Find Academic Supervisors

• Nutrition and Chronic Disease
• Cancer Epidemiology
• Obesity and Physical Activity
• +3 more

Dagfinn Aune serves as a Research Fellow at the Department of Epidemiology and Biostatistics within the School of Public Health, Faculty of Medicine at Imperial College London. He concurrently holds positions as Associate Professor at Oslo New University College and Senior Researcher at the Cancer Registry of Norway in Oslo. His work centers on large-scale epidemiological investigations into diet, obesity, and chronic disease mechanisms across international populations. Education: PhD in Epidemiology, Norwegian University of Science and Technology (2016) MSc in Nutrition, University of Oslo (2008) Research interests focus on the interplay between dietary patterns, adiposity, physical activity, and smoking with chronic disease outcomes. His work examines how these factors influence cancer risk (particularly breast, gastrointestinal, and hematological malignancies), pregnancy complications, diabetes progression, and mortality across diverse populations. He employs systematic review methodologies and analyzes data from major cohorts including EPIC and Norwegian registries. Publication trends reveal consistent emphasis on obesity-cancer relationships, with recent work (2023-2025) expanding into metabolomic mediators, cardiometabolic interactions, and rare cancer epidemiology. His research frequently utilizes systematic reviews, meta-analyses, and multinational cohort studies to establish evidence for cancer prevention guidelines. Scientific Awards: No awards specified in source materials Advising and grant activity centers on major collaborative projects including the World Cancer Research Fund's Continuous Update Project, the EPIC study, and South American case-control research. While specific student mentorship isn't documented, his leadership in systematic review protocols suggests substantial training responsibilities. His grant portfolio includes funding from WCRF International and Norwegian research councils for large-scale epidemiological analyses. Labs and teams include the Centre for Translational Nutrition and Food Research at Imperial College London, where he collaborates with nutrition scientists and biostatisticians. He maintains active roles in the EPIC consortium and WCRF International's CUP Global Programme, coordinating multinational analyses of diet-cancer relationships through the Cancer Registry of Norway.

Deian StefanView profile

Associate Professor

• Security
• Programming Languages
• Systems
• +6 more

Deian Stefan is an Associate Professor in the Department of Computer Science and Engineering at the University of California, San Diego (UCSD). His research focuses on building secure systems through interdisciplinary approaches spanning security , programming languages , and systems . Key areas include WebAssembly security , JavaScript JITs , constant-time programming , memory safety , information flow control , and program analysis tools. He co-founded Intrinsic , a web-security startup later acquired by VMWare, and contributed to standards like W3C WebAppSec and Node.js Security Working Groups. Education: PhD in Computer Science from Stanford University (2015), advised by David Mazières, John C. Mitchell, and Alejandro Russo BE and ME in Electrical Engineering from Cooper Union (2011) Research Trends: His work targets secure systems (Web frameworks, sandboxing, runtime systems), language-based security (constant-time programming, memory safety), and verification for security . Recent publications focus on mitigating speculative execution attacks, hardware-assisted sandboxing, and WebAssembly security. Awards & Recognition: Distinguished Paper Award at POPL 2021 and IEEE MICRO Top Picks 2024 Best Paper Award at CollaborateCom 2010 2010.01 Prize by Daniel J. Bernstein (DJB) Most Influential Paper Award at ICFP 2022 Teaching: He has taught graduate and undergraduate courses including Graduate Computer Security (CSE 227) , Building Secure Systems with Rust , and Programming Languages: Principles and Paradigms at UCSD since 2018. Prior teaching experience includes Stanford and Cooper Union.

Christian BizerView profile

Professor

• Data Integration
• Entity Matching
• Schema Matching
• +5 more

Professor Christian Bizer is a leading figure in web-based systems and data integration at the University of Mannheim , where he chairs Information Systems V: Web-based Systems . His research focuses on integrating data from multiple sources using large language models and LLM-based agents, with applications in product data extraction and DBpedia knowledge graph construction. He co-founded the DBpedia project and initiated the WebDataCommons initiative. Current research areas: Entity matching, schema matching, table annotation, information extraction, data discovery Key projects: WebMall benchmark, WInte.r integration framework, Schema.org analysis His work applies to e-commerce data integration and knowledge graph construction, with empirical studies on schema.org adoption. He supervises PhD students including Alexander Brinkmann and Ralph Peeters. Scientific Awards: Best Paper at iiWAS 2024 SWSA Ten-Year Award at ISWC 2019 Yahoo FREP Award 2015 Semantic Web Challenge winners Teaching includes courses on web data integration, web mining, large language models, and data mining for master's programs. He leads the DWS PhD colloquium and team projects on LLM agents for data integration.

