Find Academic Supervisors

Ted McCormickView profile

Professor

• Early Modern History
• Intellectual History
• History of Science
• +3 more

Ted McCormick is Professor of History at Concordia University's School of Irish Studies, specializing in early modern British/Irish/Atlantic history and the history of science. His award-winning research explores demographic thought, colonial governance, and scientific projects in the 17th-18th century Atlantic world. McCormick holds a PhD from Columbia University and has held fellowships at the Huntington Library, University of Sydney, and Irish research institutions. His research examines how scientific knowledge and economic thought shaped colonial policies, population management, and technological projects. Current work focuses on mechanical inventions in colonial contexts through his SSHRC-funded project 'Engines of Division'. Recent publications analyze food systems, projecting cultures, and knowledge-power relationships in early modernity. McCormick teaches courses on early modern Britain/Ireland, scientific revolution, and Enlightenment thought. He mentors graduate researchers studying colonial knowledge systems, scientific networks, and cross-cultural encounters. Honors include two John Ben Snow Prizes for monographs on political arithmetic and demographic thought.

Liane ColonnaView profile

Assistant Professor

• AI Ethics
• Data Protection Law
• Algorithmic Regulation
• +2 more

Liane Colonna is an Assistant Professor in Law and Information Technology at the Department of Law, Stockholm University , where she investigates ethical and legal challenges arising from AI-driven practices in higher education. She also engages in methodologically oriented research at the intersection of AI and Law, contributing to the Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society. Additionally, Liane serves as the director of the Swedish Law and Informatics Research Institute (IRI) and is a member of the New York Bar since 2008. Primary Affiliation: Department of Law, Stockholm University Institute Leadership: Director, Swedish Law and Informatics Research Institute (IRI) Professional Status: Member of the New York Bar Research Interests: Ethical and legal challenges of AI in higher education Methodological approaches in AI and Law Data protection and privacy by design Regulatory frameworks for AI and emerging technologies Privacy implications of lifelogging and health IoT International data governance and surveillance law Publications demonstrate expertise in AI regulation, GDPR compliance, and privacy-preserving technologies, particularly for assisted living and educational contexts. Her work bridges technical implementation with legal accountability, emphasizing human oversight and ethical design.

Stefan KlusView profile

Lecturer

• Data-driven model reduction
• Transfer operator approximation
• Machine learning
• +8 more

Dr. Stefan Klus is a Lecturer at the School of Mathematics and Physics, University of Surrey. His research focuses on data-driven model reduction, transfer operator approximation, and kernel-based machine learning applied to dynamical systems. He specializes in interdisciplinary applications across quantum physics, fluid dynamics, and computational biology. Education: PhD in Industrial Mathematics (2011, Paderborn University) and Habilitation (2020, Freie Universität Berlin). Research Interests : Data-driven modeling and reduced-order methods Koopman operator theory and transfer operators Machine learning for dynamical systems (e.g., Deeptime library) Tensor decompositions and quantum systems analysis Graph-based analysis (e.g., microbiome dynamics) Publications : Klus has contributed to over 50 peer-reviewed articles, with recent work emphasizing: Kernel methods for quantum chemistry and physics Tensor-based approaches for high-dimensional systems Applications in climate science (e.g., Pacific SST modeling) Agent-based modeling and social systems Technical Contributions : Co-developer of the Deeptime Python library for dynamical modeling Pioneer in Koopman operator-based model reduction Advanced graph kernel methods for microbiome analysis

• Artificial Intelligence
• Machine Learning
• Medical Technology
• +7 more

Anis Yazidi is a Professor at Oslo Metropolitan University, affiliated with the Faculty of Technology, Art and Design and the Department of Information Technology. His research focuses on Artificial Intelligence, Machine Learning, Medical Technology, and IoT Security, with a particular emphasis on Applications of AI in Healthcare, EEG Signal Processing, and Digital Transformation. Active research projects include AI Mind (dementia diagnostics), Glycopathology in dry eyes, and Pain and mental distress analysis Completed projects: Digital hate speech analysis, AI in reproductive technology, Nano-antibiotics development His recent publications (2023-2025) demonstrate expertise in: Tsetlin Automaton algorithms for concept learning EEG classification using visibility graphs and vision transformers AI ethics frameworks for medical practice Deepfake detection methodologies Collaborative work spans institutions in Norway, Czech Republic, and international AI research communities.

