جست‌وجوی استاد و پژوهشگر

Antonio Bianchiمشاهده پروفایل

استادیار

• Computer Security
• Systems Security
• Software Security
• +۹ مورد دیگر

Antonio Bianchi is an Assistant Professor in the Department of Computer Science at Purdue University, co-founder of the PurSec Lab. His research focuses on enhancing security of edge devices such as smartphones, IoT devices, drones, and embedded systems. He has developed novel techniques in program analysis, binary analysis, fuzzing, reverse engineering, program repair, and binary patching. He is a core member of the Shellphish, OOO, and Nautilus CTF teams and won third place in the DARPA Cyber Grand Challenge. Education: PhD in Computer Science, UC Santa Barbara (2018) MSc in Computer Science, University of Illinois at Chicago (2012) MSc and BSc in Computer Engineering, Politecnico di Milano (2012 and 2008) Research Interests: His work spans software and systems security, with a focus on automated vulnerability detection, secure patching, and defense mechanisms for edge devices. He has published extensively at top venues like USENIX Security, IEEE S&P, and NDSS, and received awards including the NSF CRII Award and Purdue's Undergraduate Advising Award. Articles Overview: His recent work includes groundbreaking studies on Bluetooth protocol vulnerabilities, robotic vehicle patch validation, and secure IoT firmware updates. Articles often combine formal methods with practical tools like angr and fuzzing techniques. Awards: Seed for Success Acorn Award (Purdue, 2023 & 2024) Undergraduate Advising Award (Purdue CS, 2024) Best Paper Award at WOOT 2020 NSF CRII Award (2019) Advising & Grants: He has advised PhD students now in academia and industry, and secured grants totaling over $10M from agencies like DARPA, NSF, and industry partners (Lockheed Martin, Google). His lab focuses on projects like FIREFLY (cyber-physical systems modeling) and DICER (assured patching). Labs & Teams: Co-founder of the PurSec Lab at Purdue, focusing on edge device security. Collaborates with Shellphish team on CTF competitions and automated hacking research.

Liu Yangمشاهده پروفایل

استاد

• Cybersecurity
• Software Engineering
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Liu Yang is a full Professor and University Leadership Forum Chair at the School of Computer Science and Engineering, Nanyang Technological University (NTU). He holds the President’s Chair in Computer Science and Engineering and serves as Executive Director of the Cyber Research Programme Office and Cyber Security Research Centre @ NTU. His research focuses on Cybersecurity, Software Engineering, and Artificial Intelligence, with contributions in formal verification, program analysis, and deep learning systems. He leads projects like the Securify initiative and develops tools such as the Process Analysis Toolkit (PAT) for system verification. Education: Ph.D. (2010) and Bachelor of Computing Science (2005) from National University of Singapore. Research Interests: Cybersecurity (malware analysis, vulnerability detection), Software Engineering (formal verification, program analysis), AI (security, robustness, explainability), and Automotive Security. His work bridges formal methods, program analysis, and machine learning to address challenges in secure systems and autonomous systems. Notable Achievements: Over 6000 citations (2020), H-index 38, awards include Nanyang Assistant Professor (2013), NRF Investigatorship (2020), and ACM Distinguished Speaker. His research spans journals like IEEE Transactions on Software Engineering and conferences such as NeurIPS, CVPR, and ICSE. Grants and Leadership: Principal Investigator of grants totaling over 5M SGD, including projects on vulnerability detection, formal verification, and cybersecurity. Organizes international conferences like ASE, ICSE, and FM, and serves on editorial boards such as IEEE Access. Labs/Teams: Leads the Cyber Security Research Centre @ NTU and collaborates on projects like the HP-NTU Digital Manufacturing Corp Lab and the National Satellite of Excellence in Singapore.

Andreas Zellerمشاهده پروفایل

استاد

• Software Security
• Automated Software Debugging
• Software Testing and Analysis
• +۳ مورد دیگر

Andreas Zeller is a Full Professor of Computer Science at Saarland University and a faculty member at CISPA Helmholtz Center for Information Security in Germany. His research focuses on software engineering, automated debugging, and software testing/analysis, with foundational contributions like Delta Debugging and the SZZ algorithm. He has held academic positions since 2001 and leads projects funded by ERC grants, including the 'Semantics of Software Systems (S3)' initiative. Education: Ph.D. in Computer Science (1997, focused on software versioning). Research interests include mining software repositories, input grammar inference, fuzzing, and open science practices. He has authored influential papers (e.g., 'Mining Software Histories to Guide Software Changes' with over 1,700 citations) and interactive textbooks like The Fuzzing Book and The Debugging Book . Key awards include ACM Fellow (2010), ERC Advanced Grants (2011, 2023), and multiple 10-Year Most Influential Paper Awards. His group at CISPA/Saarland includes PhD students and postdocs working on testing, debugging, and security.