Nadia PolikarpovaView profile

Associate Professor

• Program Synthesis
• Program Verification
• Type Systems
• +5 more

Nadia Polikarpova is an Associate Professor in the Department of Computer Science and Engineering at the University of California, San Diego . She earned her PhD from ETH Zurich in 2014 under Bertrand Meyer , followed by postdoctoral research at MIT CSAIL with Armando Solar-Lezama . Her academic contributions have been recognized with prestigious awards including the 2020 Sloan Fellowship , 2020 Intel Rising Stars Award , and 2020 NSF CAREER Award . Polikarpova's research focuses on program synthesis , program verification , and type systems . She leads the Programming Systems group at UCSD and contributes to the IFIP Working Group 2.8 on Functional Programming since 2022. Her work spans foundational research and practical tools, including projects like Synquid , SuSLik , and Laurel that combine formal methods with machine learning for code generation. Her recent publications in venues like OOPSLA , NeurIPS , and ICFP reveal trends in AI-assisted programming , live programming environments , and formal verification . She has advised numerous PhD and Master’s students including Shraddha Barke , Zheng Guo , and Tristan Knoth , many of whom have moved to prominent academic and industry positions. Notable artifacts from her lab include tools like ColDeco for spreadsheet inspection and Superfusion for eliminating intermediate data structures. 2020 : Sloan Fellow 2020 : Intel Rising Stars Award 2020 : NSF CAREER Award 2021 : Distinguished Paper at POPL 2023 : Distinguished Artifact at PLDI 2023 : Distinguished Paper at OOPSLA Polikarpova actively contributes to academic service, serving on program committees for PLDI , POPL , and OOPSLA , and co-chairing the OOPSLA Review Committee in 2023. She has delivered keynotes at APLAS'20 and PLDI'24 , emphasizing the integration of large language models with formal methods.

Deian StefanView profile

Associate Professor

• security
• programming languages
• systems
• +7 more

Deian Stefan is an Associate Professor at the University of California San Diego (UCSD) in the Department of Computer Science and Engineering . His research spans security , programming languages , and systems , with a focus on building principled and practical secure systems. He has served as a co-founder and Chief Scientist at Intrinsic (acquired by VMWare) and contributed to standards bodies like the W3C WebAppSec and Node.js Security Working Groups . His research interests include: Secure Systems : Web frameworks, browser designs, sandboxing, runtime systems Language-Based Security : Constant-time programming, memory safety, information flow control Verification : Security verification, static/symbolic analysis tools WebAssembly and JavaScript JITs security Deian Stefan has received multiple scientific awards , including several Distinguished Paper Awards at venues like POPL, ICFP, and USENIX Security, as well as the IEEE Cybersecurity Award for Practice (2022) and CSAW 2020 First Place for Applied Research. He has taught courses on Computer Security (CSE 127, CSE 227) and advanced topics in Building Secure Systems (CSE 291) using Rust, WebAssembly, and blockchain security. His work has been supported by collaborations with industry and academia, including projects like RLBox and COWL .

• Information Retrieval
• Machine Learning
• Natural Language Processing
• +3 more

Mohammad Aliannejadi is an Assistant Professor at the IRLab (formerly ILPS) within the Informatics Institute at the University of Amsterdam. His research focuses on Information Retrieval (IR), machine learning, natural language processing (NLP), and conversational systems, particularly in modeling user information needs on mobile devices and conversational search systems. He holds a Ph.D. in Informatics from Università della Svizzera italiana (USI), Lugano, Switzerland, and a M.Sc. in Computer Engineering from Tehran Polytechnic. During his Ph.D., he visited the CIIR Lab at the University of Massachusetts Amherst, USA. His research interests include conversational search systems, recommender systems, unified search frameworks, and user-centric evaluation methodologies. Notable contributions include work on clarifying questions in open-domain dialogues, contextual suggestion systems, and cross-market recommendation. Aliannejadi has organized major shared tasks and workshops, including the IGLU Contest (NeurIPS 2021) and XMRec Workshop (RecSys 2021). He serves on program committees of top IR conferences like SIGIR, CIKM, and ECIR, and has authored over 50 peer-reviewed publications in these areas. His work has received recognition, including top performance in TREC Contextual Suggestion tracks (2015, 2016). He actively contributes to the IR community through teaching, including courses on Information Retrieval and Human-in-the-Loop Machine Learning at the University of Amsterdam.