Paula SchneiderView profile

Academic

• Bookbinding
• Book Art
• Narrative Literature
• +4 more

Paula Schneider serves as Teacher for Special Tasks at the University of Art and Design Offenbach am Main , heading their book and paper workshop since 2020. She studied Book Art at Burg Giebichenstein Halle (2013-2019) and previously taught at Bezalel Academy (2017-2020). Her work bridges bookbinding , literary experimentation , and archival research through installations, artist books, and public interventions. Education : 2019: Diploma in Book Art, Burg Giebichenstein University of Halle Teaching : 2020–present: Lecturer for special tasks at HfG Offenbach 2017–2020: Annual courses at Bezalel Academy for Arts and Design, Jerusalem Screen printing tutor during studies Her artistic research explores narrative structures , time perception , and memory systems through works like Inner Monologue (2018) and Mio Mnemotop (2021). Recent projects include Night Frost (2024) examining textual accumulation and Cloudburst Working on the Textberg (2024) using mining metaphors for textual analysis. She examines book formats (e.g., leporello, monotypes, screen printing) to interrogate knowledge preservation (Rabaraababaraba, 2015) and urban observation (Praise of the Gate, 2023). Notable exhibitions include Because We Are Young (2021) analyzing GDR industrial history and Between (2019) at Halle/Leipzig Airport, which required mobile audience engagement with audio pieces about airport soundscapes. Her works have been featured in Text3 and Spin n errei tours. Contact: schneider@hfg-offenbach.de | Workshop: +49 69.80059-245 | Office: +49 69.80059-106

• Embedded Systems
• Software Verification and Validation
• Model Checking
• +5 more

Stefan Kowalewski serves as Professor of Embedded Software at RWTH Aachen University, leading the Chair of Embedded Software (Informatik 11) within the Department of Computer Science. His research spans critical domains including medical cyber-physical systems, automotive software, and industrial automation, with over 150 publications demonstrating sustained scholarly impact. Professor Kowalewski's work focuses on three interconnected research pillars: Embedded Systems Verification: Pioneering model checking techniques for PLC code, particularly addressing state space challenges in GRAFCET-based specifications Medical Cyber-Physical Systems: Developing safety-critical software for mechanical ventilation, extracorporeal membrane oxygenation, and ARDS diagnosis systems with strong clinical collaborations Automotive Software: Creating verification frameworks and safety architectures for automated vehicles through projects like UNICARagil Recent publications reveal an increasing integration of AI techniques with traditional verification methods, particularly for medical applications involving neonatal care and critical respiratory support. His 2024-2025 work shows particular emphasis on timing isolation in vehicle communication systems, middleware performance evaluation, and robust AI models for medical diagnosis. Professor Kowalewski maintains active collaborations with RWTH Aachen University Hospital's medical departments and automotive industry partners. His laboratory operates specialized facilities including the Cyber-Physical Mobility Lab for vehicle research and in-vivo testing setups for medical device validation. He has supervised numerous doctoral candidates, with recent students focusing on topics like ARDS classification algorithms, GRAFCET verification techniques, and safety architectures for software-defined vehicles. His educational contributions include developing remote teaching platforms for cyber-physical systems education.

• Marine Microbial Ecology
• Protistan Trophic Relationships
• Harmful Algal Blooms
• +3 more

David Caron is the Captain Allan Hancock Chair in Marine Science and Professor of Biological Sciences at the University of Southern California (USC), affiliated with the USC Dornsife College of Letters, Arts and Sciences. He co-founded the Center for Integrated Networked Aquatic Platforms (CINAPS) and is part of the Wrigley Institute for Environmental Studies. His research focuses on marine and freshwater microbial ecology, particularly protist trophic relationships and harmful algal blooms. Caron holds a Ph.D. from the MIT-Woods Hole Oceanographic Institution Joint Program in Biological Oceanography (1984), an M.S. (1977) and B.S. (1975) in Oceanography and Microbiology from the University of Rhode Island. Research Interests: His work spans protistan ecology, mixotrophic microalgae physiology, Antarctic protist adaptations, and molecular approaches to microbial ecology. He investigates harmful algal bloom dynamics, protist grazing impacts, and the role of environmental drivers in planktonic communities. His studies often integrate field observations, experimental work, and advanced technologies like robotic sampling platforms. Key Achievements: Caron has authored over 100 peer-reviewed publications and pioneered methods in protistan diversity assessment. He received the AAAS Fellowship (2011), American Academy of Microbiology Fellowship (2007), and the USC Raubenheimer Outstanding Senior Faculty Award (2010–2011). He served as President of the International Society of Protistologists (2004–2005). Grants & Labs: He leads CINAPS, which uses autonomous systems to monitor coastal ecosystems. His lab studies microbial communities in the Southern California Bight, focusing on harmful algal toxins (e.g., domoic acid) and their ecological impacts. Collaborations with engineers and roboticists enhance data collection and environmental modeling efforts.

