Find Academic Supervisors

• Higher Education Didactics
• Mathematics Education
• Digital Learning Tools
• +3 more

Eva Glasmachers is a Lecturer and Managing Director of the Faculty of Mathematics at Ruhr University Bochum. She holds a PhD in Differential Geometry (2010) and has been actively involved in academic leadership since 2008. Her roles include student advising, curriculum development, and managing faculty operations. Her research focuses on university-level mathematics education, emphasizing interactive teaching methods, digital learning tools (e.g., STACK), and student motivation strategies. She leads projects like VORsprung for digital study preparation and trains tutorial group instructors. She is a founding member of HDM@RUB (Center for Higher Mathematics Education) and serves on the Ruhr University Senate and the Excellence Network for Teaching. Notable publications include works on gamification in education, adaptive learning systems, and dropout prevention strategies. She collaborates extensively with educational technology centers and contributes to national didactics conferences.

• Cyber-Physical Systems
• Internet of Things (IoT) Security
• Computer Architecture
• +5 more

Hokeun Kim is an Assistant Professor in the School of Computing and Augmented Intelligence (SCAI) at Arizona State University (ASU), part of the Ira A. Fulton Schools of Engineering. He previously held positions at Hanyang University (2021-2023) and worked in industry roles at Google, LinkedIn, and HP Labs. His research focuses on cyber-physical systems, IoT security, and computer architecture, with a particular emphasis on safety and security aspects of time-sensitive systems. Education: Ph.D. in EECS, University of California, Berkeley (2017) M.S. in EECS, Seoul National University (2012) B.S. in Computer Science and Engineering, Seoul National University (2010) Research Interests: Kim’s work spans secure IoT frameworks, real-time embedded systems, and edge computing. He develops tools like the Secure Swarm Toolkit (SST) and Lingua Franca, addressing challenges in distributed system security, interoperability, and performance. Key Contributions: Authored over 30 peer-reviewed publications in top venues like IEEE Transactions, ACM Conferences, and DATE. Received the ACM/IEEE Best Paper Award (IoTDI 2017) and IEEE Micro Top Picks Honorable Mention (2017). Active in organizing conferences (e.g., DATE, FDL) and serves on technical committees for top journals/conferences. Teaching: Courses include Computer Architecture I/II, Real-Time Embedded Systems, and IoT design at both undergraduate and graduate levels.

Alexandros TaflanidisView profile

Professor

• Uncertainty Quantification
• Disaster Risk Reduction
• Bayesian Model Updating
• +3 more

Professor Alexandros Taflanidis holds a concurrent faculty position as Professor in the Department of Civil and Environmental Engineering and Earth Sciences and the Department of Aerospace and Mechanical Engineering at the University of Notre Dame's College of Engineering. He serves as the Director of Graduate Studies for CEEES. His research focuses on uncertainty quantification, disaster risk reduction, Bayesian model updating, and enhancing the sustainability and resilience of civil infrastructure systems, particularly in natural hazard contexts like hurricanes and earthquakes. His work integrates computational statistics and surrogate modeling to improve real-time emergency response and long-term risk mitigation strategies. Prof. Taflanidis earned a Ph.D. from the California Institute of Technology (2007), and M.S. and B.S. degrees in Civil and Environmental Engineering from Aristotle University of Thessaloniki (2003 and 2002). He leads projects such as the Coastal Hazards System (CHS) for Louisiana and Puerto Rico, advancing probabilistic coastal hazard analysis frameworks. His research also explores storm surge emulation, seismic response estimation, and innovative protective device designs for structures. He won the ASCE Huber Prize for his contributions to community resilience through scientific computing. His collaborative efforts include advancing machine learning for data imputation in coastal hazards and developing lifecycle assessment workflows for resilient buildings. Current research trends in his publications emphasize computational efficiency, multi-fidelity modeling, and adaptive strategies for real-time predictions. Prof. Taflanidis's work bridges academic and practical domains, addressing challenges such as climate change impacts on coastal regions and earthquake early warning systems. His lab focuses on integrating interdisciplinary approaches to create actionable solutions for infrastructure resilience.

