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Dima ArinkinView profile

Professor

• Algebraic Geometry
• Geometric Langlands Program
• Moduli Spaces
• +3 more

Dima Arinkin is a Professor in the Department of Mathematics at the University of Wisconsin–Madison, specializing in algebraic geometry with significant contributions to geometric representation theory and mathematical physics. His research focuses on: Geometric Langlands Program: Developing frameworks connecting automorphic forms and Galois representations through geometric methods Moduli Spaces: Analyzing spaces of algebraic connections, Higgs bundles, and their compactifications D-modules: Studying systems of linear differential equations via algebraic geometry Integrable Systems: Investigating geometric structures in soliton theory and Painlevé equations Irregular Singularities: Exploring connections with irregular behavior on algebraic curves Analysis of his publications (2008-2016) reveals consistent advancement in geometric Langlands through derived algebraic geometry techniques, particularly in relating singular support of sheaves to automorphic forms and establishing oper structures for connections. No scientific awards are documented in the provided materials. No information regarding student advisement or research grants appears in the source texts.

Dond Asha KisanView profile

Assistant Professor

• Numerical Analysis
• Computational Mathematics
• Finite Element Methods
• +4 more

Dond Asha Kisan is an Assistant Professor at the School of Mathematics , Indian Institute of Science Education and Research Thiruvananthapuram (IISER TVM). His research focuses on numerical analysis and computational mathematics , particularly in finite element methods for partial differential equations. He can be contacted at ashadond@iisertvm.ac.in or via phone at +91 (0)471-2778247. PhD : Mathematics, Indian Institute of Technology Bombay M.Sc. : Mathematics, K.T.H.M. College, Nashik Kisan's research spans adaptive finite element methods , stabilized formulations for convection-diffusion problems , and optimal control governed by Stokes equations . His work includes convergence analysis, nonconforming discretizations, and hybrid numerical schemes. Recent publications (2023-2025) address stochastic modeling in liquid crystal physics, advanced WENO schemes, and adaptive algorithms for control problems. Scientific Awards : No explicit awards mentioned in the data, though he held prestigious postdoctoral fellowships including National Post-Doctoral Fellowship and NBHM Post-Doctoral Fellowship. Kisan has extensive teaching experience , including MATLAB workshops and undergraduate course assistantships. He has presented at major international conferences like ICIAM and Hyperbolic Problems, demonstrating global engagement in computational mathematics.

Nigel ShadboltView profile

Professor

• Artificial Intelligence
• Web Science
• Open Data
• +7 more

Professor Sir Nigel Shadbolt is Principal of Jesus College Oxford and Professor of Computing Science at the University of Oxford. He is Chairman and Co-founder of the Open Data Institute which he established with Sir Tim Berners-Lee. His career spans multiple prestigious institutions including the University of Southampton and University of Nottingham, where he held leadership roles in AI research. He has served in significant government advisory positions including as Information Advisor to the UK Prime Minister and member of the Public Sector Transparency Board. Nigel Shadbolt earned his undergraduate degree in Philosophy and Psychology from the University of Newcastle (1st Class Honours, 1978) followed by a PhD in Artificial Intelligence from the University of Edinburgh. His academic journey includes positions as the Allan Standen Professor of Intelligent Systems at Nottingham and leadership of the Web and Internet Science Group at Southampton before joining Oxford. Shadbolt's research spans the interdisciplinary field of Web Science, which he helped originate, focusing on human-centered AI, social machines, open data, and ethical considerations in technology. His work examines how humans and computers integrate at web scale to create novel applications, with recent emphasis on children's digital autonomy and privacy. He has published over 500 articles exploring topics from cognitive psychology to computational neuroscience, Artificial Intelligence to the Semantic Web. His notable contributions include the development of data.gov.uk and leadership in establishing Oxford's Institute of Ethics in AI. His 2018 book 'The Digital Ape: how to live (in peace) with smart machines' has been described as a 'landmark book' in the field. Knighted in 2013 for services to science and engineering Fellow of The Royal Society (FRS) Fellow of the Royal Academy of Engineering (FREng) Fellow of the British Computer Society (FBCS) Technology Pioneer status by the Davos World Economic Forum UK national BT Flagship IT Award As an advisor, Shadbolt has supervised numerous PhD students who have gone on to positions at Google DeepMind, the World Bank, and other prestigious institutions. His research has been supported by multiple grants including SOCIAM, KOALA, and ReTiPS projects. He co-founded Garlik Ltd, which was acquired by Experian, demonstrating his commitment to translating research into practical applications that benefit society. Shadbolt leads the Web and Internet Science research group at Oxford, focusing on social machines - applications that succeed at web scale by integrating humans and computers in novel ways. His work on the KOALA Hero Toolkit and CHAITok system addresses critical challenges in children's data autonomy on social media platforms, reflecting his commitment to ethical technology design.