Erika LeeView profile

Professor

• Immigration History
• Asian American History
• Race and Ethnicity
• +6 more

Erika Lee is the Bae Family Professor of History and Radcliffe Alumnae Professor at Harvard University, serving as Director of the Schlesinger Library on the History of Women in America. A past president of the Organization of American Historians, she is a leading scholar of U.S. immigration, Asian American history, and xenophobia across the 19th-21st centuries. Her research centers on immigration history, Asian American history, and the intersections of race, xenophobia, law, gender, and society. Lee examines how systemic racism and exclusionary policies have shaped American identity, with particular focus on Asian American experiences and the historical roots of contemporary anti-immigrant sentiment. Lee's recent publications (2020-2024) analyze xenophobia during crises like the COVID-19 pandemic, anti-Asian discrimination, and immigration policy weaponization. Her work reveals historical patterns connecting past exclusion laws to modern nativist movements while highlighting immigrant resilience and the power of public history. Lee's honors include: American Book Award Asian/Pacific American Award for Literature Andrew Carnegie Fellowship Election to the American Academy of Arts & Sciences Immigrant Heritage Award Pioneer Award from OCA Champion for Justice Award She received the Andrew Carnegie Fellowship for research funding and testified before Congress on anti-Asian discrimination. As a public intellectual, Lee frequently contributes to media discussions on immigration and race through major outlets including the New York Times and CNN. Lee co-founded three digital humanities initiatives: Immigrant Stories (documenting immigrant experiences through digital storytelling), #ImmigrationSyllabus (educational resource on immigration history), and Immigrants in COVID America (tracking pandemic impacts on immigrant communities).

Jieh HsiangView profile

Professor

• Automated Reasoning
• Programming Language Logic
• Artificial Intelligence
• +5 more

Jieh Hsiang is a Distinguished Professor at National Taiwan University , with affiliations in the Department of Computer Science and Information Engineering, the Digital Archives and Automatic Inference Laboratory, and the Digital Humanities Research Center. He holds concurrent roles at the Institute of Information Science, Academia Sinica, and the Higher Education Research & Development Office, National Taiwan University. Education PhD in Computer Science, University of Illinois at Urbana-Champaign (1979–1982) BS in Mathematics, National Taiwan University (1972–1976) Research Interests Hsiang's work spans automated reasoning , digital libraries , digital humanities , and information retrieval . His research focuses on integrating computational methods with cultural heritage preservation , particularly through tools like DocuSky and databases such as the Taiwan Historical Digital Library . He explores AI applications in patent analysis , historical text mining , and semantic relationships in legal documents . Recent Trends in Publications His recent articles highlight advancements in BERT and GPT-2 fine-tuning for patent classification , LARGE language models for legal automation , and GIS-based analysis of historical archives . Themes include digital preservation , AI-driven legal text analysis , and cross-disciplinary computational tools for humanities scholars. Scientific Awards 2019 Ministry of Science and Technology Distinguished Research Fellow 2009 National Taiwan University Outstanding In-House Service Award 2008 Chinese Library Association Special Contribution Award 2006 IEEE Test-of-Time Award 1997 & 1999 National Science Council Outstanding Research Award 1997 Ministry of Education Outstanding Industrial-Academic Collaboration Award 1998–2001 Founder and First Chair of IFIP WG1.6 Labs and Collaborations Hsiang leads the Digital Archive and Automatic Inference Laboratory , developing platforms like DocuSky for digital humanities, Taiwan Historical Digital Library , and QGIS Cloud Maps for spatial analysis. His team collaborates internationally on projects involving historical document digitization , patent automation , and cross-domain knowledge integration .

