Find Academic Supervisors

Yu LiuView profile

Professor

• Sustainable Computing
• Energy-Efficient Software
• Programming Languages
• +3 more

Yu Liu is a Professor at the School of Computing, Binghamton University, where he has been a faculty member since 2008. His research focuses on sustainable computing, energy efficiency, and security in emerging software systems, with significant contributions to programming languages, robotics, and software-hardware interfaces. Education: MSE, Johns Hopkins University PhD, Johns Hopkins University Professor Liu's research centers on sustainable computing and energy-aware software systems. He investigates programming language designs for energy prediction, develops reliable robotics software through managed languages, and creates secure software-hardware interfaces. His work bridges theoretical foundations with practical applications in data centers, UAV systems, and multi-threaded environments, emphasizing verifiable sustainability metrics and energy-efficient resource management. His publication trends reveal a consistent focus on sustainable computing evolution, with recent work advancing verifiable sustainability frameworks in data centers (2023-2024), energy accounting for multi-threaded applications (2020), and secure cache management techniques (2022). The research spans programming language theory, robotics safety, and hardware security, demonstrating interdisciplinary integration across computer science subfields. Scientific Awards: NSF CAREER Award Google Faculty Research Award Fulbright Scholarship Professor Liu has secured significant research funding through his NSF CAREER Award and Google Faculty Research Award, supporting innovations in sustainable computing infrastructure. His Fulbright Scholarship enabled international collaboration in Slovenia, advancing global research in energy-efficient software systems. He regularly teaches core courses including Programming Languages (CS471/571) and Sustainable Computing (CS680G), mentoring the next generation of computer scientists. While specific lab affiliations aren't detailed in the source text, his research on UAV software (Jcopter) and cache security (Composable cachelets) suggests active involvement in robotics and systems security research groups at Binghamton University.

Minlan YuView profile

Professor

• Computer Science
• Networking
• Distributed Systems
• +9 more

Minlan Yu is the Gordon McKay Professor of Computer Science at Harvard University's John A. Paulson School of Engineering and Applied Sciences (SEAS). She leads the Harvard Theory and Systems group and co-leads the Harvard Power and AI initiative. Her research focuses on data networking, distributed systems, and software-defined networking, with recent emphasis on sustainable computing and AI-driven network management. She is also Assistant Director of the SRC/DARPA JUMP 2.0 ACE Center for Evolvable Computing. Key research interests include network optimization, edge AI serving, large-scale resource allocation, and fault tolerance in distributed systems. Recent work highlights include innovations in energy-efficient data centers, homomorphic encryption acceleration, and real-time network telemetry using FPGA coprocessors. Teaching responsibilities include advanced courses on networking (CS 145/243) and systems programming. She actively advises PhD students and postdocs across systems and networking domains. Her lab's work has led to impactful contributions in both academia and industry, with a focus on bridging theory and practical system implementations. Current research initiatives include the Harvard Power and AI initiative exploring energy-efficient AI workflows and the development of evolvable computing infrastructure through the ACE Center.

• 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.

Amitabh NarainView profile

Professor

• Heat Transfer
• Fluid Mechanics
• Thermal Management
• +6 more

Professor Amitabh Narain holds a PhD from the University of Minnesota (1983) and is a Professor in the Department of Mechanical and Aerospace Engineering at Michigan Technological University. He is a Fellow of the ASME and serves as an Associate Editor of ASME JOE. His research focuses on phase-change phenomena, including enhanced nucleate boiling and flow condensation, with applications to thermal management, waste heat recovery, and cooling for high-performance computing and electric vehicles. He has secured continuous NSF, NASA, and industry funding since 1986, resulting in over 85 peer-reviewed publications. Education: PhD in Mechanical Engineering, University of Minnesota (1983). Research expertise includes heat transfer, fluid mechanics, and multiphase flows. Current projects emphasize data center cooling and small-scale power generation for energy efficiency. He leads experimental and computational studies using advanced CFD/CHT tools. ASME Fellow Associate Editor, ASME Journal of Engineering for Gas Turbines and Power Former Chair/Vice-Chair of ASME committees HTD-K8 and AMD-Fluid Mechanics Research trends include high heat-flux cooling, dielectric fluids, and microstructuring for stable boiling. Recent work addresses gravity-independent cooling systems and pulsatile flow control. His NSF-funded projects (2023) explore energy-efficient cooling and waste heat recovery in data centers. Grants and collaborations involve industry partnerships for applied thermal solutions. Labs and teams: Active in experimental setups for flow boiling/condensation, CFD simulation development, and microchannel heat sink design. Collaborates with students and researchers on thermal system innovations.

