Find Academic Supervisors

• Database Systems
• Data Analytics
• Machine Learning in Databases
• +3 more

Jignesh M. Patel is a Professor at the University of Wisconsin, Madison, WI, USA , with over 25 years of contributions to database systems, data analytics, and hardware-aware query processing. His work bridges theoretical advancements with practical systems engineering. Research Interests span: Database systems optimization (query processing, transaction management) Hardware acceleration for analytics (eBPF, PIM, GPUs) Machine learning integration in databases (feature selection, model optimization) Efficient data structures (hashing, encoding, indexing) Multi-tenant and cloud database management Recent Work focuses on kernel-embedded databases (BPF-DB, 2025), memory-efficient dataframe processing (SplitDF, 2024), and algorithmic-hardware co-design for dense retrieval (DReX, 2025). He has pioneered techniques for adapting to data skew (VIP Hashing, 2022), leveraging static analysis in R optimization (ROSA, 2017), and rethinking benchmarking paradigms. Collaborations include key partnerships with: Systems researchers (Andrew Pavlo, José F. Martínez) Machine learning experts (Arun Kumar, Kevin Skadron) Education-focused colleagues (Adalbert Gerald Soosai Raj, Richard Halverson) Industry leaders (David J. DeWitt, Microsoft Research)

van Khang HuynhView profile

Professor

• Applied AI in condition-based maintenance
• Electrical machines
• Power electronics
• +3 more

van Khang Huynh is a Full Professor in Mechatronics and Energy Systems at the Department of Engineering Sciences , University of Agder , Norway. He is also a member of the Norwegian Academy of Technical Sciences (NTVA) and has served as an Associate Editor for IEEE Transactions on Transportation Electrification . Education: D.Sc. in Electromechanics & Electric Drives, Aalto University, Finland (2012) M.Sc. in Power Electronics and Motor Drives, Pusan National University, South Korea (2008) B.Sc. in Electrical Power Engineering, Ho Chi Minh City University of Technology, Vietnam (2002) Research Focus: His research spans applied AI in condition-based maintenance , electrical machines , power electronics , design optimization , finite element analysis , and smart energy systems . He leads the Intelligent monitoring research group and is a member of the Energy systems , Intelligent mechatronics (iTron) , and Machine design groups. Projects & Funding: Enhancing Capacity in Condition-based Maintenance of Wind Energy (ECO-WIND) Performance and Health Monitoring of Hydroelectric Power Plants Analytics for Asset Integrity Management of Windfarms Industrial Internet methods for electrical energy conversion systems monitoring and diagnostics Operational Management in Interconnected Renewable Resources with ICT Compact Electric Winches PhD Supervision: He has successfully supervised 8 PhD dissertations and mentored 2 additional PhD projects , all in areas related to mechatronics, renewable energy, and intelligent systems. Labs & Teams: He leads the Intelligent monitoring research group and collaborates closely with the Energy systems , Intelligent mechatronics (iTron) , and Machine design groups at the University of Agder.

Giorgio ScorzelliView profile

Researcher

• Extreme Data Management
• Scientific Visualization
• Computational Topology
• +6 more

Giorgio Scorzelli is a researcher at the University of Utah, serving as Director of Software Development for the Center for Extreme Data Management, Analysis, and Visualization (CEDMAV) and the National Science Data Fabric (NSDF) . He specializes in extreme data management, scientific visualization, and computational topology, with a focus on scalable solutions for climate science, materials science, and neuroscience datasets. His work emphasizes democratizing data access through platforms like OpenVisus , enabling efficient analysis of petascale and exascale data. Key contributions include orchestrating cyberinfrastructure, optimizing parallel I/O, and developing real-time visualization systems for heterogeneous resources. Notable scientific contributions include the NSF Grant #2127548 for NSDF development . His projects integrate cloud computing, geo-distributed storage, and FAIR digital objects to lower barriers to data democratization. Giorgio's research spans multi-resolution algorithms , computational topology , and 3D geometric modeling , with applications in infrastructure security, archaeological reconstruction, and biomedical imaging. His work bridges abstract mathematical frameworks (e.g., Boolean algebras, chain complexes) with practical software solutions.

