Find Academic Supervisors

• Distributed Systems
• Network Function Virtualization
• Systems Correctness
• +4 more

Aurojit Panda is an Assistant Professor of Computer Science at New York University's Faculty of Arts and Science. His research focuses on lightweight mechanisms for system correctness, network function virtualization, and distributed systems. He holds a Ph.D. from UC Berkeley and a B.S. from Brown University. Education: Ph.D., Computer Science, UC Berkeley (2017) B.S., Math-Computer Science, Brown University (2008) Research Interests: Network Function Virtualization (NFV) Distributed Systems Correctness Machine Learning Tooling and Optimization Operating Systems and SmartNIC Offloading Recent work includes designing distributed shared logs for datacenters, analyzing straggler effects in large model training, and developing tools like NNSmith for deep learning compiler testing. Teaching includes courses on distributed systems, operating systems, and big data/machine learning. He is actively involved in research teams such as NetSys Lab and contributes to open-source projects like NetBricks and BESS.

Yannis ViniotisView profile

Professor

• Networking
• Service Engineering
• High Speed Networks
• +7 more

Yannis Viniotis is a Professor in the Department of Electrical and Computer Engineering at NC State University. His research focuses on networking, service engineering, and high-speed network technologies. He has authored textbooks on probability theory and mathematical principles for engineers, and co-founded Orologic, a semiconductor company acquired by Vitesse in 2000. Education: Ph.D. in Electrical Engineering, University of Maryland (1988) M.S. in Electrical Engineering, University of Maryland (1985) B.S. in Electrical Engineering, University of Patras, Greece (1981) Research Interests: Dr. Viniotis specializes in Quality of Service (QoS), transport protocols, ASIC implementations, and network algorithm analysis. His work bridges theoretical foundations with practical applications in cloud computing, IoT systems, and vehicular networks. Awards: 2009 Best Paper Award (ICSOFT) Multiple Outstanding Instructor Awards (1989–1995) 1992 Best Paper Award (Institute of Management Sciences) 1985 George Corcoran Graduate Assistant Award Advising & Industry: Co-founded Orologic, where he designed high-speed network chips. His recent work focuses on cloud resource allocation and IoT security. He has advised multiple senior design projects, including work on TCP Live Play extended by Yazan Siam (2012). Labs/Teams: Active in NC State’s networking and cloud computing research groups, contributing to both academic and industry-driven projects.

Stavros KalafatisView profile

Professor

• Datacenter System Optimization
• SDN/SDS/SDI Technologies
• Robotics in Manufacturing
• +4 more

Stavros Kalafatis is an Associate Department Head and Professor of Practice in the Department of Electrical and Computer Engineering at Texas A&M University, part of the College of Engineering. He holds an M.S.E.E. from the University of Arizona (1991) and a B.S.E.E. from the University of Surrey (1989). His research focuses on datacenter system optimization, SDI/SDN/SDS improvements for server efficiency, robotics in manufacturing, and sensor systems for agricultural applications. He has received multiple awards, including the Intel Achievement Award (2005) and repeated Intel Divisional Recognition Awards (1993, 2000–2010). His work spans cutting-edge technologies like precision agriculture robotics, network performance optimization, and machine learning-driven systems for hydroponics and wildfire prediction. Recent publications emphasize interdisciplinary solutions in agriculture, networking, and environmental modeling. Kalafatis is affiliated with the Computer Engineering and Systems Group at Texas A&M and contributes to advancing practical applications of engineering and computing. Education: M.S.E.E., University of Arizona, 1991 B.S.E.E., University of Surrey, 1989 Awards: Intel Achievement Award (Lynnfield Team), 2005 Intel Divisional Recognition Award (multiple years) His research trends highlight innovations in smart systems, including digital twins for manufacturing, AI-driven crop monitoring, and network optimization for data centers. While no grants or advising records are explicitly listed, his publications reflect active collaboration with industry and academic partners.