• Computer Networking
• Internet Security
• Network Measurement
• +3 more

Paul Barford serves as Department Chair and Carl de Boor Professor in the Computer Sciences Department at the University of Wisconsin-Madison, where he founded and directs the Wisconsin Advanced Internet Laboratory and participates in the networking research group. Education B.S. in Electrical Engineering, University of Illinois Ph.D. in Computer Science, Boston University Research Focus : His work centers on computer networking and communications , emphasizing Internet data measurement, protocol analysis, and topological structure. He extensively investigates Internet security domains including fraud detection, traffic anomaly identification, malicious attack analysis, and intrusion systems—bridging theoretical frameworks with real-world security challenges. Research Support : Funded by NSF, DHS, ARO, Cisco, and Intel, his projects drive innovation in network infrastructure security and measurement methodologies. Awards & Honors EPSRC Visiting Fellowship Professional Leadership : Served as Program Committee Chair for ACM SIGCOMM (2013), ACM SIGMETRICS (2010), and ACM IMC (2006). Held board positions at National Lambdarail, editorial roles at IEEE/ACM Transactions on Networking, and co-chaired the GENI Instrumentation and Measurement Working Group. Prior industry experience includes founding Nemean Networks (acquired by Qualys) and Mdotlabs (acquired by comScore), where he served as Chief Scientist.

Anne H Schistad SolbergView profile

Professor

• Machine Learning
• Deep Learning
• Image Analysis
• +6 more

Anne H Schistad Solberg is a Professor in the Department of Informatics at the University of Oslo's Faculty of Mathematics and Natural Sciences. She leads research in digital signal processing and image analysis, with a focus on machine learning applications across multiple domains. As co-director of SFI Visual Intelligence, she oversees research on interpretable deep learning models, uncertainty quantification, contextual learning, and self-supervised learning approaches. Her research spans medical imaging (particularly cardiovascular ultrasound), environmental monitoring using satellite imagery, and seabed mapping with sonar technology. Professor Solberg's work demonstrates a consistent trajectory from foundational signal processing techniques to cutting-edge deep learning applications. Her recent publications show increasing specialization in medical image analysis, particularly in echocardiography enhancement and cardiac structure segmentation, while maintaining strong contributions to remote sensing and geophysical applications. She teaches several popular courses including IN2070, IN3310, and IN5400 (Machine Learning for Image Analysis), which is noted as the most popular master's/PhD course on deep learning at the University of Oslo. Professor Solberg serves as principal investigator for the Intelligent Cardiovascular Ultrasound Scanner (INCUS) project, collaborating with GE Vingmed Ultrasound to develop AI-enhanced cardiac imaging systems that improve diagnostic accuracy and productivity in echocardiography. Co-director of SFI Visual Intelligence research center Principal Investigator for the INCUS project (Intelligent Cardiovascular Ultrasound Scanner) Member of the Digital Signal Processing and Image Analysis (DSB) research group Member of the Strategic Research Initiative: Multimodal Medical Imaging and Image Analysis (MEDIMA) Her research group develops algorithms that address real-world challenges in medical diagnostics and environmental monitoring, with a particular emphasis on making deep learning models more interpretable and reliable for critical applications. The INCUS project, funded through User-driven Research-based Innovation (BIA), aims to reduce the time wasted during cardiac ultrasound examinations by implementing intelligent algorithms that learn from expert users and historical data.

Michael KlasenView profile

Professor

• Particle Physics
• Quantum Chromodynamics
• Physics beyond the Standard Model
• +3 more

