David Menendez is an Assistant Professor in the Department of Computer Science at Rutgers University. His research focuses on programming languages, compiler design, and formal methods. He has received prestigious awards including the ACM SIGPLAN John C. Reynolds Dissertation Award and the Best Paper Award at PLDI 2015. His work emphasizes compiler correctness, memory safety, and static analysis. Education: PhD in Computer Science from Rutgers University (inferred from his 2016 PhD student mention in the text). Research Interests: Formal verification of compilers Compiler optimization techniques Memory safety in low-level programming Automated testing and debugging tools Awards: Best Paper Award at PLDI 2015 ACM SIGPLAN John C. Reynolds Dissertation Award Distinguished Paper at ICSE 2016 Grants and Advising: Collaborates with Prof. Santosh Nagarakatte on compiler research. Current advising details are not specified in the text. Labs/Teams: Likely affiliated with Rutgers' Programming Languages and Software Engineering research groups.
Dr. Yiren Zhao is an Assistant Professor (Lecturer) in Computer Engineering at Imperial College London, part of the Faculty of Engineering. He leads the DeepWok Research Lab and holds affiliations with the UKRI Artificial Intelligence for Engineering Biology Consortium and the University of Cambridge as a Visiting Researcher. His work focuses on Large-scale GenAI Systems, emphasizing hardware-algorithm co-design, efficiency, and security. He has secured over £5M in funding since 2022 and reviews for top conferences like ICLR, ICML, and NeurIPS. Dr. Zhao earned a BEng in Electrical and Electronic Engineering from Imperial College London (2016), followed by an MPhil and PhD in Computer Science from the University of Cambridge (2017–2022). His research spans GenAI acceleration, unstructured data processing (e.g., graphs), and system-level AI safety. Recent projects include MASE (unified ML system exploration) and ImpNet (imperceptible backdoor attacks). Awards: Apple Scholar in AI/ML (2020), Microsoft Research Award (2023), and Junior Research Fellowship at St John’s College (2021). Labs/Teams: DeepWok Lab (20+ members), involved in Imperial-X and AI-4-EB initiatives. Grants: Industry/government-funded projects totaling over £5M since 2022. His work bridges computer systems and AI, with notable contributions to quantization, adversarial attacks, and hardware-aware optimization. Collaborations include the Center for Spatial Computational Learning and CaRAML group.
Marco Guarnieri is an Associate Research Professor at the IMDEA Software Institute in Spain. He holds a PhD in Computer Science from ETH Zurich (2017), an MSc in Computer Engineering from the Università degli Studi di Bergamo (2012), and a BSc in Computer Engineering from the same institution (2010). His research focuses on secure hardware-software co-design, microarchitectural side-channel attacks, and formal methods for verifying security guarantees. Education : PhD in Computer Science, ETH Zurich (2017) MSc in Computer Engineering, Università degli Studi di Bergamo (2012) BSc in Computer Engineering, Università degli Studi di Bergamo (2010) Research Interests : Security, privacy, programming languages, formal methods, and microarchitectural security. His work emphasizes practical systems for securing sensitive data storage and processing, with recent focus on leakage contracts for open-source processors and automated testing of secure speculation countermeasures. Awards : Best Paper Award at CCS 2024 for work on leakage contracts for RISC-V processors Distinguished Paper Award at CCS 2023 for Spectre attack detection Best Paper Award at S&P 2021 for hardware-software contracts for secure speculation Grants & Advising : He leads a research group at IMDEA, actively mentoring PhD students and postdocs in hardware-software security. His projects include AMuLeT (automated testing of secure speculation) and LeaVe (verifying leakage contracts). Labs/Teams : IMDEA Software Institute’s security research group, focusing on cross-layer hardware-software security solutions.
