Laurent Mydlarski is a Professor in the Department of Mechanical Engineering at McGill University, affiliated with the Faculty of Engineering. His research focuses on experimental fluid mechanics, particularly turbulent flows and scalar mixing. He holds a Ph.D. from Cornell University and B.A.Sc. from the University of Waterloo. Research interests include turbulence statistics, scalar dispersion, differential diffusion, and industrial cooling applications such as hydroelectric generators and microelectronics. His work combines experimental methods like hot-wire anemometry, laser-induced fluorescence, and particle-tracking velocimetry. Key contributions include studies on multi-scalar mixing in jets, wall shear stress in turbulent flows, and thermal anemometry probe design. His Mydlarski Lab at McGill explores both fundamental fluid dynamics and practical engineering solutions. Recent publications (2023-2025) address multi-scalar mixing metrics, electronic cooling innovations, and drag reduction on porous cylinders. Collaborations with industry focus on applying fluid mechanics principles to real-world thermal management challenges.
Mike Giles is a Professor of Numerical Analysis at the University of Oxford's Mathematical Institute and serves as Head of the Numerical Analysis Group. He is also a Professorial Fellow at Balliol College and a Fellow of the Royal Society (FRS). His academic career spans computational mathematics, scientific computing, and computational finance. Professor Giles' research primarily focuses on Monte Carlo methods, with particular emphasis on the development and numerical analysis of multilevel Monte Carlo methods over the past 15 years. His work has significant applications in computational finance, uncertainty quantification, and solving stochastic differential equations. He has also made substantial contributions to high-performance computing, especially in the exploitation of many-core GPUs for scientific computing applications. His research bridges theoretical numerical analysis with practical computational implementations. Analysis of his publication record reveals a consistent trajectory of innovation in Monte Carlo methodology, evolving from foundational work on path simulation to sophisticated multilevel techniques that dramatically improve computational efficiency. His research spans multiple disciplines including numerical analysis, computational finance, and high-performance computing, with a clear focus on developing practical algorithms that address real-world computational challenges in science and finance. Fellow of the Royal Society (FRS) Professor Giles actively teaches courses in numerical methods for the MSc in Mathematical and Computational Finance and is a leading educator in GPU programming, organizing an annual intensive course on CUDA Programming on NVIDIA GPUs. He has been instrumental in establishing JADE, Oxford's GPU supercomputer facility, which supports research in machine learning and scientific computing. His leadership extends to the Numerical Analysis Group at Oxford and the Mathematical and Computational Finance Group, where he fosters interdisciplinary research connecting mathematics, finance, and computer science. Through his educational initiatives and research leadership, Giles has significantly influenced both academic research and practical applications of advanced computational methods.
Michal Kolesár is a Professor in the Department of Economics at Princeton University , holding this position since July 2020. Previously, he served as Assistant Professor (2014-2020) with dual appointments in Economics and the Woodrow Wilson School (2018-2020), and as Visiting Assistant Professor at MIT (2016-2017). His research focuses on econometrics , particularly causal inference , instrumental variables , nonparametric regression , and robust statistical methods . His work addresses fundamental challenges in high-dimensional data analysis, treatment effect heterogeneity, and finite-sample inference validity. Current projects include developing bias-aware methods for regularized regression and analyzing dynamic causal effects in nonlinear systems. Kolesár's recent publications reveal a strong emphasis on methodological rigor with practical applications. His work spans instrumental variable techniques (addressing contamination bias, weak identification), regression discontinuity designs (discrete running variables, measurement error), and high-dimensional inference (sparsity fragility, honest confidence intervals). Key recurring themes include finite-sample optimality, coverage probability guarantees, and robustness to model misspecification. Fellow of the International Association for Applied Econometrics (2023) Journal of Econometrics best associate editor award (2023) Sloan Research Fellowship (2019) NSF grants for high-dimensional data inference (2021-2025) and nonparametric regression (2016-2019) Graduate Economics Club teaching awards (2017, 2018) As an educator, Kolesár teaches advanced econometrics courses at both undergraduate (ECO 312, ECO 313) and graduate levels (ECO 517, ECO 519, ECO 539b). He serves as Co-editor of the Journal of Business & Economic Statistics (2024-2027) and sits on editorial boards of Econometrica , American Economic Journal: Applied Economics , and others. His professional activities include extensive peer review for top journals and organization of major econometrics conferences including the 2026 Econometric Society Winter Meeting.