Boris ShorView profile

Associate Professor

• Political Science
• State Legislatures
• Political Polarization
• +7 more

Boris Shor is an Associate Professor of Political Science at the Hobby School of Public Affairs, University of Houston, where he conducts research on state legislatures, political polarization, representation, and health policy. He is associated with multiple interdisciplinary initiatives and contributes to major data infrastructure in political science. Education: Ph.D. and M.A. in Political Science, Columbia University B.A., Princeton University Shor specializes in American politics with a focus on legislative behavior, ideological measurement, and health policy. His work combines quantitative methods, roll call analysis, and survey data to understand polarization and representation across U.S. states. He has developed one of the most comprehensive datasets on state legislative ideology, influencing both academic research and policy analysis. His recent publications span top journals such as American Political Science Review , American Journal of Political Science , and Political Analysis , with a thematic focus on state-level political dynamics, methodological innovation, and health policy politics. The research consistently explores how partisanship, ideology, and institutional structures shape policy outcomes. Scientific Awards and Honors: Robert Wood Johnson Scholar in Health Policy, UC Berkeley Fellow, Center for the Study of Democratic Politics, Princeton University Shor has secured major external funding from the National Science Foundation and the Russell Sage Foundation . He has advised undergraduate, master’s, and doctoral students throughout his career. His ongoing book project examines the politics of health policy in the American states, building on his interdisciplinary background in political science and public health. He is affiliated with research centers focused on democratic governance and public policy, contributing to collaborative academic networks across institutions.

Carly WatsonView profile

Lecturer

• Eighteenth-Century Poetry
• Print Culture
• Book History
• +3 more

Dr Carly Watson is a Lecturer at the Department for Continuing Education and the Faculty of English at the University of Oxford. She directs the MSt in Literature and Arts (MLA) and the DPhil in Literature and Arts (DLA), while teaching graduate courses in bibliography, book history, and scholarly editing. PhD in English from the University of Birmingham (2014) MA and BA in English from Oxford University Her research focuses on late seventeenth- and eighteenth-century poetry, print culture, book history, and digital humanities. She specializes in the role of poetry in the literary marketplace and the intersection of material texts with cultural, societal, and technological developments. Carly’s publications leverage data from the Digital Miscellanies Index , a database she managed postdoctoral research for, to analyze trends in miscellany publishing. Her forthcoming monograph, Miscellanies, Poetry, and Authorship, 1680-1800 , redefines the miscellany form by challenging modern author-centric approaches. Notable scientific awards include the Balliol-Bodley Scholarship (2010) for archival research. Her collaborative projects include workshops at Thomas Bewick’s birthplace, funded by the Novel Impressions network (led by Dr Helen Williams). Carly’s teaching spans eighteenth-century literature, manuscript/print culture, and graduate-level bibliography courses. She integrates material texts from English Faculty libraries into classroom instruction and offers an optional course on editing practices.

• Databases
• Spatial Data Management
• Geospatial Systems
• +3 more

Mohamed Sarwat is an Associate Professor at Arizona State University specializing in databases , spatial data management , and recommender systems . His research focuses on GeoSpark —a cluster computing framework for spatial data—and its extensions like GeoSparkViz for visualization and GeoSparkSim for traffic simulation. Key Contributions: LARS* (Location-Aware Recommender System), Horton* (Graph Reachability), Sindbad (GeoSocial Platform), and Riso-Tree (Graph Database Indexing) Research Themes: Integration of spatial/temporal data with machine learning, efficient indexing for big geospatial datasets, and scalable frameworks for mobility data science His work spans collaborations with 23+ co-authors across institutions like University of Minnesota, University of Melbourne, and University of Salzburg. Current projects emphasize GeoTorchAI —a spatiotemporal deep learning system—and mobility data science infrastructure.

