Find Academic Supervisors

Gregory GangerView profile

Professor

• Computer Systems
• Cloud Computing
• Distributed Systems
• +6 more

Gregory Ganger is the Stephen J. Jatras Professor at Carnegie Mellon University's College of Engineering, holding joint affiliations with the Computer Science Department and CyLab. He has served as Director of the Parallel Data Lab (PDL) since 2000 and teaches Storage Systems (Fall) and Advanced Cloud Computing (Spring) courses. Education: Ph.D. in Computer Science & Engineering (1995, University of Michigan) M.S. in Computer Science & Engineering (1993, University of Michigan) B.S. in Computer Science (1991, University of Michigan) Dr. Ganger's research spans computer systems, focusing on: cloud computing, distributed systems, storage architectures, and machine learning infrastructure. His work addresses challenges in resource scheduling, non-volatile memory optimization, and scalable infrastructure design through projects like BigLearning, CILES, HeART, and Zoned Storage systems. Recent publications demonstrate expertise in: DNN training optimization (GraphPipe, Nonuniform-Tensor-Parallelism), sustainable storage (Storage Emissions, FairyWREN), and cloud efficiency (MACARON Cache). These works intersect machine learning, storage systems, and hardware-software co-design. Scientific Awards: 2021 OSDI Best Paper 2021 SOSP Best Paper 2021 SoCC Test of Time Award 2021 R&D 100 Award As advisor to 8 graduate students, he contributes to training the next generation of systems researchers. His lab (PDL) collaborates with industry partners on cutting-edge storage and cloud infrastructure problems.

Yu LiuView profile

Associate Professor

• Computer Architecture
• High Performance Computing
• Real-Time Systems
• +3 more

Dr. Yu Liu is an Associate Professor in the Department of Electrical and Computer Engineering at Clarkson University, Potsdam, NY. He holds a Ph.D. from Southern Illinois University Carbondale (2011) and M.S./B.S. degrees from Sichuan University (2003/2000). Prior to academia, he worked at Canadian Nuclear Laboratories (2013–2017), IBM (2011–2013), and Motorola (2003–2007). His research focuses on computer architecture, high-performance computing, thermal simulation, and wireless sensor networks , with interdisciplinary applications in nuclear science. He has secured over $1.7M in NSF funding as PI/co-PI and published >50 peer-reviewed papers. Education: Ph.D., Electrical and Computer Engineering, Southern Illinois University Carbondale (2011) M.S., Power System and Automation, Sichuan University (2003) B.S., Communication Engineering, Sichuan University (2000) Research Interests: Physics-based thermal simulation methodologies for multi-core CPUs/GPUs Data-driven and machine learning approaches in high-performance computing Interdisciplinary applications in nuclear science and environmental monitoring Real-time embedded systems and scratchpad memory architectures Grants & Awards: 5 NSF grants (e.g., REU Site: High Performance Computing with Engineering Applications) Best Paper Award at 2022 IEEE ITherm Conference Teaching & Advising: Undergraduate/Graduate courses: Software Engineering, High-Performance Computing, Computer Networks Advised 10+ graduate/undergraduate students in thermal simulation, HPC, and nuclear engineering projects Key Projects: Development of PODTherm-GP thermal simulation framework NSF-funded REU programs training over 50+ students

Jan FostierView profile

Researcher

• Bioinformatics
• High Performance Computing (HPC)
• Big Data Analytics
• +3 more

Jan Fostier is a researcher at Ghent University, affiliated with the Internet Technology and Data Science Lab (IDLab). His work focuses on High Performance Computing (HPC) and Big Data Analytics in life sciences and bioinformatics, leveraging supercomputers and GPUs to accelerate genomic data processing. He collaborates across disciplines with bioscience engineers, biologists, medical doctors, and industry partners like Janssen Pharmaceutica and Agilent. His research interests include: Bioinformatics Sequencing Data Analysis High-Performance Computing Stochastic Modelling Genomic Data Compression Recent publications highlight advancements in approximate pattern matching, de Bruijn graph construction, and nanopore signal analysis. Awards include an Outstanding Presentation Award (2015) and an Outstanding Oral Poster Presentation Award (2015). He has developed tools like Halvade , Jabba , and BLSSpeller for genomic applications.

