analytic Computing group. His research focuses on machine learning and knowledge graphs , with a particular emphasis on geometric embeddings and hyperbolic neural networks. His research interests include: Knowledge graph embeddings Hyperbolic and pseudo-Riemannian geometry in AI Temporal knowledge graph reasoning Structured multi-label prediction Recent publications highlight his work on geometric relational embeddings, complex query answering, and temporal fact reasoning using advanced manifold-based techniques.
Luca Varani is a Professor and Group Leader of the Structural Biology group at the Institute for Research in Biomedicine (IRB), affiliated with the Università della Svizzera italiana in Bellinzona, Switzerland. His research focuses on understanding the molecular mechanisms of antibody-pathogen interactions and engineering novel therapeutic antibodies. Education: Chemistry degree from University of Milan, PhD from MRC-Laboratory of Molecular Biology (University of Cambridge) Former postdoc at Stanford with EMBO fellowship Founder of CLBiotech (2022), a nanobody discovery and engineering startup Varani's research spans structural biology, immunology, and biophysics with emphasis on viral pathogenesis and antibody engineering. His work combines experimental and computational approaches to study antibody-antigen interactions, particularly against emerging pathogens like SARS-CoV-2, Zika, and Dengue viruses. His group has pioneered structure-guided antibody engineering techniques that have led to multiple high-impact publications in journals like Nature, Cell, and Science. Analysis of Varani's recent publications reveals a strong focus on SARS-CoV-2 antibody responses, with significant contributions to understanding neutralizing mechanisms, viral escape, and therapeutic antibody development. His work also extends to prion diseases, cancer immunology, and flaviviruses, demonstrating a multidisciplinary approach that bridges structural biology with translational medicine. As a reviewer for high-impact journals and international granting agencies, Varani contributes significantly to the scientific community. He also serves as an evaluator for European startup accelerator programs and consults for antibody biotechnology companies, translating academic research into practical applications. Varani leads a highly multidisciplinary research team that employs techniques ranging from NMR spectroscopy and X-ray crystallography to cellular assays and computational modeling. His laboratory has been instrumental in developing bispecific antibodies against SARS-CoV-2 and other pathogens, with several candidates advancing toward clinical trials.
Martin Huber is Professor of Applied Econometrics and Policy Evaluation at the University of Fribourg, Switzerland, within the Faculty of Management, Economics and Social Sciences, Department of Economics. He leads the Chair of Applied Econometrics and maintains an active research profile with numerous publications in top economics and statistics journals. His work bridges theoretical econometrics with practical policy applications across multiple domains including labor, health, and education economics. Professor Huber earned his Ph.D. in Economics and Finance in 2010 and served as Assistant Professor at the University of St. Gallen until 2014. He has conducted research stays at Harvard University (2011/2012) and the University of Sydney (2014 and 2019), establishing an international research network. His academic affiliations include the Committee for Econometrics of the Verein für Socialpolitik, Global Labor Organization, Soda Labs (Monash Business School), and Centre for European Economic Research (ZEW) Mannheim. Huber's research focuses on data-based causal analysis , machine learning applications in economics , and policy evaluation methods . He specializes in developing and applying statistical and econometric methods for measuring causal effects, with particular emphasis on semi- and nonparametric microeconometrics. His work spans labor economics (gender occupational segregation, maternal labor supply), health economics, education policy, and competition policy (bid-rigging cartels detection). His recent publications (2023-2025) demonstrate a clear trajectory toward integrating machine learning techniques with traditional econometric methods for causal inference. This includes developing frameworks for causal discovery, improving difference-in-differences methods with machine learning, and creating novel approaches for detecting collusion in markets. His 2023 book "Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R" (MIT Press) has become a key reference in the field. As an active researcher, Professor Huber directs several research projects including experimental evaluations of gender occupational segregation in the Swiss apprenticeship market. His work combines theoretical rigor with practical policy relevance, often employing experimental and quasi-experimental methods to address questions of causal mechanisms in social and economic phenomena. Through his Chair of Applied Econometrics, Huber supervises Ph.D. students and maintains an active research group focused on advancing causal inference methodologies. His work has significant implications for evidence-based policymaking across multiple sectors, particularly in evaluating the effectiveness of social programs and economic policies.