Nicole A. BenedekView profile

Associate Professor

• Materials Theory
• Computational Materials Science
• Complex Oxides
• +9 more

Nicole A. Benedek is an Associate Professor in the Department of Materials Science and Engineering at Cornell University, part of the College of Engineering. Her research group focuses on theoretical and computational approaches to understanding and designing functional materials, particularly complex oxides and perovskites. She integrates principles of crystal chemistry, symmetry, and density functional theory to uncover mechanisms underlying material properties and to guide the discovery of new materials with targeted functionalities. Her research interests include nonlinear phononics, ultrafast optical control of lattice dynamics, ferroelectricity, magnetism, and thermal transport in materials. She is particularly interested in how materials behave out of equilibrium and how external stimuli such as light can induce dramatic changes in their properties. This work has implications for low-power electronics, data storage, and dynamic optical devices. The recent publications from her group reflect a strong trend in controlling material symmetries and properties using light, especially through infrared and Raman resonant excitation. Her work bridges theory and experiment, often in collaboration with synthetic chemists, to validate predictions and discover new polar and multiferroic materials. She has made key contributions to understanding negative thermal expansion, light-induced phase transitions, and hybrid improper ferroelectricity. Scientific Awards: NSF CAREER Award, National Science Foundation (2015) Ralph E. Powe Junior Faculty Enhancement Award (2014) Journal of Materials Chemistry Emerging Investigator (2016) Australian Postgraduate Award (2003) Dr. Benedek advises graduate students in materials science and engineering and has mentored PhD candidates such as Ethan T. Ritz and Tucker Swenson. Her research is supported by the National Science Foundation (including the MRSEC program), the Department of Energy, and the Cornell Center for Materials Research. She leads the Benedek Group, which develops theoretical frameworks to explain and predict material behavior, emphasizing design rules for next-generation functional materials. The Benedek Group collaborates extensively with experimentalists, notably with Michael A. Hayward at Oxford University, to synthesize and characterize predicted materials. Their joint work has led to the discovery of new ferroelectric Dion-Jacobson phases and a deeper understanding of polar distortions in layered perovskites. The group combines computational modeling with physical insight to push the boundaries of materials design.

Hannu HyyppäView profile

Researcher

• Laser Scanning
• 3D Modeling
• Geoinformatics
• +5 more

Hannu Hyyppä is a Research Director and Project Employee at Aalto University's Department of Built Environment, affiliated with the MeMo research group. He leads the Research Institute of Measuring and Modelling for the Built Environment, focusing on advanced laser scanning, 3D modeling, and geoinformatics. His work spans interdisciplinary collaborations across engineering, geography, and arts, with a strong emphasis on applications in cultural heritage preservation, urban planning, and environmental monitoring. Education: Doctoral degree (D.Sc.) in Engineering and Technology, Helsinki University of Technology (2000) Licentiate degree in Engineering and Technology, Helsinki University of Technology (1989) Master's degree in Engineering and Technology, Helsinki University of Technology (1986) Research Interests: Laser scanning technologies, point cloud utilization in forestry and urban mapping, virtual reality for cultural heritage, and sustainable infrastructure modeling. His expertise includes photogrammetry, geographic information systems (GIS), and decision support systems for environmental management. Recent Contributions: Over 550 publications and 30+ active projects, including the Centre of Excellence in Laser Scanning Research (2014-2019) and the Pointcloud project (2015-2021). His work advances applications in autonomous road inspection, 3D cultural reconstructions, and smart city technologies. Awards: Recipient of the 2019 Kansallinen avoimen tieteen palkinto for innovative open science contributions. Grants & Leadership: Principal Investigator for projects like DICA (Digital Cultural Heritage) and ToToRo (Automatic Road Inspection). Active in organizing workshops and international conferences on 3D technologies and laser scanning. Labs/Teams: Oversees the MeMo group and collaborates with national organizations like the Finnish Geospatial Research Institute. Develops tools for real-time 3D mapping and virtual environments.