Katharina EggenspergerView profile

Researcher

• Automated Machine Learning (AutoML)
• Hyperparameter Optimization (HPO)
• Tabular Machine Learning
• +1 more

Katharina Eggensperger is an Early Career Research Group Leader at the University of Tübingen , leading the AutoML for Science group within the Cluster of Excellence Machine Learning for Science . She previously completed her Ph.D. at the University of Freiburg under Frank Hutter and Marius Lindauer (2022), and actively contributes to the AutoML community through open-source tool development and competition leadership. Co-developer of AutoML.org tools Faculty member of IMPRS-IS Chair for multiple AutoML workshops/conferences (2019-2025) Her research focuses on automated machine learning (AutoML) with specific attention to: AutoML Systems Hyperparameter Optimization Tabular Machine Learning Scientific Applications of ML She has organized multiple AutoML schools and conferences, including serving as Program Chair for AutoML 2024 and Non-archival Track Chair for AutoML 2025. Her work emphasizes making machine learning accessible through automation while maintaining scientific rigor and interpretability, particularly for tabular data applications. Katharina actively recruits PhD students through IMPRS-IS and collaborates with institutions like the University of Freiburg and Cyber Valley .

• Machine Learning
• Graph Neural Networks
• Data Attribution
• +4 more

Jiaqi Ma is an Assistant Professor at the University of Illinois at Urbana-Champaign (UIUC), holding dual appointments in the School of Information Sciences and the Siebel School of Computing and Data Science. Their research focuses on machine learning, graph neural networks, and data attribution, with particular emphasis on fairness in AI, large language models, and scalable algorithms. Ma has contributed to frameworks like dattri for efficient data attribution and GraSS for scalable influence functions. Research interests include graph learning (e.g., structural information analysis in text-attributed graphs), fairness in ML models (e.g., mitigating disparities in unlearning processes), and ethical AI applications. Collaborations span topics like data curation (DCA-Bench benchmark) and reinforcement learning transparency (A Snapshot of Influence). Key contributions include improving data removal while maintaining fairness (Fair Machine Unlearning), analyzing LLMs' graph structural utilization, and developing open-source tools like OpenHexAI for explainable ML evaluation. No scientific awards are explicitly listed, but their work reflects significant contributions to trustworthy AI and machine learning systems. Advising and grants: While specific students/grants are unlisted, Ma leads research teams advancing graph learning (e.g., Graph Learning Indexer platform) and safety-critical AI (e.g., unsafe data detection via attribution). Their work bridges theoretical foundations (e.g., influence functions) with practical applications (e.g., MNL model rankings).

Eugene KooninView profile

Adjunct Professor

• Microbiology
• Virology
• Bioinformatics
• +4 more

Eugene Koonin is a Senior Investigator at the National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), NIH, and holds adjunct professorships at Georgia Institute of Technology, Boston University, and the University of Haifa. A leading figure in evolutionary biology and computational genomics, he has made foundational contributions to comparative genomics, virus evolution, and the analysis of horizontal gene transfer. Education: BS in Biochemistry, Moscow State University (1978) PhD in Molecular Biology, Moscow State University (1983) Research Interests: His work spans evolutionary genomics, virus-host coevolution, discovery of novel viruses through metagenomics, and the evolutionary regimes of human cancers. He pioneered the Clusters of Orthologous Genes (COG) system and investigates thermodynamic principles underlying evolution. Publications: His recent work includes groundbreaking studies on gut viromes, RNA virus diversity, anti-CRISPR protein discovery, and SARS-CoV-2 pathogenicity. These publications reflect his integrative approach to computational biology. Scientific Awards: NIH Distinguished Investigator (2019) Benjamin Franklin Prize for Open Access (2019) Doctor Honoris Causa, Wageningen University (2018) Georgy Gamow Prize (2018) Member, National Academy of Sciences (2016) Israel Pollak Lecture Award (2011) Leadership & Collaborations: He has chaired major conferences (e.g., Gordon Research Conference on Genomics) and served as Editor-in-Chief of Biology Direct and Associate Editor of Genome Biology and Evolution . His lab at NCBI includes researchers like Kira Makarova and Yuri Wolf.