Weihang Wangمشاهده پروفایل

استادیار

• Software Engineering
• Software Security
• Computer Systems
• +۶ مورد دیگر

Weihang Wang is a WiSE Gabilan Assistant Professor in the Department of Computer Science at the University of Southern California. His research focuses on building testing and analysis techniques to improve the reliability, security, and efficiency of complex software systems, with particular expertise in WebAssembly technologies. Wang received his Ph.D. in Computer Science from Purdue University in 2018. His educational background has provided a strong foundation for his research in software engineering and security, leading to numerous publications and awards in the field. His research spans multiple critical areas including WebAssembly analysis , software security , and program analysis . Wang's work addresses fundamental challenges in detecting and mitigating vulnerabilities in modern web applications and systems. His research group develops innovative approaches to static and dynamic analysis, bug detection, and security testing, with a strong emphasis on practical applications and real-world impact. Recent projects include developing frameworks for Spring analysis, WebAssembly function identification, and business flow tampering detection. Wang's publication record shows a clear trajectory of increasing impact in WebAssembly research, with multiple papers at top-tier conferences like WWW, ICSE, and FSE. His work spans from foundational analysis techniques to practical tools that address security and performance challenges in web technologies, demonstrating both theoretical depth and practical applicability. His scientific achievements have been recognized with prestigious awards including: N2Women Rising Stars in Networking and Communications (2024) University at Buffalo Exceptional Scholar - Young Investigator Award (2022) NSF CAREER Award (2021) Facebook Testing and Verification Research Award (2019) Mozilla Research Award (2019) Maurice H. Halstead Memorial Research Award (2018) Best Poster Award at ACSAC'22 Wang has successfully advised numerous graduate and undergraduate students, many of whom have published first-author papers at top conferences and secured positions at leading technology companies. He actively serves the research community through program committee roles at major software engineering and security conferences. His work has been supported by competitive grants from NSF, Facebook, and Mozilla, demonstrating the significance and potential impact of his research directions. At USC, Wang leads a vibrant research group focused on software engineering, security, and systems. The group is currently working on cutting-edge projects related to static/dynamic bug detection, program analysis for WebAssembly, attack investigation and detection, compiler testing, and performance profiling of modern web applications.

DongGyun Hanمشاهده پروفایل

استادیار

• Software Engineering
• Code Review
• Empirical Study
• +۲ مورد دیگر

DongGyun Han is a Lecturer (equivalent to Assistant Professor) in the Department of Computer Science at Royal Holloway, University of London. His research specializes in Software Engineering, with emphases on Empirical Study, AI for Software Engineering (AI4SE), Software Engineering for AI (SE4AI), and Code Review. He holds a PhD from University College London (UCL), an MPhil from Hong Kong University of Science and Technology (HKUST), and a B.Eng from Jeju National University. Dr. Han's research integrates empirical methods with AI techniques to address challenges in software maintenance, code quality, and developer productivity. His work spans automated code review, defect prediction, vulnerability repair, and AI model applications in software artifacts. He actively collaborates with industry partners including Amazon Web Services. His recent publications focus on leveraging large language models for software tasks, analyzing dataset biases, and improving automated developer tools. Common themes include empirical validation of AI techniques, security enhancement, and optimizing developer workflows. Awards: No scientific awards mentioned in source materials. Academic Service: Dr. Han contributes extensively to program committees for top-tier conferences including ICSE, FSE, ASE, and MSR. He has chaired tracks at ICTSS 2024 and reviewed for journals including TOSEM, EMSE, and JSS. Affiliations: Previously affiliated with Singapore Management University's SOftware Analytics Research (SOAR) group and Secure Mobile Centre. Maintains industry connections through past roles at Amazon Web Services.