• Soft Materials
• Quantum Mechanics
• Machine Learning
• +3 more

Professor Nicholas E. Jackson is an Assistant Professor of Chemistry at the University of Illinois, affiliated with the College of Liberal Arts & Sciences and the Beckman Institute for Advanced Science and Technology. He holds the Lincoln Excellence for Assistant Professors Scholar distinction. His research focuses on soft materials, quantum mechanics, and machine learning, particularly in developing coarse-grained electronic structure methods and sustainable polymer design. Education: B.A. in Physics from Wesleyan University (2011), Ph.D. in Chemistry from Northwestern University (2016). Postdoctoral work as a Named Fellow and Assistant Scientist at Argonne National Laboratory (2016–2021). Joined the University of Illinois faculty in 2021. Research interests include conjugated materials theory, electronic structure predictions, and interdisciplinary applications of machine learning in materials science. His work bridges computational chemistry, materials engineering, and AI, addressing challenges in renewable energy and sustainable materials. Recent recognition: 2025 Kavli Foundation Emerging Leader in Chemistry Award for innovative research in young scientists under 40. His contributions to AI-driven materials design and thermoset fracture modeling have been highlighted in peer-reviewed journals. Advances include novel approaches to polymer reactivity prediction, molecular-level understanding of conjugated polymers, and machine learning workflows for molten salt mixtures. His lab collaborates across disciplines to advance soft materials design and computational tools for chemistry.

Jure LeskovecView profile

Professor

• Machine Learning
• Social Networks
• Data Mining
• +4 more

Jure Leskovec is a Professor of Computer Science at Stanford University, affiliated with the Stanford AI Lab, Machine Learning Group, and the Center for Research on Foundation Models. He holds academic appointments in the Department of Computer Science and is a member of Bio-X, the Institute for Human-Centered Artificial Intelligence (HAI), and the Wu Tsai Neurosciences Institute. Leskovec earned his BSc from the University of Ljubljana (2004), PhD from Carnegie Mellon University (2008), and postdoctoral training at Cornell University. His research focuses on social networks, data mining, machine learning, and computational biomedicine, with contributions to graph neural networks, drug discovery, and AI applications in healthcare. His work has been applied to combat the COVID-19 pandemic and integrated into products at major tech companies. Leskovec’s publications reflect his expertise in network analysis, medical AI, and biological systems. His recent work includes foundational contributions to graph neural networks (e.g., PyG) and medical AI frameworks. His research has garnered numerous awards, including the Microsoft Research Faculty Fellowship and ICDM Research Contributions Award. Leskovec advises numerous doctoral and postdoctoral researchers, contributing to over 200 publications. His interdisciplinary collaborations span computational biology, healthcare analytics, and social systems, with a focus on leveraging AI to address real-world challenges.

Bridget RyanView profile

Associate Professor

• Primary Care
• Patient-Centered Care
• Virtual Care
• +4 more

Bridget Ryan is an Associate Professor in the Departments of Family Medicine and Epidemiology and Biostatistics at Western University and an Adjunct ICES Scientist. Her research program centers on patient-centred primary care, with a focus on multimorbidity, patient engagement in health care, and the integration of technology (especially virtual care). She is particularly interested in compassionate virtual care delivery and co-designing care models with patients and family physicians. Dr. Ryan has received notable recognition including: Fellowship in Compassion and Artificial Intelligence from the AMS Healthcare Group She currently leads two major CIHR-funded projects: As Principal Investigator: Co-creating a Virtual and In-Person Primary Care (VIP-PC) model with patients and family physicians As Co-Principal Investigator: Developing primary-care-based tools to support discussions about social isolation Additionally, she co-leads DELPHI, a research database built from de-identified primary electronic medical records from practices in southwestern Ontario, enabling innovative primary care research through real-world clinical data.

• Global Governance
• International Institutions
• Political Theory
• +6 more

Prof. Dr. Michael Zürn is Director of the Global Governance Department at the WZB Berlin Social Science Center and Professor of International Relations at Free University Berlin since 2004. He leads the DFG-funded Cluster of Excellence ‘Contestations of the Liberal Script’ (SCRIPTS) and contributes to debates on democratic regression, authoritarian populism, and global governance legitimacy. Education: Doctorate from the University of Tübingen (1991, ‘summa cum laude’), thesis: Game Theory, Functionalism, and International Politics . Research Interests span global governance, international institutions, political theory, democratic regression, authoritarian populism, and the role of truth in liberal societies. His work analyzes how inequalities, populism, and institutional design challenge liberal democracy. Publications focus on global governance theory, legitimacy crises, and the interplay between authoritarianism and democratic norms. Recent articles examine the 2025 German elections, FIFA’s ‘sportswashing’ impact, and the erosion of democratic rationality. Scientific Awards: Berlin Science Award (2021) Grants & Projects include DFG funding for SCRIPTS cluster studies and EU Horizon 2020 support for GLOBE. He co-founded the Berlin Graduate School for Transnational Studies and the International Authority Database.

