Find Academic Supervisors

Charles LeisersonView profile

Professor

• Computer Science
• Algorithms
• Parallel Computing
• +4 more

Charles Leiserson is the Edwin Sibley Webster Professor in the Department of Electrical Engineering and Computer Science (EECS) at MIT. He is renowned for co-authoring the seminal textbook Introduction to Algorithms , now in its fourth edition, which is widely used globally. His research focuses on algorithms, parallel computing, and software performance engineering, with contributions to theoretical computer science and practical systems like the Cilk multithreaded language and the Connection Machine CM-5 architecture. Leiserson’s work spans compiler design (e.g., Pochoir for stencil computations) and high-performance computing frameworks. He explores post-Moore’s Law computational strategies, graph neural networks for financial forensics, and deterministic parallel algorithms. His educational contributions include courses like 6.172 (Performance Engineering of Software Systems) and initiatives in scalable graph learning. His research has led to innovations in parallel programming models, algorithm optimization, and hardware-software co-design. Leiserson’s interdisciplinary work bridges theory and practice, influencing both academic research and real-world applications in finance, cryptography, and supercomputing.

Prateek SAXENAView profile

Associate Professor

• Computer Security
• Machine Learning Security
• Trustworthy AI
• +4 more

Prateek SAXENA is an Associate Professor in the Computer Science Department at the School of Computing, National University of Singapore. He serves as Co-Director of the CRYSTAL Centre and teaches courses including CS3235 Computer Security and CS5562 Trustworthy Machine Learning. His research spans multiple domains within computer security and systems. Dr. SAXENA earned his Ph.D. in Computer Science from the University of California, Berkeley (2012), an M.S. in Computer Science from Stony Brook University (2007), and a B.E. in Computer Engineering from the University of Pune, India (2004). His research focuses on building better security and privacy in practical systems through principled approaches combining formal reasoning, tools and ideas from several computer science domains. Current research thrusts include machine learning security, decentralized systems security, security processors, and automatic program translation. His work has resulted in several practical artifacts powering real-world systems, including spinoffs like Zilliqa and Kyber Network. His publication record demonstrates consistent high-impact research across security domains including web security, blockchain, trusted execution environments, and machine learning security. His work shows a progression from foundational web security research to cutting-edge work on blockchain systems and machine learning security. MIT Technical Review, Top 10 Innovators under 35, Asia - 2017 Security and Privacy Research Award, 2018 Young Research Award, NUS, 2017 David J. Sakrison Memorial Prize for outstanding doctoral work, UC Berkeley, 2012 AT&T Best Applied Security Research Paper Award 2010 Dr. SAXENA has advised numerous successful PhD students who have gone on to prominent positions at Microsoft Research, Georgia Tech, ETH Zurich, and industry leaders like Zilliqa and Kyber. His research has been generously supported by CISCO Research, Google, Intel, Symantec, MoE-Singapore, DSO Labs, and NRF-Singapore. He leads the KISP Lab (Keep It Secure and Private), which has produced influential research in blockchain, trusted execution environments, and security tools.

Margo SeltzerView profile

Professor

• Computer Systems
• Operating Systems
• Database Systems
• +7 more

Margo Seltzer is a Professor and Co-Head of the Department of Computer Science at the University of British Columbia (UBC). She holds the Canada 150 Research Chair in Computer Systems and the Cheriton Family Chair in Computer Science. Her research focuses on computer systems, including operating systems, databases, data provenance, graph analytics, and interpretable machine learning. She is also involved in educational initiatives and has held leadership roles in academia, including serving as Dean of Computer Science and Engineering at Harvard University. Education: PhD in Computer Science from UC Berkeley (1992), AB in Applied Mathematics from Harvard (1983). Professional roles include Chief Technology Officer at Sleepycat Software and architect at Oracle Corporation. She has received prestigious awards such as the ACM Athena Lecturer Award, Killam Teaching Prize, and membership in the National Academy of Engineering. Research Interests: Systems, databases, transaction processing, provenance capture, healthcare informatics, and cybersecurity. Her work emphasizes practical applications of systems research, including optimizing storage, improving operating system performance, and enhancing data security. She has contributed to open-source projects like Berkeley DB and CamFlow provenance system. Key Contributions: Developed systems for provenance-aware storage, sparse decision trees (e.g., GOSDT), and intrusion detection (FRAPpucino). She advocates for reproducible research through tools like Encapsulator and Rclean. Her teaching and mentorship have influenced countless students and junior faculty in computer science. Awards: ACM Athena Lecturer (2023), SIGMOD Systems Award (2020), USENIX Lifetime Achievement Award (2019), and election to the American Academy of Arts and Sciences (2021). Her work bridges theoretical computer science with real-world applications, emphasizing both technical innovation and societal impact.

