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Elizabeth PolgreenView profile

Assistant Professor

• Programming Languages
• Program Synthesis
• Formal Verification
• +7 more

Elizabeth Polgreen is a Lecturer (~Assistant Professor) in the School of Informatics at the University of Edinburgh, where she conducts research in programming languages and formal methods, particularly program synthesis and verification. She is affiliated with the Laboratory for Foundations of Computer Science and contributes to the Programming Languages and Software Engineering research area. Her research focuses on formal program synthesis, leveraging techniques such as symbolic reasoning, genetic algorithms, and large language models to improve the scalability and automation of software verification. She explores applications in code modernization, tensor program lifting, and explainable AI. Her work bridges programming languages, AI, and formal methods to build trustworthy systems. Her recent publications (2020–2025) span top venues including PLDI, CGO, AAAI, CAV, OOPSLA, and NeurIPS, showing a strong trend in neuro-symbolic synthesis, grammar inference, and verification of AI and low-resource code. She has secured competitive funding, including a Royal Academy of Engineering fellowship and an Amazon Research Award. Scientific awards include: Royal Academy of Engineering Research Fellowship Amazon Research Award Best Paper Award at GPCE Distinguished Paper Award from CGO She advises multiple PhD students, including Yixuan Li, Alexander Brauckmann, and José Wesley de Souza Magalhães, often in collaboration with Professor Mike O'Boyle. Her research is supported by grants from the Royal Academy of Engineering and Amazon. She has delivered keynotes, tutorials, and a TEDx talk, contributing actively to outreach and education in formal methods. She leads a research group within the Laboratory for Foundations of Computer Science, focusing on trustworthy systems through synthesis and verification. Her team includes PhD students and collaborators working on cutting-edge topics in program analysis, AI for code, and compiler design.

Woosuk LeeView profile

Associate Professor

• Programming Systems
• Programming Languages
• Software Engineering
• +5 more

Woosuk Lee is an Associate Professor at Hanyang University since September 2024, previously serving as an Assistant Professor there from September 2018 to August 2024. He held postdoctoral fellowships at the University of Pennsylvania (2017-2018) and Georgia Institute of Technology (2016-2017), and completed his Ph.D. (2009-2016) and B.S. (2005-2009) at Seoul National University. His research focuses on enhancing software quality and programmer productivity through innovations in programming systems , integrating ideas from programming languages , software engineering , compilers , and security . He develops scalable techniques for program synthesis , enabling automated generation of efficient and safe software, alongside program analysis and repair tools to detect and fix bugs. His work has been presented at top-tier venues like OOPSLA, POPL, and PLDI. Professional Activities : Program Committee member for OOPSLA 2025, POPL 2025, PLDI 2024, APLAS 2023, and others; Co-Chair for PLDI 2025 workshops; Reviewer for journals including ACM Transactions on Software Engineering and Methodology. Students : PhD advisees Jaehyung Lee and Hangyeol Cho; Master’s students Jinsang Kim, Wang Ao, Gangdae Ju, Junghoon Lee, and Junseong Park; Alumni include DongKwon Lee (co-advised with Kwangkeun Yi) now at Samsung Research. Contact: Rm 403, 3rd Engineering Building, Hanyang University, Ansan-si, Gyeonggi-do, South Korea. Email: woosuk@hanyang.ac.kr .

Ravi ChughView profile

Associate Professor

• Programming Languages
• Human-Computer Interaction
• Direct Manipulation Programming Systems
• +3 more

Ravi Chugh is an Associate Professor in the Department of Computer Science at the University of Chicago. His work bridges Programming Languages (PL) and Human-Computer Interaction (HCI), focusing on direct manipulation programming systems and hole-driven development. Affiliation: University of Chicago Role: Director of Undergraduate Studies Research interests: Direct Manipulation Programming Systems Type Systems Program Synthesis Structured Editing Visual Programming His recent work includes Ragged Blocks (UIST 2025) for structured text rendering, Code Style Sheets (OOPSLA 2025) for styling code, and projects like Sketch-n-Sketch and Hazel for bimodal programming environments. Professional Activities: Program Committee: HATRA 2025, VL/HCC 2023, PLDI 2022, POPL 2021 Artifact Evaluation Co-Chair: PLDI 2018-2020 Editorial Board: Journal of Functional Programming (2020–)

