جست‌وجوی استاد و پژوهشگر

William B. Levyمشاهده پروفایل

استاد

• Neuroscience
• Computational Biology
• Biophysics
• +۳ مورد دیگر

William B. Levy is a Professor in the Department of Neurological Surgery at the University of Virginia School of Medicine. His research focuses on the neural bases of cognition and computational theories of brain function, utilizing theoretical neuroscience tools to model hippocampal and cortical interactions. Primary Appointment: Professor, Neurological Surgery Research Affiliation: Center for Excellence in Education & Research Research Interests: Biologically realistic hippocampal modeling for cognitive tasks (transitive inference, trace conditioning, maze learning) Information-theoretic analysis of neural communication under energy constraints Development of verified software for large-scale neural network simulations Recent Publication Trends: His work combines computational neuroscience (hippocampal modeling, synaptic dynamics) with biophysics (energy constraints, action potential efficiency) and cognitive science (memory, reasoning mechanisms).

Gowtham Kakiمشاهده پروفایل

استادیار

• Programming Languages
• Formal Methods
• Distributed Systems
• +۴ مورد دیگر

Gowtham Kaki is an Assistant Professor in the Department of Computer Science at the University of Colorado Boulder. His research focuses on the intersection of Programming Languages, Formal Methods, and Distributed Systems, with emphasis on automated verification techniques for concurrent and distributed programs. Education: Purdue University (PhD), BITS Pilani (Bachelors) Research Interests: Programming Languages, Formal Methods, Distributed Systems, Security, and AI Teaching: CSCI 3155 (Principles of Programming Languages), CSCI 7000 (Principles of Functional Programming), CSCI 5535 (Foundations of Programming Languages), and CSCI 7000 (Distributed Systems Verification) His work has produced 15 recent publications in verification techniques for distributed systems, including runtime-assisted convergence, CRDTs, and cryptographic secrecy. He has also received multiple awards including Google's PhD Fellowship and BITS Pilani's 30-under-30 recognition. He actively collaborates with the CUPLV research group and serves on program committees for OOPSLA, PLDI, and PaPoC conferences. His GitHub repositories demonstrate technical contributions in OCaml, taint analysis, and Z3 SMT integration.

Azalea Raadمشاهده پروفایل

دانشیار

• Programming Languages
• Formal Verification
• Weak Memory Models
• +۴ مورد دیگر

Dr. Azalea Raad is an Associate Professor (Reader) in the Department of Computing at Imperial College London, leading the Veritas Lab. She is also co-director of the UK Research Institute on Verified, Trustworthy Software Systems (VeTSS). Her research focuses on programming languages, formal verification, and weak memory models, with contributions to persistent memory technology and concurrency. Raad has held visiting roles at Facebook and Bloomberg, and has been recognized with awards such as the UKRI Future Leaders Fellowship and the SIGPLAN Distinguished Paper Award. Her work bridges theoretical foundations with practical tools for ensuring software correctness. Education & Roles: PhD (Imperial College London, 2016) Reader/Associate Professor (Imperial College London, 2021–present) Co-Director, UK VeTSS Institute (2023–present) Research Interests: Her research explores formal methods for persistent programming, including non-volatile memory semantics, weak memory models, and concurrency. She develops tools like Incorrectness Separation Logic and frameworks for verifying binaries (e.g., IsaBIL). Her work emphasizes practical applications in industrial settings, such as Intel PMDK transactions and RDMA robustness. Grants & Awards: EPSRC Research Grant: Safe and Secure Remote Direct Memory Access (2023) UKRI Future Leaders Fellowship (2021) Meta Research Gift (2022) Imperial College President’s Award (2021) Professional Activities: Program Committee Member: ESOP (2024), CAV (2022), ICFP (2022) Keynote Speaker: MFPS (2022), PLDI (2021) Labs & Teams: Leads the Veritas Lab, focusing on verified software systems, and collaborates with industry partners like Intel and Bloomberg through applied research initiatives.