William ThackerView profile

Professor

• Numerical Methods
• Parallel Processing
• Computer Science
• +3 more

William I. Thacker is a Professor of Computer Science at Winthrop University's College of Business and Technology. He holds a Ph.D. from Virginia Tech. His research focuses on the intersection of computer science, mathematics, and engineering, particularly in solving complex mathematical models for engineering applications using advanced numerical methods. He teaches courses in Numerical Methods, Parallel Processing, Data Structures & Algorithms, and an unconventional SCUBA Diving course through the P.E. department. Education Ph.D., Virginia Tech Research Interests Dr. Thacker's work emphasizes numerical methods, parallel processing, and high-performance computing. He applies these techniques to solve real-world engineering problems, often integrating interdisciplinary approaches from mathematics and computational science. His contributions include algorithm development for optimization and interpolation of scattered data. Publications His recent publications highlight advancements in numerical algorithms for optimization (e.g., QNSTOP, vtmop) and interpolation (SHEPPACK), as well as contributions to high-performance computing (HPC) symposium proceedings. These works reflect his expertise in computational methods, parallel processing, and algorithmic innovation. Awards No scientific awards explicitly mentioned in the provided texts. Teaching and Service Regular courses: CSCI 271, CSCI 311, CSCI 371 SCUBA Diving course (PESH 128) for the P.E. department Labs/Teams No dedicated lab or team explicitly mentioned, though his research may involve collaborations within the College of Business and Technology and interdisciplinary projects.

Ali ButtView profile

Professor

• Cloud Computing
• High-Performance Computing (HPC)
• Distributed Systems
• +6 more

Ali Butt is a Professor of Computer Science at Virginia Tech's College of Engineering and ECE by courtesy. He serves as Associate Department Head for Faculty Development and directs the Distributed Systems & Storage Laboratory (DSSL) and the stack@cs Center for Computer Systems . His research focuses on cloud and high-performance computing systems , systems support for machine/deep learning , storage systems , and distributed systems . He earned his Ph.D. in Electrical and Computer Engineering from Purdue University (2006). He has received prestigious awards including the NSF CAREER Award (2008) IBM Faculty Awards (2008, 2015) VT College of Engineering Dean's Award for Outstanding New Assistant Professor (2009) NetApp Faculty Fellowships (2011, 2015) VT College of Engineering Faculty Fellow (2013) His recent work explores federated learning optimizations , I/O load balancing in parallel file systems , and containerized HPC workflows . As Associate Editor for journals like IEEE Transactions on Cloud Computing and ACM Transactions on Storage, he contributes to advancing systems research. His leadership in the DSSL lab drives innovations in large-scale experimental computer systems and data-intensive computing .

Torsten HoeflerView profile

Professor

• High-Performance Computing
• Parallel Computing
• Computer Networks
• +3 more

Prof. Torsten Hoefler is a Full Professor at the Department of Computer Science, ETH Zürich. His research focuses on High-Performance Computing (HPC), parallel systems, networking, and AI-infrastructure. He leads projects on scalable interconnects, network topology design, and cloud computing benchmarks like SeBS. His work bridges theoretical foundations with practical implementations in distributed systems. Research Interests : High-Performance Computing & Networking Parallel Algorithms & Architectures AI Infrastructure & Distributed Systems Chiplet Interconnects & Topology Optimization Key Contributions : Developed tools like ATLAHS (AI/HPC network simulation) Advanced RDMA-based communication protocols (SDR-RDMA) Benchmarks for serverless computing (SeBS-Flow) His recent articles (2025) emphasize adaptive networks, low-precision AI models, and energy-efficient HPC systems. He also explores ethical computing and sustainability in supercomputing through initiatives like Core Hours & Carbon Credits.