Mohammad ShahradView profile

Assistant Professor

• Cloud Computing
• Sustainability
• Large-Scale Computing Systems
• +3 more

Mohammad Shahrad is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of British Columbia (UBC) and an Associate Faculty Member of UBC's Computer Science Department. He leads the UBC Cloud Infrastructure Research for Reliability, Usability, and Sustainability (CIRRUS) Lab. His research focuses on sustainable and efficient large-scale computing systems, particularly in cloud resource management and serverless systems. Education: Ph.D. in Electrical Engineering, Princeton University (2020) M.A. in Electrical Engineering, Princeton University (2016) B.Sc. in Electrical Engineering, Sharif University of Technology, Tehran (2014) Research Interests: Shahrad's work emphasizes energy-efficient cloud computing, serverless architecture optimization, and sustainability in distributed systems. His projects address challenges like carbon footprint reduction, resource allocation, and cold-start delays in serverless platforms. He employs interdisciplinary approaches, combining system design, algorithm development, and empirical analysis to tackle real-world cloud infrastructure problems. Recent Contributions: His research trends include carbon-aware scheduling, geospatial shifting for sustainability, and developer-centric compliance tools for serverless applications. These efforts aim to balance performance, cost, and environmental impact in modern cloud ecosystems. Scientific Awards: Community Award at USENIX ATC '20 for Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider Advising & Grants: As CIRRUS Lab lead, Shahrad mentors researchers in cloud infrastructure and sustainability. While specific grant details are not listed, his work reflects substantial industry collaboration (e.g., Microsoft Research, Azure). Labs/Teams: The CIRRUS Lab focuses on creating sustainable cloud solutions through open-source frameworks like OpenPiton and collaborative industry partnerships.

Tapio LokkiView profile

Professor

• Acoustics
• Audio Engineering
• Room Acoustics
• +5 more

Professor Tapio Lokki is a renowned academic in acoustics and audio engineering at Aalto University's School of Electrical Engineering, Department of Signal Processing and Acoustics. He transitioned from the School of Science's Department of Computer Science to streamline teaching and research in acoustics. His work focuses on concert hall acoustics, spatial sound reproduction, binaural technology, and augmented reality audio. Key projects include developing measurement techniques for concert halls and sensory evaluation methods. He holds the title of Honorary Member of the Acoustical Society of Finland and is a Fellow of the Audio Engineering Society. Research interests include room acoustics modeling, perceptual differences in concert halls, and hearing protection devices. His contributions span psychoacoustic studies, material science for sound absorption, and virtual acoustic environments. He leads the Aalto Acoustics Lab, advancing interdisciplinary applications in audio engineering and environmental acoustics.