Daniel VarroView profile

Professor

• Model-Based Systems Engineering
• Cyber-Physical Systems
• Software Engineering
• +12 more

Daniel Varro is a Professor affiliated with McGill University (Faculty of Engineering, School of Computer Science), with strong ties to Budapest University of Technology and Economics and Linköping University. He is a leading researcher in model-driven engineering, cyber-physical systems, and software engineering, actively contributing to top-tier conferences such as MODELS, ICSE, and ASE. His research focuses on model-based systems engineering (MBSE) , automated model generation , model transformations , and constraint-based consistency checking . Recently, his work has expanded into integrating large language models (LLMs) and machine learning into modeling workflows, including model querying, domain modeling, and bug detection. The recent publications reveal a strong trend toward AI-augmented modeling, logic-based solvers (e.g., Refinery), and safety assurance of autonomous systems (e.g., COLREGs compliance). His work bridges formal methods with practical software engineering challenges in industrial and safety-critical domains. Scientific Awards: No specific awards mentioned in the text. Advising and Grants: While no explicit list of students or grants is provided, his mentorship in the Doctoral Symposium and repeated leadership roles suggest active supervision and likely grant funding. He has led projects on automated model generation, model quality, and AI integration in modeling. Labs and Teams: Daniel Varro is associated with research groups focused on model-driven engineering and software evolution, likely leading or co-leading teams working on the VIATRA and Refinery frameworks for model transformation and solving.

Alex LiuView profile

Researcher

• Paleobiology
• Early Animal Evolution
• Ediacaran Biota
• +8 more

Alex Liu is a Researcher at the Department of Earth Sciences within the University of Cambridge. He specializes in palaeobiology , focusing on the origin and early evolution of animals, particularly the Ediacaran biota (~579–539 million years ago), and their co-evolution with Earth's environment. Research Focus: Refines understanding of animal body plan evolution, taphonomy, sedimentology, and macroevolutionary trends. Methodologies: Combines fieldwork, experimental studies, petrology, phylogenetics, and big-data analyses. Collaborations: Works with international museums and research teams on fossil sites in Namibia, Canada, and Brazil. Additional Interests: Explores meiofaunal evolution, paleogeography, paleoclimate, and conservation paleobiology. He supervises Cambridge NERC Doctoral Landscape Awards (DLA) projects and welcomes student contributions to taxonomic, paleoecological, and analytical studies.

Zachary KincaidView profile

Associate Professor

• Program Analysis
• Formal Methods
• Programming Languages
• +4 more

Zachary Kincaid is an Associate Professor in the Department of Computer Science at Princeton University's School of Engineering and Applied Science. His research focuses on program analysis, logic, and programming languages, with an emphasis on making program analysis compositional and robust. He received his PhD from the University of Toronto under the supervision of Azadeh Farzan. His work has been implemented in the Duet program analyzer, and he has an Erdős number of 3. Dr. Kincaid's research interests include: Compositional program analysis techniques Algebraic approaches to program analysis Termination analysis and ranking function synthesis Verification of concurrent and parallel programs Automated reasoning and decision procedures Analysis of numerical programs and loops His recent publications show a strong focus on developing novel techniques for program analysis that bridge theoretical computer science with practical verification tools, particularly in nonlinear analysis, quantified reasoning, and compositional verification. Dr. Kincaid has received research support from ONR grant N00014-19-1-2318 for his work on robust program analysis. He has advised graduate students including: Current: Jake Silverman, Nicolas Koh, Nikhil Pimpalkhare Graduated: Shaowei Zhu (PhD 2024, Researcher at Amazon), Charlie Murphy (PhD 2023, Postdoc at University of Wisconsin–Madison) Dr. Kincaid teaches courses including: COS 320 – Compiling Techniques (Spring 2024, 2022, 2020, 2019) COS 516 / ELE 516 – Automated Reasoning about Software (Fall 2025, 2022, 2018) COS 217 – Introduction to Programming Systems (Fall 2024) COS IW – Practical Solutions to Intractable Problems (Fall 2023, Spring 2023, 2018, 2017) COS IW – Little Languages (Spring 2018) COS 597D – Reasoning about concurrent systems (Fall 2016)

