Find Academic Supervisors

Dave NaumannView profile

Professor

• Formal Methods
• Software Security
• Relational Verification
• +7 more

Dave Naumann is a Professor and Chair of the Department of Computer Science at Stevens Institute of Technology, located within the Charles V. Schaefer, Jr. School of Engineering and Science. He holds a PhD (1992) and BA (1982) in Computer Science from the University of Texas at Austin. His research focuses on formal methods and software security, including relational and hyperproperty verification, fine-grained confidentiality/integrity policies, program analysis, and correctness-by-construction methodologies. Naumann leads the Cypress research group and has served in significant academic roles, including editorial board memberships for ACM Transactions on Programming Languages and Systems and Formal Aspects of Computing . His awards include the Davis Memorial Award for Research Excellence (2006) and invitations as a keynote speaker at major conferences like ETAPS and IBM Programming Languages Day. He has advised numerous PhD students and postdoctoral researchers, contributing to advancements in secure software verification. His grants include NSF awards for projects like hyperproperty abstraction and relational verification for privacy. Naumann’s work bridges theoretical foundations with practical tools, exemplified by the WhyRel prototype for modular relational verification. Professional service includes co-chairing the IEEE Computer Security Foundations Symposium and serving on program committees for POPL, CCS, and ECOOP. His consulting work with Microsoft Research, Vulcan Inc., and Galois Inc. underscores industry-academia collaboration in formal methods.

• Programming Languages
• Functional Programming
• Type Systems
• +5 more

Ningning Xie is an Assistant Professor in the Department of Computer Science at the University of Toronto. She holds a part-time Research Scientist position at Google DeepMind and is a Faculty Affiliate at the Schwartz Reisman Institute. Previously, she was a Research Associate at the University of Cambridge and earned her Ph.D. from the University of Hong Kong and B.S. from Zhejiang University. Her research focuses on foundational aspects of programming languages, including functional programming, type systems, logics, and their applications in broader domains. Key areas include algebraic effect handlers, staged compilation, type inference, and parallel computing. She has contributed to systems like MacoCaml and Perceus, and her work has been recognized with ACM SIGPLAN Distinguished Paper Awards and the Cambridge Hall of Fame Award. Dr. Xie co-chairs the Haskell Symposium 2025 and serves on committees for major programming language conferences (PLDI, ICFP, etc.). She actively organizes workshops and tutorials, including invited keynotes at Lambda Days and ZuriHac 2024. Her service roles include moderating the Types Forum and steering committees for Haskell and PLMW. Her academic contributions span over 25 peer-reviewed publications, with a focus on practical implementations and formal proofs. She advises students through her research group and emphasizes generative programming techniques in her teaching.

Yiming ZengView profile

Assistant Professor

• Quantum Networking
• Quantum Computing
• Edge Computing
• +3 more

Yiming Zeng is an Assistant Professor at the School of Computing, Binghamton University. He holds a PhD from Stony Brook University and a BS from Shanghai Jiao Tong University. His research focuses on quantum networking, quantum computing, edge computing, distributed systems, differential privacy, and decentralized optimization. He has been recognized with awards including the 2023 Sigcomm Workshop Travel Grant and the 2017 Stony Brook Academic Excellence Fellowship. Education: PhD in Electrical and Computer Engineering, Stony Brook University (2024 expected) BS in Engineering, Shanghai Jiao Tong University Research Interests: Quantum Networking: designing protocols for entanglement routing and management in quantum internets Edge Computing: optimizing edge caching, data offloading, and privacy-preserving techniques in 5G networks Decentralized Optimization: applying game theory to blockchain systems and distributed resource allocation Differential Privacy: developing methods for federated learning and data marketplaces Teaching Experience: Teaching Assistant for courses including Digital Logic Design, Electronics Laboratory, and Introduction to Electrical and Computer Engineering Labs/Teams: Active in quantum internet research and edge computing systems development, though specific lab affiliations are not explicitly stated.