Binoy RavindranView profile

Professor

• Computer Systems
• Software Verification
• Concurrency
• +7 more

Binoy Ravindran is a Professor at Virginia Tech’s College of Engineering, Department of Electrical and Computer Engineering, leading the Systems Software Research Group (SSRG). His research focuses on computer systems, emphasizing security, performance, concurrency, distributed systems, and real-time computing, with recent work in software verification and heterogeneous-ISA platforms. Key projects: Low-level Reasoning Machine (LLRM), Popcorn Linux, LibrettOS, Hyflow, HermiTux, SlimGuard, HydraVM, KairosVM. He has co-authored 15+ papers from 2025 to 2022, spanning venues like ASPLOS, POPL, PLDI, VEE, PPoPP, and MIDDLEWARE, with awards including ACM Distinguished Scientist and eight Best Paper Awards. Service roles: Editorial Boards (IEEE Transactions on Cloud Computing, ACM TECS), Program Co-Chair (ACM Systor 2025), Committee memberships across ASPLOS, PLDI, and more.

Sebastian AngelView profile

Associate Professor

• Systems
• Security
• Privacy
• +4 more

Sebastian Angel is an Associate Professor and Chair of Undergraduate Curriculum in the Department of Computer and Information Science at the University of Pennsylvania . He leads research in systems, security, privacy, and networking, with a focus on privacy-preserving systems, accountability in online services, consistency in distributed systems, and next-generation operating systems. Research Areas: Systems, Security, Privacy, Networking, Distributed Systems, Operating Systems Labs & Teams: Distributed Systems Laboratory, Security and Privacy Laboratory, Warren Center for Network and Data Sciences Education: Ph.D. in Computer Science from the University of Texas at Austin (2018), ACM SIGOPS Dennis M. Ritchie Dissertation Award, Bert Kay Best Dissertation Award Recent Publications (2025–2022) span serverless computing, zero-knowledge proofs, distributed transactions, privacy-preserving ad tech, and verifiable execution. His 2025 work includes serverless workflow optimization and structural logic verification, while 2024 focuses on caching frameworks and stateful serverless. Earlier 2023–2022 projects include secure federated learning, confidential cloud services, and private information retrieval. Scientific Awards: NSF CAREER Award (2021) JPMorgan Faculty Award (2021) ACM SIGOPS Dennis M. Ritchie Dissertation Award (2018) Bert Kay Best Dissertation Award (2018) ACM SIGMOD Research Highlights Award (2024) VLDB 2024 Best Paper Award Nominee Advising: Current PhD Students: Elizabeth Margolin, Jess Woods, Yuxuan Zhang Current Masters Students: Felix Adena, Sydnie Shea Cohen Alumni: Eleftherios Ioannidis (2025), Yiping Ma (2025), Haoran Zhang (2024), Ke Zhong (2024), Selin Butun (2025), Martin Sander (2025), Seungmin Han (2024), Andrew Beams (2022), Yifeng Mao (2021), Varad Deshpande (2020) Current Courses: CIS 4510/5510: Computer and Network Security (Fall 2025). He also organizes conferences like S&P, OSDI, SOSP, PETS, and EuroSys.

Ehat ErcanliView profile

Teaching Professor

• Computer Architecture
• Embedded System Design
• System Verification
• +3 more

Ehat Ercanli is an Associate Teaching Professor at Syracuse University, serving as the Associate Chair of Education and Operations. He holds a Ph.D. in Computer Engineering from Case Western Reserve University. His research focuses on optimizing embedded systems, computer architecture, system verification, and VLSI design automation. He has contributed to advancements in memory management, compiler optimization, and energy-efficient computing. Key research interests include embedded system design, task recomputation techniques for memory utilization, and database systems optimization. His work emphasizes practical applications in multi-core systems, low-power electronics, and compiler-driven performance improvements. His publications highlight trends in system-on-chip (SoC) optimization, shared private memory management, and energy consumption reduction strategies. Notably, his 2007 paper was ranked #3 in the ACM Digital Library’s Most Popular Papers. Dr. Ercanli’s contributions also extend to automated code generation for database applications and custom processor synthesis for image processing.

Mark HeinrichView profile

Associate Professor

• Parallel Computer Architecture
• Heterogeneous Architectures
• Active Memory and I/O Systems
• +4 more

Mark Heinrich is an Associate Professor in the Department of Computer Science at the University of Central Florida (UCF), where he also serves as Undergraduate Coordinator for CS and IT, and Senior Design Coordinator. He previously held roles at Cornell University and has industry experience co-founding companies like Phanfare and Flashbase. His research focuses on parallel computer architecture, heterogeneous systems, cache coherence protocols, and multiprocessor simulation. Heinrich holds a Ph.D. in Electrical Engineering from Stanford University (1998) under John Hennessy, and a B.S. in Electrical Engineering and Computer Science from Duke University (1991). Research Interests His work spans parallel architectures, active memory systems, scalable cache coherence protocols, and hardware/software co-design. Recent efforts include innovations in persistent memory technologies and multiprocessor simulation methodologies. Teaching In Spring 2020, he taught CS Senior Design I and II courses (COP 4934/4935), with office hours focused on senior design and undergraduate coordination. Professional Background Associate Professor at UCF since 2003 Past roles: Director of UCF's School of Computer Science (2005), Associate Director of EECS (2005-2007) Co-founder of the Cornell Computer Systems Laboratory Contributed to the FLASH multiprocessor architecture and its simulation tools Labs & Projects He has been involved in projects like Active Memory Clusters and architectural support for multiprocessor systems. His work often bridges theoretical computer architecture with practical hardware implementations.