Loris D'AntoniView profile

Associate Professor

• Program Synthesis
• Formal Methods
• Trustworthy Software
• +3 more

Loris D'Antoni is an Associate Professor at the University of California San Diego, affiliated with the Programming Systems Group and serving as a visiting academic at AWS . Previously, he co-founded a research group at UW-Madison. His research focuses on trustworthy software through Program synthesis (e.g., SemGuS toolkit) Formal verification of machine learning and network protocols Automata theory and symbolic constraints Trustworthy LLMs with grammar alignment Recent work explores semantics-guided synthesis and unrealizability logic , with applications to decision trees, LSTMs, and network routing. Publications span top venues like PLDI , OOPSLA , NeurIPS , and CAV . Notable scientific awards include Best Paper Award at ICDCN 23 Distinguished Paper Award at SBES 21 Oral Presentation at EMNLP 21 Nomination for EAPLS Award (part of ESOP 20 ) He teaches courses in programming languages ( CS-536 ) and synthesis/verification ( CS-703 ), and actively contributes to program committees at conferences like PLDI , CAV , and POPL .

Rumyana NeykovaView profile

Senior Lecturer

• Distributed Systems
• Formal Methods
• Concurrency Theory
• +4 more

Dr. Rumyana Neykova is a Senior Lecturer in Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. She holds a PhD from Imperial College London and specializes in concurrency theory, distributed systems verification, and blockchain technologies. Her research employs formal methods, type systems, and model checking to enhance software reliability and prevent communication faults in distributed architectures. Research Focus: Her work spans distributed protocol verification, blockchain ecosystems (Ethereum, smart contracts), simulation validation, and software engineering education. Recent projects include developing fluid session types for end-to-end protocol verification and analyzing developer dynamics in blockchain communities. Teaching & Supervision: Dr. Neykova teaches undergraduate modules in Logic/Computation and Software Development, supervises final-year/MSc projects, and advises industry collaborations through Brunel Talent Marketplace. Grants: SEAVEA (EPSRC, 2021-2024): Software Environment for Actionable & VVUQ-evaluated Exascale Applications Fluid Session Types (UK Research Institute, 2019-2023): End-to-end verification of communication protocols Professional Activities: Regular peer reviewer for journals (e.g., Information and Software Technology ) and conferences (e.g., ACM SIGPLAN). Co-chaired workshops including PLACES and BlochArch.

• Analytical Chemistry
• Instrumental Analysis
• Chromatography
• +5 more

Caterina Durante is an Associate Professor in the Department of Chemical and Geological Sciences at the University of Modena and Reggio Emilia. She specializes in Analytical Chemistry (Chimica analitica) and teaches instrumental analytical chemistry courses for both undergraduate Chemistry programs and Master's Degree Courses in Chemical Sciences. Her research interests span multiple areas of analytical chemistry with a strong focus on method development and optimization. She has made significant contributions to food analysis and authentication, particularly for traditional Italian products like Aceto Balsamico Tradizionale di Modena and Parmigiano Reggiano cheese. Her work integrates advanced analytical techniques including chromatography, mass spectrometry, and various spectroscopic methods with sophisticated chemometric approaches for data analysis. Her recent publications (2023-2025) demonstrate a clear research trajectory focused on developing robust analytical methods for complex matrices, with applications in food traceability, environmental analysis, and pharmaceutical quality control. The publications reveal a strong emphasis on chemometrics, particularly multivariate data analysis techniques like PCA, PLS, and PARAFAC, which she applies to interpret complex analytical data from various spectroscopic and chromatographic techniques. She actively collaborates with researchers across multiple institutions, evidenced by her numerous co-authored publications spanning food science, environmental chemistry, pharmaceutical analysis, and green chemistry applications. Her work often addresses practical analytical challenges in industrial and food production settings, with several studies focusing on real-time process monitoring and quality assessment.

