David Duvenaud is an Associate Professor at the University of Toronto , holding a Canada Research Chair in Generative Models and a Schwartz Reisman Chair in Technology and Society . He is cross-appointed to the Department of Computer Science and Department of Statistical Sciences . A Sloan Research Fellow and founding member of the Vector Institute , his work bridges deep probabilistic models , AI safety , and scientific computing . PhD in Machine Learning (University of Cambridge, 2014) Postdoc in Hyperparameter Optimization (Harvard University, 2016) Co-founded Invenia (energy forecasting company) His research spans foundational Neural Ordinary Differential Equations (NeurIPS 2018 Best Paper) and Automatic Chemical Design (ACS Central Science 2018) to recent work on AGI governance (2025) and AI safety (2024). Key contributions include stochastic variational inference , implicit differentiation frameworks , and antisymmetrization layers for quantum Monte Carlo. Recent publications (2024-2025) focus on systemic existential risks from AI , many-shot jailbreaking attacks , and epistemic uncertainty quantification . His group trains energy-based models with scalable MCMC samplers and develops invertible neural architectures (e.g., Residual Flows NeurIPS 2019). He also explores human-AI alignment through LLM Processes (NeurIPS 2024) and Sycophancy in Language Models (ICLR 2024). Canada Research Chair (2025) NSERC Grant (2025) Sloan Research Fellow (2021) Schwartz Reisman Chair (2021) Best Paper Award (NeurIPS 2018) Distinguished Paper Award (ICFP 2021) His students include James Requeima , Jesse Bettencourt , and Raymond Douglas . He teaches courses on Statistical Methods for Machine Learning and Differentiable Inference . Current work (2025) investigates systemic human disempowerment through incremental AI capabilities and sabotage risk mitigation via hyperparameter-aware evaluations.
James C. Hoe is Professor of Electrical and Computer Engineering at Carnegie Mellon University (College of Engineering). He is on sabbatical at MangoBoost and directs research in computer architecture, reconfigurable computing, and high-level hardware design. Education Ph.D., Electrical Engineering and Computer Science, MIT (2000) M.S., Electrical Engineering and Computer Science, MIT (1994) B.S., Electrical Engineering and Computer Science, UC Berkeley (1992) Research Interests Professor Hoe’s work spans computer architecture , reconfigurable computing , FPGA architectures , and high-level hardware synthesis . His group created the CoRAM abstraction for virtualized FPGA computing and leads efforts in power-efficient accelerators, in-network computing, and security-oriented FPGA systems. Scientific Awards IEEE Fellow (2013) Intel Outstanding Researcher Award (2021) Research Funding & Projects Intel / VMware Crossroads 3D-FPGA Academic Research Center – co-leading exploration of FPGA roles in future datacenters. DARPA BRASS program ($2.7 M, 4 years) – ensuring long-lived software systems remain robust to resource changes. Pigasus open-source IDS – world’s fastest FPGA-accelerated intrusion-detection system (100 Gb/s on one server). Labs & Teams He heads activities within the Computer Architecture Lab at Carnegie Mellon (CALCM) , supervising graduate researchers on CoRAM++, SPIRAL autotuning, and FPGA overlays for stream processing.
Björn Brandenburg is a researcher at the Max Planck Institute for Software Systems (MPI-SWS) in Kaiserslautern, Germany. His work focuses on real-time systems, scheduling algorithms, and operating system design, with a particular emphasis on predictable resource allocation and performance guarantees in multiprocessor and cyber-physical environments. His research interests include real-time response-time analysis (e.g., PROSA ), locking protocols for multiprocessor systems, side-channel mitigation in cloud environments, and the verification of real-time scheduling policies. He has contributed to foundational studies on deadline failure probabilities, self-suspending tasks, and predictable real-time Linux implementations. Scientific awards include recognition for outstanding papers on TimerShield (2017) Offline Equivalence (2017) . His work intersects with practical systems like LITMUSRT and ROS 2, aiming to bridge theoretical guarantees with real-world applications in safety-critical and distributed real-time systems.
