David I. August is a Professor at Princeton University specializing in programming languages and compiler systems. His research bridges theoretical compiler techniques with practical systems implementation, focusing on memory safety, speculative execution, and compiler optimization. His primary research interests include Compiler Design , Rust Programming Language safety mechanisms , and LLVM infrastructure extensions . His work emphasizes practical implementations that enhance both performance and security in modern programming systems. Recent publications demonstrate consistent contributions to memory profiling frameworks (PROMPT), Rust safety enhancements, and speculative dependence analysis. His research shows strong focus on making low-level systems programming safer without sacrificing performance. August serves regularly on program committees for major conferences including PLDI and CGO, indicating his standing in the programming languages research community. He has mentored students in compiler construction and programming language design, with research projects often involving practical implementations integrated into production-quality compiler frameworks.
Sang Kil Cha is an Associate Professor at KAIST's Graduate School of Information Security and School of Computing, where he also serves as Director of the Cyber Security Research Center (CSRC). His research focuses at the intersection of computer security and software engineering, with emphasis on building and evaluating systems that analyze programs. Dr. Cha received his B.S. from Korea University, and both his M.S. and Ph.D. from Carnegie Mellon University (CMU). His educational background forms the foundation for his experimental approach to computer science research. His primary research interests include software security, software engineering, program analysis, binary code analysis, and fuzzing. Dr. Cha's work centers on developing practical security tools and methodologies that bridge theoretical concepts with real-world applications, particularly in program analysis and vulnerability detection. His research has significant implications for improving software reliability and security through advanced analysis techniques. Dr. Cha's publication record shows a strong focus on fuzzing techniques, binary analysis, and program understanding, with recent work expanding into blockchain security and decompilation. His research consistently appears in top-tier security and software engineering conferences including IEEE S&P, USENIX Security, and CCS. ACM Distinguished Paper Award (2024, 2022, 2014) USENIX Distinguished Paper Award (2023) IEEE Best Paper Award (2021) NDSS Best Paper Award (2019) As Director of CSRC and leader of SoftSec Lab at KAIST, Dr. Cha oversees multiple research projects focused on practical security solutions. His lab develops tools like B2R2 (a binary analysis framework) and OFuzz (a fuzzing platform), which have gained recognition in the security community. Dr. Cha actively contributes to the research community through program committee roles at major conferences including PLDI, ICSE, and ISSTA.
Anaïs Bohuon is a Professor of Sociology and History of Sport at the Faculty of Sports Sciences, University of Paris-Saclay. She is also Co-responsible of the SCOS research team. Her academic career has focused on examining the intersection of gender, sports, and the body through historical and sociological lenses. Bohuon obtained her PhD in December 2008 from the University of Paris-Saclay (then University Paris-Sud), with research focusing on medical discourses and women's access to physical and sporting activities between 1880-1922. Her work has established her as a leading expert on gender verification practices in sports, particularly the controversial femininity tests that have been imposed on female athletes since 1966. Her research adopts a multidisciplinary approach at the crossroads of history, sociology, and medical studies. She examines how sports have served as sites for the naturalization of gender power relations, with particular attention to how medical discourse has shaped women's participation in athletics. Her work reveals the genealogy of contemporary femininity norms by studying the historical techniques applied to the body. Bohuon frequently collaborates with historian Grégory Quin, and together they explore how muscles have contributed to the construction of 'sex' and contemporary definitions of sexual difference. Analysis of Bohuon's publications reveals consistent focus on gender verification practices, the historical construction of sex categories in sports, and the intersection of gender with race and class in athletic contexts. Her work spans sports history from the 19th century to contemporary issues, particularly examining how medical power has been exercised through sports institutions to regulate bodies according to gender norms. Bohuon is actively engaged in public discourse on gender and sports, frequently participating in conferences, media appearances, and public events. She has contributed to popular media projects like the series 'SPORTIVE' that addresses gender equality in sports, and has been featured in numerous radio broadcasts and documentaries, including ARTE's 'Toutes musclées' (2022) and discussions about the Paris 2024 Olympics. Her scholarly work extends beyond traditional academic publications to include significant public engagement. She regularly collaborates with media outlets, participates in cultural events related to the Paris 2024 Olympics, and contributes to educational initiatives aimed at addressing gender stereotypes in sports. Her research has practical implications for contemporary sports policy, particularly regarding transgender and intersex athlete inclusion.
