Andreas Kautt is Assistant Professor of Biology at Washington University in St. Louis, investigating evolutionary mechanisms driving biological diversity through integrative approaches combining genomics, behavioral experiments, and fieldwork. Research focuses on two primary systems: North American deer mice and Missouri crayfish. Research themes include: Genomic basis of behavioral divergence and sensory evolution Molecular mechanisms of speciation in cichlid fish radiations Genetic assimilation in morphological evolution Development of novel genomic tools for speciation research Recent work explores olfaction genetics in deer mice, parallel evolution in pigmentation, and hybrid speciation mechanisms. Publications demonstrate expertise in evolutionary genomics, behavioral ecology, and molecular evolution across diverse vertebrate systems.
Dr. Constantin Christof is a Lecturer (Akademischer Rat auf Zeit) at the Department of Mathematics , Technische Universität München , with prior roles as a W2 Stand-in Professor at Universität Augsburg and Research Associate at TUM and TU Dortmund. His research focuses on Optimal Control of PDEs , Variational Inequalities , and Nonsmooth Optimization , with applications in Non-Newtonian Fluids and Neural Networks . May 2015 - July 2018: Dr. rer. nat. in Mathematics, TU Dortmund Oct. 2013 - July 2014: MAST (Part III of Mathematical Tripos), University of Cambridge Oct. 2009 - Sept. 2012: B.Sc. in Technomathematics and Mathematics, TU Dortmund Christof's work bridges Finite Element Error Analysis , Sensitivity Analysis , and Physics-Guided Machine Learning , particularly in problems involving Contact Mechanics and Parabolic PDE Constraints . His recent publications address challenges in Semilinear Elliptic PDEs , Obstacle Problems , and Nonsmooth Superposition Operators , with a focus on theoretical and numerical advancements. Scientific awards include the Dissertation Award and Best Graduate Award from TU Dortmund, and the Award for Academic Excellence by the Minister President of North Rhine-Westphalia. He has supervised 11 theses at the Master's and Bachelor's levels, covering topics from Neural Network Surrogate Models to Bingham Fluid Simulations .
James B Lewis is an Associate Professor of Korean History at the University of Oxford, affiliated with Wolfson College and the Faculty of Asian and Middle Eastern Studies. His research focuses on Korean-Japanese relations before 1850, economic and social histories of premodern Korea and Japan, global history, and environmental/epidemiological dynamics in East Asia. He has held leadership roles as past President of the Association for Korean Studies in Europe and the British Association for Korean Studies. His grants include an ERC Horizon 2020 project (grant 758347). Current projects involve co-authoring An Economic History of Korea, 1400 to 1900 and translating Amenomori Hôshû's Kôrin Teisei . Courses taught include Korean-Japanese history surveys, research methodologies, and classical texts analysis. His publications span monographs, edited volumes, and peer-reviewed articles, emphasizing quantitative methods, archival analysis, and cross-disciplinary approaches. Notable works include Frontier contact between Chosŏn Korea and Tokugawa Japan (2003), The East Asian War, 1592-1598 (2015), and studies on Korean economic indicators across centuries. Public lectures and media engagements include talks at the Ricci Institute and the Daiwa Anglo-Japanese Foundation.
Ira Hall is a Professor of Genetics and Director of the Yale Center for Genomic Health at Yale School of Medicine. His research focuses on genomic variation, structural variation analysis, and computational methods in human genetics. He leads major initiatives like the Human Pangenome Project and studies cardiometabolic disease genetics. Education: B.A. in Integrative Biology (UC Berkeley, 1998), Ph.D. in Genetics (Cold Spring Harbor Lab, 2003), postdoctoral training at Cold Spring Harbor Lab and faculty roles at University of Virginia, Washington University, and now Yale. Research interests include structural variation's role in disease, genomic data science, and developing tools for variant detection. His work integrates multi-omics data to understand genetic contributions to traits like coronary artery disease. Key achievements include co-leading the Human Pangenome Project, developing svtools for structural variation analysis, and identifying genomic drivers of cardiometabolic traits. Over 30+ peer-reviewed publications span Nature, Cell, and Genome Research. Grants include NIH/NHGRI funding for large-scale genomic projects. Collaborates with institutions globally on projects like AnVIL cloud platform and GTEx gene expression studies. Labs/Teams: Active in Yale Center for Genomic Health, Computational Biology & Biomedical Informatics program, and Wu Tsai Institute collaborations.