Emily DolsonView profile

Assistant Professor

• Artificial Life
• Evolutionary Computation
• Eco-Evolutionary Dynamics
• +5 more

Emily Dolson is an Assistant Professor in the Department of Computer Science and Engineering (CSE) at Michigan State University's College of Engineering, and core faculty in the Ecology, Evolution, and Behavior program. Her research focuses on developing algorithmic approaches to control evolutionary trajectories in complex ecological communities through computational experiments, spanning simple models to artificial life systems. This work bridges evolutionary medicine, computational theory, and empirical biology through collaborations with wet-lab scientists. Education: Ph.D., Computer Science & Engineering and Ecology, Evolutionary Biology, & Behavior, Michigan State University (2019) B.A., Computer Science and Biology, Swarthmore College (2013) Her research interests emphasize computational tools for evolutionary dynamics, including phylogenetic tracking, open-ended evolution measurement (via the MODES toolbox), and ecological theory integration into evolutionary algorithms. Recent work explores fitness seascapes, counterdiabatic driving in evolutionary systems, and scalable phylogenetic analysis. Awards: International Society for Artificial Life Outstanding Service Award (2019) International Society for Artificial Life Outstanding Student Research Award (2019) Publications highlight innovations in evolutionary computation techniques, phylogenetic informatics, and interdisciplinary applications of artificial life. Ongoing efforts include developing high-performance tools for tracking evolutionary processes at scale and exploring evolutionary mechanisms relevant to medical and environmental contexts.

Nektarios TsoutsosView profile

Assistant Professor

• Information Security
• Applied Cryptography
• Computer Architecture
• +3 more

Nektarios Tsoutsos is an Assistant Professor at the University of Delaware, specializing in information security, applied cryptography, and hardware security. His research focuses on encrypted computation, homomorphic encryption, and secure hardware architectures. He holds a PhD from New York University, where he was previously a postdoc in the Modern Microprocessor Architectures laboratory. Education : PhD in Computer Science, New York University Research Interests : Homomorphic encryption frameworks and their acceleration Hardware-software co-design for secure computing Privacy-preserving technologies in additive manufacturing and distributed systems Cryptography for machine learning and IoT Awards : New York University Ph.D. Student Fellowship Pearl Brownstein Doctoral Research Award (NYU) Grants & Projects : CAREER Grant: Accelerating Encrypted Computation on Diverse Hardware (2023) CCRI Grant: Data-Driven Cybersecurity for Smart Manufacturing (2023) His work includes developing secure processors (e.g., Juliet), accelerating FHE algorithms (e.g., Ripple), and creating datasets for 3D printing security. He collaborates on frameworks like HELM and Mastic, addressing challenges in privacy, performance, and scalability.

• Cyberinfrastructure
• Grid Computing
• Authentication
• +5 more

James Alan Basney is a Principal Research Scientist at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign. His work focuses on cyberinfrastructure, grid computing, and secure authentication mechanisms for scientific data access. Recent research highlights include: Transitioning the Worldwide LHC Computing Grid (WLCG) from X.509 certificates to token-based authentication Comparative analysis of SciTokens, verifiable credentials, and blockchain-based smart contracts for secure data access Developing the Cybershuttle framework for end-to-end cyberinfrastructure integration Creating the Falcon algorithm for efficient file transfer optimization His work intersects cybersecurity, distributed systems, and scientific computing, with a focus on privacy-preserving authentication, blockchain applications, and data management in high-throughput environments.