Elena TuzhilinaView profile

Assistant Professor

• Machine Learning
• Applied Statistics
• Computational Biology
• +5 more

Elena Tuzhilina is an Assistant Professor in the Department of Statistical Sciences at the University of Toronto, specializing in machine learning, applied statistics, and computational biology. Her research focuses on statistical tools for chromatin 3D spatial structure reconstruction and analyzing emotional disorders' impact on brain function. Ph.D. in Statistics from Stanford University Specialist's degree from Moscow State University Two-year Data Science program at Yandex School Her research spans high-dimensional data analysis , dimension reduction , and statistical modeling in biological contexts. She has developed novel algorithms for chromatin conformation reconstruction and pandemic trajectory modeling. Recent publications focus on canonical correlation analysis , low-rank matrix approximation , and 3D genome architecture , with applications in computational biology and neuroscience. Dorothy Shoichet Women Faculty in Science Award JSM Student Travel Award Outstanding Teaching Assistance at Stanford Stanford Teaching Assistant Award Elena supervises PhD students and postdoctoral fellows across disciplines including statistical sciences, biochemistry, and applied mathematics. She has secured multiple grants including a NSERC Discovery Grant and University of Toronto Accelerator Grant .

Johannes SoedingView profile

Researcher

• Computational Biology
• Bioinformatics
• Protein Structure Prediction
• +9 more

Johannes Soeding is a Research Group Leader in the Computational Biology department at the Max Planck Institute for Multidisciplinary Sciences in Göttingen, Germany. His work bridges physics, bioinformatics, and molecular biology, focusing on computational methods for biological data analysis. His research interests include computational biology, protein structure and function prediction, metagenomics, transcriptional regulation, and statistical genomics. He develops widely used software tools such as HH-suite, HHpred, MMseqs2, and Foldseek for protein sequence and structure analysis. The recent publications demonstrate a strong focus on high-throughput biological data, particularly in protein structure search (e.g., Foldseek), metagenomic gene discovery (e.g., MetaEuk), and regulatory genomics. His work combines algorithm development with deep biological insights, often published in top-tier journals like Nature Biotechnology , Science , and Nature Methods . He has been involved in significant methodological advances in sequence clustering, contact prediction, and eQTL analysis, showing a consistent trend toward scalable, data-driven approaches in genomics and proteomics. Soeding has contributed to major projects in gene regulatory networks and RNA biology, often in collaboration with experimental groups. His leadership in developing open, efficient bioinformatics tools has had a broad impact on the scientific community. He is affiliated with several graduate programs including IMPRS Physics of Biological and Complex Systems, Biomolecules: Structure - Function - Dynamics, and Genome Science, indicating active participation in training the next generation of scientists.

• Database Systems
• Stream Processing
• Distributed Data Management
• +5 more

Volker Markl is a Professor at Technische Universität Berlin in the Institute of Software Engineering and Theoretical Computer Science, with additional affiliations at the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and the German Research Center for Artificial Intelligence (DFKI). His research spans database systems, stream processing, and distributed data management with significant contributions to both theoretical foundations and practical implementations. Markl's research interests focus on next-generation data management systems, particularly for streaming and IoT environments. His work addresses critical challenges in distributed query processing, system integration, and performance optimization. He has pioneered approaches for stream processing in volatile infrastructures and developed innovative techniques for GPU-accelerated database operations. His NebulaStream project represents a major contribution to distributed stream processing systems. His publication record demonstrates consistent impact across top database venues including VLDB, SIGMOD, and ICDE. Recent work shows increasing focus on machine learning integration with database systems, privacy-preserving query processing, and educational approaches for teaching large-scale data management. Markl has mentored numerous researchers who have become prominent in the database community, with frequent collaborators including Steffen Zeuch, Tilmann Rabl, and Philipp Grulich. His leadership extends to major research initiatives and collaborations across European institutions.