Richard Nickl is a Professor of Mathematical Statistics at the University of Cambridge, affiliated with the Department of Pure Mathematics and Mathematical Statistics (DPMMS) and the Statistical Laboratory. His research focuses on high-dimensional inference, Bayesian nonparametrics, statistics for partial differential equations, and inverse problems. He has held significant grants, including an ERC Advanced Grant (2024–2029) and an EPSRC Programme Grant (2022–2027). His work bridges statistics, probability, and analysis, with contributions to theoretical foundations and computational methods in non-linear inverse problems. Key research interests include Bayesian posterior consistency, statistical inference for diffusions, and polynomial-time algorithms for high-dimensional posteriors. Notable publications include foundational monographs such as Mathematical foundations of infinite-dimensional statistical models (2016), which earned a PROSE Award, and recent advancements in Bayesian nonparametric inference for McKean-Vlasov models (2025). His group organizes workshops, such as the 2024 Statistical Aspects of Non-Linear Inverse Problems conference. Awards: 2017 PROSE Award in Mathematics. Grants: ERC Advanced Grant, EPSRC Programme Grant. Lab/Team: Research Group in Mathematical Statistics at DPMMS, focusing on inverse problems and Bayesian methodology.
John R Anderson is the Richard King Mellon University Professor of Psychology and Computer Science at Carnegie Mellon University (CMU), affiliated with the Department of Psychology within the Dietrich College of Humanities and Social Sciences. His research focuses on understanding higher-level cognition, particularly mathematical problem-solving, through the development of the ACT-R cognitive architecture—a computational framework simulating human cognitive processes. This architecture integrates behavioral, neural, and educational data to model learning and decision-making. Anderson’s work bridges cognitive science, neuroscience, and educational technology. He investigates how brain imaging (e.g., fMRI, EEG) can reveal the temporal dynamics of cognitive processes and improve instructional methods. His research emphasizes analyzing brain activity time courses to uncover underlying mechanisms of problem-solving and skill acquisition. Key Research Themes: Cognitive architectures, neural correlates of learning, computational models of memory, and intelligent tutoring systems. Notable Contributions: Development of the ACT-R architecture, integration of neuroimaging with cognitive modeling, and studies on skill transfer and learning strategies. Anderson’s publications include seminal books like Cognitive Psychology and Its Implications and How Can the Human Mind Occur in the Physical Universe? His work has advanced understanding of associative memory, strategic decision-making, and the application of cognitive models in educational technology. His lab, the ACT-R Research Group, collaborates across disciplines to model complex cognitive tasks and their neural foundations. Current projects analyze real-time brain activity to refine educational interventions and improve human-machine interaction.
Bradley J. Siwick is an Associate Professor in the Department of Chemistry at McGill University, holding the Canada Research Chair in Ultrafast Science (Tier II). He specializes in developing ultrafast electron-based techniques to study atomic and molecular dynamics in materials and chemical systems. His work bridges chemical physics, materials science, and condensed matter physics, focusing on structural dynamics, phase transitions, and nonequilibrium states. Education: B.A.Sc. (Engineering Physics, University of Toronto, 1997), M.Sc. (Physics, 1998), Ph.D. (Physics, 2004). Postdoctoral training at FOM-AMOLF Amsterdam (2004–2006). Awards: NSERC Doctoral Prize (2005). Research interests include ultrafast electron diffraction/scattering, electron-phonon coupling, and imaging transient structural changes. Techniques developed in his lab combine electron microscopy with ultrafast laser spectroscopy to observe atomic motions on femtosecond timescales. Key areas of study are phase transitions in materials (e.g., VO₂, cuprates), nanocomposites, and extreme states of matter using facilities like the Advanced Laser Light Source (ALLS). Recent articles highlight advances in momentum-resolved phonon dynamics, polaron formation, and ultrafast imaging of 2D materials. His lab, based in Otto Maass and Rutherford buildings, collaborates on frontier projects in nonequilibrium materials science. Advising: Leads the Siwick Research Group, focusing on graduate students in chemical physics and materials science. Grants: Supported by NSERC and Canada Research Chairs funding. Labs and facilities: Otto Maass 25 laboratory and ALLS (Varennes, Quebec) for high-power laser experiments.
