Find Academic Supervisors

John S. BarasView profile

Academic

• Wireless Networks
• Sensor Networks
• Control Systems
• +7 more

John S. Baras is a Distinguished University Professor at the University of Maryland, College Park, holding joint appointments in the Department of Electrical and Computer Engineering and the Institute for Systems Research (ISR). He also serves as the Lockheed Martin Chair in Systems Engineering and directs the Maryland Hybrid Networks Center (HyNet). His roles include Founding Director of ISR (1985–1991) and Director of HyNet since 1992. Baras earned his B.S. from the National Technical University of Athens and his M.S. and Ph.D. in Applied Mathematics from Harvard University. His research focuses on wireless networks, control systems, robotics, and cyber-physical systems. He is a Fellow of multiple prestigious organizations, including IEEE, SIAM, and AAAS, and has received numerous awards for his contributions to science and engineering. His research interests span networked control systems, autonomous systems, and stochastic systems. Notable contributions include foundational work on satellite and hybrid communication networks, model-based systems engineering, and robotic motion planning. He has advised 42 Ph.D. and 70 M.S. students. Baras has authored over 450 papers and three patents, with recent work addressing risk-sensitive reinforcement learning, network slicing, and autonomous vehicle coordination. His labs and teams, including HyNet, focus on industry-academic collaboration in next-generation communication and control systems.

Cunxi YuView profile

Assistant Professor

• Systems, Networking, and Architecture
• Machine Learning and Data Science
• Hardware Design
• +3 more

Cunxi Yu is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) at the University of Maryland, College Park, and an affiliated faculty member in the Department of Computer Science (CS). He holds a Ph.D. from UMass Amherst (2017) and has held postdoctoral positions at Cornell University and EPFL. His research focuses on novel algorithms, systems, and hardware designs for computing and security, with notable contributions in formal verification, logic synthesis, and optical neural networks. He has received prestigious awards including the NSF CAREER Award (2021) and Best Paper Awards at ASPLOS (2025) and DAC (2023). Dr. Yu's academic journey includes prior roles at the University of Utah and industry collaborations with IBM Research. He advises a dynamic research group with PhD students in ECE and CS, and mentors undergraduate researchers. His work bridges formal methods with machine learning, emphasizing practical tools like BoolE (Best Paper Nomination, DAC 2025) and SmoothE (Best Paper Award, ASPLOS 2025). He actively contributes to conferences such as ASAP, ICCAD, and DAC through organizing committees and TPC roles. Key research areas include: - Formal Verification: Algebraic techniques for arithmetic circuits, equivalence checking, and e-graph-based reasoning. - Optical Computing: Design frameworks like LightRidge for diffractive optical neural networks. - Hardware Automation: Reinforcement learning for logic synthesis (e.g., MapTune, Gamora) and EDA tool development. - Security: Reverse engineering of camouflaged circuits and cryptographic hardware verification. His grants include a $900K NSF grant (2024) with Prof. Zhiru Zhang (Cornell) for hardware synthesis. Recent milestones include NVIDIA Academic Research Awards (2025) and DARPA funding for combinatorial optimization.

Richard ChangView profile

Associate Professor

• Computational Complexity Theory
• NP-optimization Problems
• Approximation Algorithms
• +7 more

Richard Chang is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a Ph.D. from Cornell University (1991) and has been affiliated with UMBC since 1991, serving in various roles including tenure-track positions and joint appointments at the University of Maryland Institute for Advanced Computer Studies (1994–2004). His research focuses on computational complexity theory, particularly bounded query classes, NP-optimization problems, approximation algorithms, and relativized complexity. He has authored numerous papers on topics such as query complexity, Boolean hierarchies, and space-bounded computations. Chang's academic contributions include significant work on the theoretical foundations of computational complexity, including studies on the Boolean hierarchy, randomized reductions, and the structure of NP computations. He has secured multiple research grants, including from the National Science Foundation and the National Security Agency. His teaching spans a wide range of computer science courses, from introductory programming to advanced topics like compiler design and automata theory. He actively participates in academic service, serving on departmental, college, and university committees, as well as organizing conferences and reviewing for top journals. His work emphasizes bridging theoretical computer science with practical algorithmic challenges, contributing to both academic discourse and educational excellence.