Kevin LeachView profile

Assistant Professor

• Cybersecurity
• Software Engineering
• Dependable Systems
• +3 more

Kevin Leach is an Assistant Professor of Computer Science at Vanderbilt University's School of Engineering. His research focuses on designing dependable cybersecurity systems and software engineering practices that withstand sophisticated adversarial attacks. He holds a PhD from the University of Virginia (2016), where he received the Louis T Rader Outstanding Research Award. Prior to Vanderbilt, he was a research scientist and lecturer at the University of Michigan. Education: Ph.D. in Computer Engineering, University of Virginia MS in Computer Science, George Mason University BS with Distinction in Computer Engineering and Computer Science, University of Virginia His research investigates two core areas: leveraging hardware capabilities like Trusted Execution Environments for low-overhead security instrumentation, and understanding how developers and operators make decisions in adversarial environments. He has published over 30 refereed articles, 3 of which have received awards. Recent work includes studies on cognitive biases in cybersecurity competitions, AI-driven code assessment, and malware detection techniques. Awards: Louis T Rader Outstanding Research Award (2016) 3 award-winning papers (specific awards unspecified) His research bridges technical security mechanisms with human decision-making processes, emphasizing both system dependability and developer/operator awareness. Current projects include work on federated learning defenses, runtime security optimization for embedded systems, and ethical considerations in crowdsourced data labeling.

• Artificial Intelligence
• Machine Learning
• Generative AI
• +5 more

Jesse Spencer-Smith is a Professor of the Practice of Computer Science at Vanderbilt University's School of Engineering. His research focuses on applying artificial intelligence and machine learning to interdisciplinary challenges, including bioinformatics, astrophysics, software engineering, and archaeology. He is particularly known for pioneering work in generative AI frameworks and prompt engineering methodologies. Recent research trends include developing AI tools for protein structure analysis (e.g., SuperMetal and SuperWater), gravitational wave signal processing, and optimizing large language models for coding and archaeological artifact analysis. His work bridges computational methods with domain-specific applications, emphasizing practical problem-solving across multiple scientific disciplines. Dr. Spencer-Smith has contributed to foundational studies in prompt engineering, publishing multiple catalogs of prompt patterns to systematize interactions with AI systems like ChatGPT. His interdisciplinary approach reflects a commitment to advancing AI's role in both theoretical and applied contexts. No scientific awards or grants were explicitly mentioned in the provided texts. He currently advises no formally listed students, though his research collaborations likely involve graduate and undergraduate participants. No specific lab affiliations or teams were detailed in the available information.

Emery D. BergerView profile

Professor

• Programming Languages
• Runtime Systems
• Operating Systems
• +3 more

Emery D. Berger is a Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst. He holds a Ph.D. in Computer Science from the University of Texas at Austin (2002). His research focuses on programming languages, runtime systems, and operating systems, emphasizing reliability, security, and performance. Key contributions include influential software systems like Hoard , DieHard , and DieHarder , which have influenced industry standards such as the Windows 7 Fault-Tolerant Heap and Mac OS X memory manager. Professor Berger's honors include an ACM Fellowship (2019), NSF CAREER Award, Lilly Teaching Fellowship, and multiple best paper awards. He has served as Program Chair for PLDI 2016 and co-chair for ASPLOS 2021, and is a co-director of the PLASMA research lab. His work spans academic contributions and practical tools like CSRankings.org , a widely used academic ranking site. Research interests include systems resilience, automated debugging (e.g., Coz ), and secure memory management. His group explores deterministic multithreading ( Grace ), spreadsheet error detection ( CheckCell ), and browser-based systems ( Browsix ). Collaborations with industry include Microsoft Research and Barcelona Supercomputing Center.

Ran CanettiView profile

Professor

• Cryptography
• Information Security
• Cryptographic Protocols
• +3 more

Ran Canetti is a Professor of Computer Science at Boston University and Director of the Center for Reliable Information Systems and Cyber Security. He is also a Fellow of the International Association for Cryptologic Research and an associate editor of the Journal of Cryptology and Information and Computation . His research focuses on cryptographic protocols, with an emphasis on their design, analysis, and practical use. Canetti holds a PhD from the Weizmann Institute of Science and has held roles at IBM Watson Research Center, MIT, and Tel Aviv University. Key research areas include universally composable security, zero-knowledge proofs, privacy-preserving technologies, and cryptographic protocol design. His work spans theoretical foundations and real-world applications, such as secure messaging, differential privacy, and blockchain security. Canetti has authored influential papers like Universally Composable Security: A New Paradigm for Cryptographic Protocols (2001) and contributed to standards like the HMAC specification. His awards include Fellowship in the IACR, recognizing his impact on cryptology. He advises on cybersecurity initiatives, including privacy-preserving exposure notification systems for public health. His lab explores cutting-edge topics like quantum-resistant cryptography and verifiable computing, maintaining a focus on both academic rigor and practical deployment.