Prof. Dr. Michael Klasen is a leading theoretical physicist at the Institute of Theoretical Physics at the University of Münster, where he heads his eponymous research group. His work bridges nuclear and particle physics, with significant contributions to quantum chromodynamics and physics beyond the Standard Model. His research focuses on Particle Physics , Quantum Chromodynamics , and Physics beyond the Standard Model , with particular emphasis on understanding the quark-gluon structure of atomic nuclei and dark matter phenomena. His innovative approach connects microscopic quark-gluon dynamics with nuclear binding phenomena, creating a crucial bridge between nuclear and particle physics. Prof. Klasen's recent work analyzing nucleon binding at the quark-gluon level was recognized as a "Breakthrough of the Year 2024" by Physics World. His research group's publication in Physical Review Letters demonstrated how quarks and gluons behave differently in nucleon pairs than in free nucleons, fundamentally advancing our understanding of nuclear binding. Breakthrough of the Year 2024 from Physics World Leadership of Research Training Group 2149 "Strong and weak interactions - from hadrons to dark matter" Supervision of award-winning doctoral research including the Infineon Dissertation Prize 2025 Prof. Klasen has successfully mentored numerous PhD students, with 20 of his group's graduates continuing their academic careers at prestigious institutions including CERN and Stanford University. His research has been supported by major funding bodies including the German Research Foundation (DFG), the Helmholtz Alliance for Astroparticle Physics, and BMBF collaborative research programs. The Klasen working group maintains active collaborations with international research networks including CTEQ, DM@NLO, and RESUMMINO.

• Data-Driven Organizations
• Artificial Intelligence
• Digital Transformation
• +3 more

Javier Zamora is a Professor at IESE Business School , part of the University of Navarra. He holds a Ph.D. in Electrical Engineering from Columbia University and an M.Sc. in Telecommunications Engineering from the Polytechnic University of Catalonia. Education Ph.D., Electrical Engineering, Columbia University M.Sc., Telecommunications Engineering, Polytechnic University of Catalonia PDG, IESE Business School Research Interests : Zamora specializes in digital transformation, focusing on data-driven organizations and artificial intelligence. His work explores how new technologies reshape business models, organizational structures, and leadership strategies. Publications span topics from AI implementation in finance and sports management to cloud computing in crisis scenarios. His research emphasizes practical frameworks like the "Digital Density" concept and tools for assessing digital maturity. Professional Roles : He co-founded Inqbarna (AI-powered mobile solutions) and served as CEO of eNeo Labs (digital home products). Currently, he directs executive programs at IESE, including Digital Transformation: Senior Management Program and Navigating IT Architecture .

• Machine Learning
• Statistics
• Data Science
• +4 more

Lili Zheng is an Assistant Professor in the Department of Statistics at the University of Illinois. Her research focuses on statistical methodology, machine learning, and high-dimensional data analysis with applications in neuroscience and network science. Key areas of expertise include graphical models, stochastic processes, and algorithmic optimization. She collaborates extensively on projects involving functional connectivity analysis, neuronal data imputation, and interpretable machine learning frameworks. Her work bridges statistical theory and computational practice, addressing challenges in model inference, feature importance assessment, and low-rank tensor completion. Notable contributions include techniques for distribution-free inference, spectral clustering in patchwork learning, and Gaussian process parameter estimation using mini-batch stochastic gradient descent. Dr. Zheng's research emphasizes interdisciplinary applications, particularly in neuroimaging (calcium imaging, functional connectivity) and multi-modal data integration. She actively explores statistical challenges in big data contexts, emphasizing robust methodologies for real-world datasets.

Andrew McCallumView profile

Professor

• Machine Learning
• Artificial Intelligence
• Natural Language Processing
• +3 more

Andrew McCallum is a Distinguished Professor and Director of the Center for Data Science at the University of Massachusetts Amherst. He holds a PhD in Computer Science from the University of Rochester (1995) and a BS from Dartmouth College (1989). His research focuses on machine learning, natural language processing, and information extraction, with applications to scientific literature and knowledge base construction. He has pioneered work on conditional random fields and probabilistic databases, and led the development of systems like Rexa, an advanced research paper search engine. Affiliations: Center for Data Science, Center for Intelligent Information Retrieval, Computational Social Science Institute Key Projects: OpenReview.net, Unified Information Extraction, Automated Knowledge Base Construction His work emphasizes extracting actionable knowledge from unstructured text, with contributions to social network analysis, entity resolution, and semi-supervised learning. McCallum has over 300 publications and has received awards including the NSF ITR Grant, IBM Faculty Partnership Awards, and ACM/AAAI Fellowships. He has advised numerous students and served as ICML General Chair (2012). Recent Research Trends: Probabilistic box embeddings, case-based reasoning for knowledge bases, scalable clustering algorithms, and applications in biomedical informatics.