Judy HartView profile

Associate Professor

• Renewable Energy Materials
• Photocatalysis
• Solar Cells
• +5 more

Associate Professor Judy Hart is a materials scientist at the School of Materials Science & Engineering, UNSW Sydney , specializing in the development of semiconducting materials for renewable energy applications. Her work integrates computational (DFT) and experimental approaches to understand composition-property relationships in systems like solid solutions , heterostructures , and doped materials for photocatalysis and solar cells . She leads projects funded by ARC Discovery and Linkage grants , including work on photo-electro-catalysis systems and stabilizing ceramic materials . Education: PhD in Materials Engineering (Monash University, 2007), BEng (Materials) (Monash, 2002) Professional Experience: Senior Lecturer (UNSW, 2017–), Lecturer (UNSW, 2013–2017), University of Bristol (2007–2012) Research Interests Her research focuses on designing materials for renewable energy , particularly photoelectrochemical water splitting and organic oxidation reactions . Key areas include Density Functional Theory (DFT) , defect engineering , band gap tuning , and nanostructured materials . She investigates ferroelectric polarization effects , metal oxide heterostructures , and stability of battery components , with applications in hydrogen production , CO2 conversion , and advanced battery materials . Scientific Awards Ramsay Memorial Fellowship (University of Bristol, 2007–2009) Teaching Contributions She is co-author of the 1st Australian & New Zealand edition of "Materials Science and Engineering: An Introduction" , and teaches courses on computational materials science , corrosion-resistant surfaces , mechanical behavior of metals , and materials design .

• Programming Language Theory
• Dependent and Refinement Types
• Computational Effects
• +6 more

Danel Ahman is an Associate Professor at the Institute of Computer Science , University of Tartu , Estonia, specializing in programming language theory . His research focuses on dependent/refinement types , computational effects , and verified software . Education PhD in Theoretical Computer Science (University of Edinburgh, 2017) MPhil in Advanced Computer Science (University of Cambridge, 2012) BSc in Informatics (Tallinn University of Technology, 2010) Research Interests : Danel investigates programming languages with algebraic effects and effect handlers for verified software, exploring denotational/operational semantics and fibrational approaches to effects. His work bridges theoretical computer science with practical formal verification. Scientific Awards : Estonian Research Council grant (2025) Marie Skłodowska-Curie Fellowship (2019) PhD dissertation prize (2018) Google/Citrix dissertation awards (2012) Teaching & Supervision : He teaches courses like Logic in Computer Science and Functional Programming at the University of Tartu, and supervised BSc/MSc theses on topics including asynchronous effects and formal verification. Danel also organizes research seminars and guest lectures on F*.

• Programming Language Design
• Program Verification
• Type Theory
• +3 more

Neelakantan R. Krishnaswami is a Professor of Computer Science at the University of Cambridge's Computer Laboratory , and a Fellow of Trinity College . His research focuses on the intersection of program verification, programming language design, and foundational topics like type theory and semantics. His work spans areas such as refinement types, parser design, separation logic for systems software, and the semantics of reactive programming. Notable contributions include the Datafun language for higher-order Datalog and the λert type theory for explicit refinement types. He has also developed foundational frameworks for verifying imperative programs using advanced type systems and logical relations. Key publications include 'Explicit Refinement Types' (ICFP 2023), 'flap: A Deterministic Parser with Fused Lexing' (PLDI 2023), and 'CN: Verifying Systems C Code' (POPL 2023). His work frequently addresses challenges in efficiency, correctness, and modularity for both functional and imperative systems. His awards include Distinguished Paper Awards at PLDI 2019 and POPL 2020. His research integrates theoretical rigor with practical tooling, exemplified by contributions to languages like Coq, Lean, and Haskell.