Pier Palamara is an Associate Professor of Statistical and Population Genetics at the University of Oxford's Department of Statistics, affiliated with the Centre for Human Genetics. He holds a PhD in Computer Science from Columbia University (2014) and completed postdoctoral training at Harvard Chan School of Public Health and the Broad Institute of MIT and Harvard. His research integrates statistics, computer science, and genetics to develop methods for analyzing large genomic datasets, focusing on evolutionary parameters, demographic history, complex trait genetics, and disease variation. Key research interests include reconstructing population movements via genetic data, studying natural selection and mutation rates in human genomes, and developing scalable algorithms for genomic analysis. He leads the Palamara Lab, which collaborates on projects like the Genomics England haplotype reference panel and the UK Biobank imputation. His lab's work is supported by grants and partnerships, and they develop software tools such as ASMC, Quickdraws, and Threads. Recent publications highlight contributions to Indo-European genetic origins, scalable mixed-model association methods, and ancient DNA analysis of European farmers. He advises graduate students and has mentored researchers in computational biology and statistical genetics.
David Frazier is a Professor in the Department of Econometrics & Business Statistics at Monash University, specializing in simulation-based inference, financial econometrics, and nonparametric/semiparametric modeling. He teaches ETC 1010: Data Modeling and Computing. His research focuses on robust statistical methods, Bayesian computation, and model misspecification. Key projects include 'Consequences of Model Misspecification in Approximate Bayesian Computation' (2020-2025) and 'Loss-based Bayesian Prediction' (2020-2025). Recent work addresses forecasting in misspecified models, weak identification in econometric frameworks, and robust variational Bayes techniques. His contributions align with UN Sustainable Development Goals related to economic and environmental sustainability. Projects: 4 active/funded projects with ARC, Brown University, and international collaborators. Publications: Over 37 peer-reviewed articles in journals like the Journal of the American Statistical Association and Journal of Econometrics. Research interests include advancing Bayesian methodologies for complex models, with applications in asset pricing and economic forecasting. His work emphasizes reliability in statistical inference under model uncertainty and computational efficiency.
Dr. Prashant Saxena is a Senior Lecturer in the Department of Infrastructure & Environment at the University of Glasgow (since 2018). He previously held positions as an Assistant Professor at the Indian Institute of Technology Hyderabad (2015-2018) and postdoctoral roles at the University of Lausanne (2014-2015) and the University of Erlangen-Nuremberg (2012-2014). He completed his PhD in Applied Mathematics at the University of Glasgow (2012) and a Bachelor/Master of Technology in Mechanical Engineering from the Indian Institute of Technology Kanpur (2009). His research focuses on the mechanics of soft solids and structures, particularly under extreme deformation. Key areas include smart composites with multi-physics coupling (electro-mechanical and magneto-mechanical) and soft biological tissues. He employs tools like nonlinear solid mechanics, continuum mechanics, and numerical analysis to study instabilities in these materials. His work emphasizes the exploitation of instabilities as design features in engineering applications. Research grants include EPSRC funding (2021-2024) and multiple awards from India's Science and Engineering Research Board (SERB). Notable awards: EPSRC New Investigator Award (2021), Ramanujan Fellowship (2015-2018), and multiple SERB Early Career Awards. Teaching roles include Finite Element Analysis, Dynamics, and Structural Mechanics courses at the University of Glasgow. Professional activities include editorial roles in Mathematics and Mechanics of Solids and organizing international conferences. His publications span over 40 papers in journals like Journal of the Mechanics and Physics of Solids and Proceedings of the Royal Society A , with a focus on magnetoelastic deformation, instabilities, and computational mechanics.
Zigong Xu is a Postdoctoral Scholar Research Associate in Physics at the California Institute of Technology (Caltech), affiliated with the Division of Physics, Mathematics, and Astronomy. His research focuses on solar energetic particles (SEPs), heliospheric physics, and cosmic ray dynamics. His work leverages data from missions like Solar Orbiter, Parker Solar Probe, and Chang’E-4 to study particle acceleration mechanisms, interplanetary shock dynamics, and the propagation of energetic particles in the solar environment. His research interests span solar flares, coronal mass ejection interactions, and the interplay between solar eruptions and the Earth-Moon radiation environment. He has contributed to understanding phenomena such as inverse velocity dispersion in SEPs, cosmic ray cavities in near-Earth space, and the composition variations of 3He-rich SEP events. Collaborations with multi-spacecraft missions highlight his expertise in analyzing particle data across diverse heliospheric distances. Zigong has explored topics including galactic cosmic ray shielding on the lunar surface, thermodynamic properties of solar protons, and the role of coronal shocks in particle acceleration. His studies often involve advanced statistical methods and comparative analyses of observations from instruments like EPT and HET aboard Solar Orbiter, and ISOIS on Parker Solar Probe. No formal awards or grants are explicitly mentioned, though his extensive publication record reflects active engagement in the field. He collaborates with international teams on missions such as Chang’E-4’s Lunar Lander Neutron and Dosimetry (LND) experiment, advancing lunar surface radiation studies.