René Jr Landry is a full Professor in the Department of Electrical Engineering at École de technologie supérieure (ETS), Université du Québec, specializing in Global Navigation Satellite Systems (GNSS), avionics, and wireless communication technologies. His academic journey includes a B.Ing. from Polytechnique Montréal, M.Sc. from University of Surrey (UK), and Ph.D. from SupAréo in Toulouse. He maintains active research leadership through two key laboratories: LASSENA (Laboratory of Space Technologies, Embedded Systems, Navigation and Avionics) and LACIME (Communications and Microelectronic Integration Laboratory). His research spans critical aerospace navigation domains including GNSS signal processing, inertial navigation systems, software-defined radio for avionics, radio frequency interference mitigation, and indoor positioning technologies. Landry's work addresses real-world challenges in satellite navigation robustness, precision positioning in urban/denied environments, and next-generation avionic system security. His current projects focus on blockchain-enhanced IoT security, AI-driven GNSS disruption analysis, and adaptive RF front-ends for multi-band avionics applications. Analysis of his recent publications reveals strong emphasis on resilient positioning systems through multi-constellation integration (particularly Iridium-NEXT), blockchain applications for navigation security, and explainable AI techniques for GNSS signal quality assessment. His work increasingly bridges traditional navigation engineering with cutting-edge security and machine learning paradigms. 2014 Prix d'excellence du c.a. pour les services à la collectivité Landry has supervised over 100 graduate students across doctoral, master's, and research projects since 2005, with current supervision extending through Summer 2025. His research funding supports multiple industry partnerships focused on avionics certification, software-defined radio implementations, and next-generation navigation systems. The LASSENA laboratory under his leadership develops certified avionic products from open-source SDR platforms and advances multi-sensor fusion techniques for challenging navigation environments. His research infrastructure includes specialized facilities for GNSS signal simulation, avionics hardware testing, and multi-sensor integration. Current work emphasizes flight-tested validation of RF front-end technologies, blockchain-secured navigation data, and real-time interference mitigation systems for aviation applications.
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.
Pavel Panchekha is an Assistant Professor in the School of Computing at the University of Utah, where he holds the Warnock Chair for Junior Faculty. His research spans programming languages, web browsers, and numerical analysis, with a focus on developing programming language techniques to address challenges across computer science. Dr. Panchekha received his educational training at prestigious institutions: PhD in Computer Science from the Paul G. Allen School for Computer Science and Engineering at the University of Washington, advised by Michael D. Ernst and Zachary Tatlock BS in Mathematics from MIT Panchekha's research program has two major thrusts. First, he works on web browser internals , with projects including fuzzing layout invalidation, multi-tenant garbage collection, and optimizing 2D graphics. He is also authoring a textbook on web browsers that informs much of this research. Second, he focuses on automatic numerical analysis , with projects such as automatic accuracy improvement, synthesis via term rewriting, scalable static accuracy analysis, and math library implementation. He leads the FPBench and Herbie projects, which are major deployments of his research. His scholarly output demonstrates consistent contributions across programming languages, verification, and numerical methods. Recent work shows a growing emphasis on bidirectional typing systems, layout invalidation in browsers, and robust floating-point error analysis. His publications reveal a trajectory from foundational work on floating-point accuracy (notably the Herbie tool that won a Distinguished Paper Award at PLDI 2015) toward more comprehensive systems for program synthesis, verification, and browser optimization. Panchekha has received significant recognition for his research contributions: NSF Fellowship ARCS Foundation Fellowship Adobe Research Fellowship Wissner-Slivka Foundation Fellowship 2015 PLDI Distinguished Paper Award for work on the Herbie numerical analysis and repair tool As an advisor, Panchekha mentors a substantial group of students across multiple levels. He currently advises six students: Marisa Kirisame (PhD), Bhargav Kulkarni (PhD), Yumeng He (PhD), Artem Yadrov (MS), Jesus Ponce (BS), and Jonas Regehr (BS). Previously, he has advised over twenty students including PhD candidates like Ian Briggs and numerous MS and BS students. His advising spans theoretical topics in programming languages and practical applications in web browsers and numerical computing. Panchekha leads research groups focused on programming languages applications to web browsers and numerical analysis. His work on the Herbie tool for floating-point accuracy improvement has become influential in the programming languages community, and his more recent work on browser internals is shaping how researchers understand and optimize modern web rendering engines. He is currently developing a textbook on web browsers that aims to synthesize knowledge about browser architecture and implementation.