Joseph P. NearView profile

Associate Professor

• Data Privacy
• Differential Privacy
• Computer Security
• +5 more

Joseph P. Near is an Associate Professor in the Department of Computer Science at the University of Vermont's College of Engineering and Mathematical Sciences. He maintains his office in E458 Innovation Hall and is actively engaged in teaching, research, and service activities. His work bridges theoretical computer science with practical privacy-preserving technologies. His educational background includes a B.S. in Computer Science from Indiana University and both M.S. and Ph.D. degrees in Computer Science from MIT. Ph.D., Massachusetts Institute of Technology M.S., Massachusetts Institute of Technology B.S., Indiana University Near's research focuses on practical applications of data privacy, particularly differential privacy, secure computation techniques, and programming language approaches to security. His work addresses real-world challenges in implementing privacy-preserving systems that maintain data utility while protecting individual information. He has developed frameworks for differential privacy implementation and has extensively studied the usability challenges faced by practitioners implementing privacy protections. His recent publications reveal a strong focus on making differential privacy more practical and accessible, with numerous contributions to choreographic programming for secure computation, language-based security approaches, and tools for evaluating privacy guarantees. The research trajectory shows increasing attention to usability issues alongside technical innovations, reflecting a maturing field where practical adoption challenges are becoming as important as theoretical advances. Near actively mentors multiple Ph.D. students through the UVM PLAID lab and the UVM Center for Computer Security and Privacy. His service contributions include organizing workshops like TPDP (Theory and Practice of Differential Privacy) and serving on program committees for major security conferences including CCS, USENIX Security, and PETS. His teaching portfolio includes specialized courses on Data Privacy and Secure Distributed Computation, reflecting his research expertise. He has co-authored significant educational resources including the book "Programming Differential Privacy" and is working on "Differential Privacy for Databases," demonstrating his commitment to making these complex topics accessible to practitioners.

Eivind WittemannView profile

Assistant Professor

• Art and Conflict
• Visual Arts
• Comics and Graphic Narratives
• +3 more

Eivind Wittemann is an Assistant Professor at the Department of Visual and Performing Arts at the University of Agder in Kristiansand, Norway. His office is located at G2032, Universitetsveien 25, and he can be contacted via email at eivind.wittemann@uia.no or phone (+47 38142388). He is an active member of the research group 'Art and Conflict', focusing on art as a platform for dialogue and societal critique. Research Focus: Wittemann's work explores intersections of art with conflict resolution, environmental criticism, and narrative experimentation. His research spans visual storytelling through comics, environmental art addressing ecological destruction, and collaborative art processes. Key themes include: Artistic responses to infrastructure development and nature destruction Graphic novel creation and autobiographical narratives Art as a mediator in social conflicts and critical debates Experimental methodologies in artistic development Publication Trends: His recent works (2020-2025) demonstrate strong focus on: Environmental critique through projects like 'Dominus Naturae' examining highway construction impacts Graphic narrative development in the 'Vilma and daDDy' series Collaborative art research through the 'Art and Conflict' initiative Explorations of materiality in sculpture and installation art Earlier works show foundational interest in cultural memory, digital art, and exhibition practices. Professional Engagement: Wittemann contributes to sustainability seminars and experimental art processes, including the 2024 KoK Sustainability Seminar addressing art's role in ecological and community contexts. His collaborative projects emphasize co-creation strategies and critical discourse development.

Marios PapaefthymiouView profile

Professor

• Energy-Efficient Computing
• Charge-Recovery Technologies
• Computer Architecture
• +7 more

Marios Papaefthymiou is a Professor of Computer Science and Ted and Janice Smith Family Foundation Dean of the Donald Bren School of Information and Computer Sciences at the University of California, Irvine. Previously, he held faculty roles at the University of Michigan (including Computer Science & Engineering Division Chair) and Yale University. His research focuses on energy-efficient computing, charge-recovery technologies, and high-performance systems. Education: Ph.D., Electrical Engineering and Computer Science, MIT (1993) S.M., Electrical Engineering and Computer Science, MIT (1990) B.S., Electrical Engineering, Caltech (1988) Research Interests: Papaefthymiou pioneered charge-recovery (adiabatic) technologies, demonstrating energy-efficient silicon prototypes. His work spans energy-efficient design, high-performance computing, and electronic design automation. He co-founded Cyclos Semiconductor to commercialize these innovations, used in AMD/IBM server chips. Current interests include AI ethics, cybersecurity, and machine learning. Awards: Arthur Greer Memorial Prize (Yale) Outstanding Achievement Award (U. Michigan EECS) IEEE Fellow (2009) NSF CAREER/ITR Awards Advising & Grants: Advised numerous students (e.g., H.-S. Wu, Z. Zhang) and secured grants from NSF, ARO, DARPA, and industry partners. As Dean, he expanded the School’s fundraising to $10M annually, launched new programs, and founded centers like the HPI Research Center for Machine Learning. Leadership: Spearheaded initiatives like the Steckler Center for Responsible Technology and the Initiative on AI, Law & Society. Strengthened alumni engagement through events and the ICS Industry Showcase.