Prateek SAXENAمشاهده پروفایل

دانشیار

• Computer Security
• Machine Learning Security
• Trustworthy AI
• +۴ مورد دیگر

Prateek SAXENA is an Associate Professor in the Computer Science Department at the School of Computing, National University of Singapore. He serves as Co-Director of the CRYSTAL Centre and teaches courses including CS3235 Computer Security and CS5562 Trustworthy Machine Learning. His research spans multiple domains within computer security and systems. Dr. SAXENA earned his Ph.D. in Computer Science from the University of California, Berkeley (2012), an M.S. in Computer Science from Stony Brook University (2007), and a B.E. in Computer Engineering from the University of Pune, India (2004). His research focuses on building better security and privacy in practical systems through principled approaches combining formal reasoning, tools and ideas from several computer science domains. Current research thrusts include machine learning security, decentralized systems security, security processors, and automatic program translation. His work has resulted in several practical artifacts powering real-world systems, including spinoffs like Zilliqa and Kyber Network. His publication record demonstrates consistent high-impact research across security domains including web security, blockchain, trusted execution environments, and machine learning security. His work shows a progression from foundational web security research to cutting-edge work on blockchain systems and machine learning security. MIT Technical Review, Top 10 Innovators under 35, Asia - 2017 Security and Privacy Research Award, 2018 Young Research Award, NUS, 2017 David J. Sakrison Memorial Prize for outstanding doctoral work, UC Berkeley, 2012 AT&T Best Applied Security Research Paper Award 2010 Dr. SAXENA has advised numerous successful PhD students who have gone on to prominent positions at Microsoft Research, Georgia Tech, ETH Zurich, and industry leaders like Zilliqa and Kyber. His research has been generously supported by CISCO Research, Google, Intel, Symantec, MoE-Singapore, DSO Labs, and NRF-Singapore. He leads the KISP Lab (Keep It Secure and Private), which has produced influential research in blockchain, trusted execution environments, and security tools.

• Epidermolysis Bullosa
• Genetic Disorders
• Clinical Trials
• +۴ مورد دیگر

Johann Bauer is a Senior Lecturer and Head of the Research Program for Molecular Therapy in Genodermatoses at the University Clinic for Dermatology and Allergology. He leads critical research initiatives in genetic skin diseases, with a focus on epidermolysis bullosa and related disorders. Role: Head of Department and Research Program Expertise: Molecular therapy, clinical trials, RNA editing His research spans genetic skin diseases , clinical trial design , and therapeutic development , with recent work on gene deletion mechanisms in Kindler syndrome and drug repositioning for chronic wounds. He has contributed to 2025 publications in epidermolysis bullosa , soft tissue infections , and oncology . Bauer's projects include "First in EB" Phase II trials of Rigosertib and the PACE study for critical limb ischemia, alongside collaborations with teams like Zimmermann and Laimer. He organizes FIZ Network! Seminars and participates in events like the ÖGDV Science Days .

Utpal Boraمشاهده پروفایل

پژوهشگر

• Computer Architecture
• Programming Languages
• Semantics
• +۳ مورد دیگر

Utpal Bora is a Researcher at the University of Cambridge's Department of Computer Science and Technology. His research focuses on Programming Languages, Semantics, Verification, and Computer Architecture with an emphasis on static analysis of parallel programs, compiler optimization techniques, and performance analysis. He has contributed to projects such as LLOR (automated OpenMP program repair) and Llov (static data-race detection for OpenMP). His work bridges compiler design, parallel computing, and formal methods to improve software reliability and hardware efficiency. Research Interests: Static Analysis of Parallel Programs Compiler Optimization (LLVM) Data-Race Detection in OpenMP Instruction-Level Parallelism (ILP) Performance Modeling (CPI Analysis) Formal Verification of Concurrent Systems Recent work trends show a focus on enhancing parallel programming correctness through automated repair and static analysis tools, alongside optimizing code execution via compiler-level transformations and hardware architecture improvements. His contributions address critical challenges in parallel computing scalability and compiler-driven performance enhancement.