Xuan ZhangView profile

Associate Professor

• Artificial Intelligence Hardware
• Machine Vision Sensors
• Electronic Design Automation
• +3 more

Xuan Zhang serves as Associate Professor in Electrical and Computer Engineering at Northeastern University, leading the Sensory AI Lab since joining in January 2024. Her research bridges computer architecture, integrated circuits, and artificial intelligence to develop miniaturized AI systems for autonomous physical platforms. She earned her PhD in Electrical and Computer Engineering from Cornell University in 2012. Her educational background forms the foundation for her interdisciplinary work spanning hardware and software co-design. Dr. Zhang's research focuses on artificial intelligence hardware, machine vision sensors, and security for autonomous systems. She pioneers techniques for efficient in-sensor computing, analog circuit optimization via machine learning, and hardware-level privacy preservation. Her work addresses critical challenges in energy efficiency, robustness, and security for edge AI deployment, particularly in resource-constrained environments like medical devices and autonomous vehicles. Analysis of her 2023-2025 publications reveals three dominant trends: (1) hardware-accelerated privacy mechanisms for sensors, (2) machine learning-driven analog circuit design automation, and (3) energy-efficient architectures for neural network inference. These works consistently target real-world applications in healthcare, autonomous systems, and semiconductor design. Her accolades include the prestigious NSF CAREER Award (2020) and leadership in a $10 million federal semiconductor initiative. She contributes to national efforts in AI-powered chip design through the National Center for the Advancement of Semiconductor Technology. Dr. Zhang advises graduate researchers in the Sensory AI Lab, securing significant funding for projects spanning hardware security, in-sensor computing, and autonomous system assurance. Her lab collaborates with federal agencies and industry partners on cutting-edge semiconductor research. The Sensory AI Lab operates at the hardware-software interface, developing novel architectures for intelligent edge devices. Current projects include optical privacy preservation, robust analog design tools, and energy modeling frameworks for in-sensor visual computing systems.

Linghao SongView profile

Assistant Professor

• Accelerator Architecture
• FPGAs
• Hardware Acceleration Systems
• +4 more

Linghao Song is an Assistant Professor in the Department of Electrical & Computer Engineering at Yale University. His research focuses on accelerator architecture design, FPGA-based acceleration systems, and ReRAM-based computing. He is affiliated with the School of Engineering & Applied Science and holds expertise in sparse matrix processing, high-level synthesis, and task-parallel programming frameworks. Education: Ph.D. and M.S. from Duke University and University of Pittsburgh, respectively, with a B.S.E. from Shanghai Jiao Tong University. Research Interests: Song's work spans FPGA-accelerated computing, resistive memory (ReRAM) architectures for deep learning and graph processing, and high-performance sparse matrix operations. His recent projects include the TAPA framework for FPGA programming, ReFloat for iterative linear solvers, and the Sextans/Serpens accelerators for sparse matrix computations. Key Contributions: Over 20 peer-reviewed publications on topics like ReRAM-based accelerators (e.g., GraphR, PipeLayer), FPGA optimization frameworks (TAPA, RapidStream), and novel hardware designs for neural networks and graph analytics. His work emphasizes energy efficiency, scalability, and cross-domain applicability of hardware accelerators. Awards: Recipient of the Duke ECE Outstanding Dissertation Award (2021), EDAA Outstanding Dissertation Award (2020), and National Scholarship of China (2012). Labs/Teams: Leads research in FPGA acceleration and memory-based computing, collaborating on projects involving HBM integration, resistive memory architectures, and task-parallel dataflow frameworks.