Changhuei Yang is the Thomas G. Myers Professor of Electrical Engineering, Bioengineering, and Medical Engineering at California Institute of Technology, serving as Executive Officer for Electrical Engineering and Investigator at Heritage Medical Research Institute. He holds a Ph.D. and three master's degrees from MIT, with appointments at Caltech since 2003. Research focuses on: Advanced microscopy techniques including Fourier Ptychography Wavefront shaping for biological tissue imaging Optical phase conjugation for deep-tissue applications Compact medical devices for cerebral monitoring Publications demonstrate leadership in computational imaging, with recent advances in stain-free embryo analysis, portable cerebral blood flow monitors, and high-resolution volumetric imaging techniques using neural representations. Honored as National Academy of Inventors member. Research applications span deep-tissue biochemical imaging, incisionless surgery, and optogenetic activation systems.
Prof. Dr. André Rubbia is a Full Professor of Experimental Physics at ETH Zurich's Department of Physics, holding this position since December 2003 after serving as Associate Professor from 1998. His research spans neutrino physics, astro-particle physics, and dark matter detection through major international collaborations including CERN, Gran Sasso National Laboratory, and Fermilab. He currently serves as Co-Spokesperson for the billion-dollar DUNE neutrino project at Fermilab, managing over 900 scientists. His educational background includes: Diploma in Physics from the University of Geneva (1990), with thesis work on the L3 experiment at CERN's LEP accelerator Ph.D. in Physics from MIT (1993) under Nobel Laureate S.C.C. Ting, focusing on high-energy electron-positron collisions Rubbia's research centers on fundamental particle interactions, particularly neutrino oscillations and physics beyond the Standard Model. He pioneered liquid Argon Time Projection Chamber (LAr TPC) technology and dual-phase detection systems, enabling breakthroughs in neutrino mass measurements and dark matter searches. His work spans underground laboratories (Gran Sasso, Canfranc), the LHC's CMS detector, and neutrino beam experiments like T2K. Recent explorations include antimatter gravity tests, electron-positron bound states, and dark hidden sector searches. His 2025 publications reveal intense focus on neutrino oscillation parameter precision (T2K, Hyper-Kamiokande), FASER's LHC neutrino program, and DarkSide-20k dark matter detector development. Key themes include cross-section measurements, advanced detector technologies (SiPMs, emulsion tracking), and statistical methods for oscillation analysis, reflecting integration of theoretical modeling with cutting-edge instrumentation. Scientific recognition includes: Breakthrough Prize for Fundamental Physics (2016) awarded to the international team for discovering matter-anti-matter asymmetry in neutrino oscillations APS Viewpoint selection for editing the paper announcing first electron neutrino appearance at accelerators Rubbia has supervised over fifty PhD and Master's theses while securing substantial research funding as Principal Investigator for 20+ Swiss National Science Foundation projects and Coordinator of two EU FP7 Design Studies. His DUNE leadership involves complex international grant management across 30+ countries. He leads ETH Zurich's experimental particle physics group across multiple facilities: the ICARUS neutrino detector at Gran Sasso, CMS at CERN, DUNE at Fermilab, and DarkSide-20k for direct dark matter detection. His team developed the first underground ton-scale liquid argon detector and maintains collaborations with Japanese (Super-Kamiokande) and American (Fermilab) institutions.