Josep TorrellasView profile

Professor

• Computer Architecture
• Parallel Processing
• Hardware Reliability
• +1 more

Josep Torrellas is the Saburo Muroga Professor of Computer Science at the University of Illinois at Urbana-Champaign. He directs the SRC/DARPA JUMP 2.0 ACE Center for Evolvable Computing and leads research in computer architecture, with focus on parallel processing, energy efficiency, and hardware reliability. Dr. Torrellas has received major awards including the IEEE Harry H. Goode Memorial Award, UIUC Campus Mentoring Award, and IEEE Technical Achievement Award. He is a Fellow of IEEE, ACM, and AAAS. His recent publications demonstrate strong focus on cloud security, serverless computing, and AI acceleration. Research consistently addresses hardware/software co-design for emerging computing paradigms. He has graduated 48 PhD students, many now faculty at top institutions. Dr. Torrellas teaches courses in parallel computer architecture and advises students in the ACE Center for Evolvable Computing.

• Parallel and Distributed Algorithms
• Network Embedded Systems
• Multi-agent Systems
• +4 more

Gul A Agha is a Research Professor and Professor Emeritus in the Department of Computer Science at the University of Illinois at Urbana-Champaign. He holds affiliations with the Open Systems Laboratory and focuses on concurrent computing, distributed systems, and actor-based models. His work on the Actor Model is foundational in concurrent programming, with contributions to languages, systems, and formal verification techniques. Education: Ph.D. in Computer & Communication Science from the University of Michigan (1985). Research Interests: Parallel and distributed algorithms, network embedded systems, multi-agent systems, and concurrent programming languages. His group develops high-performance systems for real-time, fault-tolerant applications, combining theoretical models with practical implementations. Key Achievements: Named ACM Fellow (2018) for contributions to concurrent systems and actor models. Led projects in structural health monitoring using wireless sensors, such as the Little Calumet River Bridge and 2nd Jindo Bridge. Pioneered actor-based frameworks for IoT and cloud computing. Grants & Awards: Includes NSF-funded projects on cyber-physical systems and cloud computing assurance. Recognized for innovations in distributed consensus (Synod) and energy-efficient parallel algorithms. Labs/Teams: Director of the Open Systems Laboratory, collaborating on actor platforms (Actornet) and middleware for sensor networks. Advised over 20 graduate students in distributed systems and formal methods.

Michael FranzView profile

Professor

• Software Systems
• Compiler Design
• Virtual Machine
• +9 more

Professor Michael Franz is a Distinguished Professor and ICS Alumni Professor in the Donald Bren School of Information and Computer Sciences at the University of California, Irvine. He also holds a courtesy appointment in the Department of Electrical Engineering and Computer Science in the Henry Samueli School of Engineering. Franz directs UCI's Secure Systems and Software Laboratory and is a Fellow of AAAS, ACM, IEEE, and an Inaugural Fellow of IFIP. His educational background includes: Doctor of Technical Sciences in Computer Science from ETH Zurich (advisor: Niklaus Wirth) Dipl. Informatik-Ingenieur ETH degree from ETH Zurich Professor Franz pioneered mobile code and dynamic compilation research, creating early just-in-time compilation systems and co-inventing trace compilation technology that became Firefox's JavaScript engine. His current research focuses on Software Systems, particularly compiler and virtual machine techniques for making software safer, faster, or both. His work spans Computer Security, Trustworthy Computing, and Software Engineering, with recent emphasis on multivariant execution, automated software diversity, and probabilistic memory safety. Franz's research bridges theoretical foundations with practical applications, resulting in technologies deployed in major software systems used by hundreds of millions. His publication record demonstrates consistent leadership in security and systems research, with recent work focusing on survivable systems, binary analysis, and cross-platform security solutions. The publications reveal an evolution from foundational compiler techniques to sophisticated security mechanisms addressing real-world vulnerabilities, with strong emphasis on practical implementation and measurable impact. Professor Franz has received numerous prestigious awards: ACM Charles P. 'Chuck' Thacker Breakthrough in Computing Award (2020) Humboldt Research Award (2019) Distinguished Professor at UCI (2022) UCI's 'Innovator of the Year Award' (2018) Fellowships from all four major computing professional organizations Multiple Best Paper Awards at top-tier conferences As an advisor, Franz has graduated over 40 Ph.D. students, with recent graduates including Mitchel Dickerson and André Rösti. His research group has secured over $24 million in competitive grants (more than $16 million as sole PI) and received over $1 million in unrestricted industry gifts. Franz maintains strong industry connections, with many former students now at Google, Apple, and Meta, and his research directly influences commercial technologies. Leading the Secure Systems and Software Laboratory, Franz fosters a collaborative environment focused on developing innovative security solutions. The lab maintains global research partnerships and continues to advance areas like multivariant execution systems, automated software diversity, and practical security mechanisms. Current projects emphasize developing systems that maintain functionality even when compromised, addressing the evolving landscape of cyber threats with scientifically rigorous approaches.