Pedro M. B. Silva Girão is a Full Professor in the Department of Electrical Engineering at Instituto Superior Técnico (IST), University of Lisbon (UL), and a Senior Researcher at Instituto de Telecomunicações where he heads the Instrumentation and Measurements Group and coordinates the Basic Sciences and Enabling Technologies area. His dual institutional roles position him at the forefront of academic research and technological innovation in Portugal. His research program focuses on instrumentation, transducers, and measurement techniques with specialized applications in biomedical and environmental domains. Key interests include wireless sensor networks for health monitoring, metrology standards, and digital data processing methodologies. This work bridges engineering principles with real-world healthcare and ecological challenges, emphasizing practical implementations in diagnostic systems and environmental sensing. Analysis of his 2019-2024 publications reveals a strong thematic trajectory in IoT-enabled healthcare solutions and precision environmental monitoring. Recurring motifs include gait rehabilitation through mixed reality systems, advanced dosimetry for liver cancer radioembolization, microvascular reactivity assessment, and water quality sensor networks. His output demonstrates consistent interdisciplinary collaboration between engineering, medical, and environmental science communities. Dr. Girão's scientific recognition includes: IEEE Senior Member status IEEE IMS Distinguished Lecturer appointment Honorary Chairmanship of IMEKO TC19—Environmental Measurements As leader of the Instrumentation and Measurements Group at Instituto de Telecomunicações, he directs a multidisciplinary team developing next-generation measurement systems. Current initiatives integrate microwave Doppler radar, wearable biopotential sensors, and wireless networks for unobtrusive health monitoring and environmental assessment, with active partnerships across medical institutions and ecological agencies.
Ioan Todinca is a Professor of Computer Science at the University of Orléans, France, affiliated with the LIFO (Laboratoire d'Informatique Fondamentale d'Orléans) research laboratory. His academic career spans over two decades, with significant contributions to theoretical computer science, particularly in graph algorithms and distributed computing. Faculty of Science, University of Orléans LIFO Research Laboratory Member of Institut thématique pluridisciplinaire Modélisation, Systèmes, Langages (since 2014) Former director of MIPTIS doctoral school (2012-2014) Former head of Computer Science degree program (2007-2011) Former leader of LIFO Graphs, Algorithms and Computational Models team (2008-2012) Todinca's research focuses primarily on graph algorithms, with expertise in exact algorithms (moderately exponential), parameterized algorithms, and algorithms for specific graph classes. He has made significant contributions to techniques involving tree decompositions, treewidth, minimal separators, and potential maximal cliques. More recently, his work has expanded into distributed algorithms, especially in communication-constrained models like the broadcast congested clique. His research bridges theoretical foundations with practical algorithmic approaches for NP-hard problems. The analysis of his recent publications reveals a strong trend toward distributed computing problems, particularly in congested network models. His work spans from fundamental graph theory problems (cycle detection, graph modification) to applications in quantum computing and model checking. The consistent focus on communication complexity, verification, and efficient algorithms across different computational models demonstrates his ability to adapt theoretical computer science principles to emerging computational paradigms. Todinca has supervised numerous PhD students and has been actively involved in the theoretical computer science community through conference organization and editorial work. His publications appear consistently in top-tier venues including SIAM Journal on Computing, Algorithmica, and proceedings of major conferences like STACS, WG, and DISC. Teaching responsibilities include algorithms, graph theory, and discrete structures for undergraduate and graduate students, with previous experience teaching databases, programming, and software engineering. His educational materials are hosted on the university's Celene platform.
