Find Academic Supervisors

Saumya DebrayView profile

Professor

• Compilers
• Program Analysis
• Code Optimization
• +5 more

Saumya Debray is a Professor at the Department of Computer Science , University of Arizona , with research interests in Compilers , Program Analysis and Optimization , and Programming Language Implementation . Their work bridges theoretical and applied computer science, focusing on security implications of program transformations and compiler-assisted system optimization. Education: Ph.D., The State University of New York at Stony Brook (1986). Contact: Office: GS 735 | Phone: 520-621-4527 | Email: debray@cs.arizona.edu. Research Themes: Debray’s research spans three decades, with core contributions in: JIT Compiler Analysis: Bug localization, dynamic code generation, and exploitation frameworks. Code Obfuscation & Stylometry: Evading detection through optimization-based obfuscation. Malware Analysis: Deobfuscation techniques, taint analysis, and dynamic defense modeling. Binary Rewriting: Energy optimization, code compaction, and kernel specialization. Their work intersects compiler design , cybersecurity , and system optimization , with applications in executable analysis , malware detection , and undergraduate CS education .

• Computer Architecture
• Non-Volatile Memory Systems
• Deep Learning Systems
• +3 more

Jishen Zhao is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, San Diego (Jacobs School of Engineering). His research focuses on computer architecture, non-volatile memory systems, and deep learning acceleration. Dr. Zhao has published extensively in top venues including ISCA, MICRO, ASPLOS, and IEEE Transactions. He collaborates with researchers at UCSD and beyond to advance systems for emerging applications in AI and autonomous vehicles. Dr. Zhao's primary research areas include persistent memory systems, hardware/software co-design for deep learning, and safety-critical computing. He develops techniques for crash consistency, memory disaggregation, and efficient neural network deployment. His work on autonomous vehicles addresses scenario generation and perception-aware system design. Recent projects explore LLM applications for software engineering and hardware verification. Analysis of Dr. Zhao's 2024-2025 publications reveals a strong shift toward AI-integrated systems research. He applies large language models to tasks like RTL verification and software issue localization while continuing to innovate in memory systems for serverless computing. There is growing emphasis on safety-critical systems for autonomous vehicles and energy-efficient neural network training using novel hardware architectures. Information about Dr. Zhao's scientific awards, advising activities, grants, and laboratory facilities was not available in the provided documentation.

Joachim RosenthalView profile

Professor

• Coding Theory
• Cryptography
• Algebraic Geometry
• +2 more

Joachim Rosenthal is a Professor of Applied Mathematics at the University of Zurich's Department of Mathematics, leading the Applied Algebra Group. His research integrates coding theory, cryptography, and algebraic geometry with applications in communications and security systems. His primary research explores algebraic coding theory including convolutional codes, subspace codes, and post-quantum cryptography. He develops algorithms for error correction, code optimization, and cryptographic protocol analysis, with emphasis on mathematical structures in finite fields and rings. Professor Rosenthal serves as President of the Swiss Mathematical Society (2024-2025) and sits on IEEE Information Theory Society's Board of Governors. He has organized multiple international conferences on coding theory and cryptography, including the Zurich COST Meeting and Workshop on Convolutional Codes. His editorial contributions include roles at Archiv der Mathematik and SIAM Journal on Applied Algebra and Geometry. Recent publications focus on code construction methods, complexity analysis in group-based cryptography, and algebraic approaches to error-correcting codes.