• Operating Systems
• Distributed Systems
• Reliable Systems
• +4 more

Christian Dietrich is a Professor for Reliable Distributed Systems at Technical University of Braunschweig since 2024, where he heads the Reliable System Software research group within the Institute of Operating Systems and Computer Networks, part of the Faculty of Electrical Engineering, Information Technology, and Physics. He previously held positions at Leibniz Universität Hannover where he completed his distinguished doctoral research. Professor Dietrich's research focuses on operating systems, distributed systems, and reliable systems with particular expertise in memory management, real-time systems, and embedded systems. His work spans both theoretical foundations and practical implementations, with significant contributions to system software reliability and efficiency. His research interests include operating system design, memory management techniques, real-time computing, embedded systems, fault tolerance, and compiler optimizations for system software. Dietrich's recent publications demonstrate a strong focus on memory management innovations (particularly for persistent memory), virtualization techniques, and reliability mechanisms for distributed systems. His work frequently bridges the gap between theoretical computer science and practical system implementation, with many contributions finding their way into production systems. The research shows increasing emphasis on hardware-software co-design and adapting operating systems to modern hardware capabilities. His scientific achievements have been recognized with numerous prestigious awards: USENIX ATC Distinguished Artifact Award (2023) for LLFree USENIX ATC Best Paper Award (2017) for cHash RTAS Best Paper Award (2015) for dOSEK Multiple Outstanding Paper Awards at ECRTS, OSPERT, and ISORC Wissenschaftspreis Hannover (2020, awarded in 2024) Professor Dietrich has secured significant research funding including multiple DFG projects (DI 2840/1-1, DI 2840/2-1) and has been involved in collaborative projects with industry partners. His teaching portfolio includes advanced courses on operating systems, programming languages, and compilers, for which he received teaching excellence awards. He leads an active research group focused on reliable system software with ongoing projects including ParPerOS (Parallel Persistency OS) and ATLAS (Adaptable Thread-Level Address Spaces). The Reliable System Software group maintains strong connections with both academic and industrial partners, contributing to open-source projects and collaborating on cutting-edge research in system software reliability. The group's work has practical impact, with some findings leading to more than 100 accepted patches in the Linux mainline kernel.

Timothy PetersView profile

Associate Professor

• Cultural Legal Studies
• Legal Theory
• Theology and Law
• +4 more

Associate Professor Timothy Peters is an Associate Professor in Law and Associate Dean, Research at the University of the Sunshine Coast's School of Law and Society. He holds a PhD, LLB (Hon I), and BComm from Griffith University. His research focuses on cultural legal studies, examining intersections between legal theory, theology, and popular culture, particularly in film, comics, and speculative fiction. He co-edited Envisioning Legality and the Routledge Handbook of Cultural Legal Studies , and authored A Theological Jurisprudence of Popular Cinema . Peters' work critiques corporate personhood and sovereignty through political theology, supported by a 2020 ARC Discovery Early Career Researcher Award. He teaches corporate law, securities regulation, and cultural legal studies. Professional roles include presidency of the Law, Literature and the Humanities Association of Australia and editorial board memberships in critical legal journals. His research spans corporate technology (AI, DAOs), legal iconography in media, and biopolitical environmental ethics. Peters advises students in corporate law, banking, and cultural legal studies, with publications analyzing law in Star Wars , Avatar , and Dark Knight films. His interdisciplinary approach integrates theology, cinema, and legal theory to reimagine corporate legality beyond neoliberal frameworks.