Michael James Herdman is an Honorary Visiting Associate Professor at the National University of Singapore’s Saw Swee Hock School of Public Health. He serves as Head of Health Outcomes Research at the Office of Health Economics in London and Director of Insight Consulting & Research in Barcelona. His work focuses on patient-reported outcome (PRO) measures, including their development, validation, and application in healthcare evaluation. He has been a key member of the EuroQol Group for 25 years, contributing to initiatives like the EQ-5D-5L tool and pediatric health measurement standards. Education: MSc in Bioethics and Law from the University of Barcelona (1996–1998) and BSc Philosophy (Honors) from the University of Hull (1981–1985). Research Interests: Central to Herdman’s work are PRO measures, health technology assessment, and outcomes research, particularly in younger populations and pediatric health. He has authored over 150 peer-reviewed articles and book chapters, with notable contributions to cross-cultural adaptation of health instruments and systematic reviews on pediatric vaccines. Professional Activities: Provides consulting services to pharmaceutical companies and public health organizations. His work bridges academic research and practical applications in health economics and policy. Labs/Teams: Active in the EuroQol Group’s Executive Committee and Younger Populations Working Group, and leads Insight Consulting & Research.
Zainab Hermes is an Associate Instructional Professor in the Department of Near Eastern Studies at the University of Chicago, where she has taught since 2018. She holds a PhD in Linguistics from the University of Illinois at Urbana-Champaign (2018), earned through experimental research combining phonetics and neuroscience methodologies. Education PhD in Linguistics, University of Illinois at Urbana-Champaign (2018) Research Interests Her work focuses on experimental linguistics, particularly the articulation of Arabic dialects (Cairene, Lebanese, Jordanian, Saudi). Key projects involve: MRI studies of vocal tract configurations for back consonants MEG investigations of neurological representations during Arabic diglossic code-switching Self-paced reading studies on L2 acquisition of Arabic grammatical gender Publications & Methodologies Her research employs advanced imaging techniques (rt-MRI, EMA) and neurolinguistic methods (MEG) to analyze speech production and processing. Her teaching includes courses on Arabic linguistics, dialectology, and academic reading. Academic Contributions She collaborates on interdisciplinary studies bridging phonetics, neuroscience, and language acquisition frameworks.
Michelle Dimitris is an Assistant Professor in the Department of Community Health and Epidemiology at Dalhousie University’s Faculty of Medicine. Her research focuses on advanced epidemiologic methods applied to pregnancy and child health globally, particularly in understanding pregnancy weight gain patterns and their implications for outcomes like gestational diabetes and preterm birth. She holds a PhD from McGill University, an MSc from Queen’s University, and a BScH from Queen’s University in Life Sciences. Her work includes studies on twin vs. singleton pregnancies, methodological challenges in epidemiology during pandemics, and global health research trends. Notable collaborations involve the National Institutes of Health (NIH) grants and fellowships, including a Fonds de Recherche Santé Doctoral Award. She contributes to professional societies like the Society for Pediatric and Perinatal Epidemiologic Research (SPER) and the Society for Epidemiologic Research (SER). Key research themes include causal inference approaches, perinatal epidemiology, and addressing gaps in global health studies. Recent publications analyze gestational weight gain trajectories, pandemic impacts on pregnancy outcomes, and methodological rigor in epidemiological studies.