David E. BreenView profile

Professor

• Biomedical Image Informatics
• Geometric Modeling
• Textile Modeling and Design
• +12 more

David E. Breen is a Professor in the Department of Computer Science within the College of Computing & Informatics (CCI) at Drexel University. He leads the Geometric Biomedical Computing Group and is affiliated with the Metadata Research Center and the Center for Biological Discovery from Big Data. His research spans interdisciplinary domains including biomedical image informatics, geometric modeling, textile modeling, and bio-inspired self-organization algorithms. Education: PhD, Computer and Systems Engineering, Rensselaer Polytechnic Institute MS, Computer and Systems Engineering, Rensselaer Polytechnic Institute BA, Physics, Colgate University His research interests focus on computational methods for biomedical applications, including shape and image analysis for cancer diagnosis, 3D reconstruction of biological tissues, and video analysis of animal behavior. He also investigates geometric modeling techniques for textiles and self-organizing systems. His work integrates computer science with biology, medicine, and engineering to solve complex problems in biomedical computing. The recent publications highlight a strong trend in computational modeling of textiles, biomedical image informatics, and AI-driven data analysis. Key themes include geometric modeling of knitted fabrics, deep learning for medical image classification, agent-based modeling of cancer metastasis, and metadata generation for biological image collections. His work bridges fundamental geometric algorithms with practical applications in healthcare and digital archives. Scientific Awards: No specific awards mentioned in the provided text. Breen has advised numerous students and collaborators across multiple domains, particularly in biomedical computing and textile modeling. His research has been supported through affiliations with major centers and collaborations with institutions such as Johns Hopkins University and the Max Planck Institute. He has been involved in projects related to NSF Center for Visual & Decision Informatics and has contributed to over 100 technical publications. He leads the Geometric Biomedical Computing Group , which conducts research at the intersection of biology, medicine, engineering, and computer science. The group develops algorithms and software for geometry-related computing problems in biomedical applications. Collaborations include the Drexel Integrated Laboratory for Cellular Tissue Engineering, Dr. Dan Marenda's Lab, and Dr. Aleister Saunder's Lab in Drexel's Biology Department.

• Software Evolution
• Software Libraries
• APIs
• +5 more

Thomas Degueule is a CNRS researcher in the Software Engineering group at LaBRI (Bordeaux, France). His research focuses on software evolution , modularity , and comprehension , with a particular emphasis on software libraries , APIs , software ecosystems , and domain-specific languages (DSLs) . Prior to his current role, he worked as a postdoctoral researcher at CWI (Amsterdam) and earned his PhD at IRISA (Rennes, France). Research Themes : Software evolution, API analysis, dependency management, empirical software engineering, DSL engineering Projects : ANR JCJC ALIEN (PI), H2020 CROSSMINER (WP leader), ALE (associate member), LEOC Clarity (member), ANR INS GEMOC (member), ITEA2 MERgE (member) Software Tools : Roseau, Maracas, BreakBot, Melange, Eclipse GEMOC Studio, K3, Alex, Scava His recent publications highlight trends in API breaking changes , dependency evolution , DSL interoperability , and automated software analysis (see articles list for details). He also contributes to software education through tools like MOON and Immediate Feedback for Jupyter Notebooks. Thomas has supervised PhD students including Gustave Monce (University of Bordeaux), Lina Ochoa (now assistant professor at Eindhoven University), Corentin Latappy (post-doc at University of Bordeaux), and Christophe Casseau (lecturer at University of Bordeaux). He actively participates in academic service, serving on program committees for conferences such as ICSE , ASE , ICSME , ISSTA , and SLE , and organizing workshops like SLEBoK and MLE 2021 .

Frank CantersView profile

Professor

• Urban Remote Sensing
• GIS Applications
• Urban Form Dynamics
• +3 more

Frank Canters is a Professor of cartography, GIS, and remote sensing at the Department of Geography of Vrije Universiteit Brussel (VUB), leading the Cartography and GIS Research Group. His research focuses on urban remote sensing, spatial modeling of urban environments, and urban ecosystem services. He is renowned for pioneering the Canters projection, a minimum-error world map projection, and has contributed extensively to urban land-use mapping and decision-support systems for urban planning. His work spans over three decades, with 281+ publications and collaborations across multiple disciplines. Key areas include urban form dynamics, remote sensing applications for vegetation and land-use analysis, and spatial justice in green infrastructure distribution. He has supervised 83 students and developed tools like the Q-LavHA plugin for volcanic hazard modeling. Recent research highlights include integrating public perceptions into green space accessibility models, assessing allergenic potentials of urban greenery via LiDAR, and advancing machine learning approaches for urban vegetation mapping. His contributions bridge geospatial technologies with urban sustainability and policy.