Miryung Kim is a Professor and Vice Chair of Graduate Studies in UCLA's Computer Science Department, where she directs the Software Engineering and Analysis Laboratory. She is renowned for her pioneering work in software evolution, code clone management, and establishing the emerging field of Software Engineering for Data Intensive Computing (SE4DA and SE4ML). Her research focuses on automated testing and debugging for Apache Spark, developer tools for heterogeneous computing, and conducting systematic studies of refactoring practices in industry. She led the first large-scale study of data scientists in industry and developed JDebloat, a Java bytecode debloating tool that made significant tech transfer impact to the Navy. Her recent publications demonstrate strong trends in fuzz testing for big data analytics and heterogeneous computing, with a focus on natural input generation, co-dependence awareness, and leveraging hardware probes for acceleration. Her work bridges software engineering with data-intensive and heterogeneous computing paradigms. ACM SIGSOFT Influential Educator Award (2022) ICSME Most Influential Paper Award (2023 and 2020) NSF CAREER award Google Faculty Research Award Okawa Foundation Research Award Humboldt Fellow ACM Distinguished Member As an academic advisor, she has produced eight tenure-track faculty members at institutions including Columbia, Purdue, and Virginia Tech. Her research has been supported by National Science Foundation, Air Force Research Laboratory, Google, IBM, Intel, Okawa Foundation, Samsung, and Office of Naval Research. She previously served as Program Co-Chair of ESEC/FSE 2022 and has delivered keynotes at ASE 2019 and ISSTA 2022. She maintains active industry collaborations, serving as an Amazon Scholar at Amazon Web Services and having spent time as a visiting researcher at Microsoft Research.
Clément Pit-Claudel is an Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL), leading the SYSTEMF lab focused on programming languages, formal methods, and systems engineering. His work bridges mathematical formalisms with practical system development to achieve full assurance in critical software and hardware. PhD in Computer Science from MIT (2016) William A. Martin Memorial Thesis Award recipient Former Senior Applied Scientist at Amazon AWS Teaching accolades including the Frederick C. Hennie III Teaching Award Research spans three axes: extensible proof-producing compilers for performance-critical systems, verified hardware compilation with cycle-accurate semantics, and interactive theorem prover tooling for democratizing verification technology. Key projects include Kôika for hardware verification, Alectryon for Coq proof visualization, and Fiat for correct-by-construction program synthesis. Recent publications address JavaScript regex verification (ICFP 2024), cryptographic server integration (PLDI 2024), and hardware simulation optimization (ASPLOS 2021). Articles demonstrate expertise in functional-to-imperative translation, domain-specific compiler extensions, and hardware-software co-verification. Scientific contributions recognized through: Distinguished artifact award (SLE 2020) MIT William A. Martin Thesis Award Frederick C. Hennie III Teaching Award Teaching philosophy emphasizes hands-on lab instruction , oral assessment , and automated tooling . Courses taught include Software Construction (undergraduate) and Interactive Theorem Proving (graduate) at EPFL. Research service includes program committee roles at Dafny, POPL, and SPLASH conferences.
Marco Porta is a Full Professor at the University of Pavia, Department of Electrical, Computer and Biomedical Engineering. He teaches Web and Multimedia Technologies in the Computer Engineering Master's program and Web Design and Technologies in the interdepartmental CIM Bachelor's program. His research focuses on Eye Tracking, Vision-Based Perceptive Interfaces, and Human-Computer Interaction, with recent emphasis on AI applications for human-centered systems. He leads the Computer Vision & Multimedia Lab and chairs teaching councils for CIM and CoD programs. Education: Master's in Electronic Engineering (Polytechnic of Milan) and Ph.D. in Electronic & Computer Engineering (University of Pavia). Professional roles include vice-chair of IEEE's Technical Committee on Factory Automation. Over 118 publications in journals/conferences, with contributions to biometrics, e-learning interfaces, and industrial automation. Research highlights include gaze-based authentication systems, interactive museum interfaces, and ergonomic in-vehicle infotainment evaluations. Current projects explore gaze-driven intelligent tutoring systems and public space interaction frameworks.