• Security and Privacy
• Internet Measurement
• Data Mining
• +4 more

Gang Wang is an Associate Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the Siebel School of Computing and Data Science. He also holds affiliate roles in the Department of Electrical and Computer Engineering, the Informatics Program (School of Information Sciences), and the Coordinated Science Laboratory (CSL). He joined UIUC in 2019, previously serving as an Assistant Professor at Virginia Tech. Education: Ph.D. in Computer Science from UC Santa Barbara (2016), advised by Ben Y. Zhao and Heather Zheng; B.E. from Tsinghua University (2010). Awards include the NSF CAREER Award (2018), Amazon Research Award (2021), and multiple best paper awards in top conferences like USENIX Security and ACM CCS. Research focuses on Security and Privacy, Internet Measurement, and Data Mining. Key areas include email spoofing vulnerabilities, adversarial machine learning, and AI-driven security tools. Recent projects involve explainable AI for phishing detection, benchmark contamination in LLMs, and mitigating deepfake disinformation. Publications span top venues like USENIX Security, IEEE S&P, ACM CCS, and IMC. He collaborates with industry partners and researchers in HCI and AI. Current roles include Associate Director of the Capital One Illinois Center for Generative AI Safety (ASKS) and leadership in NSF-funded initiatives like the ACTION AI Institute.

• Systems and Network Security
• Applied Cryptography
• Cybersecurity
• +9 more

Dr. Angelos D. Keromytis is the John H. Weitnauer, Jr. Endowed Chair Professor and Georgia Research Alliance (GRA) Eminent Scholar at the School of Electrical and Computer Engineering , Georgia Institute of Technology . He is a globally recognized leader in systems and network security and applied cryptography , with over 250 publications and 67 issued US patents. He is an elected Fellow of both the IEEE and ACM, and previously served as a Program Manager at DARPA and Program Director at NSF. Education: Ph.D. in Computer Science, University of Pennsylvania (2001) M.Sc. in Computer Science, University of Pennsylvania (1997) B.Sc. in Computer Science, University of Crete, Greece (1996) Research Interests: Dr. Keromytis's research spans a broad spectrum of cybersecurity topics, including: Systems and Network Security : He has led foundational work in secure systems design, intrusion detection, and network anomaly detection. Applied Cryptography : His work includes cryptographic protocols, secure communications, and privacy-preserving systems. Hardware and Side-Channel Security : He has pioneered techniques for detecting hardware Trojans using electromagnetic side-channels. Cloud and IoT Security : He has developed novel approaches to securing cloud services and IoT devices. Software Security : His work includes defenses against malware, return-oriented programming (ROP), and automated software patching. Scientific Awards: John H. Weitnauer, Jr. Endowed Chair Georgia Research Alliance (GRA) Eminent Scholar IEEE Fellow (2018) ACM Fellow (2017) ACM Distinguished Scientist (2012) DARPA Superior Public Service Medal DARPA Results Matter Award Advising and Grants: Dr. Keromytis has advised over 30 Ph.D. students and numerous postdocs. He has secured over $35M in research funding from agencies like DARPA, NSF, IARPA, ONR, and AFRL. His recent grants include: DARPA SMOKE : $22.7M for "Antikythera" cybersecurity framework NSF SaTC : $1.2M for mobile network anti-tracking architecture DARPA CHASE : $1.7M for network abuse behavioral engine DARPA OPS-5G : $7.3M for large-scale adversary defense ONR : $4.4M for dormant hardware Trojan detection Labs and Teams: He co-founded and co-directs the Center for Cyber Operations Enquiry and Unconventional Sensing (COEUS) at Georgia Tech. Previously, he founded and directed the Network Security Lab (NSL) at Columbia University, which produced foundational research in network security, intrusion detection, and software protection.

Mathias PayerView profile

Associate Professor

• Software Security
• System Security
• Binary Exploitation
• +3 more

Mathias Payer is an Associate Professor at EPFL's School of Computer and Communication Sciences (IC), leading the HexHive Laboratory . His work focuses on software security, particularly addressing memory corruption and type violations through binary analysis and compiler-based techniques. He contributes to research in secure system design, fault isolation, and fuzzing methodologies. Current PhD students : Di Bartolomeo Luca, Feng Zhiyao, Hofhammer Florian, Lyu Tao, Mao Philipp Yuxiang, Zhang Chibin, Zheng Han Past EPFL PhD students: Badoux Nicolas Daniel, Bhattacharyya Atri, Hazimeh Ahmad His research explores software security in areas like: Protecting applications from vulnerabilities Binary exploitation and mitigation Compiler-driven security hardening Strong sanitization and privilege separation Memory corruption detection The HexHive group develops tools and frameworks for: Automated fuzz driver generation Gradual compartmentalization State inference for feedback optimization Secure cell architectures Recent publications highlight advancements in: Fuzzing hybrid approaches (e.g., DUMPLING, MendelFuzz) Memory safety validation (QMSan, Pacmem) Compiler-assisted defenses (Gradient, Type++)