Samuel GuyerView profile

Adjunct Associate Professor

• Programming Languages
• Program Analysis
• Software Reliability
• +7 more

Samuel Guyer is an Adjunct Associate Professor in the Department of Computer Science at Tufts University. His research focuses on programming languages, compilers, program analysis, and runtime systems, with an emphasis on enhancing communication between runtime systems and programmers. He holds a Ph.D. and M.Sc. from the University of Texas at Austin. Education: Ph.D., Computer Science, University of Texas at Austin M.Sc., Computer Science, University of Texas at Austin Research Interests: Dr. Guyer explores techniques to improve software reliability, memory management, and runtime performance. Key areas include domain-specific programming languages, compiler optimizations, and tools for debugging memory managers. His work often addresses challenges in aviation software safety, garbage collection strategies, and object lifecycle analysis. Article Trends: Recent work emphasizes runtime systems analysis (e.g., Permchecker for memory managers, Iceberg for Java concurrency), visualization tools (Heapviz, Garbology), and safety-critical systems (avionics fault monitoring). His research bridges theoretical insights with practical tools for industry-relevant problems. Grants: CAREER: Cooperative Virtual Machines (NSF grant) SHF grants for garbage collection and runtime bug detection Labs/Teams: Collaborates on projects involving compiler infrastructure (e.g., C-Breeze), domain-specific compilers (Broadway), and runtime analysis frameworks. His work often intersects with industry needs for robust software systems.

Raffi KhatchadourianView profile

Associate Professor

• Software Engineering
• Programming Languages
• Machine Learning Systems
• +3 more

Raffi Khatchadourian is an Associate Professor in the Department of Computer Science at Hunter College, part of the City University of New York (CUNY). He specializes in Software Engineering, Programming Languages, and Machine Learning Systems. His research focuses on automated software evolution, secure software engineering, and refactoring techniques, with notable contributions to tools like Hybridize Functions and μAkka. He holds a PhD in Computer Science from Ohio State University, along with MS and BS degrees in Computer Science from Ohio State and Monmouth University, respectively. His educational background includes advanced training in Computer Science, with a focus on theoretical and practical aspects of software systems. His research interests span automated refactoring, program analysis, and the integration of machine learning with traditional software engineering practices. Key projects include frameworks for assessing safety in deep learning systems (ReLESS) and mutation testing for actor concurrency in Akka (μAkka). Khatchadourian’s work emphasizes tool development and open-source contributions, such as the Common-Eclipse-Refactoring-Framework and Hybridize-Functions-Refactoring. He has secured grants from the National Science Foundation (NSF) for combating technical debt in machine learning systems and improving imperative-to-graph execution migration. His teaching spans graduate courses on programming languages and software engineering, reflecting his commitment to advancing computational education. His lab, Ponder Lab, focuses on empirical studies and tool creation for software evolution and concurrency. Notable grants include SHF-funded projects addressing practical analyses and safe transformations in deep learning programs. His research has addressed challenges in migrating deep learning code to graph execution, optimizing Java 8 streams, and analyzing legacy software refactoring.

Sazadur RahmanView profile

Assistant Professor

• Hardware Security
• Supply Chain Security
• Electronic Design Automation
• +7 more

Sazadur Rahman is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Central Florida (UCF), affiliated with both ECE and Computer Science departments under the Cyber Security and Privacy Cluster. He holds a Ph.D. and M.Sc. from the University of Florida and a B.Sc. from Bangladesh University of Engineering and Technology. Previously, he worked as a Security Architecture Engineer at Intel Corporation, focusing on processor security hardening and threat modeling. His research interests include hardware security, semiconductor supply chain security, and AI-assisted chip design. He has published over 20 peer-reviewed papers and contributed to patents and textbooks. Education Ph.D. Electrical Engineering, University of Florida, 2022 M.Sc. Electrical and Computer Engineering, University of Florida B.Sc. Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology Research Interests His work centers on securing electronic design automation (EDA) tools, semiconductor supply chains, and hardware systems against reverse engineering, piracy, and attacks. Key areas include: Hardware obfuscation techniques (e.g., logic locking, watermarking) CAD tools for security assessment and mitigation Machine learning applications in secure chip design Secure heterogeneous integration and FHE acceleration Professional Activities Technical Program Committee Member: IEEE HOST Conference (2024) Reviewer: Top journals/conferences like IEEE Transactions on CAD, ACM TODAES, and DAC Awards 2022 IEEE/ACM DAC PhD Forum Finalist 2023 IEEE/ACM DATE Best Paper Nomination 2022 IEEE VTS TTTC Best Thesis Runner-Up Research Contributions His publications focus on innovative solutions like LLE for IC piracy mitigation, iPROBE for probing attack protection, and ReTrustFSM for RTL obfuscation. He has developed tools for threat modeling using NVD databases and evaluated cloud-based EDA platforms' security.