Daniel GritznerView profile

Researcher

• Deep Learning
• Transfer Learning
• Semantic Segmentation
• +7 more

Daniel Gritzner is a researcher at the Institute for Information Processing (Leibniz Universität Hannover) , specializing in computer vision, remote sensing, and scenario-based software engineering. His work bridges academic research with real-world applications in renewable energy, geospatial analysis, and automated code generation. Studied Computer Science (B.Sc. 2010, Diploma 2014) at the University of Mannheim Focus areas: Deep Learning, Semantic Segmentation, Remote Sensing, Formal Specifications His research integrates computer vision with remote sensing , applying techniques like transfer learning and domain adaptation to aerial/satellite imagery. Key projects include SegForestNet for segmentation and WindGISKI for wind turbine site selection. Recent publications highlight advancements in semantic segmentation, hyperspectral band optimization, and scenario-based controller synthesis. Collaborative work with Jörn Ostermann and others demonstrates interdisciplinary approaches across IEEE, Springer, and arXiv platforms. Technical contributions include the open-source SegForestNet framework, implementing binary space partitioning trees for geospatial analysis. This toolchain combines Python/Rust with PyTorch, emphasizing reproducibility and practical deployment in industrial/energy domains.

Angel RuizView profile

Professor

• Healthcare Operations
• Emergency Medical Services
• Mathematical Modeling and Optimization
• +3 more

Angel Ruiz is a Full Professor at Laval University’s Faculty of Medicine, specializing in healthcare operations and optimization. He co-directs CIRRELT’s Laboratory on Health Service Networks and contributes to CERVO’s Clinical and Cognitive Neuroscience research axis. Laval University, Faculty of Medicine CIRRELT’s Laboratory on Health Service Networks (Co-Director) CERVO Brain Research Centre (Researcher) His research focuses on mathematical modeling, logistics optimization, and simulation frameworks to improve healthcare systems, including pandemic planning, emergency medical services, and biomedical sample transportation. He has developed systematic review tools and prioritization frameworks for rehabilitation services. Recent publications emphasize location-allocation models for vaccination facilities, stochastic programming for food bank networks, and real-time patient transport systems. While no awards or student lists are explicitly mentioned in accessible content, his work bridges healthcare management with operational research.

Stephanie ForrestView profile

Professor

• Computational Immunology
• Computer Security
• Automated Program Repair
• +5 more

Dr. Stephanie Forrest is a Professor at Arizona State University's School of Computing and Augmented Intelligence (SCAI) and serves as Director of the Biodesign Center for Biocomputation, Security and Society . She is also affiliated with the Santa Fe Institute (SFI) as External Faculty and the ASU-SFI Fellowship . Education: B.A. from St. John's College and M.S./Ph.D. in Computer Science from the University of Michigan. Her research spans the biology of computation and computation in biology , including computational immunology , cybersecurity , automated software repair , evolutionary computation , and complex systems . Recent work focuses on GPU code optimization , malware analysis , and privacy-preserving wastewater epidemiology . Her publications (15 most recent) reveal trends in evolutionary algorithms for software repair, cybersecurity frameworks inspired by biological systems, and high-performance computing applications in epidemiology and genetics. Awards include IEEE S&P Test of Time (2020) , ACM/AAAI Allen Newell (2011) , and ICSE Most Influential Paper (2019) . Cybersecurity: Developed anomaly detection, instruction-set randomization, and CRISPR-inspired DoS mitigation. Software Repair: Pioneered biologically inspired methods for bug fixing, vulnerability closure, and energy optimization. Biological Modeling: Agent-based simulations of SARS-CoV-2 spread, cancer evolution, and immune system dynamics.

Davide Dell'AnnaView profile

Assistant Professor

• Human-centered Artificial Intelligence
• Human-AI Collaboration
• Social and Responsible AI
• +3 more