Zachary Tatlock is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where he leads the Programming Languages & Software Engineering Group (PLSE) and the SAMPL Group. His research spans programming languages, formal verification, compilers, and computational fabrication. He is also an Amazon Scholar with AWS's Automated Reasoning Group and previously advised OctoML. Tatlock's work bridges theoretical foundations with practical systems, focusing on making it easier to write tricky code while ensuring correctness through rigorous proofs and measurements. PhD in Computer Science & Engineering, University of California, San Diego (2014) Thesis: Reducing the Costs of Proof Assistant Based Formal Verification Advisor: Sorin Lerner BS in Computer Science (Honors) and Mathematics, Purdue University (2007) Professor Tatlock's research focuses on the intersection of programming languages, formal methods, and systems. His work in compilers and formal verification aims to make it easier to write tricky code while ensuring correctness through rigorous proofs. He explores computational fabrication techniques that bridge digital design with physical manufacturing. His recent work on equality saturation (via the egg framework) has transformed program optimization and synthesis. Tatlock also investigates floating-point numerics, distributed systems verification, and hardware/software co-design, always seeking to balance theoretical rigor with practical implementation. Tatlock's recent publications demonstrate a strong focus on equality saturation techniques (egg framework), computational fabrication, and verified systems. His work increasingly integrates machine learning with program analysis and synthesis. There's a clear trajectory toward more practical applications of formal methods in real-world systems, particularly in numerical computing and fabrication. His research group has made significant contributions to e-graph technology, floating-point accuracy, and the verification of distributed systems. Distinguished Paper Award for Rewrite Rule Inference Using Equality Saturation (OOPSLA 2021) Spotlight Paper Award for Dynamic Tensor Rematerialization (ICLR 2021) Distinguished Paper Award for egg: Fast and Extensible Equality Saturation (POPL 2021) Faculty Appreciation for Career Education & Training (FACET) Award (2020) NSF CAREER Award: Verifying Distributed System Implementations (2017) Distinguished Paper Award for Automatically Improving Accuracy for Floating Point Expressions (PLDI 2015) Distinguished Teaching Award Nomination (2015) Professor Tatlock has advised numerous doctoral, master's, and undergraduate students who have gone on to prominent positions in academia and industry, including faculty positions at the University of Utah and Brown University, and leadership roles at companies like OctoML and Certora. His research is supported by significant funding from NSF, DARPA, DOE, and industry partners, totaling millions of dollars. Current grants include projects on computer-aided reasoning, formal verification, computational fabrication, and machine learning systems. He has served on numerous program committees and organized workshops including FPTalks, EGRAPHS, and PNW PLSE. As co-leader of the Programming Languages & Software Engineering (PLSE) research group and affiliate of the SAMPL Group at the University of Washington, Tatlock has developed influential tools including egg (an equality saturation toolkit), Carpentry Compiler, and Odyssey. His group actively collaborates with industry partners including Amazon Web Services, where he serves as an Amazon Scholar. The group has made significant contributions to equality saturation, floating-point accuracy, program synthesis, and computational fabrication, with applications ranging from compiler optimization to 3D printing.
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 .