Jianer ChenView profile

Professor

• Algorithms and complexity
• Computer graphics
• Bioinformatics
• +6 more

Jianer Chen is a Professor in the Department of Computer Science and Engineering at Texas A&M University, part of the College of Engineering. He holds multiple academic positions and has contributed significantly to research in algorithms, computer graphics, bioinformatics, and computer networks. Educational Background: Ph.D. Mathematics, Columbia University, 1990 Ph.D. Computer Science, New York University, 1987 M.Phil. Mathematics, Columbia University, 1990 M.A. Mathematics, Columbia University, 1989 M.S. Computer Science, New York University, 1984 B.S. Computer Science, CSUT, P.R. China, 1982 Research Interests: His work focuses on Algorithms and Complexity , advancing computational efficiency and theoretical foundations. He explores Computer Graphics , including geometric modeling and Bézier patch subdivision. In Bioinformatics , he develops algorithms for phylogenetic trees and genetic data analysis. His Computer Networks research addresses data center optimization and sensor network reliability. Publications Trends: Recent work emphasizes parameterized algorithms, kernelization techniques, and their applications to big data, graph theory, and geometric problems. He also contributes to optimization in scheduling and network protocols, reflecting interdisciplinary engagement with both theoretical and applied computer science. Awards & Honors: AFS Distinguished Faculty Achievement Award (university level), 2007 E.D. Brockett Professorship Award, 2005 Janet Fabri Award (Best Ph.D. Dissertation), 1988 Multiple recognitions for teaching and research excellence Advising & Grants: Chen has secured grants such as the NSF Research Initiation Award (1991) and Amoco Faculty Award (1998). Though no advisees are listed, his work spans mentoring doctoral and master’s students in algorithm design and computational theory. His research initiatives often address practical challenges in high-performance computing and network reliability. Labs/Teams: No specific labs or teams are explicitly mentioned in the provided texts. However, his collaborations suggest involvement in interdisciplinary groups focused on bioinformatics, data center networks, and geometric modeling.

• Computer Science
• Foundations of Computation
• Set Theory
• +4 more

S. Hugtenburg is affiliated with TU Delft's Electrical Engineering, Mathematics and Computer Science faculty, specifically within the Computer Science & Engineering-Teaching Team. His work focuses on foundational computer science concepts, education technology, and resource management in computing systems. Research interests include the foundations of computation, set theory, proof techniques, and predicate logic. He has contributed to undergraduate education through textbook development (e.g., the Delftse Foundations series) and explored the use of platforms like Stack Overflow in computer science education. His publications span computational theory, educational methodologies, and systems optimization. Notable achievements include the TU Delft Education Fellow award (2022), recognizing contributions to pedagogical innovation.

Kevin XueView profile

Researcher

• Computer Systems
• Resource Management
• Virtualization
• +4 more

Kevin Xue is a Ph.D. student at the Computer Science and Engineering Division of the University of Michigan , advised by Professors Mosharaf Chowdhury and Ryan Huang . He focuses on computer systems , particularly efficient and fair application scheduling on personal devices . Education: Master's from Carnegie Mellon University , joint Bachelor's from Columbia University and City University of Hong Kong His research spans systems , virtualization , and real-time computing , with publications on topics like Arm-based confidential VMs , memory contiguity in datacenters , and video conferencing optimization . His work at ISCA '23 earned the Best Paper Award and IEEE Micro Top Pick Selection . Kevin is an active contributor to open-source projects, with 294 contributions in the last year. His GitHub profile highlights collaborations with institutions like Apple , Databricks , and Meta . He maintains connections with peers at Columbia University , Stanford , and Carnegie Mellon University , and his ORCID is 0009-0002-5311-2826 .

Wyatt LloydView profile

Professor

• Distributed Systems
• Networking
• Cloud Computing
• +7 more

Wyatt Lloyd is a Professor in the Computer Science department at Princeton University, leading the S* Network Systems (SNS) group with Mike Freedman, Amit Levy, and Mae Milano. His research focuses on distributed systems, networking, and cloud computing, emphasizing consistency models, geo-replication, and fault tolerance. He holds a PhD from Princeton (2013), followed by a postdoc at Facebook and an assistant professorship at the University of Southern California before returning to Princeton in 2017. Education : PhD, Computer Science, Princeton University, 2013 Postdoctoral Researcher, Facebook, 2013–2014 Assistant Professor, University of Southern California, 2014–2017 Research Interests : Lloyd’s work addresses tradeoffs between consistency guarantees and system performance in large-scale systems. Notable projects include TurboDB (NSDI ’24) for skewed workloads, Gryff (NSDI ’20) for consensus-unified storage, and Tectonic (FAST ’21), Facebook’s exabyte-scale filesystem. His group explores causal consistency, read-optimized transactions, and geo-distributed storage solutions. Publications : Recent work spans concurrency control (Natural Concurrency Control, OSDI ’23), caching optimizations (Learning Relaxed Belady, NSDI ’20), and fault-tolerant systems (Speculative Recovery, ATC ’22). These contributions balance strong consistency with high performance. Grants & Recognition : Supported by NSF grants (e.g., CNS Core, CISE), his work addresses modern distributed system challenges. Over 30 students have been advised, contributing to influential projects like Eiger, COPS, and Janus. Labs/Teams : The SNS group at Princeton focuses on systems research, collaborating on projects like the S* Network Systems initiative. Tools developed include Eiger (Apache Cassandra fork) and frameworks for causal consistency and distributed transactions.