Stephen W. KecklerView profile

Adjunct Professor

• Computer Architecture
• Deep Learning Accelerators
• GPU Computing
• +4 more

Stephen W. Keckler is an Adjunct Professor at the Department of Computer Science , The University of Texas at Austin , and serves as Vice President of Architecture Research at NVIDIA . He is an ACM Fellow , IEEE Fellow , and Sloan Foundation Research Fellow . Education: BS in Electrical Engineering, Stanford University (1990) SM in Computer Science, Massachusetts Institute of Technology (1992) PhD in Computer Science, MIT (1998) Research Interests focus on computer architecture for deep learning , GPU computing , and energy-efficient systems . His work explores memory compression , network-on-chip designs , and heterogeneous computing . Publication Trends highlight advancements in deep learning accelerators , GPU memory systems , and energy-efficient architectures . Notable themes include sparsity exploitation , multi-chip modules , and fault-tolerant GPU pipelines . Scientific Recognition : ACM Fellow IEEE Fellow Sloan Foundation Research Fellow Best Paper Awards at ASPLOS 2009 and ISPASS 2011 Laboratory Affiliations : Computer Architecture and Technology Laboratory (CART) TRIPS Project (Tera-Op Reliable Intelligently adaptive Processing System) NVIDIA Research

Nils Ole TippenhauerView profile

Professor

• Cyber-Physical System Security
• Industrial Control Systems Security
• Physical-Layer Security
• +7 more

Nils Ole Tippenhauer is a faculty member at the CISPA Helmholtz Center for Information Security , leading the SCy-Phy research group . His academic journey includes an Assistant Professorship at the Singapore University of Technology and Design (SUTD) (2014–2018), a PhD in Computer Science from ETH Zurich (2012), and a Diploma in Computer Engineering from Hamburg University of Technology (2007). He also holds an exchange study year at the University of Waterloo (2004–2005) supported by a DAAD scholarship. Research Interests focus on practical systems security , particularly Security of Cyber-Physical Systems Industrial Control Systems (ICS) and Industrial IoT (IIoT) Physical-Layer Security and Wireless Security Privacy-Preserving Technologies (e.g., DP3T project) Embedded Systems Security Threat Detection & Defenses His work integrates both theoretical and applied approaches, addressing vulnerabilities in critical infrastructures like water systems and power grids. Recent Publications highlight trends in Anomaly detection evasion in industrial networks Microarchitectural side-channel defenses Localization techniques in cellular networks Security analysis of ICS protocols Data-driven vulnerability assessments for robotics Cyber-physical simulation for infrastructure security Scientific Awards include Best paper at DIMVA'23 Distinguished Paper at ACSAC 2022 Best paper at CPSIOTSEC 2022 Best paper at CPSS 2017 K-H Ditze Award for diploma thesis (2007) SG Mark Institution award (2016) Runner-Up at smart energy hackathon (2013) Advising and Grants feature PhD defenses of Daniele Antonioli and Hamid Reza Ghaeini (2022), co-organizing conferences like WiSec and CPSS , and leading projects such as the National Science Experiment (NSE) with 50,000 mobile sensors in Singapore. He also contributed to the DP3T project for privacy-preserving contact tracing. Labs and Teams include the SCy-Phy research group at CISPA and the development of testbeds like SWaT (Secure Water Treatment), WADI (Water Distribution), and EPIC (Electric Power and Industrial Control) at SUTD. These platforms enable hands-on security research in realistic industrial environments.