Jane Wang is a Professor in the Department of Food Science at the University of Arkansas , where she has served since 1999, progressing from Assistant to Full Professor. She also holds the title of Director of the Experiment Station in the Department of Food Science. Her research focuses on starch structure-functionality relationships , rice quality , and biomaterial utilization , with over 120 refereed publications and 5 patents. Education: B.S. in Agricultural Chemistry (1986) from National Taiwan University , M.S. in Food Science (1989) from the University of Minnesota , and Ph.D. in Food Science (1992) from Iowa State University . Postdoctoral research in starch chemistry at Iowa State University (1993-1994). Research Interests: Jane Wang's work explores starch chemistry, rice processing optimization, and value-added applications of agricultural byproducts. She investigates how starch modifications affect food and pharmaceutical properties, with a particular focus on parboiling, germination, and enzymatic treatments. Her research also examines the impact of environmental factors on rice starch development and quality. Scientific Awards: Outstanding Departmental Research Award (2008) Outstanding Volunteer, IFT Carbohydrate Division (2007) Outstanding Mentor, University of Arkansas (2005) Grants & Professional Service: She has secured over $3M in research funding, including USDA-NIFA grants and industry contracts with more than 50 food companies. Jane has served on numerous academic committees (Patent, Promotion & Tenure, Curriculum) and held leadership roles in professional organizations like IFT and AACC. She has also acted as associate editor for Cereal Chemistry and Carbohydrate Polymers , and reviewed for multiple journals and agencies. Labs & Teams: Dr. Wang leads the Carbohydrate Research Program at the University of Arkansas, focusing on starch structure-functionality, rice fortification, and biomaterial development. Her lab collaborates with industry partners and academic institutions to advance food science applications.
Azadeh Davoodi is a Vilas Distinguished Achievement Professor and Associate Chair of Undergraduate Studies in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. Her research focuses on Electronic Design Automation (EDA), integrated circuit debug, and machine learning applications in VLSI design. She holds editorial roles in journals like IEEE TCAD and ACM TRETS, and has chaired major conferences such as ISPD 2015 and served on technical program committees for DAC, ICCAD, and others. Education: PhD in Electrical Engineering, University of Maryland-College Park (2006) Research Interests: Machine learning for VLSI chip design VLSI design automation for machine learning IC-CAD for emerging nanotechnologies Hardware security Recent Research Trends: Her work bridges machine learning and hardware design, with publications on neural network optimization, distributed inference, and explainable AI for circuit design. She emphasizes energy-efficient CNNs, latency reduction in edge computing, and security in split manufacturing. Awards: 2025 DATE Best Paper Candidate 2024 Vilas Distinguished Achievement Professor 2015 ACM Best Paper Award 2011 NSF CAREER Award Service and Grants: Leads NSF-funded projects on explainable ML for CAD and holds grants for distributed neural network synthesis. Her service includes roles as IEEE HKN member and editorial board positions. Labs/Teams: Engages in interdisciplinary research teams at UW-Madison, focusing on EDA innovation and hardware-software co-design.
Dr. Alison Oates is an Associate Professor at the University of Saskatchewan's College of Kinesiology, specializing in biomechanics and motor control. Her research focuses on neuromuscular adaptations, healthy aging, and managing chronic conditions through gait analysis and balance control. She holds a PhD from the University of Waterloo, with postdoctoral training at McGill University on locomotor rehabilitation post-stroke. Her academic background includes a B.Sc. in Kinesiology from Waterloo, followed by advanced studies in dynamic stability during gait termination in Parkinson's patients. She teaches advanced courses such as Motor Control of Neurological Conditions (KIN 422.3) and Sensorimotor Control of Posture & Locomotion (KIN 822.3). Dr. Oates' research explores biomechanical and neuromuscular aspects of balance and gait, particularly in neurologically impaired populations and older adults. Recent work includes studies on haptic feedback systems, sex-and-gender-based analysis in balance research, and fall prevention strategies. Her articles highlight innovative methods like IMU-based motion capture and clinical applications for spinal cord injury and stroke rehabilitation. While no formal academic awards are listed, her contributions to gait rehabilitation and biomechanical measurement techniques are widely recognized. She currently oversees research projects investigating the efficacy of haptic input on walking stability and neuromuscular adaptation mechanisms. Her work bridges clinical practice and biomechanical theory to improve rehabilitation outcomes for individuals with neurological disorders.