Eric Koskinenمشاهده پروفایل

دانشیار

• Software Verification
• Concurrency
• Programming Languages
• +۵ مورد دیگر

Eric Koskinen is the Charles Berendsen Associate Professor (with tenure) of Computer Science at Stevens Institute of Technology in Hoboken, New Jersey. He is also a co-founder of the Commute Workshop at PLDI 2022 and has previously held positions as Researcher at Yale University and Visiting Professor at New York University. Education: Ph.D. in Computer Science, University of Cambridge (UK) Research Interests: Koskinen's research lies at the intersection of software verification , programming languages , and concurrency . He develops automated techniques to ensure reliable and efficient software, with a particular emphasis on commutativity analysis , parallelization , and language-level abstractions for multicore and distributed systems. His recent focus includes the Veracity programming language that introduces commute blocks to simplify concurrent programming. Scientific Awards & Honors: POPL 2023 Distinguished Paper Award Provost's Early Career Award for Research Excellence (2020) CAV 2011 Award Paper Advising & Funding: Prof. Koskinen currently advises three Ph.D. students—Adam Chen, Parisa Fathololumi, and Mihai Nicola—and has recently graduated Cyrus Liu (Ph.D. 2022). His research group has been generously supported by more than $5 million in competitive grants from the NSF, ONR, and DARPA. Recent awards include: NSF: Concurrent Objects ($593k, 2023) ONR: AVTA Transition ($215k, 2022) NSF: Dynamic Analysis ($399k, 2021) NSF: Commutativity Analysis ($495k, 2020) ONR: Temporal Alignment ($3.2M, 2017) Labs & Tools: His group maintains an active open-source tool suite including Veracity (interpreter for commute blocks), Servois2 (commutativity synthesizer), Dynamite (termination/non-termination checker), DarkSea (temporal verifier for binaries), CityProver (commutativity verifier), Knotical (trace-refinement synthesizer), and DrNLA (non-linear to linear integer arithmetic rewriter).

Eric A. Rossمشاهده پروفایل

استاد پژوهشی

• Biostatistics
• Bioinformatics
• Clinical Trial Design
• +۷ مورد دیگر

Eric A. Ross is a Research Professor and Assistant Vice President of Biometrics and Information Sciences at Fox Chase Cancer Center, where he directs both the Biostatistics and Bioinformatics Facility and the Population Studies Facility within the Cancer Prevention and Control program. He holds a PhD in Statistics from Temple University, an ScM in Biostatistics from Johns Hopkins University, and a BA in Biological Sciences from the University of Delaware. His research interests include biostatistics, bioinformatics, clinical trial design, cancer research, and health informatics. He specializes in developing innovative statistical methodologies for oncology trials and integrating large-scale data using web-based technologies to improve cancer research and patient outcomes. His recent publications highlight a strong focus on clinical trial methodology, molecular oncology, and data integration. Key themes include risk-adapted therapies for bladder cancer, confounding control in clinical studies, and reproductive factors in breast cancer. His work often involves multicenter collaborations and leverages genomic and epidemiological data to identify biomarkers and optimize treatment strategies. Dr. Ross is a member of the American Statistical Association and the International Biometrics Society. His scientific contributions are reflected in over 200 peer-reviewed publications, with recent work appearing in high-impact journals such as Journal of Clinical Oncology , Annals of Internal Medicine , and Clinical Cancer Research . He leads a multidisciplinary team providing biostatistical and informatics support across clinical, translational, and basic science research at Fox Chase. His lab emphasizes improving research efficiency, data quality, and the application of advanced computational tools in cancer investigations. He has collaborated extensively with researchers in urology, oncology, and epidemiology, contributing to significant advances in personalized cancer therapy and data-driven decision making.

Michael Pradelمشاهده پروفایل

استاد

• Software Engineering
• Program Analysis
• Machine Learning for Code
• +۶ مورد دیگر

Michael Pradel is a Professor at the University of Stuttgart , leading the Software Lab within the Computer Science Department . He is also a faculty member at the International Max Planck Research School for Intelligent Systems and a member of the Stuttgart ELLIS Unit . Education: Studied computer science at TU Dresden and Ecole Centrale Paris , with a master thesis at EPFL . Completed his PhD at ETH Zurich on program analyses for error detection. Research Interests: Focuses on software engineering , machine learning for code , program analysis , quantum software testing , and automated program repair . His work integrates LLMs for tasks like code execution, bug detection, and test generation. Scientific Awards: Ernst-Denert Software Engineering Award Emmy Noether grant (1.3M Euro) by DFG ERC Starting Grant (1.5M Euro) ACM SIGSOFT Distinguished Paper Awards (FSE, ISSTA, ASE, ASPLOS, MSR) ACM Distinguished Member Students: Supervised Matteo (PhD on quantum software testing), Luca Di Grazia (postdoc at USI Lugano), Beatriz Souza , Huimin Hu , and Doehyun Baek (PhD students). Collaborated with visiting professors like Cristian Cadar (Humboldt Research Award). Service: Holds leadership roles in top conferences including PC co-chair for FSE 2027, area chair for ICSE 2026, and associate chair for OOPSLA 2026. Current Projects: Developing techniques like DyLin (dynamic linter for Python), Testora (regression detection via NL intent), and LintQ (static analysis for quantum programs). His lab explores neural software analysis , code search , and LLM agents for program repair.