Jay StraderView profile

Professor

• Compact Objects
• Black Holes
• Neutron Stars
• +5 more

Jay Strader is a Professor in the Department of Physics and Astronomy at Michigan State University, where he serves as Graduate Director for the astronomy PhD program and Associate Chair for astronomy. His research focuses on compact objects, particularly black holes and neutron stars in globular clusters, neutron star binaries in Fermi gamma-ray sources, and intermediate-mass black holes. He has received a Packard Fellowship for Science and Engineering and grants from NSF and NASA. His research group includes postdoc Ryan Urquhart, graduate students Thomas Do and Rebecca Kyer, and several undergraduates, with past students like Teresa Panurach (now director of NoVEL Consortium) and Samuel Swihart (NRC fellow at Naval Research Lab). Education: PhD in Astronomy, UC-Santa Cruz/Lick Observatory Awards: Packard Fellowship Collaborations: Member of Rubin Observatory's Stars, Milky Way, and Local Volume science collaboration since 2008 Previous Positions: Hubble Fellow and Menzel Fellow at Harvard-Smithsonian Center for Astrophysics (2007-2012) Program Initiatives: Co-founder of PAREDS program for early research opportunities at MSU His work has been supported by NSF and NASA grants, and he has contributed to studies on black holes in M22, hypervelocity globular clusters around M87, and transitional millisecond pulsars. His group collaborates with Laura Chomiuk and contributes to data catalogs like the M31 globular cluster velocity dispersion database.

Mark HoggardView profile

Research Fellow

• Geodynamics
• Sea-Level Modelling
• Nuclear Test Monitoring
• +3 more

Dr. Mark Hoggard is an ARC DECRA Research Fellow at the Research School of Earth Sciences, The Australian National University (ANU). His research focuses on geodynamics, sea-level modelling, nuclear test monitoring, and critical mineral systems. He holds a PhD from ANU and has studied at institutions including Cambridge University, Harvard, and Columbia. Hoggard’s work integrates geophysical data with numerical modelling to explore Earth’s dynamic processes, including mantle convection, glacial isostatic adjustment, and lithospheric evolution. Affiliations: Research School of Earth Sciences (ANU), Geoscience Australia (collaborative projects). Education: PhD (ANU), MA (Cambridge), BSc (ANU). Research Interests: Dynamic topography and its influence on sea-level records. Mantle structure and its relationship to mineral systems. Glacial cycles and ice sheet dynamics. Seismic monitoring of underground nuclear tests. Recent Article Trends: Recent work emphasizes geodynamic corrections to Pliocene sea-level estimates, mantle rheology influences on ice sheet models, and statistical methods for distinguishing seismic events from explosions. Key themes include linking deep Earth processes to surface observations and advancing methods for critical mineral exploration. Grants & Projects: Leads projects such as CoastRI GIA Modelling (2024–2027) and Next Generation Sea-Level Modelling (2022–2025). Collaborates with institutions like Los Alamos National Laboratory on nuclear test detection algorithms. Labs/Teams: Part of ANU’s Geodynamics group and the Exploring for the Future program at Geoscience Australia, focusing on Australia’s crustal structure and mineral potential.

Soroosh ShafieeView profile

Assistant Professor

• Optimization under Uncertainty
• Robust Optimization
• Optimal Transport
• +3 more

Soroosh Shafiee is an Assistant Professor in the School of Operations Research and Information Engineering at Cornell University since July 2023. Before joining Cornell, he held postdoctoral positions at the Tepper School of Business (Carnegie Mellon University) and the Automatic Control Laboratory (ETH Zurich). He earned a B.Sc. and M.Sc. in Electrical Engineering from the University of Tehran and a Ph.D. in Operations Research from École Polytechnique Fédérale de Lausanne (EPFL). His research focuses on optimization under uncertainty, robust optimization, optimal transport, and their applications in machine learning and finance. Specific interests include designing algorithms for data-driven optimization, analyzing statistical and computational complexity, and exploring nonconvex optimization structures. Swiss National Science Foundation Early PostDoc Mobility Fellowship (2020) PhD Thesis Distinction Award, EPFL (2020) His work bridges theoretical foundations with practical applications, contributing to areas such as distributionally robust optimization, Wasserstein-based methods, and scalable algorithm development. His research has been published in top venues like Journal of Machine Learning Research and Operations Research .