Andrew A. ChienView profile

Professor

• Sustainable Computing
• Cloud Software
• Hardware and System Architecture
• +7 more

Andrew A. Chien is the William Eckhardt Distinguished Service Professor of Computer Science at the University of Chicago and a Senior Computer Scientist at Argonne National Laboratory. He leads the Large-Scale Sustainable Systems Group and directs the CERES Center for Unstoppable Computing. His research focuses on sustainable computing, cloud software/hardware, supercomputing architectures, and energy-efficient systems. Chien holds ACM, IEEE, and AAAS Fellowships and has served on advisory boards for NSF, DARPA, and multiple universities. He previously led Intel’s Research division, founded Entropia, and held professorships at UC San Diego and UIUC. His educational contributions include courses on sustainable computing, data-intensive systems, and computer architecture for scientists. Education: Sc.D., S.M., S.B. in Computer Science/Electrical Engineering from MIT Affiliations: UChicago, Argonne, NSF CISE Advisory Committee, DARPA ISAT Study Group Key Projects: Zero-Carbon Cloud, CERES Center, Recode/UDP Architecture, Global View Resilience Chien’s research bridges computational sustainability and scalable systems, addressing energy grids, data center efficiency, and low-carbon computing. His work has been recognized through awards like the NSF Young Investigator Award (1994) and the Argonne Impact Award (2020).

Seda OgrenciView profile

Professor

• Design Automation
• Real-Time Edge AI/ML for Science
• Thermal-Aware Circuit Design
• +3 more

Seda Ogrenci is a Professor of Electrical and Computer Engineering and Computer Science at Northwestern University. She holds affiliations with the McCormick School of Engineering and leads the Ogrenci-Memik Lab. Her research focuses on thermal-aware design, edge AI/ML acceleration, and energy-efficient computing systems. She teaches courses like EECS 303 (Advanced Digital Design), EECS 355 (FPGA Design), and EECS 459 (VLSI Algorithmics). Education includes a PhD in Computer Science from UCLA, MS in Electrical and Computer Engineering from Northwestern, and BS from Bogazici University. Her work spans thermal management, 3D stacked memory systems, and reconfigurable architectures. She authored the book Heat Management in Integrated Circuits (2016) and holds patents on thermal sensors and energy harvesting. Recent projects include ML-based real-time control at the edge, FPGA-accelerated ML monitoring, and in-pixel AI for X-ray detectors. Awards include the NSF CAREER Award (2006) and EECS Best Teacher Award (2013). She advises students like Dawei Li and Yingyi Luo and contributed to grants on thermal-aware HPC systems.

• Multiphysics Modeling
• Thermal-Hydraulics
• Monte Carlo Transport Methods
• +3 more

April Novak is an Assistant Professor at the University of Illinois at Urbana-Champaign (UIUC) in the Department of Nuclear, Plasma, and Radiological Engineering. She holds a joint appointment at the National Center for Supercomputing Applications (NCSA). Her research focuses on multiphysics modeling, thermal-hydraulics, and advanced reactor design, particularly using the MOOSE computational framework. She earned her PhD in Nuclear Engineering from UC Berkeley (2020) and a BS from UIUC (2015). Dr. Novak’s work emphasizes porous media modeling for pebble bed reactors (PBRs), conjugate heat transfer, and Monte Carlo transport methods. She has validated models against experiments like SANA and contributed to tools like Pronghorn and Cardinal. Her research integrates high-performance computing (HPC) for reactor simulations, with recent projects on lead-cooled fast reactors and sodium fast reactor bypass flows. Recipient of the R&D 100 Award (2023) and the Innovations in Nuclear Technology Award (2018), her teaching accolades include the Students' Award for Excellence in Undergraduate Teaching (2024). She advises on multiphysics coupling between neutronics and thermal-hydraulics and collaborates on the Virtual Test Bed (VTB) for advanced reactor models.