Muhammad SalmanView profile

Associate Professor

• Biomechanics
• Vibration Analysis
• Mechanical Engineering
• +3 more

Dr. Muhammad Salman is an Associate Professor in the Department of Mechanical Engineering at Kennesaw State University (KSU), where he has served since 2012 after the merger of Southern Polytechnic State University into KSU. He holds a PhD in Mechanical Engineering from Georgia Institute of Technology (2012), an M.S. from Georgia Tech (2008), and prior degrees from the University of Engineering and Technology in Lahore, Pakistan, including a B.S. (1998) and M.S. (2003). He also completed M.S.-level courses in Mechatronics Engineering at TUHH, Germany (2005). His research focuses on biomechanics, particularly in dynamics and vibrations of human musculoskeletal systems, with an emphasis on non-invasive measurement techniques like surface wave and shear wave methods to assess muscle/tendon stiffness. He has developed cost-effective devices for stiffness quantification and published extensively in journals such as Journal of Biomechanics and Acoustical Society of America . Dr. Salman has received notable recognition, including the PhD Fulbright Scholarship (2006) , and has secured grants totaling over $500,000, including an NSF CAREER Award (though not funded) and OVPR grants for tendon stiffness research. His work involves collaborations with students on projects like motorcycle stability systems, muscle fatigue analysis, and biomedical sensor development. He teaches courses in dynamics, vibrations, thermodynamics, and design, and has mentored numerous undergraduates and graduates in research through programs like NCUR and GURC. His lab emphasizes experimental research, with a focus on biomechanical applications of vibration analysis and sensor technology. Recent projects include developing low-cost stiffness measurement tools and studying tendon behavior under fatigue. He actively participates in conferences such as ASME IMECE and the American Society of Biomechanics, showcasing innovations in both mechanical engineering and biomedical research.

• Solar Energy
• Photovoltaics
• Materials Science
• +3 more

Professor James Durrant at Swansea University's School of Engineering and Applied Sciences is a leading expert in Materials Science and Engineering . Based at the SPECIFIC research center and collaborating with his team at Imperial College London, he spearheads the £7 million ‘Sêr Solar’ initiative focused on low-cost, large-area photovoltaic technologies . His work bridges fundamental research in organic solar cells and perovskite systems with industrial applications in the printed solar manufacturing sector. His research interests span the Charge carrier dynamics Stability mechanisms in solar cells Nonfullerene acceptor design Perovskite crystallinity control Interface engineering Environmental degradation pathways with a strong emphasis on translating scientific insights into scalable, sustainable solutions. Analysis of his recent publications reveals a focus on Nonfullerene organic photovoltaics Perovskite defect passivation Charge separation in low-driving-force systems Transparent solar technology Catalytic heterostructures Photostability under operational stress His work consistently addresses efficiency-stability trade-offs in emerging solar technologies. Professor Durrant supervises postgraduate research and has contributed to EngD and PhD programs , including projects on perovskite circular economy and organic photovoltaic scalability . His lab at Swansea's Bay Campus (Engineering East, A202) specializes in advanced photovoltaic characterization and development.

Ramon CanalView profile

Professor

• Secure microarchitectures
• System reliability
• Virtualization and operating systems
• +5 more

Ramon Canal is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona School of Informatics and the Computer Architecture Department. He has served as Vice Dean of postgraduate studies and leads the VirtuOS (Virtualization and Operating Systems) research group. His academic background includes BSc, MSc, and PhD from UPC, with thesis supervision by Antonio González (UPC) and James E. Smith (University of Wisconsin-Madison). He completed sabbaticals at Harvard University (2006-2007) and University of Cyprus (2019-2020). Education: PhD, MSc, BSc in Computer Engineering (UPC) Research focus: Microarchitecture security, reliability across circuit/system levels, cloud optimization Recent publications address privacy in IoT, secure hardware accelerators, and safety-critical systems. His work contributes to the DRAC project (2019-2022), Red-RISCV network, and Horizon's Vitamin-V project. Awards include HiPEAC Paper Awards, IEEE Senior Member status, Fulbright recognition, and multiple education excellence accolades. Scientific Honors HiPEAC Paper Award (ISCA-44, 2017) IEEE Senior Member (2016) Best Paper Nominee (ICCD-32, 2014) UPC Outstanding PhD Award supervision (2011) He advises current MSc students and has mentored multiple PhD graduates. Professional activities span academic leadership, research collaborations with Barcelona Supercomputing Center (BSC), and technical contributions to reliability analysis frameworks like RECIPE and FRACTAL.