Scott ShenkerView profile

Professor

• Networking
• Software-Defined Networks
• Datacenter Infrastructure
• +4 more

Scott Shenker is a Professor at the University of California, Berkeley, and a Research Director at the International Computer Science Institute (ICSI). He previously served as Chief Scientist at ICSI (2012-2021) and held roles at Xerox PARC, University of Southern California, and Cornell University. PhD in Physics, University of Chicago (1983) ScB in Physics, Brown University (1978) His research spans Internet architecture, software-defined networks, datacenter infrastructure, and game theory. He has contributed to distributed systems, privacy mechanisms, and network protocols, with a focus on scalable and resilient designs. Recent work includes advancements in memory management for distributed systems, cloud resource optimization, and SDN frameworks. His 15 most recent publications highlight innovations in datacenter networking, packet scheduling, and storage efficiency. IEEE Computer Society Women of ENIAC Computer Pioneer Award (2023) Fiat Lux Faculty Award (2022) IETI Distinguished Fellow (2020) National Academy of Sciences Member (2019) Paris Kanellakis Theory and Practice Award (2017) ACM SIGCOMM Test of Time Paper Awards (2017, 2011, 2006) IEEE Internet Award (2006) ACM and IEEE Fellowships National Academy of Engineering Member (2012) Shenker has advised numerous PhD and Master’s students, including A. Ermolinskiy, M. Perry, Y. Harchol, and T. Das. His research teams at UC Berkeley and ICSI explore next-generation networking solutions, including open-source frameworks like Spark and Mesos.

Angelos BilasView profile

Professor

• Computer Systems
• Computer Architecture
• Storage Systems
• +4 more

Angelos Bilas is a Professor of Computer Science at the University of Crete, Greece, and a collaborating researcher at FORTH-ICS (Foundation for Research and Technology-Hellas). He received his PhD in Computer Science from Princeton University in 1998 and has held academic positions at the University of Crete since 2002, including Department Chair (2016-2020). His research focuses on systems software for storage systems, computing architectures, and parallel systems with emphasis on flash storage optimization. PhD, Princeton University (1998) MA, Princeton University (1995) BEng, University of Patras (1993) His research interests span computer systems, storage architectures, and parallel computing , with notable contributions in memory-mapped I/O optimization, LSM key-value store design, and heterogeneous accelerator integration. He has developed frameworks like TeraHeap for DRAM pressure mitigation in big data systems and Arax for decoupling applications from accelerators. Prominent trends in his recent publications include flash storage optimization (TeraHeap), LSM tree efficiency (Tebis), and cloud-HPC convergence (EVOLVE, KNoC). His work appears in top venues like ASPLOS, USENIX ATC, and ACM Transactions on Storage. Scientific recognitions include: Marie Curie Excellent Teams Award (2005-2009) Best Presentation Award, USENIX HotStorage'20 He has served on editorial boards (ACM Transactions on Storage) and program committees (ACM HotStorage, HPCA). His research involves 35 master’s and 8 PhD students, with 45+ EU/national projects and 4 patents licensed to industry.