• Software Engineering
• Cybersecurity
• Behavioral Biometrics
• +3 more

Dr. Daqing Hou is a Professor at Clarkson University's Coulter School of Engineering & Applied Sciences, affiliated with the Department of Electrical & Computer Engineering and Computer Science. His research bridges software engineering, cybersecurity, behavioral biometrics, and education research. He earned his Ph.D. in Computing Science from the University of Alberta, and M.S./B.S. in Computer Science from Peking University. Research focuses on improving software development efficiency through project-based learning (PjBL), empirical studies, and human factors. Key areas include behavioral biometrics (keystroke/mouse dynamics), smart housing/energy systems, and cybersecurity solutions. He has pioneered tools like CReN for managing code clones and has contributed to Eclipse/UIMA frameworks. Recent publications emphasize behavioral authentication methods, mobile biometrics evaluation, and framework design recommendations. His work has been recognized with awards including IEEE ICSME 2014 Best Paper Nomination and IBM Innovation Awards (2005/2007). Teaching spans software engineering, GUI design, databases, machine learning, and compilers. He advises students on topics like API usability, security systems, and programming language tools.

• Software Verification
• Side-channel Analysis
• Computer Security
• +3 more

Tegan Brennan is an Assistant Professor at the Department of Computer Science within the Charles V. Schaefer, Jr. School of Engineering and Science at Stevens Institute of Technology. She holds a PhD in Computer Science from the University of California Santa Barbara (2020). Her research focuses on software verification, side-channel analysis, computer security, and program analysis. Prior to academia, she worked as an Applied Scientist at Amazon (2020). Her research interests emphasize securing computational systems through rigorous analysis of timing channels, adaptive neural networks, and compiler-induced vulnerabilities. She has contributed to methods like probabilistic reachability analysis and fuzzing techniques for identifying security flaws. Brennan has received accolades such as the UCSB Outstanding Dissertation Award (2020) and ICSE Student Research Competition Third Place (2020). She actively serves on program committees for IEEE Security and Privacy, CSF, and BAR conferences, reflecting her leadership in the cybersecurity community. Her grants include CRII: SaTC funding for studying timing channels in neural networks. Courses taught include CS284 (multiple semesters), CS516, CS396, and CS810-E, covering software engineering and advanced security topics.

Sankha GuriaView profile

Assistant Professor

• Program Synthesis
• Type Systems
• Programming Languages
• +2 more

Sankha Guria serves as an Assistant Professor in the Department of Electrical Engineering & Computer Science at The University of Kansas, where he conducts research at the intersection of programming languages and software engineering. His primary research focuses on advancing program synthesis techniques and type system design, with significant contributions to abstract interpretation-guided synthesis (Absynthe), effect-guided program generation (RbSyn), and security-aware declassification frameworks (ANOSY). He also investigates type-level computations for dynamic languages, particularly addressing challenges in Ruby and JavaScript through transparent object proxies and contract systems. Analysis of his publication timeline reveals strong continuity in programming languages research since 2015, with recent work (2021-2023) emphasizing lightweight abstractions for synthesis and refinement types, while maintaining foundational work on dynamic language security. His research consistently bridges theoretical formal methods with practical language implementation challenges, particularly in the context of modern scripting languages.

Randy FortierView profile

Academic

• Software Security
• Web/Mobile Development
• Computer Graphics
• +3 more

Randy Fortier is an Associate Teaching Professor and Associate Dean of Science (Undergraduate) at Ontario Tech University's Faculty of Science. He specializes in Computer Science education with a focus on software security, web/mobile development, graphics, and game development. His academic career includes teaching roles at the University of Windsor (1997-2003) and Thompson Rivers University (2003-2013). Education: BSc (Honours Computer Science, Software Development) from University of Windsor (1997), MSc (Computer Science) from University of Windsor (2003). Research interests span software security, mobile/web development, computer graphics, and game development. His earlier work focused on natural language processing and distributed virtual environments. His publications explore semantic web technologies, mobile speech interfaces, and scalable distributed systems architectures. Teaching portfolio includes over 15 courses ranging from introductory programming to advanced topics like interactive media and simulation modeling. He currently holds administrative leadership in undergraduate science education.