Carolin Pflueger is an Associate Professor at the Harris School of Public Policy , University of Chicago, and holds affiliations as a NBER Faculty Research Fellow and CEPR Research Affiliate . Her work bridges macroeconomics and finance, focusing on inflation dynamics, monetary policy impacts, and financial market risk perception. University: University of Chicago School: Harris School of Public Policy Affiliations: NBER, CEPR Role: Associate Professor Her research explores how inflation and monetary policy influence financial markets, including models connecting Treasury bond risk to stagflation drivers and analyzing economic agents' perceptions of policy uncertainty. Recent work leverages cross-sectional data of stock prices and economic forecasts to quantify macrofinancial linkages. Notable scientific recognitions include the Fama DFA Prize (2023), AQR Insight Award Finalist (2018), and the Arthur Warga Award (2014). She has received NSF Grant 2149193 for macrofinance research. Contact: cpflueger@uchicago.edu | GitHub Code Repositories
Alexis Berne is an Associate Professor at the Environmental Remote Sensing Laboratory (LTE) within the School of Architecture, Civil and Environmental Engineering (ENAC) at École Polytechnique Fédérale de Lausanne (EPFL). He co-directs the SSIE-GE program and serves as a member of the CDS (Commission for Doctoral Studies) . His research spans radar meteorology, precipitation microphysics, polar precipitation, and geostatistics, with a focus on mountainous and polar regions. Current Positions Associate Professor, LTE, EPFL (2013–present) Co-Director, SSIE-GE, EPFL PhD Program Committee Member, EDCE-GE, EPFL Research Interests include the remote sensing of precipitation, particularly snowfall and ice production mechanisms, using radar and geostatistical methods. His work addresses atmospheric processes in extreme environments like Antarctica and the Swiss Alps, leveraging machine learning and numerical modeling for climate analysis. Teaching encompasses courses on remote sensing, atmospheric processes, and climate change, emphasizing interdisciplinary approaches and spatiotemporal variability. He advises current PhD students such as Heather Anne Corden and Gionata Ghiggi, alongside mentoring past students like Jacopo Grazioli and Timothy Hugh Raupach.
Alison J. Mackey is Professor and Chair of the Department of Linguistics at Georgetown University, College of Arts and Sciences. She is a leading scholar in second language acquisition (SLA), with a focus on interaction, feedback, research methodology, and language learning across the lifespan. Her research interests include second language acquisition , task-based language teaching , research methodology , interaction and corrective feedback , and language learning in children and adults . She has published extensively in top-tier journals and book series, shaping methodological standards in the field. Her recent publications reflect a strong trend in methodological rigor , interactionist approaches , and practical applications of SLA research. Themes include data elicitation , stimulated recall , task design , and pragmatic development , spanning both theoretical and classroom-based inquiry. Mildenberg Prize (2012) for The Handbook of Second Language Acquisition American Association for Applied Linguistics Distinguished Scholarship and Service Award International Association of Task-based Language Learning and Teaching Distinguished Achievement Award CHOICE Outstanding Academic Title (2012) Alison Mackey has advised numerous scholars through co-authorship and editorial leadership. She is Editor-in-Chief of Cambridge University Press Annual Review of Applied Linguistics and Editor of the Routledge Second Language Research series, guiding the publication of cutting-edge research. While specific grants are not listed, her editorial work and high citation count (>35,000) reflect significant research impact and funding support. She leads and contributes to major research initiatives such as the IRIS Repository , promoting open-access research instruments in SLA. Her work fosters collaboration across institutions and supports methodological transparency and replication in the field.
Aaron Tohuvavohu is a Research Fellow in the Division of Physics, Mathematics, and Astronomy at the California Institute of Technology. His work focuses on high-energy astrophysics, particularly gamma-ray bursts (GRBs) and multi-messenger astronomy. He is deeply involved in the Neil Gehrels Swift Observatory mission, specializing in real-time localization of transient events using the BAT-GUANO pipeline and collaborating with gravitational-wave detectors like LIGO/Virgo/KAGRA. His research emphasizes rapid-response observations of GRBs and gravitational-wave events, leveraging the Interplanetary Network (IPN) for precise localization. He has contributed to studies of short-hard GRBs associated with compact object mergers and long-duration GRBs linked to hypernovae. Notable projects include the CASTOR mission concept for UV photometry and detector characterization for next-generation astronomical instruments. Aaron's recent work includes analyzing Swift/XRT and UVOT observations of GRB afterglows, setting upper limits for electromagnetic counterparts to gravitational-wave triggers, and improving IPN triangulation algorithms. His publications reflect a systematic approach to transient astronomy, integrating data from multiple observatories for comprehensive event characterization.