Mohsen ImaniView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Computer Architecture
• +3 more

Mohsen Imani is an Assistant Professor at the Donald Bren School of Information and Computer Sciences, University of California, Irvine, and director of the Bio-Inspired Architecture and Systems Lab (BIASLab) . His research bridges neuroscience, machine learning, and embedded systems to develop hyperdimensional computing (HDC) as a neuro-symbolic AI technique. PhD in Computer Science and Engineering from UC San Diego Led 35+ member team with 17 PhD students Received $750,000 ONR YIP award and $1M DARPA grant Research focuses on: Hyperdimensional computing for real-time cognitive systems Energy-efficient edge AI with brain-inspired architectures Privacy-preserving federated learning frameworks Security monitoring with interpretable reasoning His 15+ most recent publications span: 2025 work on quantum HD factorization and uncertainty-robust cognitive maps 2024 breakthroughs in photonic neuro-symbolic computing and genome matching 2023 foundational work on DNN hardware acceleration Awards include: DARPA Young Faculty Award SRC Young Faculty Award ONR Young Investigator Award Eight best paper awards/nominations Teaching CS 151: Digital Logic Design and CS 257: Brain-Inspired Learning Systems in Winter 2025. His lab released the first open-source library for brain-inspired HD computing.

David BromanView profile

Professor

• Programming Languages and Compilers
• Real-Time Systems and Cyber-Physical Systems
• Probabilistic Machine Learning
• +2 more

David Broman is a Professor at KTH Royal Institute of Technology in Sweden, leading the Division of Software and Computer Systems (SCS) and serving as Associate Director Faculty for Digital Futures. He holds a Ph.D. in Computer Science from Linköping University (2010), with visiting roles at UC Berkeley (2012–2016) and Stanford University (2023–2024). His research spans programming languages, real-time systems, and probabilistic machine learning, emphasizing secure and efficient compilation techniques. Education: Ph.D. in Computer Science (Linköping University, 2010) Visiting Roles: UC Berkeley (2012–2014 part-time), Stanford University (2023–2024) Research Interests: David focuses on advancing programming language theory, compilers, and probabilistic methods. Key areas include transformer-based compilation, cyber-physical systems, and formal verification. His work bridges theory and practice, addressing challenges in software reliability and efficiency. Awards: Notable recognitions include the Best ETAPS Paper Award (2023), Distinguished Artifact Award (ESOP 2022), and Teacher of the Year (KTH 2017). His contributions also include grants from the Swedish Foundation for Strategic Research and Wallenberg AI, Autonomous Systems and Software Program (WASP). Advising & Grants: David mentors graduate students (e.g., Gizem Caylak, Viktor Palmkvist) and leads projects funded by WASP, focusing on next-generation compilation techniques. He also contributed to tools like Miking, Timed C, and FlexPRET. Labs & Teams: His team develops frameworks for probabilistic programming and real-time systems, emphasizing collaboration with industry and academia through initiatives like Digital Futures at KTH.