Vasiliki KalavriView profile

Assistant Professor

• Distributed Data Processing
• Streaming Computation
• Large-Scale Graph Analysis
• +3 more

Vasiliki Kalavri is an Assistant Professor in the Department of Computer Science at Boston University, where she co-leads the Complex Analytics and Scalable Processing (CASP) Systems lab. She holds a PhD from KTH Royal Institute of Technology and the Catholic University of Louvain (UCLouvain), awarded through the EMJD-DC joint doctoral program, and completed a postdoctoral fellowship at ETH Zurich, supported by the ETH Zurich Postdoctoral Fellowship. Her research focuses on distributed data processing, streaming computation, and large-scale graph analysis, with recent work emphasizing self-managed stream processing systems, secure collaborative analytics (via Multi-Party Computation), and scalable graph machine learning. Education includes a PhD (KTH/UCLouvain), MS (Polytechnic University of Catalonia), and undergraduate degrees from National Technical University of Athens (2010) and Polytechnic University of Catalonia (2012). She is a PMC member of Apache Flink and co-authored the textbook *Stream Processing with Apache Flink*. Her research contributions span foundational systems for stream processing (e.g., Strymon, CAPSys), secure analytics (SECRECY, TVA), and graph ML (GCNSplit, In situ Sampling). Awards include the ETH Zurich Postdoctoral Fellowship. She advises a team of PhD students focused on distributed systems and security. Teaching includes CS 551 (Streaming and Event-based Systems) and CS 210 (Computer Systems). Service roles include leadership in the BU-ACM Women student chapter and chairing the CS Graduate Awards Committee. Her work appears in top venues like OSDI, NSDI, EuroSys, and VLDB.

Jishen ZhaoView profile

Professor

• Computer Architecture
• System Software
• Machine Learning
• +5 more

Professor Jishen Zhao leads research in computer architecture, system software, and machine learning at UC San Diego's Jacobs School of Engineering. He heads the Non-Volatile System Laboratory (NVSL), ML Systems Group, and contributes to PRISM and MICS centers. His work spans memory systems, ML-infused architectures, and autonomous vehicle computing systems. Recent achievements include ACM SIGSOFT Distinguished Paper (ISSTA 2024), IEEE Micro Top Picks recognition (2021-2022), and MICRO Hall of Fame induction (2019). He advises Ph.D. students like Hengyu Zhao and Xiao Liu, and collaborates on tools like PRO-V for RTL verification and MAGE for hardware design. Key research areas include persistent memory systems (e.g., SubZero filesystem), hardware-software co-design (e.g., Learn-to-Share framework), and autonomous vehicle safety (COLA latency optimization). He serves on program committees for ISCA, MICRO, and HPCA, reflecting his industry leadership in computer architecture.

Johan BoyeView profile

Associate Professor

• Natural Language Processing
• Spoken Dialogue Systems
• Multimodal Dialogue Systems
• +6 more

Johan Boye is an Associate Professor at the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, part of the Speech, Music, and Hearing department. He leads the SWE-QUEST project, developing automated question generation for Swedish language education, funded by Vinnova and Digital Futures. His research focuses on dialogue systems, natural language processing, and spatial language understanding, with applications in education, robotics, and human-computer interaction. Education background includes a docent title (Swedish associate professor) and extensive academic experience. He has supervised over 20 master’s and PhD theses in NLP and AI, with recent topics including large language models, coreference resolution, and multimodal retrieval systems. Teaching responsibilities include courses on language technology, search engines, and speech processing. His work spans cross-disciplinary collaborations with Stockholm University and RISE Research Institutes in the Digital Futures initiative, addressing societal challenges through digital innovation. Key projects include the SpaceBook EU project (2010–2014) exploring pedestrian navigation via dialogue systems and the NICE game (2005) for child-computer interaction. Research outputs include over 50 peer-reviewed publications in journals like the Journal of Natural Language Engineering and conferences such as ACL and SIGDIAL. He maintains active roles in academic service, including editorial work and program committees for NLP conferences. His lab develops tools like Textinator for NLP evaluation and UDon2 for dependency tree manipulation, emphasizing open-source contributions to the research community.