António Fidalgo serves as an Adjunct Professor at the Católica Lisbon School of Business & Economics, Catholic University of Portugal, where he concurrently holds the position of Academic Director for the Masters in Applied Management program. His prior academic appointments include teaching roles at University of Magdeburg (Germany), Fresenius University (Germany), and Boston University (USA). His educational qualifications comprise: M.A. in Economics from Universitat Pompeu Fabra, Spain Ph.D. in Economics from Lausanne University, Switzerland Fidalgo specializes in cliometrics—the quantitative analysis of economic history—with research concentrated on pre-Industrial Revolution to Industrial Revolution periods. His work examines: Long-term economic development trajectories Historical living standards and agricultural production systems Economic inequality dynamics across centuries Methodological innovations in quantitative economic instruments Reproducibility frameworks for empirical economic research As Academic Director of the Masters in Applied Management, he oversees program development and student mentorship. While specific research grants and advisee details remain undisclosed in available records, his leadership role demonstrates significant engagement in graduate education administration and curriculum design within quantitative economics.
Carlos Cinelli is an Assistant Professor in the Department of Statistics at the University of Washington, where he conducts research at the intersection of causal inference, statistical methodology, machine learning, and artificial intelligence. He is also a data science fellow at the eScience Institute and affiliate faculty of the Center for Statistics and the Social Sciences, demonstrating his interdisciplinary approach to causal methodology. Dr. Cinelli received his Ph.D. in Statistics from the University of California, Los Angeles, advised by Chad Hazlett and Judea Pearl, two prominent figures in causal inference. His research focuses on developing new causal and statistical methods for transparent and robust causal claims in empirical sciences, with particular attention to challenges faced by social and health scientists. His work spans theoretical developments in causal identification, sensitivity analysis frameworks, and practical software implementations that enable researchers to assess the robustness of their causal conclusions. Cinelli's research program addresses fundamental questions about how unobserved confounding affects causal estimates and develops tools to quantify how sensitive findings are to potential violations of causal assumptions. His work on omitted variable bias frameworks has been particularly influential across multiple disciplines. Through his publications, Cinelli has established himself as a leading researcher in causal inference methodology, with papers appearing in top journals across statistics, machine learning, epidemiology, and social sciences. His work demonstrates both theoretical rigor and practical relevance, often accompanied by open-source software implementations that make his methods accessible to applied researchers. Best paper award at SBE 2024 in Econometrics Royalty Research Fund (RRF) Award recipient NSF/MMS research support As an advisor, Cinelli has successfully guided PhD students like Nick Irons to dissertation completion. He actively seeks new students with strong interests in causal inference. His research is supported by multiple funding sources including the National Science Foundation and the University of Washington's Royalty Research Fund. Cinelli contributes to the academic community through editorial work for the Journal of Causal Inference and by developing widely used software packages like sensemakr for sensitivity analysis.
Dr. Maud Borie is a Senior Lecturer in Environment, Science & Society at King’s College London’s Department of Geography, within the School of Global Affairs. Her work bridges Human Geography and Science and Technology Studies (STS), focusing on biodiversity governance, environmental policy, and green finance. She holds a PhD from the University of East Anglia and has held visiting fellowships at Harvard Kennedy School. Borie’s research explores the politics of environmental knowledge and its societal implications, including nature-based solutions and green finance mechanisms. She has contributed to global initiatives like the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) and co-founded the Mediterranean Alliance for Wetlands. Her recent projects include analyzing green finance’s reliance on scientific legitimacy and mapping resilience strategies in cities. She teaches courses on environmental policy, qualitative methods, and geographies of financialization. Borie has been awarded grants for interdisciplinary projects such as ‘deep listening with machines for equitable environmental futures’ and ‘forestscapes’ immersive soundscapes. Her research outputs span over 18 peer-reviewed articles, with topics ranging from climate change framing to urban resilience in the Global South. Awards: Planetary-scale interpretation (2023), Rethinking environmental policy (2022), Forestscapes collaboration (2023) Grants: Creative Collaboration Seed Fund (2023), EU/PEARL disaster resilience projects Labs/Teams: KingsCAT (Social Media Research), Political Ecology, Biodiversity & Ecosystem Services (PEBES) group