• Control Systems
• IoT and Smart Grids
• Renewable Energy Systems
• +3 more

Seyed Amir Alavi is a Teaching Fellow at the School of Electronic Engineering and Computer Science, Queen Mary University of London. His research focuses on control systems, IoT integration in energy grids, and fractional-order control methodologies. He specializes in microgrid design, distributed control strategies, and state estimation techniques for smart energy systems. His work addresses challenges in renewable energy integration, delay compensation in power systems, and battery health monitoring for electric vehicles. Key research areas include: IoT-based distributed control systems for microgrids Advanced control algorithms for DC and AC power systems Quantum computing testbed infrastructure development Application of machine learning in battery diagnostics Resilient communication networks for energy systems Recent publications highlight innovations in: Privacy-preserving IoT data collection methods Event-triggered control for distributed systems Forecast-based consensus control using deep learning No academic awards or grants are explicitly mentioned in the provided materials. His work contributes to both theoretical advancements and practical implementations in smart grid technologies and energy management systems.

• Autonomous UAV maneuverability
• UAV aided data collection
• Wireless sensor networks
• +9 more

Umair Chaudhry is a Visiting Professor at Queen Mary University of London's School of Electronic Engineering and Computer Science. He teaches the postgraduate module Computer Architecture and Networks , focusing on software engineering, systems analysis, digital logic, computer architecture fundamentals, and internet protocols. His research spans cutting-edge areas including autonomous UAV systems, wireless sensor networks, IoT, 5G networks, vehicular ad-hoc networks, and software-defined networking. Notably, he also explores comparative religion and history alongside technical fields. Teaching Focus: Binary digital logic and information representation Von Neumann Architecture and memory hierarchy Internet protocols (DNS, HTTP) and packet-switched networks Research Interests: Unmanned aerial vehicle (UAV) systems and data collection Wireless network architectures (Mesh, Ad-hoc, 5G) Software-defined networking (SDN) and network performance optimization Cross-disciplinary work combining technology with humanities No academic publications or awards are explicitly listed in the provided materials.

• Machine Learning
• Natural Language Processing
• Topic Modeling
• +4 more

Wray L. Buntine is a faculty member at Monash University in Melbourne, Australia, specializing in machine learning, natural language processing, and Bayesian methods. His research bridges theoretical foundations and practical applications, with a strong focus on NLP innovations, topic modeling, and efficient learning techniques. His research interests span: Machine Learning : Bayesian neural networks, active learning, and low-resource model optimization. Natural Language Processing : Topic modeling, machine translation, LLM evaluation, and dialogue systems. AI Applications : Healthcare (e.g., medication recommendation), education (e.g., dialogue classification), and graph-based anomaly detection. Recent publications (2023–2025) demonstrate a shift toward LLM-centric research, including automatic evaluation of topic models, uncertainty-aware language agents, and logical verification frameworks. His work frequently integrates Bayesian approaches with deep learning, emphasizing model interpretability and data efficiency. While no awards or grants are detailed in the source text, Buntine leads collaborative projects across NLP and ML, often co-authoring with researchers at Monash University and international institutions. Labs or teams are not explicitly referenced.

Avi SilberschatzView profile

Professor

• Database Systems
• Operating Systems
• Storage Systems
• +4 more

Avi Silberschatz is the Sidney J. Weinberg Professor of Computer Science at Yale University, where he previously chaired the Department of Computer Science (2005–2011). He holds a chaired professorship and has held prior roles at Bell Laboratories and the University of Texas at Austin. His research focuses on database systems, operating systems, storage systems, and network management. He is a Fellow of ACM, IEEE, and AAAS, and has received prestigious awards including the ACM Karl V. Karlstrom Educator Award (1998) and the IEEE Taylor L. Booth Education Award (2002). Silberschatz has advised over a dozen PhD students, many now leading roles in academia and industry. He authored influential textbooks like Operating System Concepts and Database System Concepts , and holds over 40 patents. Current research explores non-volatile memory technologies and their integration into systems. Contact: avi@yale.edu. Research & Awards Key areas include database systems, operating systems, and cybersecurity. Awards include Bell Labs President’s Award (1998, 1999, 2004) and VLDB Test of Time Award (2019). His work bridges theoretical foundations and practical applications, with contributions to transaction management, storage systems, and distributed computing. Education & Grants Over two dozen grants supported his work, and he has pioneered educational materials in computer science. Collaborations include projects with Prof. Robert Soulé on next-gen memory systems.