Soudeh GhorbaniView profile

Assistant Professor

• Systems and Networking
• Cloud Computing
• Data Center Optimization
• +4 more

Soudeh Ghorbani is an Assistant Professor of Computer Science at Johns Hopkins University (on leave since 2023) and a full-time Scientist at Meta. She directs the Hopkins Networking Lab and founded the Introduction to Computing Research (ICR) program. Her research focuses on foundational networked systems, including cloud infrastructure, data center optimization, and network congestion control, with grants from NSF, Google, Meta, Intel, and VMware. Education: Ph.D. in Computer Science, University of Illinois Urbana-Champaign (2016) M.Sc. in Computer Science, University of Toronto (2011) B.Sc. in Computer Engineering, Sharif University of Technology (2009) Research Interests: Systems and networking, cloud computing infrastructures, distributed AI training, network bottlenecks, formal methods, and control theory. Her work targets making the Internet faster and more reliable through provable system designs. Publication Trends: Recent articles (2020-2025) emphasize data center networks, congestion control, packet deflection, and network verification. Key themes include microburst mitigation, traffic pattern analysis, and scalable network algorithms. Awards: Facebook Faculty Research Award (for microburst detection) Intel Fast Forward Award Advising & Grants: Advises 8 PhD/MS students. Research supported by NSF, Google, Meta, Intel, and VMware. Directs the Foundational Networked Systems Lab, focusing on cloud/datacenter innovations. Labs & Teams: Leads the Hopkins Networking Lab. Founded ICR to introduce undergraduates to computing research. Lab members include PhD students Kevin Lu, Sana Mahmood, Sepehr Abdous, and Erfan Sharafzadeh.

Rishabh IyerView profile

Assistant Professor

• Computer Systems
• Performance Analysis and Optimization
• Operating Systems
• +5 more

Rishabh Iyer is an Assistant Professor in the Electrical Engineering and Computer Sciences department at the University of California, Berkeley. His research bridges computer systems, networking, and formal methods with a focus on performance predictability and reliability. Prior to Berkeley, he completed his PhD at EPFL and undergraduate studies at IIT Bombay. His educational background includes: PhD in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL) Bachelor's degree from Indian Institute of Technology Bombay (IIT Bombay) Iyer's research centers on performance interfaces for computer systems – creating succinct abstractions that allow engineers to reason about system performance without understanding implementation details. His work spans three major directions: (1) Extracting performance interfaces from implementations, (2) Designing systems with predictable performance, and (3) Formally verifying performance claims. This research combines operating systems, networking, computer architecture, and formal verification techniques to address performance unpredictability in modern systems. His group develops tools like PIX for network functions, KFlex for kernel extensions, and Software LPN for hardware accelerators. His publications reveal strong focus on performance modeling for network functions, kernel extensions, and hardware accelerators, with recent work expanding into real-time systems and SD-WAN validation. The research consistently targets practical impact, with deployments at companies like Meta and Alibaba. Scientific recognition includes: ACM SIGOPS Dennis M. Ritchie Award Eurosys Roger Needham PhD Award Dimitris N. Chorafas Award Best Paper at VDAT 2019 Iyer actively advises students at UC Berkeley and teaches courses including CS 294-262 (Performance Analysis) and CS 168 (Internet Architecture). Previously at EPFL, he taught Principles of Computer Systems, Software Engineering, and Vector Calculus. His group seeks talented students interested in building reliable, high-performance systems. Current research directions include performance interfaces for distributed applications, next-generation kernel extensions, and formally verified network systems. He leads research within UC Berkeley's systems community and maintains strong connections with EPFL's Dependable Systems Lab where he completed his PhD.

• Computer Engineering
• Biomedical Informatics
• Ontology Development
• +5 more

Dr. Vanja Luković is an Associate Professor in the Department of Computer and Software Engineering at the Faculty of Technical Sciences in Čačak, University of Kragujevac, Serbia. With over two decades of academic experience, she has established herself as a prominent researcher in the intersection of computer engineering and biomedical applications, particularly in the development of innovative diagnostic systems for spinal deformities. Her educational background includes a Doctorate in Technical Sciences (2015) with a dissertation on "Ontologically based information system for diagnosing and monitoring spinal deformities," a Master's degree in Electrical Engineering (2007) focusing on visualization systems, and a Bachelor's degree in Electrical Engineering with specialization in Industrial Energy (2000). Dr. Luković's research spans multiple domains including biomedical informatics, ontology development for medical applications, digital circuit design, and educational technology. Her work demonstrates a consistent focus on applying computer engineering principles to solve real-world medical challenges, particularly in the area of scoliosis diagnosis and monitoring. She has pioneered the development of the ScolioMedIS system, a web-based information system for non-invasive 3D visualization and monitoring of spinal deformities. Her publication record reveals a strong trajectory in both medical informatics and computer engineering, with recent work expanding into AI applications for medical diagnostics, data storage optimization, and educational technology. The evolution of her research shows a natural progression from foundational work in ontology development to more applied research in medical diagnostics and educational tools. The first MIMICS INNOVATION AWARD 2016 for the EMEA region awarded by Materialise (Leuven, Belgium) The 3rd place for the early-stage StartUp: ScolioMedIS at the 2nd SwissBioLabs Start-Up Challenge "Diagnostics goes digital" Dr. Luković has led and participated in numerous research projects funded by Serbian Ministry of Science and international collaborations including TEMPUS projects. Her work on remote laboratories for educational purposes has significantly impacted computer engineering education. She has also contributed to multiple textbooks and manuals for digital circuit design education, demonstrating her commitment to pedagogical innovation. Her laboratory work primarily focuses on the Computer Science Laboratory at the Faculty of Technical Sciences, where she has developed remote experiment platforms for digital circuit design education and the ScolioMedIS system for medical applications.