Christopher KruegelView profile

Professor

• Systems Security
• Malware Analysis
• Web Security
• +7 more

Christopher Kruegel is a Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), where he conducts research in systems security. He is affiliated with the International Secure Systems Lab (iSecLab) and was a co-founder of Lastline, Inc., which was acquired by VMware in 2020. His work focuses on creating practical security solutions that address real-world problems through system building and experimental validation. Professor Kruegel's research spans multiple areas of computer security including malware analysis, web security, network security, and vulnerability analysis. His work often involves developing systems that analyze programs for malicious behavior, scanning web applications for vulnerabilities, and improving privacy on social networks. He has made significant contributions to firmware security, smart contract analysis, and mobile security through his extensive publication record. His 15 most recent publications (2022-2023) demonstrate a strong focus on practical security solutions across diverse domains including firmware security (Shimware, Fuzzware), blockchain and smart contract security (Confusum Contractum, NFT security), mobile security (TEEzz, Columbus), and vulnerability detection techniques (Actor, Toss a Fault to Your Witcher). His research shows consistent innovation in security tools and methodologies with several papers receiving distinguished awards. Fellow of the Institute of Electrical and Electronics Engineers Outstanding Graduate Mentor Award, UCSB Academic Senate Distinguished Artifact Award for Fuzzware paper Distinguished Paper Award for Ramblr paper Best Student Paper Award for Detecting Spammers On Social Networks Professor Kruegel has advised numerous graduate students and collaborated extensively with researchers at UCSB and beyond. His work has been funded by various research grants supporting his security research initiatives. He is actively involved in the International Secure Systems Lab, which focuses on practical security solutions for real-world problems.

Joachim WeickertView profile

Professor

• Image Processing
• Computer Vision
• Mathematical Modeling
• +4 more

Joachim Weickert is a Professor of Mathematics and Computer Science at Saarland University where he heads the Mathematical Image Analysis Group since 2001. He received his diploma and Ph.D. in mathematics from the University of Kaiserslautern (1991, 1996), and a habilitation degree in computer science from the University of Mannheim (2001). Prior to his current position, he worked as a research assistant at the University of Kaiserslautern, as a post-doctoral researcher at the universities of Utrecht and Copenhagen, and as an assistant professor at the University of Mannheim. His research focuses on image processing, computer vision, and scientific computing, with special emphasis on techniques based on partial differential equations, variational principles, wavelets, morphological and nonlocal methods, as well as neuroexplicit approaches. He has developed mathematical models and efficient numerical algorithms for image restoration, enhancement, segmentation, compression, optic flow computation, stereo reconstruction, shape from shading, and signal processing methods for tensor fields. These ideas have been successfully applied in industry, biomedical image analysis, and other fields. Analysis of his recent publications reveals a strong trend toward combining traditional PDE-based methods with modern deep learning approaches, particularly in the areas of image inpainting and compression. His work increasingly explores the connections between numerical algorithms for partial differential equations and neural network architectures, demonstrating how mathematical foundations can inform cutting-edge AI techniques while maintaining strong theoretical guarantees. Gottfried Wilhelm Leibniz Prize (2010), considered the most important research award in Germany ERC Advanced Grant (2017) for "Inpainting-based Compression of Visual Data" Elected member of Academia Europaea - The Academy of Europe Jan Koenderink Prize for Fundamental Contributions in Computer Vision (2014) Multiple DAGM Prizes and Best Paper Awards throughout his career AAIA Fellow (2021) and Highly Ranked Scholar (2024) distinctions Professor Weickert has supervised over 250 bachelor's and master's theses and initiated the Master Programme in Visual Computing at Saarland University, the first of its kind in Germany taught in English. He has established numerous interdisciplinary collaborations with colleagues from medicine, bioinformatics, pharmacy, physics, mechatronics, and mechanical engineering. As Principal Investigator for Visual Computing within the Multimodal Computing and Interaction Cluster of Excellence, and former dean of the Faculty of Mathematics and Computer Science (2008-2010), he has played a significant leadership role in advancing visual computing research and education. He heads the Mathematical Image Analysis Group, which has been at the forefront of developing mathematical methods for image analysis. The group maintains strong connections with both theoretical mathematics and practical applications, bridging the gap between fundamental research and real-world implementation across various domains including medical imaging, industrial inspection, and multimedia processing.