• Algorithms and Theory
• Computer Graphics and Vision
• Security, Privacy and Cryptography
• +3 more

Michael Goodrich is a Professor at the University of California, Irvine (UCI), Department of Computer Science since 2001, and Technical Director of the ICS Center for Algorithms and Theory of Computation. Previously, he was a professor at Johns Hopkins University (1987-2001). His research focuses on high-performance algorithms, data structures, and their applications to security, machine learning, geometric computing, and distributed systems. He has over 300 publications and authored influential textbooks. Education: B.A. in Mathematics and Computer Science, Calvin University, 1983 Ph.D. in Computer Science, Purdue University, 1987 Research Interests: Algorithm design and complexity Cryptography and privacy-preserving systems Geometric computing and computational geometry Machine learning and data structures Network security and cloud storage Notable Contributions: Pioneered efficient solutions for sorting, convex hulls, and privacy-preserving data access Advances in quantum algorithms, graph theory, and distributed systems Consultant for AT&T, Walt Disney Animation Studios, and NSF Awards and Honors: ACM Distinguished Scientist AAAS Fellow IEEE Fellow and ACM Fellow Recipient of IEEE Technical Achievement Award Elected Foreign Member of the Royal Danish Academy Grants and Collaborations: $1.2M NSF grant for geometric graphs research (2022) Collaborations with NSA, ONR, DARPA, and industry partners

Alexey TumanovView profile

Assistant Professor

• Machine Learning
• Distributed Systems
• Resource Management
• +4 more

Alexey Tumanov is an Assistant Professor in the School of Computer Science at Georgia Institute of Technology, part of the College of Computing. His research focuses on systems for machine learning, resource management, and scheduling in distributed environments. He holds a PhD from Carnegie Mellon University and conducted postdoctoral research at UC Berkeley under Ion Stoica. Previously, he worked at the University of Toronto and in industry on cloud computing and datacenter systems. Education: PhD in Computer Science, Carnegie Mellon University (2019) Postdoc, UC Berkeley RISELab (2019) MSc in Computer Science, University of Toronto (2012) BSc in Computer Science, University of Toronto (2010) Research Interests: Tumanov's work addresses challenges in distributed machine learning, including efficient resource management for inference and training pipelines, scheduling algorithms for soft-real-time systems, and federated learning. His lab (SAIL) develops systems like SARATHI-SERVE and RocketKV to optimize LLM inference and co-scheduling. He emphasizes practical deployments in healthcare (HOLMES) and cloud environments. Key Contributions: Ray distributed framework for AI (OSDI 2018) ESCHER scheduler for ephemeral cloud resources (SoCC 2022) InferLine ML pipeline orchestration (SoCC 2020) Awards: NSERC CGS-D3 Scholarship (2016) Best Paper at EuroSys 2016 (TetriSched) Google PhD Fellowship Nominee (2018) Lab & Teaching: Leads the Systems for Artificial Intelligence Lab (SAIL) at Georgia Tech. Teaches advanced courses on operating systems (CS3210) and systems for ML (CS8803-SMR). Supervises 15+ graduate students across PhD and MS programs.