Lenya Ryzhik is a Professor in the Department of Mathematics at Stanford University, specializing in analysis and partial differential equations with applications in various physical contexts. His research spans stochastic processes, wave propagation, and front dynamics in random media, with significant contributions to understanding reaction-diffusion systems and their applications in mathematical biology and physics. Professor Ryzhik's research interests focus on the mathematical analysis of partial differential equations arising in physical systems. His work particularly emphasizes stochastic PDEs, wave propagation in random media, front propagation in reaction-diffusion systems, and homogenization theory. He investigates how randomness and complex structures affect wave propagation, front speeds, and transport phenomena, with applications ranging from combustion theory to population dynamics and quantum mechanics. The publication record demonstrates a consistent focus on understanding propagation phenomena in complex environments. Ryzhik's research shows a progression from classical PDE analysis toward increasingly sophisticated stochastic frameworks, particularly examining high-dimensional systems and random media. His recent work has focused on KPZ fluctuations, random heat equations, and non-local reaction-diffusion models, revealing deep connections between probability theory and partial differential equations. Alfred P. Sloan Research Fellowship (2002-2004) AFOSR NSSEFF Fellowship (2010-2015) Ryzhik has advised graduate students including Alexandra Stavrianidi, and has secured substantial research funding throughout his career. His grant history includes multiple NSF awards (DMS-9971742, DMS-0203537, DMS-0604687, DMS-0908507, DMS-1311903), ONR funding (N00014-02-1-0089, N00014-04-1-0224), and FRG support for collaborative research on nonlinear evolution problems. He co-organized a Summer School and Workshop on 'Recent Advances in PDEs and Fluids' at Stanford in 2013. Ryzhik maintains an active research group collaborating with leading mathematicians worldwide, particularly with researchers at institutions like NYU, Chicago, and various European universities. His work frequently involves interdisciplinary collaborations bridging mathematics with physics and biology.
Valentino Tosatti is a Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University. His research focuses on complex and differential geometry, geometric analysis, and partial differential equations (PDEs), with connections to algebraic geometry and dynamical systems. He explores topics such as Kähler geometry, Calabi-Yau manifolds, symplectic geometry, geometric flows, and the Monge-Ampère equations. His work often addresses the interplay between geometric structures and their analytic properties. Education: He earned his PhD in Mathematics from Harvard University in 2009 under the supervision of Shing-Tung Yau. Prior to that, he completed a Laurea (BSc) at the University of Pisa and a Minor Thesis at Harvard. Research Interests: Tosatti's work emphasizes the study of geometric flows (e.g., Kähler-Ricci flow), collapsing behavior of Calabi-Yau metrics, and canonical currents on K3 surfaces. His contributions include foundational results on the regularity of solutions to Monge-Ampère equations and the asymptotic analysis of geometric structures under degenerations. Publications and Trends: His recent articles address themes like volume regularity, collapsing metrics, and geometric flows, reflecting a deep engagement with the analytic and geometric challenges in complex geometry. He has also organized conferences and workshops on topics such as geometric analysis and complex geometry. Professional Activities: Tosatti serves on editorial boards for journals including the Canadian Journal of Mathematics and Mathematische Zeitschrift. He has contributed to organizing events like the 2026 Oberwolfach workshop on Complex Geometry and Dynamical Systems and has been involved in academic seminars at institutions like Columbia University and Northwestern University.
Gustav Amberg is a Professor at KTH Royal Institute of Technology, affiliated with the Flow Mechanics research group within the School of Engineering Sciences. His primary appointment is in the Department of Mechanics, where he focuses on fluid dynamics, multiphase flow, and interfacial phenomena. He holds a permanent full professorship with no indication of兼职 roles. Research interests center on dynamic wetting mechanisms, phase-field modeling, and computational fluid dynamics applied to complex fluid systems. His work explores contact line behavior, microstructured surface interactions, and material phase transformations. Notable areas include rapid droplet spreading, viscoelastic fluid dynamics, and boiling heat transfer on engineered surfaces. Recent studies investigate the interplay between surface topography and wetting dynamics, oscillatory contact line phenomena, and numerical benchmarking across molecular and continuum models. He has pioneered methods for simulating surfactant effects in multiphase flows and developed novel approaches for analyzing weld pool behavior during sintering processes. No academic awards or grants are explicitly listed in the provided materials. His advising record remains undisclosed, though his prolific publication history suggests active research supervision. Laboratory affiliations are not detailed, but his work aligns with KTH's broader initiatives in computational mechanics and materials science.