Navpreet Kaur is an Associate Professor in the Department of Physical Therapy at Carlow University. She holds a Doctor of Philosophy (Orthopedics and Sports Science) and a Doctor of Physical Therapy from Rocky Mountain University of Health Professions, alongside a Bachelor in Physiotherapy from Guru Nanak Dev University, India. Her research focuses on kinetic chain dynamics, balance testing (Star Excursion/Y Balance Tests), muscle activation during rehabilitation, musculoskeletal disorder interventions, and educational methodologies in healthcare. Kaur has published peer-reviewed articles in journals like International Journal of Sports Physical Therapy and Journal of Sport Rehabilitation , and presented at conferences such as the American College of Sports Medicine. Her awards include the 2021 Board Excellence in Scholarship Award. Kaur is actively involved in professional organizations like the American Physical Therapy Association (APTA) and serves as a manuscript reviewer for Journal of Athletic Training and International Journal of Sports Physical Therapy . Her work emphasizes bridging clinical practice with evidence-based research, particularly in orthopedic and sports physical therapy. She explores gender differences in muscle activation patterns and innovative teaching methods for physical therapy students.
Walter Szeliga is a Professor and Department Chair at Central Washington University. He holds a Ph.D. from the University of Colorado (2010). His research focuses on seismology, GPS, and InSAR technologies, with emphasis on earthquake early warning systems, crustal deformation monitoring, and natural hazards mitigation. Dr. Szeliga leads efforts in integrating real-time geodetic data streams for disaster response and has contributed to the development of ShakeAlert® systems. His work spans global geophysical networks, ionospheric perturbations, and paleotsunami studies. Key research interests include: Real-time GNSS applications for seismic monitoring Crustal deformation analysis using InSAR and GPS Earthquake source characterization through multi-method approaches Historical seismotectonic reconstructions Disaster forecasting and early warning system optimization Recent studies highlight advancements in trapping atmospheric lee waves detection via GNSS, volcanic plume dynamics during the 2022 Tonga eruption, and long-term paleotsunami records in Chile. His work bridges geophysical instrumentation with computational modeling to address critical questions in tectonic processes and hazard assessment. Scientific contributions include 50+ peer-reviewed articles on topics ranging from Cascadia subduction zone dynamics to global navigation satellite system innovations. His research has implications for civil infrastructure resilience, space weather impacts, and international geohazard collaboration frameworks.
Nicolas Roulin is an Associate Professor of Industrial/Organizational (I/O) Psychology at Saint Mary’s University, Halifax, Canada. He holds a PhD in Work and Organizational Psychology from the University of Neuchâtel, Switzerland, and previously served as a Senior Lecturer at the University of Lausanne and an Assistant Professor at the University of Manitoba. His research focuses on personnel selection, including impression management tactics, faking detection, employment discrimination, and innovative selection tools like social media and asynchronous video interviews. Education: Ph.D. in Work and Organizational Psychology, University of Neuchâtel M.Sc. and B.Sc. in Management, University of Lausanne Research interests include applicant behavior during selection processes, cross-cultural interview practices, and the integration of new technologies in recruitment. Key projects include studies funded by SSHRC (e.g., on asynchronous video interviews and cultural impression management). Awards: SIOP Fellow. Editorial roles include Associate Editor for the International Journal of Selection and Assessment (IJSA) and contributions to Personnel Psychology . He has authored/co-authored influential works like The Psychology of Job Interviews and the 8th edition of Recruitment and Selection in Canada . Consulting work includes advising multinational assessment firms and Canadian consulting companies. He actively supervises graduate students and teaches courses on staffing, assessment, and HR management.
Iain Gordon is a Professor and Head of the School of Mathematics at the University of Edinburgh. He holds a BSc in Mathematics from the University of Bristol and a Part III Mathematics degree from the University of Cambridge. His research focuses on representation theory, Lie algebras, quantum groups, and Cherednik algebras, with notable contributions to the study of symplectic reflection algebras and categorification. He has held positions at the University of Glasgow and Bielefeld University, and received the Seggie Brown Fellowship during his postdoc. As Head of School, he oversees the School’s academic mission, including the expansion of the Bayes Centre and the International Centre for Mathematical Sciences (ICMS). Education: BSc Mathematics, University of Bristol Part III Mathematics (MASt), University of Cambridge Key Roles: Professor of Mathematics, University of Edinburgh (2006–present) Head of School of Mathematics, University of Edinburgh (since 2017) His research interests revolve around algebraic structures with geometric interpretations, particularly Cherednik algebras and their connections to representation theory, combinatorics, and mathematical physics. Notably, he proved a significant combinatorial theorem linking noncommutative algebras and combinatorics, earning recognition in the mathematical community. His work has fostered interdisciplinary collaborations, bridging pure mathematics with emerging fields like quantum algebra and geometric representation theory. The School’s growth under his leadership, including the Bayes Centre’s expansion and ICMS initiatives, reflects his commitment to advancing mathematical research and education. Awards: Seggie Brown Fellowship, University of Edinburgh (Postdoc, early career support) Research Contributions: Pioneering studies on rational Cherednik algebras and their categories Geometric approaches to representation theory Applications of Cherednik algebras to symmetric functions and combinatorics His leadership emphasizes balancing research excellence with societal impact, exemplified by the School’s role in major UK government-funded initiatives for mathematical sciences.