Giles Reger is a Lecturer in the Formal Methods Group within the School of Computer Science at the University of Manchester. His primary roles include research and teaching in theorem proving, runtime verification, and formal methods. He has been actively involved in projects such as the Centre for Digital Trust and Society and the SCorCH project focusing on secure code verification. Educational background: Giles holds a BA in Computer Science from the University of Cambridge (2009), an MSc in Advanced Computer Science from the University of Manchester (2010) with the Highest Achiever of the Year Award, and a PhD from the University of Manchester (2014) titled Automata based monitoring and mining of execution traces . Research interests focus on two core areas: theorem proving (quantifier reasoning, first-order theories, collaborative proof search, and integration of SAT/SMT solvers) and runtime verification (temporal specifications, monitoring algorithms, violation explanation, and benchmarking). His work emphasizes practical applications in tool development and real-software analysis. Notable awards include the ACM SIGSOFT Distinguished Paper Award (2024) for his paper on LLM-generated invariants. His research contributions span over 50 publications, with active involvement in funded projects like SCorCH (Secure Code for Capability Hardware) and the Centre for Digital Trust and Society. Advising and grants: Reger welcomes PhD/MSc students in theorem proving, program verification, and related fields. He has supervised multiple research students and leads collaborative projects involving international researchers. His lab, the Formal Methods Group, develops tools like the Vampire theorem prover and contributes to runtime verification frameworks.
Christophe Hauser is an Assistant Professor at Dartmouth College and a member of the Institute for Security, Technology and Society (ISTS). His research focuses on software security, binary program analysis, reverse engineering, and vulnerability discovery across software and hardware systems. He integrates formal methods, machine learning, and program analysis to enhance cybersecurity defenses. Education: Joint PhD from CentraleSupélec (France) and Queensland University of Technology (Australia). Prior roles include Research Lead at USC Information Sciences Institute (USC-ISI) where he founded the Binary Analysis and Systems Security (BASS) group, and postdoctoral researcher at UC Santa Barbara’s Seclab. Research Interests: Binary code and firmware analysis, intrusion detection, usable security, privacy-preserving systems. Notable projects include BinPool (vulnerability dataset), BinHunter (vulnerability localization), and Harm-DoS (DoS mitigation). His work emphasizes practical applications such as automated fuzzing, decompilation analysis, and neuro-symbolic code search systems. He has contributed to open-source tools like angr and developed frameworks for firmware integrity validation (BootKeeper).
Arie Gurfinkel is a Professor at the University of Waterloo, holding a joint appointment in the Department of Electrical and Computer Engineering and the Cheriton School of Computer Science. His research focuses on automated program analysis, software model checking, automated reasoning, and abstract interpretation. He develops tools like SeaHorn, Avy, and others to enhance the verification and testing of complex computer systems. His work emphasizes formal methods, machine learning integration, and hardware/software verification. Recent publications highlight advancements in interpolation-based model checking, constrained Horn clauses, and algorithm selection for hardware verification. Gurfinkel's contributions include open-source tools and frameworks widely used in academic and industrial verification efforts. He actively seeks motivated graduate students interested in logic, automated reasoning, and formal methods. His research has been presented in top-tier conferences and journals, reflecting his expertise in formal verification and software engineering.
Waleed Meleis is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University and serves as Vice Provost for Graduate Education. He holds an MS and PhD from the University of Michigan and a BSE from Princeton University. His primary research focuses on combinatorial optimization, machine learning, assistive technology, and large-scale social experimentation platforms like Volunteer Science. He pioneered the Enabling Engineering student group, which designs assistive devices for individuals with disabilities, supported by over $350K in external funding. His leadership roles include Interim Vice Provost for Oakland Campus and Associate Dean for Graduate Education, driving significant enrollment growth and program development. Notable awards include multiple Martin W. Essigmann Teaching Awards and the Eta Kappa Nu Professor of the Year Award. His work bridges technical innovation with societal impact, particularly in healthcare and education. Education: PhD, Computer Science and Engineering, University of Michigan, 1996 MS, Computer Science and Engineering, University of Michigan, 1992 BSE, Electrical Engineering, Princeton University, 1990 Research: Combines algorithm design for engineering problems (e.g., cloud computing, spectrum management), social science experimentation platforms, and assistive technology development for rehabilitation. Leadership: Vice Provost for Graduate Education since 2023 Interim Vice Provost and Academic Lead for Oakland Campus (2023–2024) Associate Dean for Graduate Education (2020–2022) Awards: Recognized for teaching excellence and innovation in education across multiple years, including the 2010 Eta Kappa Nu Professor of the Year Award. Publications: Over 50 peer-reviewed papers in areas spanning reinforcement learning, distributed systems, and biomedical engineering. Grants: Secured funding from NSF, Army Research Lab, and private foundations for projects including Volunteer Science and Enabling Engineering initiatives. His interdisciplinary Dialogue of Civilizations course explores scientific revolutions, blending historical and computational perspectives. Enabling Engineering has delivered 60+ projects with clinical partners, emphasizing inclusive engineering education.