Daniel S. KatzView profile

Academic

• Parallel and Distributed Computing
• High-Performance Computing (HPC)
• Fault Tolerance
• +6 more

Daniel S. Katz is a Research Professor and Chief Scientist at the National Center for Supercomputing Applications (NCSA) at the University of Illinois Urbana-Champaign. He holds Research Associate Professor appointments in the Siebel School of Computing and Data Science and the School of Information Sciences (iSchool). His work focuses on advancing scientific software sustainability, open science practices, and high-performance computing (HPC). Katz earned his B.S., M.S., and Ph.D. in Electrical Engineering from Northwestern University (1988–1994). Roles and Affiliations: Chief Scientist, NCSA (100%, 2020–Present) Research Associate Professor, School of Information Sciences (0%, 2016–Present) Research Associate Professor, Computer Science (0%, 2016–Present) Editor-in-Chief, Journal of Open Source Software (JOSS) Co-founder, US Research Software Engineer Association (US-RSE) Research Interests: Katz's research spans parallel/distributed computing, fault tolerance, software sustainability, and open science policies. He advocates for FAIR (Findable, Accessible, Interoperable, Reusable) principles in research software and promotes equitable software practices. His work includes developing frameworks for software citation, improving reproducibility in AI, and fostering collaboration through community-driven initiatives. Awards: 2024 US-RSE Impact Award 2023 IEEE Computer Society Golden Core recognition R&D 100 Award (2018) for Swift/T workflow system Grants and Projects: Katz leads efforts in strategic initiatives like the FARR Research Coordination Network for FAIR and AI readiness. He collaborates on projects funded by the NSF and NASA, including work on sustainable HPC software and AI training programs at NCSA. Labs and Teams: He contributes to NCSA's research initiatives and is affiliated with the Better Scientific Software (BSSw) Fellowship program. His work integrates with teams like the Research Software Alliance (ReSA) to advance software engineering practices in academia.

• Analog Integrated Circuit Design
• Electronics Engineering
• Photonics
• +3 more

Robert Fox is an Associate Professor and ECE Associate Chair at the University of Florida's Department of Electrical & Computer Engineering. He holds a Ph.D. in Electrical Engineering from Auburn University (1986), an M.S. in Electrical Engineering from Auburn University (1981), and a B.S. in Physics from the University of Notre Dame (1972). His research focuses on analog integrated circuit design, with contributions to photonics, semiconductor technology, and high-density components. Notable awards include the UF EDGE Outstanding Faculty Award (2005) and the SRC Inventor Recognition Award (2005). His work spans cutting-edge areas like monolithic silicon photonics and 3D integrated laser technologies. While no advising or grant details are explicitly listed, his publications reflect a strong emphasis on innovation in electronics and biomedical applications.

• High-Performance Computing
• Reconfigurable Computing
• Computer Architecture
• +4 more

Herman Lam is an Associate Professor in the Department of Electrical & Computer Engineering at the University of Florida. He also serves as the UF Site Director for the NSF SHREC Center, focusing on reconfigurable computing and high-performance systems. His research emphasizes heterogeneous computing, FPGA acceleration, and computer architecture design. Dr. Lam holds a PhD in Electrical Engineering (University of Florida, 1979), an ME in Electrical Engineering (University of Florida, 1974), and a BSEE from Georgia Institute of Technology (1972). His work spans academic and industrial collaboration, with notable contributions to scalable reconfigurable supercomputing (e.g., Novo-G) and FPGA-based machine learning acceleration. His research interests include high-performance heterogeneous computing, reconfigurable computing, and computer architecture optimization. He has pioneered frameworks like HgPCN for embedded point cloud inference and APR-OIS for near-sensor processing. Recent work focuses on fault-tolerant systems, FPGA-pipelined simulations, and science gateway platforms like SCAIGATE. Dr. Lam has received prestigious awards, including the 2018 Dell EMC AI Challenge for a heterogeneous computing system and the 2012 NSF Schwarzkopf Prize. He is also recognized for teaching excellence, earning the 1993 University of Florida Teaching Improvement Award. His research teams collaborate with NSF-funded initiatives and industry partners, advancing applications in computational fluid dynamics, genomics, and embedded AI systems. Key projects include the CHREC Space Processor (CSP) for hybrid space computing and virtual FPGA platforms like VirtualRC.