• Programming Languages
• Formal Verification
• Compilers
• +5 more

Clément Pit-Claudel is a Tenure-Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL), leading the SYSTEMF Laboratory in the School of Computer and Communication Sciences. His work bridges programming languages, formal verification, and systems engineering to build high-assurance software and hardware components. PhD in Computer Science from MIT (2016), thesis on proof-producing compilers MSc in Computer Science from MIT BSc in Computer Science from École Polytechnique (France) Research Interests focus on correct-by-construction program synthesis , domain-specific compilers , and formal verification . He develops tools like Alectryon for interactive Coq proof visualization and Rupicola for verified compiler construction. His work spans hardware description languages (e.g., Kôika ), software verification (e.g., Fiat ), and regex engine formalization (e.g., Elk and Warblre ). Recent publications include foundational work on JavaScript regex mechanisms (ICFP 2024), relational compilation (PLDI 2022), and hardware simulation (ASPLOS 2021). His lab SYSTEMF emphasizes full assurance without compromise through machine-checked proofs and hardware-software co-design. Awards include the MIT Frederick C. Hennie III Teaching Award (2016) and MIT William A. Martin Thesis Award (2016). He has served as program committee member for conferences like PLDI, POPL, and Coq Workshop. Teaching includes Software Construction (400+ students at EPFL) and Interactive Theorem Proving graduate course. He has advised doctoral students in formal methods and compiler design.

Sachith SeneviratneView profile

Research Fellow

• Machine Learning
• Computer Vision
• Deep Learning
• +9 more

Dr. Sachith Seneviratne is a Research Fellow at the University of Melbourne's Melbourne School of Design, specializing in Computer Vision and Health. His research bridges Machine Learning, Urban Design, and Public Health, with a focus on Deep Learning, Contrastive Representation Learning, and Agent-Based Modelling. He holds a PhD in Machine Learning from Monash University, exploring automated parallelized machine learning models. His work has collaborations with NASA, Harvard University, and Currnt Research Hub. He is affiliated with the Transport, Health and Urban Design (THUD) research group, focusing on 'Data and Value,' 'Future Cities,' and 'Healthy Communities and Infrastructure.' His recent publications span facial deepfake detection, urban design impacts on health, and automated architecture generation using LLMs. Research interests include generative design, automated infrastructure planning, and the ethical implications of facial recognition under privacy constraints (e.g., masked faces). He has pioneered methods for collecting population-level bicycling data via smartphones/Bluetooth beacons and developed novel architectures like Arch-LLM for neural architecture generation. His work on subgrid-informed flood mapping and physics-informed neural networks demonstrates cross-disciplinary innovation. Consulting work includes machine learning projects for NASA and Harvard. His lab teams focus on creating interpretable AI systems for environmental and health applications, such as Ginn-kan for physics simulations and Ginn-lp for symbolic equation discovery. Current projects aim to quantify urban design's impact on non-communicable diseases and improve walkability through micro-scaled spatio-temporal analysis.

Daniel LohmannView profile

Professor

• Operating Systems
• Embedded Systems
• Real-Time Systems
• +4 more

Professor Daniel Lohmann leads the Systems Research and Architecture (SRA) group at Leibniz Universität Hannover since 2017, following his role as Associate Professor (Privatdozent) at Friedrich-Alexander-Universität Erlangen-Nürnberg (2009–2016). His work focuses on configurable system software, emphasizing embedded systems, real-time systems, and dependable architectures. Key projects include danceOS (dependability in embedded OS), Sloth (minimal-effort kernels), and AspectC++ (aspect-oriented C++ extension). His research is funded by DFG and addresses challenges in variability management, fault tolerance, and real-time scheduling. Research interests span operating systems design, software product lines, generative programming, and aspect-oriented development. Notable contributions include the CiAO OS family and the Sloth RTOS, leveraging aspect-oriented techniques for flexibility and efficiency. His work on configuration analysis (e.g., static variability in Linux) and fault mitigation (e.g., AN-Codes for soft errors) highlights his expertise in system reliability and optimization. Publications emphasize real-time systems, embedded software, and software engineering, with awards including the Best Paper Award at SPLC 2010 and an Outstanding Paper at RTAS 2017. He supervises theses on system software tailoring, fault tolerance, and industrial software ecosystems. His groups collaborate on invasive computing (SFB/TRR 89) and hardware-aware OS design.