Pinaki SarderView profile

Associate Professor

• Computational Pathology
• Artificial Intelligence in Healthcare
• Kidney Disease Analysis
• +3 more

Pinaki Sarder, Ph.D., is an Associate Professor in the Department of Medicine – Section of Quantitative Health at the University of Florida (UF), with affiliate roles in the Department of Electrical & Computer Engineering and Biomedical Engineering. He also serves as Associate Director for Imaging at the Intelligent Critical Care Center. Previously, he held tenure as an Associate Professor at the University at Buffalo (UB) in Pathology & Anatomical Sciences and Biomedical Engineering. His academic journey includes postdoctoral training in optical radiology at Washington University in St. Louis (WUSTL) and a Research Fellowship at Harvard University's School of Public Health. He earned his B.Tech. from IIT Kanpur and M.Sc./Ph.D. in electrical engineering from WUSTL. Dr. Sarder's research focuses on computational fusion of spatial omics data, particularly in diabetic kidney disease, leveraging AI and digital pathology. His work is funded by NIH, KPMP, and HubMAP. Key contributions include developing tools like ComPRePS for automated image analysis and the HistoLens platform for accessible pathology visualization. He is an editorial board member of the Journal of the American Society of Nephrology and Associate Editor of IEEE Journal of Biomedical Health Informatics. His awards include UB’s 2018 Exceptional Scholars – Young Investigator Award. He leads NIH-funded projects exploring kidney disease mechanisms, including the Cosmic Kidney Disease initiative investigating spaceflight-induced renal dysfunction. Dr. Sarder also contributes to educational initiatives, such as internship curricula promoting STEM diversity and consensus-based evaluation metrics for NIH programs. Research interests span computational pathology, AI-driven diagnostic tools, kidney disease biomarker discovery, and translational medical imaging. His lab develops open-source tools like DUET for collagen/elastin quantification and FUSION for multi-omics data integration with histology. Grants: NIH, KPMP Consortium, HubMAP Consortium Labs: Computational Microscopy Imaging Laboratory Teams: Intelligent Critical Care Center, Kidney Precision Medicine Project (KPMP)

Andrew GrimshawView profile

Professor

• Grid Computing
• Parallel Processing
• Distributed Systems
• +3 more

Andrew Grimshaw is a Professor of Computer Science at the University of Virginia's School of Engineering and Applied Science. He received his Ph.D. from the University of Illinois at Urbana-Champaign in 1988. His career has focused on advancing distributed computing, grid systems, and high-performance computing. Grimshaw is best known for designing the Legion system, a foundational grid operating system, and co-founding Avaki Corporation (acquired by Sybase), which commercialized grid technologies. Education: Ph.D. in Computer Science, University of Illinois at Urbana-Champaign, 1988 Research Interests: Grimshaw's work spans distributed systems architecture, parallel processing, and cyberinfrastructure. He pioneered systems like Mentat and ELFS, and contributed to Grid Computing standards through projects such as XSEDE and the Global Grid Forum. His research emphasizes scalable, fault-tolerant systems and interoperability between heterogeneous resources. Publications: His work reflects advancements in grid computing, GPU algorithms, and federated systems. Key themes include global virtual computing, market-based resource allocation, and standards-based job execution. Recent efforts focus on XSEDE's Global Federated File System (GFFS) and service-oriented cloud federations. Awards: Frost & Sullivan Technology Innovation Award (2003) Grants & Roles: Grimshaw has served on NSF advisory committees, the NPACI Executive Committee, and the Global Grid Forum. His leadership in Avaki and XSEDE highlights his commitment to bridging academic and industrial computing challenges. Current projects explore campus bridging and standards-driven cyberinfrastructure integration. Labs/Teams: Associated with the University of Virginia's Computer Science department and XSEDE initiatives, his work drives collaborative research on distributed systems and high-performance computing frameworks.

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.