Davide Dell'Anna is an Assistant Professor in the Responsible AI group of the Department of Information and Computing Sciences at Utrecht University. He is a member of the Hybrid Intelligence Centre, a 10-year program funded by the Dutch Ministry of Education, Culture and Science through NWO. His academic journey includes a Ph.D. from Utrecht University (2021), a Master's degree from the University of Turin (2016), and prior postdoctoral positions at Delft University of Technology (2021-2023) and within the Hybrid Intelligence Centre (2023-2024). Dr. Dell'Anna's research focuses on developing methodologies and solutions for Artificial Intelligence systems to cooperate synergistically and proactively with humans. His work specifically emphasizes automated and data-driven mechanisms that account for human intentionality and expertise to ensure AI behaviors are aligned with human norms and values. His research spans multiple domains including healthcare, social computing, and transportation, with applications in dementia therapy, epidemic simulation, and human-robot interaction. His scholarly output demonstrates a consistent focus on Human-centered AI, Norm-aware Systems, and Hybrid Intelligence. His recent publications explore quality models for Hybrid Intelligence teams, social norm-aware robot architectures, consent mechanisms for responsible autonomy, and replication practices in Requirements Engineering. His work bridges theoretical foundations with practical applications, particularly in healthcare contexts. Distinguished PC Member award - AAMAS 2025 (recognizing 35 out of 684 PC members, 5.1%) "Quality Champion" PC award - ECAI 2023 (recognizing 58 out of 700 eligible PC members, 8.3%) Outstanding PC member award - AAMAS 2023 (recognizing 16 out of 436 PC members, 3.7%) Dr. Dell'Anna actively supervises students and has mentored numerous Master's students including Karpínski, van Lindonk, Willems, and Brigola. He has secured competitive research funding including an NWO Open Competition Domain Science - XS Grant (€50,000) for developing human-like norm-aware cognitive robots. He serves as Associate Editor for CEUR-WS and co-chairs major international workshops including COINE@AAMAS 2025 and HHAI 2025, demonstrating significant leadership in the AI research community.

Emilio Jesús Gallego AriasView profile

Research Fellow

• Theorem Proving
• Functional Programming
• Computer Music
• +7 more

Emilio Jesús Gallego Arias is a non-tenured Research Fellow at the French National Center for Scientific Research (CNRS), hosted at the Institute of Fundamental Computer Research (IRIF) of CNRS and University of Paris Cité. He is also a member of the PiCube Inria team. Previously, he held postdoctoral positions at the University of Pennsylvania (2012–2014) and MINES ParisTech (2014–2019). His research spans mechanically-verified functional and logic programming , with a focus on the Coq proof assistant and the Mathematical Components Library . He develops tools like coq-lsp (language-server for Coq IDEs) and jsCoq (web interface), replacing earlier projects like SerAPI . His work bridges programming language theory , digital signal processing , and formal verification , particularly in the ANR FEEVER project for verifying Faust programs. His 15 most recent works (2014–2024) address type systems , differential privacy , and formal verification in domains like audio processing and mechanism design . Publications span journals (e.g., Journal of Privacy and Confidentiality), conferences (ICML, POPL, FARM), and workshops (CoqPL, UITP). He contributes to open-source projects (GitHub), including DFuzz (linear dependent types), DualQuery (privacy algorithms), and RAM (relational machine). He uses formal methods in collaborative development platforms (Gitter, GitLab) and advocates for free software and accessible audio technology .

Kathleen FisherView profile

Adjunct Professor

• Programming Languages
• Domain-Specific Languages (DSL)
• Program Synthesis
• +4 more

Kathleen Fisher is an Adjunct Professor in the Computer Science Department at Tufts University and currently serves as the Director of the Information Innovation Office at DARPA. She previously held roles as Professor and Department Chair at Tufts (2016-2021), Program Manager at DARPA, and Principal Member of Technical Staff at AT&T Labs Research. Her academic journey began with a PhD in Computer Science from Stanford University. Kathleen’s research focuses on advancing programming languages through domain-specific languages (DSLs), program synthesis, and formal methods. Her work addresses challenges in ad hoc data management, secure systems, and integrating machine learning with programming language design. Notable projects include the Hancock and PADS systems for data processing, Forest for filestore management, and verified parser generators. She has received prestigious accolades, including ACM Fellow, Hertz Foundation Fellow, and SIGPLAN Distinguished Service Award. Her service includes leadership roles in ACM SIGPLAN, CRA-W, and as General Chair for ICFP 2015. Kathleen has advised PhD student Matt Ahrens and led impactful DARPA programs like HACMS and PPAML. As co-founder of the Programming Language Mentoring Workshop (PLMW), she actively contributes to diversity initiatives in computer science. Her research group, TuPL, explores DSLs, program synthesis, and language-based security, maintaining projects such as Autobahn and PADS.