Henry D. PfisterView profile

Professor

• Information Theory
• Error-Correcting Codes
• Quantum Computing
• +3 more

Henry D. Pfister is the Addy Family Professor of Electrical and Computer Engineering at Duke University, with a secondary appointment in Mathematics. He holds affiliations with the Pratt School of Engineering and the Duke Quantum Center. His research focuses on information theory, error-correcting codes, quantum computing, and machine learning applications in communications. Pfister earned his Ph.D. from UC San Diego and has held prior roles at Texas A&M University, École Polytechnique Fédérale de Lausanne, and Qualcomm. Education: Ph.D. in Electrical Engineering, UC San Diego (2003); M.S. degrees in Public Policy and Environmental Management from Duke University; J.D. and additional degrees from UNC Chapel Hill. Research interests include Reed-Muller codes, quantum error correction, neural decoders for DNA storage, and capacity-achieving coding schemes. Recent work highlights include proving Reed-Muller codes achieve capacity on binary-erasure channels and developing quantum-enhanced classical communication protocols. Publications span topics like polar codes for quantum channels, belief-propagation algorithms, and neural network-based decoding. Notable grants include NSF funding for DNA storage coding and quantum simulation projects. Pfister has advised over 20 graduate students and is a recipient of the STOC Best Paper Award and NSF CAREER Award.

Jason DahlstromView profile

Adjunct Assistant Professor

• Embedded Systems
• Computer Architecture
• Engineering Education
• +3 more

Jason Dahlstrom is an Adjunct Assistant Professor of Engineering at Dartmouth College's Thayer School of Engineering and Owner of Web Sensing LLC. His research focuses on embedded systems security, computer architecture optimization, and engineering education innovations. He holds a BS in computer engineering (University of New Hampshire, 2006), MS in biomedical engineering (Dartmouth, 2008), and PhD in embedded system security (Dartmouth, 2015). His work emphasizes cybersecurity for critical infrastructure, particularly in vehicle systems and military communication networks. Key contributions include real-time binary analysis frameworks, FPGA-integrated security monitors, and tactical network interface controllers. He has authored patents related to data security appliances and distributed sensing systems. Recent publications explore vehicle system hardening, cross-domain container security, and hardware-assisted monitoring. His research bridges theoretical computer architecture with practical embedded system implementations, addressing modern threats in connected devices and defense applications.

• Computer Vision
• Generative Models
• Image-Text Joint Modeling
• +5 more

Svetlana Lazebnik is a Full Professor and Willett Faculty Scholar in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), part of the Grainger College of Engineering. She holds a Ph.D. from UIUC (2006) and previously served as an Assistant Professor at the University of North Carolina at Chapel Hill (2007–2011). Her research focuses on computer vision, including generative models for virtual try-on, image stylization, scene understanding, and joint modeling of images and language. She has advised numerous Ph.D. students and postdocs, many of whom now hold prominent academic and industry roles. Education: Ph.D. in Computer Science, UIUC (2006); supervised by Jean Ponce. Research Interests: Her work spans generative adversarial networks (GANs), diffusion models, virtual try-on systems (e.g., Dressing-in-Order, Street Try-On), exemplar-based stylization, and large-scale photo analysis. She has pioneered spatial pyramid matching and contributed to binary code learning for image retrieval. Key Awards: NSF CAREER Award (2008), Microsoft Research Faculty Fellow (2009), Sloan Research Fellow (2013), IEEE Fellow (2021), and the Longuet-Higgins Prize (2016) for her CVPR 2006 paper. Teaching: Recent courses include CS 444 (Deep Learning for Computer Vision), CS 543 (Computer Vision), and a Ph.D. Job Search Seminar. She has also taught at UNC Chapel Hill. Grants & Funding: Supported by NSF, Amazon, AWS, Microsoft, Sloan Foundation, Google, ARO, and Adobe. Notable grants include CCF 2348624 and IIS 1718221. Labs/Groups: Leader in the Illinois CS Vision Group, contributing to collaborative projects on embodied AI, multi-agent systems, and visual-semantic reasoning.