• Internet of Things (IoT)
• Geospatial Data Analysis
• Disaster Management
• +5 more

Philip James is a researcher affiliated with Newcastle University (School of Engineering) and the University of Salford (School of Environment and Life Sciences). His work bridges computer science , urban infrastructure , and geospatial analytics . Key research themes include Internet of Things (IoT) , edge computing , smart city applications , and disaster management . Recent projects involve developing simulation frameworks like IoTSim-Edge and IoTSim-Osmosis for modeling IoT and edge environments. His publications show a strong focus on sensor networks , geospatial data , and urban resilience . He has contributed to advancing ontology-based systems for emergency response and smart transport solutions using CCTV and stereo cameras. Philip James collaborates extensively with researchers like Rajiv Ranjan , Stuart Barr , and Tejal Shah , working on applications ranging from landslide detection to social media analytics in crises .

Mosharaf ChowdhuryView profile

Associate Professor

• AI/ML Systems
• Energy Efficiency in AI
• Memory Disaggregation
• +4 more

Mosharaf Chowdhury is an Associate Professor at the University of Michigan's College of Engineering, Department of Electrical Engineering and Computer Science. He leads the SymbioticLab (https://symbioticlab.org/), focusing on AI/ML systems optimization and energy-efficient computing. Current roles: Associate Professor, Director of SymbioticLab Key projects: Infiniswap (memory disaggregation), Salus (GPU sharing), FedScale (federated learning), Zeus (GPU energy optimization) Original co-creator of Apache Spark Research Interests center on large-scale systems for AI/ML and big data, with emphasis on: Energy consumption optimization Memory disaggregation via CXL GPU resource management Data privacy in distributed systems Federated learning scalability Scientific Awards include multiple paper awards from top systems venues (NSDI, OSDI, ATC, MICRO) and fellowships. Teaching includes courses like EECS 489 (Computer Networks) and EECS 598 (Systems for AI/ML).

• Internet Measurement
• Network Security
• Fraud Detection
• +3 more

Paul Barford serves as Department Chair and Carl de Boor Professor in the Computer Sciences Department at the University of Wisconsin-Madison, where he leads the networking research group and founded the Wisconsin Advanced Internet Laboratory. His career uniquely bridges academic research and industry entrepreneurship, having spent eight years in technology development prior to academia. He holds a B.S. in Electrical Engineering from the University of Illinois and a Ph.D. in Computer Science from Boston University. His international academic engagement includes visiting professorships at the University of Cambridge (Computer Laboratory), Wolfson College fellowships, and scholarly work at the University of Oxford. Prof. Barford's research centers on internet measurement and security, specializing in analysis of internet data, protocols, and topological structures. His current investigations explore fraud detection systems, traffic anomaly identification, and malicious attack mitigation, with recent work pioneering environmental sensing applications using existing fiber-optic infrastructure. Analysis of his recent publications reveals three dominant research thrusts: (1) DNS infrastructure analysis through corpus construction and graph decomposition, (2) cloud networking optimization via peering strategies and topology programming, and (3) photonic sensing innovations leveraging commodity optical hardware for environmental monitoring. His scholarly contributions are recognized through significant research funding and professional honors: EPSRC visiting fellowship at University of Cambridge Visiting fellowship at Wolfson College, University of Cambridge Prof. Barford secures substantial research support from the National Science Foundation (NSF), Department of Homeland Security (DHS), Army Research Office (ARO), Cisco, and Intel. His entrepreneurial impact includes founding Nemean Networks (acquired by Qualys) for intrusion detection and co-founding MdotLabs (acquired by comScore) for advertising fraud detection, translating academic research into commercial security solutions. The Wisconsin Advanced Internet Laboratory serves as his primary research hub, providing experimental infrastructure for internet measurement studies, security protocol validation, and photonic sensing development, with active collaborations across government and industry partners.