Professor Michael Winikoff is a prominent academic at Victoria University of Wellington's School of Information Management, where he joined in June 2019 and served as Head of School from early 2021 to early 2025. Previously, he was Head of Department at University of Otago's Department of Information Science (February 2011 to December 2016) and Associate Professor at RMIT University's School of Computer Science and IT. His career spans over two decades of research in autonomous systems and agent-oriented software engineering. His educational background includes a PhD from the University of Melbourne (1994-1997). His research focuses on improving software creation methodologies, particularly for intelligent agents that exhibit robust and flexible behavior. He is best known for developing the Prometheus methodology for agent-based systems design. More recently, his work has expanded to address societal consequences of autonomous systems and trust issues, with significant contributions to explainable AI (XAI). His publication record demonstrates consistent contributions to autonomous systems research, with recent work focusing on explainability frameworks, trust calibration, and certification of reliable autonomous systems. His 15 most recent publications (2018-2025) show a clear evolution from technical agent design toward broader societal implications, particularly the intersection of technical design and human trust in autonomous systems. The publications span journals like Artificial Intelligence and IEEE Internet Computing, as well as major conferences including AAMAS. Past President of International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) Co-Editor-in-Chief of Journal of Autonomous Agents and Multi-Agent Systems (JAAMAS) Chair of ICORE rankings management committee Editor-in-Chief for International Journal of Agent-Oriented Software Engineering (IJAOSE) Vice President of Computing Research and Education Association of Australasia (CORE) Professor Winikoff has led significant research projects funded by the Australian Research Council, including work on adaptive personae for interactive toys, service-oriented negotiation in multi-agent systems, and advanced software engineering for intelligent agent systems. His current research continues this trajectory, focusing on making autonomous systems more explainable and trustworthy through engineering approaches that consider both technical and human factors. He maintains active collaborations across institutions, with recent work involving researchers from RMIT University and other international partners.
Lindsey Westover, PhD, PEng, serves as an Associate Professor in the Department of Mechanical Engineering and Associate Dean in the Faculty of Engineering at the University of Alberta. Her research and teaching activities are centered in the Biomedical Engineering program, with her laboratory located in the Donadeo Innovation Centre for Engineering (13-224, 9211 116 St, Edmonton, AB T6G 2H5). She maintains an active research profile while contributing to academic leadership through her deanship. Her educational background includes: 2018: Postdoctoral Fellowship in Rehabilitation Medicine, University of Alberta 2016: Ph.D. in Mechanical Engineering, University of Alberta 2011: M.Sc. in Mechanical Engineering, University of Calgary 2007: B.Sc. in Mechanical Engineering, University of Calgary Dr. Westover's research program spans biomechanics and biomedical engineering with emphasis on noninvasive assessment of biological structures, vibration analysis for percutaneous implants, joint biomechanics (ligaments and cartilage), spinal deformity analysis through asymmetry metrics, mechanical testing of biological tissues, and computational modeling of biological systems. Her work integrates laboratory experiments, computational methods, and in vivo studies to develop innovative diagnostic and therapeutic approaches. Analysis of her 15 most recent publications (2018-2020) reveals consistent focus on bone mechanics, implant stability, and symmetry analysis across orthopedics, audiology, and dentistry. Key themes include osseointegration evaluation using ASIST technology, pelvic/spinal deformity quantification, and computational modeling of biological structures. Her work appears in high-impact journals spanning engineering and clinical disciplines, demonstrating strong interdisciplinary collaboration. Scientific recognition includes: Nomination for Ear and Hearing 2018 Editor's Award for bone conduction device research Dr. Westover mentors graduate students through co-authorship on numerous publications and teaches core mechanical engineering courses including MEC E 451 (Vibrations and Sound), MEC E 390 (Numerical Methods), and MEC E 200 (Introduction to Mechanical Engineering). Her research is supported by collaborative grants with clinical partners and engineering colleagues. She leads biomechanics research within the Department of Mechanical Engineering, collaborating extensively with the Faculty of Rehabilitation Medicine and surgical departments. Her laboratory develops advanced testing systems like ASIST for implant stability evaluation across hearing devices and dental applications, while her computational work informs clinical approaches to scoliosis management and fracture reconstruction.