Jesse ChanView profile

Associate Professor

• Numerical Methods for PDEs
• Scientific Computing
• Discontinuous Galerkin Methods
• +5 more

Jesse Chan is an Associate Professor in the Department of Computational Applied Mathematics and Operations Research at Rice University. He earned his Ph.D. from the University of Texas at Austin and a bachelor's degree from Rice University. His research focuses on high-order numerical methods for partial differential equations, including discontinuous Galerkin (DG) methods, entropy stability, and efficient implementations on modern architectures. He has received the NSF CAREER Award (2020) and leads the development of open-source software like Trixi.jl and StartUpDG.jl. Education: Ph.D., Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin (2013) B.A., Computational and Applied Mathematics, Rice University (2008) Research Interests: Numerical Methods for PDEs High-Order Finite Element and DG Methods Entropy Stability and Conservation Laws Scientific Computing and HPC Wave Propagation and Fluid Dynamics Recent Work Trends: His publications emphasize robust entropy-stable schemes, cut-cell methods, and reduced-order modeling for nonlinear conservation laws, with applications to fluid dynamics and wave propagation. He also explores GPU acceleration for DG methods. Awards: NSF CAREER Award (2020) Advising & Grants: Advised students Brian Christner and Raymond Park (recent MA theses) Funded by NSF grants DMS-CAREER-1943186 and DMS-2231482 Labs/Teams: Active contributor to the Trixi.jl framework and collaborator on open-source DG tools like StartUpDG.jl.

Victor CaloView profile

Professor

• Geomechanics
• Fluid Dynamics
• Flow in Porous Media
• +7 more

Victor Calo is the John Curtin Distinguished Professor at Curtin University's School of Elec Eng, Comp and Math Sci (EECMS) within the Faculty of Science and Engineering. He holds the CSIRO Professorial Chair in Computational Geoscience and leads the Centre for Optimisation and Decision Science. His work focuses on advancing high-performance computing (HPC) tools for geomechanics, fluid dynamics, and multiphysics modeling in resource extraction industries. Calo earned a Civil Engineering degree from the University of Buenos Aires, followed by a Master’s in Geomechanics and Ph.D. in Civil and Environmental Engineering from Stanford University. Research Interests : Geomechanics, fluid dynamics, flow in porous media, phase separation, HPC, multiphysics modeling, block copolymer self-assembly, and numerical methods for engineering systems. His research emphasizes developing open-source software to democratize advanced computational techniques. Key Achievements : Highly Cited Researcher (2013), 170+ peer-reviewed publications, 2 patents, and over 18 invited talks/keynotes in 2 years. His work bridges computational methods with geoscience applications, including reservoir simulation and material science. Grants & Collaborations : CSIRO Chair endowment, collaborations with KAUST (e.g., Center for Numerical Porous Media), and partnerships in multiphase flow modeling. Active in organizing mini-symposia at international conferences. Labs/Teams : Leads the Computational Geoscience group at Curtin, focusing on HPC-driven solutions for resource extraction challenges and materials science problems.

Rodney ClarkeView profile

Professor

• Information Systems
• Organizational Systems
• Business Processes
• +3 more

Rodney J. Clarke is a Professor of Operations and Systems at the University of Wollongong (UOW) and holds an Associate Professorship at Karlstad University, Sweden. He leads the School of Management, Operations and Marketing (SMOM) as its Foundation Head of Discipline (Operations). His academic background includes a Ph.D. in Information Systems and Semiotics from UOW (2000) and a Docent in Information Systems from Karlstad University (2007). He is a Fellow of the British Computing Society (FBCS) and has earned over $4.7 million in research funding through grants and contracts. Clarke’s research focuses on Systemic Semiotics, organizational systems, and disaster management, exemplified by projects like the PetaJakarta flood mapping initiative. He has supervised 1 postdoc, 8 PhDs, and 2 MRes students, receiving two nominations for UOW’s Excellence in Supervision Award. His administrative roles include serving on committees such as the Technology Transfer Office (TTO) and High Performance Computing (HPC) Steering Committee at UOW. His teaching spans undergraduate to doctoral levels, with a focus on systems development, multimedia, and research methodologies. Clarke co-founded the Business Research Laboratory (BRL) and the Centre for Responsible Organisations and Practices (CROP), and chairs the Collaboration Laboratory (Co-Lab) within the SMART Infrastructure Facility. He actively contributes to academic leadership, including presidencies in professional associations like the Australasian Association of Information Systems (AAIS).