Rachel B. Baker is an Associate Professor in the Policy, Organizations, Leadership, and Systems Division at the University of Pennsylvania's Graduate School of Education. Her research focuses on enhancing access and success in higher education for underserved groups, particularly in community colleges. She leads a National Science Foundation-funded study on cross-enrollment programs and collaborates on projects measuring curricular complexity and online education effectiveness. Key Affiliations: Wheelhouse Center for Community College Leadership, Editorial Boards of Research in Higher Education and Journal of Research on Educational Effectiveness Funding Sources: NSF, Institute of Education Sciences, Spencer Foundation, College Futures Foundation Her work addresses three core themes: policy impacts on student decisions, enrollment equity across race/socio-economic status, and interventions to improve self-regulatory skills via online data. Recent studies include analyzing cross-enrollment effects on transfer success and instructor professional development in online settings. Awards: 2019 NAEd/Spencer Postdoctoral Fellowship, 2016 IES Outstanding Fellow, Jack Kent Cooke Dissertation Fellowship Grants: NSF 5-year cross-enrollment study, IES training programs, Spencer Foundation initiatives Baker’s team develops metrics for curricular complexity and explores how course requirements influence student outcomes. She advocates replacing the 'pipeline' metaphor with 'pathway' to emphasize inclusive educational trajectories.
Professor Manolis Gavaises is a leading academic in the field of mechanical engineering and computational fluid dynamics at City St George's, University of London, where he holds the position of Professor in the School of Engineering and Mathematical Sciences. He earned his PhD from Imperial College London and has been a faculty member since 2001, progressing to full Professor in 2009. His research is centered on advanced modeling of multi-phase flows, cavitation, and fuel injection systems, with extensive collaborations across Europe and industry partners such as Delphi, Caterpillar, and BP. Education: DIC, Mechanical Engineering, Computational Fluid Dynamics, Imperial College London, 1997 PhD, Mechanical Engineering, Computational Fluid Dynamics, Imperial College London, 1997 Diploma (5 years), Mechanical Engineering, National Technical University of Athens, 1992 His research interests span computational fluid dynamics, cavitation, fuel injection, atomization, high-pressure and supercritical flows, and alternative fuels . He has developed advanced numerical models and experimental techniques, including X-ray phase contrast imaging and high-pressure test rigs. His work integrates fundamental DNS and LES simulations with industrial applications in automotive, marine, aerospace, and medical devices such as heart valves. The recent publications reflect a strong trend toward real-fluid thermodynamic modeling (e.g., PC-SAFT), multi-component fuel behavior, cavitation erosion, and advanced diagnostics . His research increasingly incorporates machine learning and high-fidelity imaging to understand complex flow phenomena across energy, transportation, and biomedical domains. Scientific Awards and Recognitions: Richard Way Prize (1998) Arch T. Collwell Merit Award (1998) Best Oral Paper, SAE World Congress (2006) PE Publication Award, IMechE (2007) Best Presentation Award, Engine Combustion Processes (2009) Fellow, IMechE (2013) Fellow, IMA (2015) As a dedicated mentor, Professor Gavaises has supervised 13 PhDs to completion and currently guides 23 doctoral students. He has secured over €16 million in EU and UK funding, including multiple Horizon 2020 Marie Skłodowska-Curie ITN projects (CAFÉ, HAOS, IPPAD), which support 46 early-career researchers globally. He has created academic opportunities for post-docs and junior faculty, significantly advancing the research profile of his institution. He leads the International Institute of Cavitation Research (IICR), co-founded in 2011 with partners from Loughborough University, TU Delft, and Imperial College, supported by The Lloyd’s Register Foundation. His lab maintains strong experimental capabilities, including a 2000bar pressure flow rig with micro-transparent nozzles and collaborations with Argonne National Laboratory for X-ray imaging.
Kamal Sen is an Associate Professor in the Department of Biomedical Engineering at Boston University, serving as Director of the Natural Sounds and Neural Coding Laboratory and Director of Admissions and Recruitment for Master’s Programs. He holds a PhD and MA in Physics from Brandeis University and a BA in Physics from Bates College. His research focuses on understanding how neurons encode natural sounds, particularly in the auditory cortex. Key areas include neural coding efficiency, hierarchical auditory processing, and the role of learning in shaping receptive fields. He developed the BOSSA algorithm to address sound segregation challenges in noisy environments, with applications for hearing aid technology. Sen’s work integrates electrophysiological techniques with theoretical approaches from signal processing, information theory, and systems theory. His lab explores neural discrimination of behaviorally relevant sounds and models cortical processing dynamics using computational frameworks. Recent studies investigate parvalbumin neuron contributions to temporal coding and cortical noise reduction in complex auditory scenes. His publications span neural circuit modeling, fNIRS applications in BCI, and biomimetic algorithms for auditory scene analysis. Research highlights include exploring schizophrenia-related gene effects on neural circuits and developing 3D neurosphere models for Parkinson’s disease.