Staal A. Vinterbo is a Professor at the Department of Information Security and Communication Technology within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). His research focuses on privacy-preserving technologies, cryptography, and their intersections with machine learning, bioinformatics, and medical informatics. He has contributed to advancements in differential privacy, data anonymization, and secure computational methods.
Xinran Zhu is an Assistant Professor at the University of Illinois Urbana-Champaign College of Education, specializing in Learning Design & Leadership and Instructional Design, Technology, & Organization. Her research intersects learning sciences, learning analytics, and AI in education, focusing on designing technology-supported learning environments for authentic classroom settings. Ph.D. in Learning Sciences and Technologies, University of Pennsylvania (2024) M.A. in Educational Psychology, University of Connecticut Graduate studies in learning technologies, University of Minnesota Her research spans three main areas: (1) design and implementation of educational technologies, particularly social annotation tools for knowledge building; (2) AI integration in education to augment collaborative learning; and (3) computational discourse analysis using network analysis and NLP to generate actionable insights. Recent projects include SynthesisAI , a GenAI-powered chatbot for knowledge synthesis, and the Synthesis Lab , a precursor tool for integrating peer ideas in collaborative writing. Dr. Zhu teaches courses on ubiquitous learning, advanced learning technologies, and eLearning system design. She employs co-design methodologies to develop and implement technologies in both lab and real-world classroom settings, emphasizing student agency and ethical AI partnerships.
Prof. Dr. Ioachim Pupeza serves as Group Leader in the Department of Spectroscopy/Imaging at the Leibniz Institute of Photonic Technology (Leibniz-IPHT) in Jena, Germany. His research focuses on advanced optical measurement techniques, particularly in the field of field-resolved spectroscopy and precision optical measurements. Dr. Pupeza's research interests center around optical spectroscopy with a particular emphasis on field-resolved techniques that capture the complete electric field waveform of light-matter interactions. His work spans infrared spectroscopy , molecular fingerprinting , ultrafast laser technology , and precision optical measurements . He has made significant contributions to electro-optic sampling techniques, which enable characterization of electric-field waveforms across the terahertz to visible spectral range. His research also extends to mid-infrared light generation , terahertz spintronic emitters , and cavity-enhanced spectroscopy , with applications ranging from fundamental physics to medical diagnostics. Analysis of Dr. Pupeza's recent publications reveals a strong trend toward increasingly sophisticated field-resolved spectroscopy techniques with applications in both fundamental science and practical diagnostics. His work has evolved from basic measurement techniques to applications in cancer detection through molecular fingerprinting of biofluids. A consistent theme across his publications is the pursuit of higher precision, broader bandwidth, and improved sensitivity in optical measurements, often achieving attosecond-level precision. His research bridges physics, engineering, and medical applications, demonstrating how fundamental optical advances can translate to real-world diagnostic tools. Dr. Pupeza leads the research group "Field-Resolved Optical Precision Measurement Methods" at Leibniz-IPHT, which appears to collaborate extensively with other research institutions and groups. His work involves sophisticated laser systems including high-power Yb:YAG thin-disk oscillators, femtosecond enhancement cavities, and dual-oscillator systems for precision measurements. The group's research has implications for molecular spectroscopy, medical diagnostics, and fundamental studies of light-matter interactions at the most fundamental time scales.