Cristian Ene is a Researcher at Grenoble Alpes University and a member of the VERIMAG Laboratory. He holds a PhD in Computer Science (2001) from Grenoble Alpes University. His primary roles include teaching and conducting research in formal verification of cryptographic protocols, computer security, and distributed systems. He is actively involved in developing automated tools for cryptographic protocol analysis, such as contributions to the Tamarin Prover framework. Research Interests : His work focuses on formal methods for verifying cryptographic systems, including model counting, security protocol analysis, and decidability in process calculi. He explores topics such as information flow control, fault-injection countermeasures, and automated theorem proving for asymmetric encryption. Publications : His recent work spans formal verification techniques, optimization in Max#SAT solving (e.g., BaxMC), and cryptographic protocol analysis. Earlier contributions include foundational studies on process decomposition in π-calculus and formal security models in the random oracle framework. Teaching : He teaches courses on cryptographic engineering, formal verification of security protocols, programming languages, and compiler design. Course materials include slides, assignments, and practical exercises using tools like Tamarin Prover. Labs & Teams : He is affiliated with the VERIMAG Laboratory, which specializes in formal methods and embedded systems research. His work integrates theoretical foundations with practical applications in secure system design and automated verification.
Natasha Sharygina is a Full Professor of Informatics at the University of Lugano (USI) in Switzerland. She leads the USI Formal Verification and Security group, focusing on improving software and hardware verification through formal methods like model checking and SAT/SMT techniques. Her research emphasizes applying these methods to computer security, electronic design, and program analysis. Education: PhD in Informatics from The University of Texas at Austin (2002). Research Interests: Her work spans formal verification, model checking, SMT-based solvers, and security analysis. She develops theoretical frameworks and practical tools for verifying large-scale systems, with applications in safety-critical and distributed computing environments. Funding & Awards: Her research has been supported by grants from the Swiss National Science Foundation, EU STReP/COST projects, Hasler Foundation, and TASSO Career Award. She has been recognized with the ACM Recognition of Service Award and CMU Technical Excellence Awards. Grants & Projects: Key initiatives include 'Beyond Symbolic Model Checking through Deep Modelling' (2019–2023), EU-funded 'Rich-Model Toolkit', and Swiss TASSO Career Award (2005–2010). She has led efforts in parallel SMT solving and runtime verification. Labs & Teams: Director of the USI Formal Verification and Security Lab, which develops tools like Golem (CHC solver) and OpenSMT (SMT solver). Collaborates globally on projects like SAFARI and FunFrog for program verification.
William N. Sumner is an Associate Professor and Associate Director, Academic and Administration in the School of Computing Science at Simon Fraser University. He holds a Ph.D. in Computer Science from Purdue University (2013) and a B.Sc. in Computer Science from Hope College (2005). His research focuses on automated debugging tools, concurrency, parallelism, program analysis, and software quality. He teaches courses such as Software Development Methods, Software Testing, and Automated Software Analysis. Sumner actively recruits graduate and undergraduate students for research in improving software development processes through automation. His work emphasizes reducing repetitive tasks in software development using techniques like test case reduction and program analysis. Education: Ph.D., Computer Science, Purdue University, 2013 B.Sc., Computer Science, Hope College, 2005 Research Interests: Sumner’s research addresses challenges in software development automation, including automated debugging, test suite assessment, and program hardening. He develops tools like Pardis to optimize test case reduction and improve software reliability. His work intersects with concurrency, parallelism, and program transformation to enhance developer productivity and software quality. Recent Contributions: Recent publications include advancements in type batched program reduction (2023) and leveraging models for test case reduction in software repositories (2021). His Pardis framework (2019) improves test case reduction efficiency by addressing priority inversion in structured inputs. Teaching & Engagement: Sumner teaches courses such as CMPT 373 (Software Development Methods), CMPT 473 (Software Testing), and CMPT 479 (Automated Software Analysis). He emphasizes hands-on projects, such as the Geotagged Meeting Planner in CMPT 276, focusing on teamwork, agile methodologies, and software engineering best practices.