Gagandeep Singh is a tenure-track Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC). His work focuses on creating intelligent computing systems with formal guarantees about behavior and safety, integrating Machine Learning, Formal Methods, and Systems research. Affiliation: University of Illinois at Urbana-Champaign; VMware Research Research Interests: Formal Methods, Machine Learning, Artificial Intelligence, Programming Languages, Neural Network Verification, Automatic Differentiation His research emphasizes scalable verification techniques for neural networks, abstract interpretation, and systems integration. Recent work trends include applying formal methods to ensure safety in deep learning models and optimizing numerical analysis through domain decomposition and convex hull approximations. He contributes to academic communities as a committee member in conferences like POPL, VMCAI, PLDI, and SAS, while authoring key publications in top venues such as POPL, PLDI, OOPSLA, and SAS.
Dilian Gurov is a Professor in Computer Science at KTH Royal Institute of Technology, associated with the Digital Futures Faculty and the Division of Theoretical Computer Science. He also coordinates the Doctoral Programme in Computer Science at the CSC school. Before joining KTH in 2002, he earned a Ph.D. from the University of Victoria, Canada (1998), and worked at the Swedish Institute of Computer Science (1997-2002). His research focuses on software specification and verification, including contracts, program models, logics, and tools, as well as multi-agent strategic planning involving knowledge-based strategies in imperfect information settings. Key contributions include the CAV Distinguished Paper Award 2023 for 'Automatic Program Instrumentation for Automatic Verification' and an EASST award for 'Checking Absence of Illicit Applet Interactions: A Case Study' (2004). He leads projects funded by VR (SEFROS, ContraST) and Vinnova (AVerT2) and collaborates with industries like Scania on formal verification of C programs. His service roles span over 30 conference committees and organization roles, including PC memberships for iFM, TAP, and ISoLA. Teaching responsibilities include courses such as 'Formal Methods,' 'Program Semantics and Analysis,' and 'Knowledge in Games with Imperfect Information.' His work emphasizes practical applications of formal methods, bridging academic research with industry needs through collaborations and tool development (e.g., CVPP, ProMoVer, TriCo).
Susanna de Rezende is an Assistant Professor in the Department of Computer Science at Lund University (LTH). She is affiliated with the ELLIIT initiative on IT and mobile communication, the LTH Profile Area: AI and Digitalization, and the MIAO group collaborating with the University of Copenhagen. Her research focuses on computational complexity, proof complexity, circuit complexity, and communication complexity. She holds a PhD from KTH Royal Institute of Technology (2019) and a Master's from the University of São Paulo (2014). Her research explores connections between proof systems, circuit lower bounds, and communication complexity, with recent contributions to lifting theorems, automatability, and average-case hardness. She has received awards including the Stockholm Mathematics Centre Prize and Wallenberg Academy Fellow status. Current projects include funded PhD positions in theoretical computer science and editorial work for ZML: Zeitschrift für Mathematische Logik und Grundlagen der Mathematik. Key articles address proof complexity trade-offs, clique hardness in Sherali-Adams, and graph coloring challenges. Collaborations span institutions like the Czech Academy of Sciences and the Simons Institute. She advises multiple PhD students and collaborates on foundational research in complexity theory, supported by WASP, ELLIIT, and VR grants.
Andrea Vitaletti is an Associate Professor at Sapienza University of Rome , affiliated with the Department of Computer Engineering, Automatics and Management Antonio Ruberti (DIAG) in the College of Engineering. His academic career spans over two decades of research in networking and algorithmic topics. PhD in Computer Science, Sapienza University of Rome (1998–2002) Assistant Professor (Ricercatore) at Sapienza (2007–2019) Co-founder of spin-offs WSENSE (2012–2019) and WLAB (2002–2016) Research Interests focus on decentralized systems , particularly blockchain technologies , Internet of Things (IoT) , federated machine learning , and data privacy . His work bridges theoretical algorithmic research with practical implementations in wireless sensor networks and distributed ledger systems. Scientific Contributions include over 90 publications, 2 patents, and leadership in the EU FET OPEN project PLEASED. His applied research has been recognized with multiple awards: 2000: Wonderland Contest - Media and Communication 2002: Simagine Innovation Prize 2004: Simagine Bronze Award 2007: Premio Perotto Top Prize 2012: Italiacamp Winner He leads the Wireless Sensor Networks lab at DIAG, supervising 2 PhD students, 1 post-doc, and 5 master students. His teaching portfolio includes courses on IoT, blockchain, cybersecurity, and digital entrepreneurship since 2000.