Jehoshua BruckView profile

Professor

• Information Theory
• Distributed Storage Systems
• DNA Data Storage
• +4 more

Jehoshua (Shuki) Bruck is the Gordon and Betty Moore Professor of Computation and Neural Systems & Electrical Engineering at the California Institute of Technology. He leads the Distributed Information Systems Group and serves as the founding director of Caltech's Information Science and Technology (IST) program. His work bridges information theory, storage systems, and computational biology. Bruck holds B.Sc. (Summa cum Laude) and M.Sc. degrees from the Technion-Israel Institute of Technology (1982-1985) and a Ph.D. in Electrical Engineering from Stanford University (1989). He has held academic positions at Caltech since 1994, advancing from Associate Professor to Moore Professor. Research Focus: His dual-track research explores Physical implementations of coding schemes for flash memories (rank modulation, rewriting codes) Biological computation mechanisms, particularly DNA sequence evolution via replication Secure distributed storage systems and RAID schemes Awards & Recognition: Recipient of the Feynman Teaching Prize (2008), Sloan Fellowship, NSF Young Investigator Award, and multiple IEEE best paper awards. Holds over 40 patents and authored 350+ publications. Industry Contributions: Co-founder of storage startups Rainfinity (acquired by EMC) and XtremIO, which pioneered flash storage solutions. Collaborates with NASA-JPL on non-volatile memory for space missions.

Mark WheelhouseView profile

Teaching Professor

• On-line Teaching and Assessment
• Automated Testing
• Automated Program Verification
• +9 more

Dr. Mark Wheelhouse is a Teaching Professor in the Department of Computing at Imperial College London. He serves as Joint Maths and Computing (JMC) Director and Undergraduate Second Year Coordinator. His roles include curriculum development, lab coordination, and overseeing the JMC degree program. He lectures on first-year modules like "Logic & Reasoning" and "Reasoning about Programs". Education: Joint Masters in Mathematics and Computer Science from Imperial College London (2003-2007), graduating with first-class honours and winning the Donald Davies Memorial Prize. Previously, he completed a PhD under Prof. Philippa Gardner, focusing on extending Context Logic for concurrent program analysis, resulting in Segment Logic. Research interests span online education, automated testing systems (e.g., LabTS), formal verification techniques, concurrency, and programming language theory. He advocates for online learning platforms like EdStem and Piazza to enhance teaching support. Lab involvement includes developing the automated Lab Testing System (LabTS) and advancing formal logic frameworks for program analysis. His work intersects theoretical computer science with practical educational tools.

Daniel SanchezView profile

Professor

• Computer Architecture
• Systems & Networking
• Parallel Computing
• +5 more

Dr. Daniel Sanchez is a Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), where he leads the Computation Structures Group within the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on computer architecture, scalable systems, and memory hierarchies, with particular emphasis on multicore and many-core systems, quality-of-service guarantees, and runtime systems. Education: Ph.D. in Electrical Engineering, Stanford University (2012) M.S. in Electrical Engineering, Stanford University (2009) B.S. in Telecommunications Engineering, Technical University of Madrid (UPM) (2007) Research Interests: Dr. Sanchez’s work spans computer architecture innovations such as cache partitioning (KPart), software-defined caches (Jenga), and accelerators for sparse computing (Azul, Terminus). He designs systems that enhance performance, energy efficiency, and scalability in modern computing environments. His projects include the Swarm Architecture for ordered parallelism and architectures supporting fully homomorphic encryption. Articles Trends: Recent publications emphasize accelerators for sparse algorithms, cryptographic hardware (e.g., Fully Homomorphic Encryption), and high-performance computing. His work bridges hardware-software co-design to tackle challenges in irregular applications, memory hierarchies, and secure computing. Awards & Grants: No scientific awards explicitly listed, but his work has been recognized in top conferences (e.g., MICRO, ISCA). Advising & Teaching: He advises over 20 Ph.D. and master’s students, including current advisees Axel Feldmann and Hyun Ryong Lee. He teaches courses like 6.5900 Computer System Architecture and 6.191 Computation Structures at MIT. Labs & Teams: Leader of the Computation Structures Group at MIT CSAIL, collaborating with researchers like Joel Emer, Srini Devadas, and Armando Solar-Lezama. His team explores cutting-edge architectures and systems for next-generation computing.