Matti Rintala is a University Lecturer at Tampere University's Faculty of Information Technology and Communication Sciences, specifically within the Computing Sciences department. His primary responsibilities include teaching core courses such as Principles of Programming Languages and Functional Programming 1, alongside contributing to Data Structures and Algorithms 1. His expertise spans programming languages, data structures, algorithms, and concurrency. Research interests focus on C++ programming paradigms, concurrency mechanisms, and educational technology. Notable work includes leveraging modern C++ features for high-level synthesis, optimizing exception handling in concurrent systems, and analyzing student preferences in hybrid learning environments. His articles consistently address practical challenges in software engineering and distributed systems. While no formal advising or grant details are provided, his teaching and research contributions highlight a commitment to advancing both theoretical and applied aspects of computing sciences. No scientific awards are documented in the provided materials.
Barton P. Miller is a Vilas Distinguished Achievement Professor and the Amar & Balinder Sohi Professor of Computer Sciences at the University of Wisconsin, Madison, where he has made significant contributions to computer science research and education. As a faculty member in the Computer Sciences Department within the College of Engineering, he directs major research initiatives including the Paradyn Tools project and leads cybersecurity efforts as Chief Scientist of the DHS-funded Software Assurance Marketplace (SWAMP) research center. Miller received his B.A. degree from the University of California, San Diego in 1977, and M.S. and Ph.D. degrees in Computer Science from the University of California, Berkeley in 1980 and 1984. His educational background laid the foundation for his pioneering work in software testing and analysis. His research spans multiple critical areas of computer science, with a primary focus on binary code analysis and instrumentation , software security , and distributed and parallel program performance . Miller is particularly renowned for founding the field of Fuzz random software testing in 1988 and dynamic binary code instrumentation in 1992. His work bridges theoretical computer science with practical applications, addressing real-world challenges in high-performance computing systems, cybersecurity, and scalable distributed systems. His research has direct applications in national security through his work with DHS and TrustedCI, the NSF Cybersecurity Center of Excellence. Miller's publications reveal a consistent focus on binary analysis tools, security vulnerability detection, and performance optimization techniques. His recent work shows increasing emphasis on ransomware analysis, GPU performance optimization, and practical security tool development for developers. The trajectory of his research demonstrates how foundational work in binary instrumentation has evolved to address contemporary cybersecurity challenges while maintaining relevance to high-performance computing environments. Among his notable honors, Miller is a Fellow of the ACM and recipient of the prestigious Jean-Claude Laprie Award in Dependable Computing , an R&D 100 Award , and multiple best paper awards including at HPDC 2009 and CCGrid 2018. His contributions to the field have been recognized through distinguished lectureships at institutions including Ben Gurion University and IBM T.J. Watson Research Center. As an educator, Miller has mentored numerous students and taught courses spanning operating systems, software security, and distributed systems. He has received teaching awards and developed educational resources including free and open software security training materials. His work with TrustedCI has focused on cybersecurity for scientific communities, helping researchers secure their computational infrastructure while maintaining research productivity. Miller also co-directs the MIST software vulnerability assessment project in collaboration with colleagues at the Autonomous University of Barcelona. Miller directs the Paradyn Tools project, which investigates program scalability and binary program analysis technologies for use in HPC, systems design, and cyber-security. His work extends to practical applications through collaborations with government agencies including DHS and the U.S. Secret Service Electronic Crimes Task Force. His research group has developed tools like Dyninst, MRNet, and the Wisconsin Safety Analyzer that have become foundational in their respective domains.