Grace Lim is an Assistant Professor in the Department of Management at the Nanyang Business School, Nanyang Technological University, Singapore. Her research focuses on inclusion, diversity, and the empowerment of disadvantaged employees in organizations, particularly those from lower social class backgrounds and women. Education: Ph.D. in Business (Organizational Behavior and Human Resources), Singapore Management University B.Sc. in Psychology, National University of Singapore Her research employs a range of methodologies, including field surveys, experiments, archival data, and qualitative methods, to ensure robust and generalizable findings. She investigates how individuals can exercise agency to overcome structural disadvantages in the workplace, contributing to the fields of organizational behavior, human resources, and social psychology. Her recent publications reflect a strong trend in studying diversity, inclusion, and equity, with a focus on social class, gender, leadership, and employee well-being. The research spans interdisciplinary themes, integrating insights from psychology, management, and sociology to understand workplace dynamics. Scientific Contributions: Published in top-tier journals such as Organizational Behavior and Human Decision Processes and Academy of Management Annals Research on social class, gender, inclusion, and leadership has been influential in shaping organizational practices Dr. Lim is actively involved in advancing knowledge in organizational behavior and human resources. She has not supervised any listed students yet but continues to contribute through impactful research and academic engagement. She is a member of the Centre for Leadership and Cultural Intelligence at NTU, collaborating on initiatives related to cultural intelligence and inclusive leadership.
Rasmus Kyng is an Assistant Professor in the Department of Computer Science at ETH Zurich, where he has been since 2019. His research focuses on fast algorithms for graph problems, convex optimization, and their applications in machine learning. He has received grants from the Swiss National Science Foundation, including project grants and a starting grant. Education: B.A. in Computer Science from the University of Cambridge (2011), PhD in Computer Science from Yale University (2017), advised by Daniel A. Spielman. Postdoctoral positions included Harvard University (2018–2019) and a research fellowship at the Simons Institute, UC Berkeley (2017). Research Interests: Development of nearly linear-time algorithms for fundamental graph problems (e.g., maximum flow, minimum-cost flow), dynamic graph algorithms, discrepancy theory, and fine-grained complexity. His work bridges numerical linear algebra and combinatorial optimization, emphasizing practical implementations such as the Laplacians.jl package. Awards: FOCS Best Paper Award (2022), Inaugural ICBS Frontiers of Science Award (2022), Machtey Award (Best Student Paper, FOCS 2017). Teaching: Advanced Graph Algorithms and Optimization (ETH Zurich, 2020–2023), Algorithms, Probability, and Computing (ETH Zurich, 2020–2022). Supervised numerous PhD students and mentored postdocs in theoretical computer science. Labs/Teams: Co-leads a research group with Maximilian Probst Gutenberg, focusing on dynamic graph algorithms and optimization. Collaborations include work on sparsification, spectral graph theory, and machine learning applications.
Professor Charlotte Deane is a leading academic in structural bioinformatics, holding the position of Professor at the University of Oxford's Department of Statistics and Executive Chair of the Engineering and Physical Sciences Research Council (EPSRC). She leads the Oxford Protein Informatics Group (OPIG), focusing on protein structure prediction, immunoinformatics, and AI-driven drug discovery. Her research integrates computational methods with biological insights, developing tools widely used in academia and industry. Prior roles include Head of the Department of Statistics, Deputy Head of the Mathematical, Physical and Life Sciences (MPLS) Division at Oxford, and Chief Scientist of Biologics AI at Exscientia. During the COVID-19 pandemic, she served on SAGE and as UKRI's COVID-19 Response Director. In 2022, she was awarded an MBE for her contributions to pandemic research. Her research group's work spans antibody design, T-cell receptor analysis, and small molecule discovery, with a focus on open-source software development. Current projects include advancing AI methods for protein structure prediction and therapeutic antibody engineering. Recent publications highlight innovations in computational drug design, antibody developability, and machine learning applications in structural biology.