Zhendong SuView profile

Professor

• Programming Languages
• Compilers
• Software Engineering
• +3 more

Zhendong Su is a full professor in the Department of Computer Science at ETH Zurich since August 2018. Previously, he held a full professorship at UC Davis from 2003 until June 2019. He earned his Ph.D. in Computer Science from UC Berkeley and dual Bachelor’s degrees in Computer Science and Mathematics from UT Austin in 1995. Affiliations: ETH Zurich: Full Professor (since 2018) UC Davis: Full Professor and Chancellor’s Fellow (2003–2019) IEEE Fellow, ACM Fellow, and Member of Academia Europaea His research focuses on programming languages, compilers, software engineering, computer security, and education technologies . Key contributions include compiler validation (e.g., Project Yin-Yang for SMT solvers and DBMS testing), testing tools like SQLancer, and educational innovations such as the Algot visual programming language. Recent work emphasizes secure AI (e.g., CipherSteal for TEE-shielded models) and compiler reliability (e.g., Artemis/Apollo for JIT validation). He has pioneered techniques like metamorphic testing and equivalence modulo inputs (EMI) for compiler validation, uncovering thousands of bugs in GCC/LLVM and SMT solvers. Awards: ICSE MIP Award (2022), ACM SIGSOFT Impact Paper (2018), NSF CAREER Award, and multiple industrial awards. His students have won IEEE TCSE Rising Star and SIGSOFT Impact Paper awards, securing roles at top universities and companies like Google and NVIDIA. Service: Steering committee member of ISSTA and ESEC/FSE, ACM Distinguished Speaker, and Associate Editor for ACM TOSEM. Program chaired ISSTA 2012 and co-chaired FSE 2016. Labs/Teams: Leads research groups on compiler validation, secure AI, and education technologies. Projects include Yin-Yang (SMT testing), SQLancer (DBMS fuzzing), and Algot (visual programming for education).

• Cybersecurity
• Electronic Identity
• Network Security
• +7 more

Antonio Lioy is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin. He serves as the Cyber Security Representative for the university in national and European government collaborations, is a member of the SmartData@PoliTO interdepartmental center, and acts as Scientific Advisor for the DRIVESEC partnership. His research is deeply rooted in cybersecurity, electronic identity, network and web security, and quantum-resistant systems. His research interests focus on cybersecurity , electronic identity , network security , web security , and quantum cryptography . He leads the TORSEC Security Group and conducts research in LAB 7, with a strong emphasis on trusted computing, post-quantum cryptography, IoT security, and secure network infrastructures. His work aligns with ERC sectors in computer systems and cryptology, and supports UN SDGs on innovation and sustainable cities. His recent publications show a strong trend toward post-quantum cryptography , remote attestation , trusted execution environments , and secure network virtualization . These works appear in top venues such as IEEE, ACM, and IFIP conferences, with a focus on securing future digital infrastructures against emerging threats. Themes include integrity management in softwarized networks, standard-based attestation, and quantum-resistant PKI strategies. He has supervised numerous PhD students, including Davide Colaiacomo, Francesco Vaccaro, Flavio Ciravegna, Grazia D'Onghia, Lorenzo Ferro, Francesco Settanni, Enrico Bravi, Silvia Sisinni, Luca Mannella, and Ignazio Pedone, whose research spans cybersecurity, quantum computing, and IoT. He leads multiple high-profile research projects such as Q-FENCE, QUBIP, SERICS, and FISHY, funded by Horizon Europe and national programs, demonstrating significant grant acquisition and leadership. He is actively involved in research labs and teams, primarily the TORSEC - Security Group (DAUIN) and LAB 7 - Research Laboratory (DAUIN) , which focus on applied cybersecurity research. His projects often involve collaboration with industry and government bodies, emphasizing real-world impact in secure digital identity, critical infrastructure protection, and quantum-safe transitions.