Rajit Manohar is the John C. Malone Professor of Electrical & Computer Engineering at Yale University, with appointments in Applied & Computational Mathematics and Computer Science. He is a core member of the interdisciplinary Computer Systems Lab (CSL), which bridges ECE and CS departments. His research focuses on asynchronous VLSI design, neuromorphic computing, and hardware-software co-design. Education: Manohar holds a B.S., M.S., and Ph.D. from the California Institute of Technology. His academic career spans over two decades, with notable contributions to asynchronous circuit theory and neuromorphic engineering. Research Interests: Manohar's work emphasizes energy-efficient asynchronous architectures, concurrency control, and biologically inspired computing. He explores topics like formal methods for circuit verification, cognitive systems, and dynamic sensor networks. His lab develops tools like Fluid (asynchronous synthesis) and Neurobench (neuromorphic benchmarking). Publications: Recent work includes advancements in asynchronous logic synthesis (Maelstrom), neuromorphic frameworks (Neurobench), and scalable brain-computer interfaces (SCALO). His research often intersects NSF-funded projects in energy-aware computing and neuromorphic systems. Awards: Inaugural Misha Mahowald Prize (2025), MIT TR35 (2000s), IBM Goldberg Award (2023) Grants & Labs: Manohar leads NSF-supported initiatives in carbon-aware networking and neuromorphic hardware. The Computer Systems Lab collaborates across disciplines to advance sustainable computing and neuro-inspired architectures.
Michael Gullans is an Adjunct Assistant Professor in the Department of Physics, Department of Computer Science, and the Institute for Advanced Computer Studies (UMIACS) at the University of Maryland. He is also a physicist in the Nanoscale Device Characterization Division at NIST. His research focuses on quantum information systems, quantum simulators, and fault-tolerant computing, emphasizing error correction, noise mitigation, and statistical physics applications in many-body quantum dynamics. Gullans holds a PhD from Harvard University (2013) and has held postdoctoral positions at QuICS and Princeton University. His work bridges theoretical quantum computing and experimental implementations, with contributions to quantum error correction protocols, analog quantum simulation, and the interplay of disorder and noise in quantum systems. Recent publications address scalable quantum architectures, low-depth random circuits, and hybrid fermion-qubit systems. He teaches advanced courses on quantum technology and quantum error correction. Key collaborations include NIST, QuICS, and institutions exploring silicon spin qubits and reconfigurable atom arrays. His research aims to advance fault-tolerant quantum computation and reliable quantum simulators for studying complex systems.
Mark Santolucito is an Assistant Professor of Computer Science at Barnard College, Columbia University. He holds a PhD in Computer Science from Yale University, where his research focused on program synthesis and computer music. His current work explores program synthesis techniques to enhance programmer productivity, particularly in lowering barriers to entry for underrepresented groups and optimizing workflows for advanced developers. He leads the Barnard PL (Programming Languages) Labs, which develops tools like TSL (Temporal Stream Logic) for synthesizing reactive systems and analyzing infrastructure-as-code (IaC). His research intersects formal methods with creative applications in music and live coding, emphasizing accessibility and usability. Education: PhD in Computer Science (Yale University), focusing on program synthesis and computer music. Research interests include program synthesis, temporal logic specifications, infrastructure configuration analysis, and music technology. He emphasizes human-centered design in his work, aiming to make programming more accessible through tools like TSL and interactive synthesis environments. Projects include TSL Move Cube, Block-based Editor for Temporal Logic, and Spiral Analysis for medical software migration. Notable contributions include developing TSL synthesis pipelines, optimizing Arduino configurations, and exploring static analysis for cost prediction in cloud deployments. His work bridges theoretical foundations with practical applications in both software engineering and creative computing. Labs/Teams: Leads Barnard PL Labs, collaborating on projects like TSL Synthesis Engine and Static Analysis for IaC. Active in workshops such as SEConfig and FMCAD.