Bo Yuanمشاهده پروفایل

استاد

• Cybersecurity
• Malware Analysis
• Computational Intelligence
• +۳ مورد دیگر

Bo Yuan is a Professor in the Department of Cybersecurity at Rochester Institute of Technology (RIT), affiliated with the Golisano College of Computing and Information Sciences. He served as Department Chair from 2014 to 2022, leading significant growth in cybersecurity programs. His research focuses on computational intelligence applied to cybersecurity, including malware analysis, machine learning, and covert channel detection. Education: Ph.D. in Systems Science (1996, Binghamton University), MS and BS in Mathematics (Shanghai Normal University, China). Research Interests: Cybersecurity, malware detection, computational intelligence, and machine learning applications in security. He has secured over $23M in grants, including NSF CyberCorps® SFS (2015-2024, 2019-2024, 2024-2029) and DoD Cyber Scholarship Programs. His work includes developing covert channel detection methods, improving malware analysis via machine learning, and advancing cybersecurity education through game-based learning. Grants/Projects: Multiple NSF and DoD grants totaling millions, focusing on cybersecurity workforce development and research. He leads RIT’s CAE-CD and CAE-R initiatives. His research has been applied in competitions like the Northeast Collegiate Cyber Defense Competition (NECCDC). Teaching includes courses on cybersecurity analytics, machine learning, and authentication models. He advises students on topics like adversarial machine learning and network security.

• Computer architecture
• Computing with novel technologies
• Brain-inspired computing

Georgios Tzimpragos is a Professor in the Department of Electrical & Computer Engineering at the University of Wisconsin-Madison, with a focus on computer architecture and novel computing technologies. Previously, he was an Assistant Professor at the University of Michigan (2022–2025) and earned his PhD from UC Santa Barbara (2022), focusing on neuro-inspired temporal paradigms for superconducting computing. His research explores overcoming technology limitations in superconductors, quantum computing, and biological computing systems, aiming to bridge computation and verification for improved correctness and security. Education: PhD in Computer Science, University of California-Santa Barbara (2022) MS in Computer Science, University of California-Davis (2016) BS in Computer Science, National Technical University of Athens (2012) Research Interests: His work spans computer architecture, novel computing technologies (e.g., superconductors, flexible electronics), and brain-inspired computing. Recent projects include developing energy-efficient superconducting circuits, quantum computing hardware, and neuromorphic systems that integrate biological principles. His group emphasizes formal verification and semantic gap reduction in computing systems. Recent Publications Trends: His articles address topics like superconducting logic design, quantum circuit simulation, and neuromorphic hardware acceleration. Recent work highlights include clockless superconducting logic, evolutionary neural network optimization, and formal methods for circuit validation. Awards & Honors: James E. Smith Professorship (UW-Madison, 2025) ACM SIGARCH & IEEE CS TCCA Outstanding Dissertation Award (2023) Quantum Research Institute Fellowship (U-Michigan, 2024) Grants & Teaching: Teaches E C E 554 (Digital Engineering Laboratory) and has received grants supporting superconducting and quantum computing research. His lab collaborates with industry partners on low-power and scalable architectures.

Dave Naumannمشاهده پروفایل

استاد

• Formal Methods
• Software Security
• Relational Verification
• +۷ مورد دیگر

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
• +۵ مورد دیگر

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 Zengمشاهده پروفایل

استادیار

• Quantum Networking
• Quantum Computing
• Edge Computing
• +۳ مورد دیگر

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. Nearمشاهده پروفایل

دانشیار

• Data Privacy
• Differential Privacy
• Computer Security
• +۵ مورد دیگر

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 Wittemannمشاهده پروفایل

استادیار

• Art and Conflict
• Visual Arts
• Comics and Graphic Narratives
• +۳ مورد دیگر

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 Papaefthymiouمشاهده پروفایل

استاد

• Energy-Efficient Computing
• Charge-Recovery Technologies
• Computer Architecture
• +۷ مورد دیگر

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 Imaniمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Computer Architecture
• +۳ مورد دیگر

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 Bromanمشاهده پروفایل

استاد

• Programming Languages and Compilers
• Real-Time Systems and Cyber-Physical Systems
• Probabilistic Machine Learning
• +۲ مورد دیگر

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
• +۳ مورد دیگر

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
• +۹ مورد دیگر

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.