Yuhong Nan is an Associate Professor in the School of Software Engineering at Sun Yat-sen University, China, specializing in software security and privacy leakage analysis for emerging platforms including IoT, mobile systems, and blockchain. Previously a Post-doctoral Research Associate at Purdue University under Prof. Dongyan Xu, she builds practical security tools to detect and mitigate vulnerabilities in real-world systems. Dr. Nan earned her PhD from Fudan University in 2018 supervised by Prof. Min Yang. Her academic journey spans rigorous research in security engineering with emphasis on empirical validation and tool development for complex platform ecosystems. Her research program focuses on uncovering systemic security flaws through innovative analysis techniques. Key contributions include vulnerability detection in smart contracts (e.g., state dependencies, reentrancy), privacy leakage analysis in mobile/IoT ecosystems, and countermeasures against deceptive UI patterns. She employs hybrid approaches combining static/dynamic analysis, machine learning, and large-scale empirical studies to develop deployable security solutions. Analysis of her 15 most recent publications (2023-2025) reveals dominant themes in blockchain security (60%), particularly smart contract/DApp vulnerabilities, with significant work in mobile privacy (30%) and cross-platform threats (10%). Her methodology consistently leverages fine-grained static analysis, semantic enrichment, and feedback-driven fuzzing, yielding tools like SmartAxe and Midas that have influenced industry practices. Dr. Nan actively mentors graduate researchers with 17 advisees including Tencent-employed graduates, and serves as a trusted reviewer for premier journals (IEEE TDSC, TMC, TOPS) and conference committees (ASIACCS, ICICS). Her leadership in security communities bridges academic research with practical defense mechanisms. At Sun Yat-sen University, she directs a high-output research group that collaborates with industry partners to address evolving threats in decentralized systems, maintaining her position among top publishing authors in USENIX Security, CCS, and NDSS venues through rigorous technical innovation.
Claire Le Goues is a Professor of Computer Science at Carnegie Mellon University, primarily affiliated with the Software and Societal Systems Department (S3D) within the School of Computer Science (SCS). She serves as the Associate Department Head for Faculty within S3D and leads the squaresLab research group. Le Goues also co-directs the REUSE@CMU summer program and teaches software engineering and program analysis at undergraduate, master's, and PhD levels. Her research spans software engineering and programming languages, with a particular focus on how to construct, maintain, evolve, improve/debug, and assure high-quality software systems. Le Goues has made significant contributions to automated program repair, program analysis, and defect detection. Her work often bridges theoretical foundations with practical applications, addressing real-world challenges in software development and maintenance. Le Goues' recent publications demonstrate a clear trend toward integrating large language models and generative AI with traditional software engineering techniques. Her research examines how these technologies can enhance program repair (BatFix, AdverIntent-Agent), vulnerability detection (Interpretable Vulnerability Detection Reports), and testing (LWDIFF for WebAssembly). This represents an evolution from her earlier foundational work in program repair (GenProg) toward leveraging contemporary AI advancements. She has mentored numerous students through her squaresLab research group and has been instrumental in developing educational programs that prepare the next generation of software engineers. Le Goues is also known for her advocacy for double-blind review processes in academic conferences, having implemented this approach when co-chairing the Symposium for Search-Based Software Engineering in 2014.
Nicolás Quesada is an Associate Professor in the Department of Engineering Physics at Polytechnique Montréal, where he holds the MEI Chair in Quantum Photonics. He serves as Director of COPL (Centre d'optique, photonique et laser) and is a member of INTRIQ (Institut transdisciplinaire d'informatique quantique). His research program focuses on quantum information, quantum computing, and quantum optics, with particular emphasis on photonic implementations of quantum technologies. Dr. Quesada earned his B.Sc. in Physics from Universidad de Antioquia in 2010, followed by M.Sc. and Ph.D. degrees in Physics from the University of Toronto. During his doctoral studies, he was awarded both Vanier and Stoicheff scholarships. Prior to joining Polytechnique Montréal, he worked at Xanadu Quantum Technologies as lead developer of the Strawberry Fields and The Walrus software libraries, where he led theoretical efforts demonstrating photonic quantum advantage. His research interests span quantum photonics, quantum computing, and quantum optics, with specific focus on Gaussian Boson Sampling, squeezed light generation, non-Gaussian light sources, and quantum benchmarking techniques. His group develops theoretical frameworks and computational tools for next-generation quantum light sources needed for fault-tolerant quantum computers, quantum communication networks, and quantum sensors. His work bridges theoretical quantum information science with practical photonic implementations. Analysis of his recent publications reveals a strong focus on advancing Gaussian Boson Sampling as a platform for quantum advantage, developing mathematical frameworks for quantum optics, and engineering practical photonic quantum devices. His work spans from fundamental quantum optics to applied quantum computing, with increasing emphasis on verification and benchmarking of quantum computational advantage. Dr. Quesada has received notable recognition including the Vanier Canada Graduate Scholarship and the Stoicheff Scholarship during his doctoral studies. His research has attracted significant funding, including a $6 million grant for quantum projects at Polytechnique Montréal announced in January 2025 and involvement in a $1.91 million NSERC quantum sensing project led by Professor Denis Seletskiy. He has supervised two Master's students to completion in 2024: Dalbec-Constant, N. who worked on photon counting from transition-edge sensors, and Zhao, J. who researched optimal pumps for spontaneous parametric down-conversion. His research group collaborates extensively with both academic and industry partners in the quantum technology sector. As Director of COPL, he oversees one of Canada's leading photonics research centers, facilitating interdisciplinary research across quantum optics, classical optics, and laser technologies.