Tomoki NakamaruView profile

Assistant Professor

• Domain-Specific Languages
• Mining Software Repositories
• Notebook Programming
• +5 more

Tomoki Nakamaru is an Assistant Professor at the Department of Multidisciplinary Systems Science, Graduate School of Arts and Sciences, The University of Tokyo. He holds a Ph.D. in Information Science and Engineering from The University of Tokyo, advised by Prof. Shigeru Chiba. Education: PhD (2021), The University of Tokyo M.Sc. (2018), The University of Tokyo B.Eng. (2016), The University of Tokyo His research focuses on Domain-Specific Languages , Mining Software Repositories , and Notebook Programming . He develops tools like Multiverse Notebook and Silverchain to enhance code exploration and API usability. He has published extensively at top venues like OOPSLA and PLDI , covering topics from Fluent Interface Generation to Runtime Monitoring . His 15 most recent works span 2017–2025. Scientific Awards: Yamashita Memorial Research Award (2023) University of Tokyo Business Reform Special Award (2021) JSST Student Encouragement Awards (2019–2020) Distinguished Artifact Award at OOPSLA (2019) Dean's Award, UTokyo (2018) Nakamaru serves on program and artifact committees for conferences like ECOOP , OOPSLA , and ‹Programming› . He teaches courses including Practical Programming and Introduction to Information Systems .

• Organic Chemistry
• Supramolecular Chemistry
• Catalysis
• +7 more

Dr. Keith Andrews is an Assistant Professor in the Department of Chemistry at Durham University. With a research focus on enzyme mimics and supramolecular chemistry , his work bridges synthetic organic chemistry with molecular recognition and catalysis. He teaches "Enzyme Mimics in Organic Synthesis" at the Year 4 level. MChem from Imperial College London PhD from University of Nottingham (2013-2016) Post-doctoral work at University of Oxford (2016-2023) His research develops soluble organic cages through chemical self-assembly, aiming to desymmetrize these structures for atomic precision in molecular sensing and catalysis. Current projects include enzyme mimic catalysts for biomolecule transformations and polymer degradation. Notable scientific achievement: Royal Commission 1851 Research Fellowship awarded in 2019. Publications highlight breakthroughs in non-symmetric cage synthesis , acyl transfer catalysis , and silane reagent applications . Primary advisee: Betty Raynal Research group established at Durham University in 2023

• Organic synthesis
• Flow Chemistry
• Microfluidics
• +7 more

Professor Ian Baxendale serves as Director of Education in the Department of Chemistry at Durham University, where he leads pioneering research in chemical synthesis methodologies. With over two decades of academic contributions, he has established himself as a leading expert in flow chemistry and microreactor technology, focusing on improving the speed, efficiency, and safety of chemical transformations for pharmaceutical and industrial applications. Dr. Baxendale's research interests span organic synthesis (natural products, heterocyclic and medicinal chemistry), organometallic chemistry, catalyst design, microfluidics, microwave-assisted synthesis, and solid-supported reagents. His primary research direction centers on the synthesis of biologically potent molecules, utilizing advanced synthesis tools including microwave reactors, membrane reactors, and flow chemistry platforms to facilitate bond formation and expedite purification procedures. A central aspect of his work involves developing new chemical reactions that address limitations of standard laboratory conditions while enhancing automation to delegate repetitive tasks from chemists to machines. Analysis of his 15 most recent publications reveals a consistent focus on flow chemistry applications, particularly in pharmaceutical development, fragrance chemistry, and heterocyclic compound synthesis. His work demonstrates a strong trend toward practical industrial applications, with increasing emphasis on sustainable chemistry practices, process optimization, and the integration of computational methods with experimental synthesis. The publications show his research group's expertise in developing continuous flow processes for complex molecule synthesis, with particular attention to reaction engineering and green chemistry principles. Professor Baxendale has maintained an exceptionally productive research program, with publications spanning from 2002 through 2025. His work frequently appears in high-impact journals including Organic Process Research & Development, Journal of Organic Chemistry, and Beilstein Journal of Organic Chemistry. He has developed numerous innovative synthesis techniques that have been adopted by both academic and industrial researchers, particularly in the pharmaceutical sector where flow chemistry offers significant advantages for process development and scale-up. As Director of Education in the Department of Chemistry, Professor Baxendale oversees educational programs while maintaining an active research group that collaborates with scientists worldwide. His research laboratory serves as a hub for developing next-generation synthesis technologies, with particular emphasis on integrating automation with chemical synthesis to create more efficient and sustainable production methods for complex organic molecules.