Gianni AntichiView profile

Senior Lecturer

• Networks
• Computer Architecture
• Programmable Hardware
• +3 more

Dr. Gianni Antichi is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science, and an Associate Professor at Politecnico di Milano. His research focuses on network architecture, programmable hardware, and data plane optimization. He holds grants from EPSRC and Facebook Research, and has received multiple awards including Best Paper at SIGCOMM 2017. Antichi teaches modules on distributed systems, computer networks, and Internet protocols. Research Interests: End-host networking stacks, programmable hardware (SmartNICs/FPGA), network telemetry, data center optimization, and traffic analysis. His work spans from low-level data plane design to high-level network monitoring solutions. Key Awards: EPSRC New Investigator Award (2020), Facebook Networking Research Award (2020), Best Student Paper at EuroSys 2025, and ACM SIGCOMM Best Paper (2017). Grants & Projects: Leads NEAT (EPSRC-funded network telemetry project), and collaborates with industry on software data plane optimization. Active in mentoring PhD students and researchers in distributed systems and network hardware. Labs/Teams: Part of Queen Mary’s Centre for Networks, Communications and Systems, focusing on programmable networking and high-performance systems.

Kevin DrewView profile

Assistant Professor

• Molecular Interactions
• Proteomics
• Computational Biology
• +4 more

Kevin Drew is an Assistant Professor in the Department of Biological Sciences at the University of Illinois Chicago's College of Liberal Arts and Sciences. His research focuses on developing computational and biochemical tools to systematically characterize molecular interactions in cells, with applications in understanding disease mechanisms and therapeutic development. Education includes a Ph.D. in Biology – Molecular Biophysics from New York University School of Medicine (2014), M.S. in Computer Science from University of Chicago (2005), and B.S. in Computer Science from University of Iowa (2003). Research interests span molecular interactions, proteomics, computational biology, structural biology, machine learning applications in biology, macromolecular assemblies, and drug design. The Drew Lab employs biochemical, computational, and proteomic approaches to identify cellular macromolecular assemblies, characterize their structural states, determine 3D structures, and develop interaction modulators. Publications demonstrate consistent focus on proteomics, computational modeling of protein complexes, and biomolecular interaction analysis. Recent work emphasizes high-throughput methods for complex identification, evolutionary conservation of interactions, and therapeutic targeting of protein interfaces. No awards or student advising information was available. Lab activities at the Drew Lab include systematic characterization of macromolecular assemblies using interdisciplinary approaches.

AbdullahView profile

Researcher

• Plant Breeding
• Agriculture
• Genetics
• +3 more

Abdullah is a researcher in the field of plant breeding and genetics at Texas A&M University's College of Agriculture and Life Sciences. His academic background includes a B.S. and M.S. in Agriculture (Plant Breeding and Genetics) from the University of Agriculture, Faisalabad, Pakistan, completed in 2008 and 2010 respectively. He holds a Ph.D. in Plant Breeding and currently works in the Agronomy Lab, focusing on wheat plant breeding and genetic improvement strategies. His research emphasizes enhancing crop yields through genetic advancements and optimizing breeding techniques for wheat varieties. Notable areas of exploration include genotype-environment interactions, trait selection, and molecular breeding approaches. Abdullah's recent publications span interdisciplinary topics including compiler optimization, cache indexing strategies, and deep learning acceleration techniques—reflecting a unique blend of agricultural and computational research interests. These works address challenges in hardware-software co-design, parallel computing efficiency, and cybersecurity in distributed systems. Though no formal awards are listed, his work demonstrates contributions to both agricultural science and computer systems engineering. His current research program involves collaborations with computational scientists to integrate data-driven methods into plant breeding programs.