• Cybersecurity
• Blockchain
• Artificial Intelligence
• +۳ مورد دیگر

Yang Xiang is a Full Professor and Dean of the Digital Research & Innovation Capability Platform at Swinburne University of Technology. He holds a PhD in Computer Science from Deakin University and has over 20 years of experience in cybersecurity research, focusing on network security, blockchain, and AI. As an IEEE Fellow, he serves as Editor-in-Chief for SpringerBriefs on Cyber Security Systems and Networks and Associate Editor for multiple IEEE journals including Transactions on Dependable and Secure Computing. His research integrates AI with cybersecurity to address vulnerabilities in distributed systems and IoT. Key areas include federated learning privacy, blockchain bridge security, and intrusion detection using graph neural networks. He leads Swinburne's blockchain initiatives and has published over 300 papers. Professor Xiang has received the IEEE Fellowship for contributions to cybersecurity. He actively supervises doctoral students in areas like fuzzing tools, 6G security, and automated software testing. His grants include projects on AI-driven manufacturing cybersecurity and distributed energy optimization.

Weihang Wangمشاهده پروفایل

استادیار

• Software Engineering
• Software Security
• Computer Systems
• +۳ مورد دیگر

Weihang Wang is the WiSE Gabilan Assistant Professor of Computer Science at the University of Southern California, located in Los Angeles. His research focuses on software engineering, security, and systems, with an emphasis on improving the reliability and efficiency of complex software systems through testing and analysis techniques. He holds a Ph.D. in Computer Science from Purdue University (2018). His work spans WebAssembly security, static analysis frameworks, decompilation techniques, and automated detection of vulnerabilities like intrusive ads and business flow tampering. Key contributions include tools like WaSCR (side channel repair), WBSan (bug detection), and Jasmine (static analysis for Spring technologies). Education: Ph.D. in Computer Science, Purdue University (2018) Recent research trends reflect a strong focus on WebAssembly's security challenges, leveraging AI and neurosymbolic approaches (e.g., StackSight). His grants include NSF support for static analysis frameworks and industry awards from Facebook and Mozilla. Awards: N2Women Rising Stars (2024), NSF CAREER (2021), and multiple industry recognitions Advising and grants highlight collaborations with NSF and tech companies. He advises students/post-docs on topics like automated testing and cybersecurity. His work bridges theoretical software analysis with practical system implementations.

Aseem Rastogiمشاهده پروفایل

پژوهشگر

• Programming languages
• Type systems
• Program verification
• +۴ مورد دیگر

Aseem Rastogi is a Senior Principal Researcher at Microsoft Research India specializing in programming languages, type systems, program verification, and software security. He is a core designer and developer of F*, a language for program verification, and has made significant contributions to Project Everest, which builds verified secure communications components including cryptographic libraries and parsers. Dr. Rastogi earned his PhD from the University of Maryland, College Park under Michael Hicks and completed his M.S. at Stony Brook University with Rob Johnson. His research spans formal methods, programming language theory, and practical security applications, with recent work focusing on integrating Large Language Models with formal verification techniques. His publication record demonstrates expertise across multiple domains including concurrent separation logic, secure multi-party computation, and verified systems programming. Recent work shows a clear trend toward applying LLMs to traditional verification challenges, with publications on memory safety, Rust compilation error fixing, and loop invariant generation. Dr. Rastogi has served on numerous conference program committees including as PC co-chair for ISEC 2024 and Diversity, Equity, and Inclusion co-chair for POPL 2024. He has organized workshops such as VeriCrypt and taught F* at multiple summer schools, demonstrating strong commitment to academic community building. As part of Project Everest, he collaborates across Microsoft Research labs to develop verified security-critical components. His work on EverParse has hardened attack surfaces through formally proven parsers, while CrypTFlow enables secure medical image analysis through privacy-preserving machine learning techniques.

• Cybersecurity
• Software Security
• Phishing Detection
• +۴ مورد دیگر

Adam Doupé is a full professor at Arizona State University, specializing in cybersecurity and software security. His research focuses on automated vulnerability analysis, phishing detection, binary decompilation, and security in web technologies. Key research areas include: Cybersecurity Software Security Phishing and Fraud Detection Binary Analysis Automated Vulnerability Discovery His recent work explores large-scale phishing mitigation using machine learning (e.g., ScamNet), improving binary decompilation techniques (e.g., SAILR), and analyzing fraud browser detection via fingerprints. Trends show a strong emphasis on practical security tools, human-centric security analysis, and firmware vulnerability discovery. While no specific awards or grants are listed in the DBLP data, Doupé actively contributes to security education through frameworks like SENSAI and CTF-as-a-service. He collaborates extensively with researchers such as Yan Shoshitaishvili, Ruoyu Wang, and Tiffany Bao.