Tiark Rompf is an Assistant Professor at Purdue University , with research spanning programming languages, compilers, and systems. His work bridges domains including architecture, databases, machine learning, and AI through projects like Reachability Types and Rhyme. Co-director of the Purdue Center for Programming Principles and Software Systems (PurPL) Scientific Advisor at SambaNova Systems Previously a member of the Scala team at EPFL His research focuses on: Runtime code generation and advanced compiler technology Expressive data-centric query languages (Rhyme, Datalog) Reachability type systems for memory safety and effect handling Metaprogramming and logical relations for formal verification Recent publications highlight contributions to Datalog compilation (Flan), nested data structures (Rhyme), and polymorphic reachability types. He leads projects exploring: Compiler optimizations for emerging architectures (GPU, TPU, FPGA) ML-driven compiler improvements Secure multi-party computation via metaprogramming Scientific awards include: NSF CAREER Award (2016) Google Faculty Research Awards (2017, 2018) DOE Early Career Research Award (2017) ACM SIGPLAN PL Software Award (2019) GPCE Test of Time Award (2020) Students and alumni from his group have joined institutions like Databricks, DeepMind, Galois, and Meta. He teaches advanced compiler courses including: CS 590 - Advanced Topics in Compilers CS 352 - Compilers CS 502 - Graduate Compilers
Thomas Stoll is a tenured Professor at the Faculty of Science and Technology , University of Lorraine, Nancy, France. He leads research in Analytic and Combinatorial Number Theory , focusing on Diophantine equations , digital expansions , and sum-of-digits functions . He is affiliated with the IECL (Institut Élie Cartan de Lorraine) and has coordinated ANR-FWF research projects like MuDeRa and ArithRand .
Jasmin Blanchette is a Professor of Theoretical Computer Science and Theorem Proving at Ludwig-Maximilians-Universität München (LMU), where he also serves as the Dean of Studies for Computer Science since January 22, 2024. He is affiliated with the Institute for Informatics and leads the Theoretische Informatik und Theorembeweisen research unit. Additionally, he is a guest researcher in the VeriDis group at Loria, Nancy. Research Interests: His research centers on strengthening proof automation for general-purpose logics and enhancing the usability of proof assistants. He combines automatic and interactive methods, bridging human and artificial intelligence in formal verification. His work spans higher-order logic, automated and interactive theorem proving, formalization of mathematical results, and foundational mechanisms for (co)datatypes and (co)recursive functions. Key projects include Sledgehammer, Nitpick, Matryoshka, Nekoka, IsaFoL, and Lean Forward. Publication Trends: His recent publications (2023–2025) show a strong focus on higher-order automated reasoning, superposition calculus, proof automation in Isabelle/HOL, and formalization of logical and mathematical concepts. There is a consistent emphasis on verification, efficiency, and integration of SAT/SMT techniques into higher-order provers. Scientific Awards: FroCoS 2023 Best Paper Award (with Visa Nummelin and Sander Dahmen) CADE 2023 Best Paper Award for 'Verified given clause procedures' (with Qi Qiu and Sophie Tourret) IPA Dissertation Award (awarded to student Petar Vukmirović) Dutch Prize for ICT Research 2022 Advising and Grants: He supervises a large team of postdocs and PhD students at LMU and co-supervises students at other institutions. His leadership in major collaborative projects like Matryoshka indicates significant grant funding and collaborative research efforts. He is editor-in-chief of the Journal of Automated Reasoning and serves on numerous steering and program committees, reflecting strong academic leadership and visibility. Labs and Teams: He leads a research group at LMU’s Institute for Informatics, focusing on theorem proving and formal methods. He is also associated with the VeriDis group at Loria, Nancy, and collaborates widely across Europe in the automated reasoning community.