Dr. Lauren Hammond serves as Lecturer in Teacher Education at the Institute for Education, Teaching and Leadership within the Moray House School of Education and Sport at the University of Edinburgh, a position she assumed in August 2022 after eight years at IOE, UCL's Faculty of Education and Society. Her academic career bridges secondary school teaching in London and Singapore with higher education expertise in geography teacher education, curriculum development, and doctoral supervision. Her educational background includes a PhD in Geography Education from University College London (2020), an MA in Geography Education from the Institute of Education (2009), a PGCE in Secondary Geography from the University of Bristol (2006), and a BA (Hons) in Geography from King's College London (2004). This foundation supports her interdisciplinary research at the intersection of children's geographies, geography education, and geographies of education. Dr. Hammond's research centers on children's rights, urban educational spaces (particularly London), and empowering young people through geography. She employs participatory methods including storytelling and mapping with youth, investigating how educational spaces reproduce social injustices and how geographical concepts illuminate educational processes. Her work critically examines geography's construction in schools and universities while exploring teacher education for complex socio-political contexts. Her recent publications reveal strong thematic continuity in children's geographies and geography education, with growing emphasis on race, climate change, and pandemic research ethics. Key trends include participatory methodologies, urban justice frameworks, and critical analyses of teacher development in volatile educational landscapes. Dr. Hammond holds significant professional recognition including: Fellow of the Royal Geographical Society (FRGS) Senior Fellow of the Higher Education Academy (SFHEA) She actively supervises postgraduate students and has secured competitive research funding including UCL's Centre for Teachers and Teaching Research grant (£3,500) for race and educational spaces (2023), an IOE Early Career Impact Fellowship (£1,000) on children's urban rights (2021), and seed funding for PGCE mentoring evaluation (£8,317.50, 2017). Her collaborative approach extends to organizing major conferences and leading cross-institutional networks. As deputy secretary of the RGS's Geography and Education Research Group and membership officer of the Geographies of Children, Youth and Families Research Group, she actively shapes research communities. Her leadership extends to the Geography Education Research Collective and Geographical Association's special interest groups, fostering national and international scholarly collaboration.
Lindell Bromham is a Professor at the Research School of Biology , Australian National University, focusing on evolutionary biology, cultural evolution, and interdisciplinary research. Their work spans genomic mutation rates to global linguistic diversity, with notable projects on language endangerment and Galton’s problem in cross-cultural studies. Broad research themes: evolutionary biology, cultural evolution, macroecology, linguistics Key contributions: interdisciplinary funding disparities, language evolution models, parasite-culture interactions Recent articles emphasize language endangerment risk factors, methodological innovations in cross-cultural analysis, and population size effects on language evolution. Awards include Eureka Prize Finalist (2021) and media recognition in Nature and New Scientist . Supervises students in evolutionary and linguistic research.
Swiss Federal Institute of Technology in LausanneSwitzerland
Nicolas Thomä is a Full Professor and head of the Thomä Lab at the École Polytechnique Fédérale de Lausanne (EPFL), where he holds the Paternot Chair in Cancer Research. He is affiliated with the School of Life Sciences (SV) and the Institute of Chemical and Biological Technology (ISREC), leading the UPTHOMAE research unit. His work bridges structural biology, chemical biology, and cancer research, with a focus on transcriptional regulation and targeted protein degradation. His research interests center on chromatin biology and the molecular mechanisms by which transcription factors access gene promoters within chromatin. He investigates how multi-protein complexes regulate gene expression, particularly focusing on the role of E3 ubiquitin ligases and molecular glues in targeted protein degradation. His lab combines structural techniques (including cryo-EM), biochemical assays, and functional genomics to unravel how small molecules can rewire protein interactions and induce degradation of disease-relevant proteins, especially transcription factors involved in cancer. The recent publications of his lab demonstrate a strong trajectory in understanding the structural basis of transcription factor binding to nucleosomes (e.g., OCT4-SOX2, MYC-MAX, CLOCK-BMAL1) and the mechanism of action of molecular glues like thalidomide. These studies highlight a shift toward therapeutic innovation through chemical biology, aiming to develop novel strategies for targeting 'undruggable' proteins in human diseases. Scientific Awards No specific awards listed in the provided text. Advising and Grants Thomä actively supervises a team of PhD students and postdoctoral researchers, including David Domjan, Laurin Tim Kanis, Alessandro Minafra, and Pierre Alexander Miranda Herrera. His lab is supported by institutional funding from EPFL and likely external grants related to cancer research, structural biology, and chemical biology, though specific grants are not mentioned. The lab’s interdisciplinary approach suggests collaboration with pharmaceutical and biotech partners. Labs and Teams The Thomä Lab, based at EPFL’s SV building, includes a multidisciplinary team of scientists, technical specialists, and administrative support. Key members include Fiona Bello (Technical Specialist), Regina Baur, Alexandra Bendel, Manuel Carminati, and others. The lab is structured around two main research pillars: Transcription Factors in Chromatin Biology and Ubiquitin Biology and Molecular Glues, reflecting its dual focus on fundamental mechanisms and therapeutic applications.