Jingling Xue is a Scientia Professor at the School of Computer Science and Engineering at the University of New South Wales (UNSW) in Sydney, Australia. As an IEEE Fellow of the Computer Society, he leads the Programming Languages and Compilers research group, focusing on practical applications of compiler optimization and program analysis techniques. His work bridges theoretical foundations with real-world software systems, particularly in developing open-source tools for large-scale program analysis. Professor Xue received his B.Eng and M.Eng degrees from Tsinghua University in 1984 and 1987, respectively, followed by a PhD from the University of Edinburgh in 1992. His academic journey has established him as a leading figure in programming languages and compiler technology. Xue's research spans programming languages, compiler technology, and program analysis with emphasis on practical relevance. His current projects include compiler techniques for improving parallelism and locality, pointer/alias analysis for million-line-scale programs, and static/dynamic analysis for detecting bugs and security vulnerabilities in real-world applications like web browsers and Android apps. His group actively develops open-source tools to support scientific replicability and reproducibility in these areas. His recent publications demonstrate a strong focus on applying program analysis techniques to modern challenges including AI compilers, homomorphic encryption, security vulnerability detection, and graph processing systems. The work shows evolution from traditional compiler optimization to addressing emerging domains like privacy-preserving computation and deep learning systems while maintaining rigorous theoretical foundations. Scientific Awards: Best Paper Award at CGO'13 Best Paper Award at CGO'16 Distinguished Paper Award at ECOOP'16 Distinguished Paper Award at ICSE'18 Distinguished Paper Award at ISSTA'19 Distinguished Paper Award at ASE'19 Distinguished Artifact Award at ISSTA'23 Best Artifact Award at FSE'23 Distinguished Paper Award at ASE'23 Test-of-Time Award at CGO'21 Professor Xue has successfully supervised 30 PhD students to completion, many of whom now work as professors or researchers in academia and industry. He has served as Program Chair for major conferences including LCTES'13, CC'18, CGO'20, and General Chair for LCTES'20. His group currently focuses on memory safety in Rust, smart contract analysis, AI compilers, compilation for privacy-preserving computation, and adversarial attacks in deep learning. The Programming Languages and Compilers group maintains strong connections with industry partners, translating theoretical advances into practical tools for real-world software development challenges. Their work on pointer analysis, memory safety, and compiler optimizations continues to influence both academic research and industrial practice.
Shaohua Li is an Assistant Professor at The Chinese University of Hong Kong (CUHK), specializing in the correctness and security of critical software systems with emphasis on compilers. His research spans Software Engineering , Programming Languages , and Security , focusing on innovative compiler testing methodologies. Key areas include leveraging large language models for test generation, optimizing fuzzing techniques through prefix-guided execution, and decoupling sanitization mechanisms to reduce overhead in vulnerability detection. His work addresses fundamental challenges in ensuring reliability of systems programming infrastructure. Recent publications demonstrate a cohesive trajectory toward practical compiler validation: from empirical rustc bug analysis to SAND's low-overhead sanitization framework. The research consistently bridges theoretical formal methods with real-world implementation challenges in security-critical systems, showing particular strength in adapting AI techniques for traditional software testing problems.