Anthony J. Gambino is a Postdoctoral Research Associate in the Department of Educational Psychology at the University of Connecticut. His research focuses on gifted education, teacher evaluation, and multilevel modeling techniques. Ph.D. in Research Methods, Measurement, and Evaluation (University of Connecticut) M.A. in Measurement, Evaluation, and Assessment (University of Connecticut) B.S. in Psychology (Wagner College) His work addresses critical issues in educational equity, including disparities in gifted program identification by race, poverty, and language status. He develops and evaluates statistical tools for multilevel modeling and contributes to understanding the role of teacher rating scales in educational assessments. Gambino’s publications emphasize methodological rigor in educational research, particularly in behavioral interventions like PBIS and analytical frameworks for teacher effects. He maintains active engagement in advancing evaluation curricula for graduate programs.
Robert C. Dunn is a Professor in the Department of Chemistry at the University of Kansas, where he leads an active research group focused on developing novel optical and spectroscopic techniques for chemical and biological analysis. His laboratory specializes in single-molecule detection methods, high-resolution microscopy, and advanced capillary electrophoresis systems. Professor Dunn's research interests span analytical chemistry, biophysics, and nanotechnology. His group develops instrumentation including backscatter interferometry, near-field scanning optical microscopy, and scanning resonator microscopy to study biological systems at the nanoscale. Key research areas include membrane biophysics (investigating lipid domains and protein dynamics), nuclear pore complex function, and the development of ultrasensitive detection methods for clinical diagnostics and biochemical analysis. His recent publications demonstrate strong focus on miniaturized separation and detection platforms, particularly high-speed capillary electrophoresis systems integrated with novel optical detection schemes. Research trends show advancement towards point-of-care diagnostic tools, with innovations in refractive index sensing, femtoliter-volume detection, and label-free biosensing applications. Professor Dunn mentors graduate and undergraduate researchers in his group, with current students including Prabhavie Opallage (graduate student), Stanslaus M Kariuki (undergraduate), and Mei Ling Upp (undergraduate). His laboratory is developing new chemical analysis approaches using optical techniques including whispering gallery mode sensing, scanning resonator microscopy, and single-molecule fluorescence imaging.
Amy Zavatsky is a Reader in Engineering Science at the University of Oxford and Tutorial Fellow at St Edmund Hall, with faculty service since 1996. Her work bridges mechanical engineering and clinical orthopaedics, focusing on lower extremity biomechanics and gait analysis within the Department of Engineering Science. Education: BSc in Bioengineering, University of Pennsylvania DPhil in Engineering Science, University of Oxford (Thouron Award recipient) Research Focus: Prof. Zavatsky pioneers orthopaedic biomechanics research with emphasis on foot/ankle kinematics, knee osteoarthritis mechanisms, and gait compensations. Her work integrates theoretical modeling with in vitro experimentation to develop clinical applications for cerebral palsy, flatfoot, and running injuries. Current projects advance multi-segment foot modeling and cognitive-efficient data visualization for clinical gait analysis. Publication Trends: 2021-2025 works reveal three converging themes: (1) Open-source foot modeling ( OpenOFM ), (2) Data visualization for clinical decision-making, and (3) Sensor optimization using statistical methods. These publications consistently bridge engineering innovation with orthopaedic clinical practice through collaborations with the Oxford Gait Laboratory. Scientific Recognition: Philip Leverhulme Prize (2003) for outstanding early-career scholarship University Teaching Award (2008) for biomechanics instruction and MSc Biomedical Engineering development Departmental Teaching Awards: Silver (2021), Bronze (2022) Institution of Mechanical Engineers Thomas Stephen Prize (1993) Academic Leadership: Prof. Zavatsky directs undergraduate engineering tutorials at St Edmund Hall while teaching mechanical/civil/biomedical engineering courses. She previously served as Director of Graduate Studies (2016-17), Acting MSc Biomedical Engineering Director (2006-07), and Junior Proctor (2012-13). Her DPhil supervision targets lower-limb biomechanics projects requiring strong engineering fundamentals. Research Infrastructure: Based at the Institute of Biomedical Engineering (Nuffield Orthopaedic Centre), she collaborates extensively with the Oxford Gait Laboratory. Her biomechanics research group utilizes motion capture systems and multi-segment modeling to translate engineering principles into clinical rehabilitation protocols.