Kate SmithView profile

Assistant Professor

• Quantum Computing
• Computer Architecture
• Quantum Compilation
• +5 more

Kate Smith is an Assistant Professor of Computer Science at Northwestern University, affiliated with the McCormick School of Engineering. She holds a PhD in Electrical Engineering from Southern Methodist University (SMU), along with MS and BS degrees in Electrical Engineering and Mathematics from the same institution. Her research focuses on quantum computing, specifically in system architecture, optimized compilation, error mitigation, and security. Prior to joining Northwestern in 2024, she worked at Infleqtion managing the Superstaq compiler team and as a postdoctoral scholar at the University of Chicago under the CQE/IBM program. She has contributed to over 25 peer-reviewed publications and served on technical committees for major conferences like MICRO, ISCA, and DAC. Education: SMU (PhD 2019, MS 2015, BS in EE/Math 2014). Professional experience includes roles at EPFL (Switzerland), Texas Instruments, and the Darwin Deason Institute for Cyber Security. Her honors include the 2022 HPCA Best Paper Award, MIT EECS Rising Star (2021), and the IEEE TC-MVL Early Career Award (2021). Research interests span quantum compilation, distributed systems, qudit processing, and quantum security. She co-organized the 2023 CCC Workshop on Next Steps in Quantum Computing and chaired the 2022 ISMVL conference. Her work emphasizes bridging hardware-software gaps to enable scalable quantum systems. Grants and collaborations include the EPiQC group at the University of Chicago and projects funded by the Swiss NSF. Teaching experience includes courses on quantum computing fundamentals and digital design at SMU, University of Chicago, and adjunct roles.

Michael A. BenderView profile

Professor

• Algorithms
• Data Structures
• Cache and I/O-Efficient Computing
• +7 more

Michael A. Bender is the John L. Hennessy Chaired Professor of Computer Science at Stony Brook University. His work spans both theoretical and applied domains in algorithms, data structures, and storage systems. He co-founded Tokutek, Inc., a database company acquired by Percona in 2015, and has held visiting positions at MIT and King's College London. Education: PhD in Computer Science from Harvard University (1998), DEA and Magistère in Computer Science from École Normale Supérieure de Lyon (1993), BA in Applied Mathematics from Harvard (1992). His research focuses on cache-oblivious algorithms , I/O-efficient computing , parallel systems , and scheduling . His work addresses scalability in large-scale data management and computational geometry, with applications in bioinformatics and robotics. The 15 most recent publications highlight advancements in list labeling , hash table design , graph algorithms , and memory optimization . These papers reflect his commitment to solving practical problems with rigorous algorithmic approaches. Awards include: PODS Best Paper Award (2024) ASPLOS Distinguished Paper Award (2023) USENIX FAST Best Paper Award (2016) Chancellor's Award for Excellence in Teaching (2015) R&D 100 Award (2006) He has led the Stony Brook Computer Science Honors Program and advised graduate students in algorithmic research. His grants portfolio includes 39 funded projects, emphasizing algorithm engineering and systems optimization.

Peter DruschelView profile

Professor

• Distributed Systems
• Operating Systems
• Peer-to-Peer Systems
• +7 more

Peter Druschel is the founding director of the Max Planck Institute for Software Systems (MPI-SWS) and leads the Distributed Systems Group. He holds adjunct professorships at Saarland University and the University of Maryland, reflecting his strong academic affiliations in computer science. He has previously served as a Professor of Computer Science at Rice University and has held visiting positions at MIT, Microsoft Research Cambridge, and LIP6. Education: Ph.D. in Computer Science, University of Arizona, 1994 His research centers on building secure, compliant, and privacy-preserving distributed and mobile systems. Key interests include accountable systems, peer-to-peer networks, operating systems, and network security. He has led foundational work in systems like Pastry, Scribe, and Glacier, and currently focuses on privacy compliance in data processing through projects like Thoth and iPic. His work is supported by major grants from the ERC, Max Planck Society, DFG, BMBF, and Google. The recent publications highlight a consistent trend in secure and privacy-aware systems, with a focus on policy enforcement, isolation mechanisms, anonymity, and mobile security. These works span top venues such as USENIX Security, OSDI, MobiSys, and SIGCOMM, reflecting sustained impact in systems and security communities. Scientific Awards: NSF CAREER Award (1995) Alfred P. Sloan Fellowship (2000) SIGOPS Mark Weiser Award (2008) Microsoft Research Outstanding Collaborator Award (2016) EuroSys Lifetime Achievement Award (2017) Druschel has advised numerous PhD and master’s students and postdoctoral researchers at MPI-SWS. He has co-directed major collaborative programs including the Cornell-Maryland-Max Planck Pre-doctoral School and the Maryland Max Planck Ph.D. Program. His leadership extends to professional service, having chaired SOSP, OSDI, NSDI, and EuroSys, and served on editorial boards of CACM, TOCS, and Royal Society Open Science. He is a member of Academia Europaea and the German Academy of Sciences Leopoldina. Labs and Teams: Distributed Systems Group, MPI-SWS imPACT ERC Synergy Project Collaborators include Bobby Bhattacharjee, Deepak Garg, Miguel Castro, Ion Stoica, and others