Samer FarajView profile

Professor

• Health Management
• Healthcare Collaboration
• Innovation Management
• +6 more

Samer Faraj is a Professor and Canada Research Chair in Technology, Innovation & Organizing at McGill University's Desautels Faculty of Management. He leads the Research Group on Complex Collaboration and directs the PhD program. His research focuses on healthcare collaboration, innovation, and the impact of emerging technologies on organizations. He holds affiliations with the Department of Social Studies of Medicine and has been a visiting professor at institutions like HEC-Paris and Cambridge University. Faraj earned a BSc from the University of Wisconsin-Milwaukee (1980), an SM in Technology & Policy from MIT (1986), and a PhD in Management from Boston University (1998). His work has been funded by SSHRC, NSF, IBM, and the Quebec government, totaling over CAD $7.4M in grants. His research interests span healthcare collaboration, organizational change, and digital innovation. Notable contributions include studies on robotic surgery coordination, AI's role in organizing, and open-source health IT systems. He has authored over 130 peer-reviewed articles and serves on editorial boards for Organization Science and Information and Organization . Faraj has received prestigious awards like the FNEGE 2018 Prix Académique, AOM Best Paper Awards, and the 2013 Desautels Best Doctoral Advisor Award. His work is highly cited, with 23K+ Google Scholar citations. He advises numerous PhD students and leads interdisciplinary research initiatives, including a focus on postgenomics ecosystems and open science consortia. Current projects include the governance of open science, digital infrastructure development, and AI's implications for strategy and organization. His work bridges academic inquiry with real-world applications, emphasizing the societal and organizational impacts of technological change.

Laia BecaresView profile

Professor

• Social Epidemiology
• Health Inequalities
• Racism and Health
• +3 more

Laia Becares is a Professor of Social Science and Health at King's College London, part of the School of Global Affairs and the Department of Global Health & Social Medicine. She previously held roles at the University of Sussex (2018-2022) and the University of Manchester (2010-2018), where she maintains an Honorary position. She serves as an Editor of Sociology of Health and Illness and on the Academic Reference Group of the NHS Race and Health Observatory. Her work is funded by organizations such as the Nuffield Foundation and the Health Foundation. Laia holds a PhD in Social Epidemiology from University College London (UCL) and a Master's in Public Health from Boston University School of Public Health. Her research employs an interdisciplinary approach, collaborating with sociologists, psychiatrists, geographers, and demographers to understand how discrimination and marginalization perpetuate social and health inequities. Key areas include racism, homophobia/heterosexism, LGBTQ+ inequalities, and the impact of systemic oppression across life stages. She co-developed the Queerantine Study on pandemic impacts on LGBTQ+ communities and leads the ESRC Centre for Society and Mental Health, fostering student mentorship in health inequality topics. Her scientific awards include ESRC/MRC Postdoctoral Research Fellowship (2010-2012), Hallsworth Research Fellowship (2012-2016), and ESRC Future Research Leader Fellowship (2012-2015). Recent work focuses on ethnic healthcare disparities in multimorbidity and longitudinal studies of racism's effects on health outcomes. Ongoing projects include LGBTQ+ policymaking networks and the GHSM Anti Racism Steering Group, addressing structural inequities in academia and healthcare. Laia’s grants include Nuffield Foundation funding for ethnic inequalities in later life and Health Foundation support for healthcare equity studies. She advocates for integrating lived experiences into research design, particularly through the Evidence for Equality National Survey (EVENS). Her lab affiliations include Queer@King’s and the ESRC Centre for Society and Mental Health, emphasizing collaborative, community-driven approaches.

Robert ÖstlingView profile

Professor

• Applied Microeconomics
• Behavioral Economics
• Political Economy
• +4 more

Robert Östling is a Professor of Economics at the Stockholm School of Economics (SSE), affiliated with the Department of Economics and the Karl-Adam Bonnier Center for Governance within the House of Governance and Public Policy. He holds a PhD from SSE (2008) and previously worked at Stockholm University's Institute for International Economic Studies until 2018. His research focuses on applied microeconomics and behavioral economics, particularly examining how wealth impacts attitudes, behavior, and life outcomes using Swedish lottery data. He teaches econometrics, behavioral economics, and economics for MBA students, and serves as program director for SSE's MSc in Economics. Key roles include board membership of the Swedish Economics Association and the Expert Group on Public Economics (ESO), and membership in the scientific advisory board of the Swedish Consumer Protection Agency. He co-founded the popular economics blog Ekonomistas , recognized as 'Swede of the Year' in 2017. Awards include the Assar Lindbeck Medal (2021) and the Arnberg Prize (2009). His research spans wealth effects on labor supply, health, child development, and political behavior. Notable projects include studying lottery winners' long-term well-being and portfolio decisions. Teaching innovations include using animated GIFs for econometrics instruction. He has contributed to policy debates on economic reforms, consumer protection, and pandemic responses. Outreach activities include public writing and policy advisory roles. His research has been featured in outlets like the New York Times and Swedish media. He remains active in academic networks, including the Network for Evidence-Based Policy.