Sean RenView profile

Associate Professor

• Natural Language Processing
• Commonsense Reasoning
• Graph Neural Networks
• +3 more

Sean Ren is an Associate Professor in Computer Science at the University of Southern California, where he holds the Andrew and Erna Viterbi Early Career Chair. He directs the INK Research Lab and serves as Research Team Leader at USC's Information Sciences Institute. Affiliated with the USC NLP Group and Machine Learning Center, his research focuses on developing robust NLP systems through knowledge-aware architectures and data-efficient learning. His research interests include: Evaluation methods exposing NLP limitations in reasoning tasks Augmenting models with commonsense/knowledge via novel algorithms Graph neural networks for relational inference Model robustness verification and enhancement Neural-symbolic integration for interpretable AI Recent publications demonstrate strong emphases on language model reasoning, knowledge distillation, and compositional generalization. His group's ACL/NeurIPS papers frequently address robustness gaps in state-of-the-art models. Honors include: ACL Outstanding Paper (2023) MIT TR Innovator 35 Asia Pacific (2023) NSF CAREER Award (2021) Forbes 30 Under 30 (2019) ACM SIGKDD Dissertation Award (2018) Research is supported by NSF, DARPA, IARPA, and industry partners (Google, Amazon, Meta). He leads the INK Lab with focuses on label-efficient learning and knowledge-guided NLP, while actively recruiting PhD students for projects bridging symbolic and neural paradigms.

• Neuroscience
• Behavioral Genetics
• Electrophysiology
• +3 more

Rui M. Costa is a Professor of Neuroscience at Columbia University, with appointments in Neurology and the Mortimer B. Zuckerman Mind Brain Behavior Institute. His research focuses on understanding how molecular networks in the brain influence neural circuits to shape behaviors, particularly in action control and disorders like Autism Spectrum Disorders and Obsessive-Compulsive Disorder. Primary Affiliation: Columbia University Departments: Neuroscience, Neurology Institute: Mortimer B. Zuckerman Mind Brain Behavior Institute Research Interests Molecular and neural circuit mechanisms of action control Goal-directed actions vs. habits Behavioral disorders: Autism and OCD Neural plasticity in motor learning Publication Trends His recent work explores corticostriatal dynamics, basal ganglia pathways, and endocannabinoid modulation in habit formation. Studies also investigate Foxp2 mutations, motor learning consolidation, and two-photon imaging of neural activity in rodents.

Trenton R. FosterView profile

Associate Professor

• Endocrine Surgery
• Thyroid Surgery
• Parathyroid Surgery
• +7 more

Trenton R. Foster, M.D., is an Associate Professor of Surgery at Mayo Clinic College of Medicine, serving as a Consultant in the Division of Endocrine Surgery within the Department of Surgery. He holds multiple leadership positions including Associate Program Director for the General Surgery Residency Program and Associate Director of Student Clerkships Programs. Dr. Foster is also the Physician Lead for the Collaborative Endocrine Surgery Quality Improvement Program (CESQIP) and serves on several important committees including the Clinical Competency Committee and the Department of Surgery Equity, Inclusion, and Diversity Committee. Dr. Foster's research focuses on optimizing surgical management of endocrine disorders, with particular emphasis on determining appropriate surgical extent for thyroid cancer, improving preoperative localization for parathyroid disease, and refining diagnostic approaches for adrenal tumors. His work utilizes national and institutional databases to understand disease behavior and improve patient outcomes through evidence-based practice. Analysis of Dr. Foster's recent publications (2023-2025) reveals a strong focus on clinical outcomes research across the spectrum of endocrine surgery. His work addresses critical questions regarding optimal surgical approaches for thyroid, parathyroid, and adrenal conditions, with particular attention to minimally invasive techniques, long-term outcomes, and quality improvement initiatives. The research demonstrates expertise in analyzing complex surgical datasets to derive practical clinical insights that directly impact patient care. His scientific achievements include: 2025 Focused Practice Designation in Adult Complex Thyroid and Parathyroid Surgery from the American Board of Surgery 2019 Dennis Wasson, M.D. Award for Outstanding Graduating Chief Resident from Yale University Multiple research awards from 2015-2016 including the SVS Foundation Resident Research Prize and Department of Surgery Best Basic Science Research Award at Yale Golden Key National Honor Society membership during undergraduate studies Dr. Foster actively mentors residents and medical students through his roles in the General Surgery Residency Program and student clerkships. He collaborates extensively with colleagues in endocrinology, radiology, and pathology to provide comprehensive, multidisciplinary care for patients with endocrine disorders. His research directly informs clinical practice, leading to improved preoperative evaluation, optimized surgical approaches, and enhanced postoperative care protocols while maintaining safety and effectiveness.