Arvind is the Johnson Professor of Computer Science and Engineering at MIT and a member of CSAIL (Computer Science and Artificial Intelligence Laboratory). He holds a B.Tech. from IIT Kanpur (1969), M.S. and Ph.D. from the University of Minnesota (1972-1973). His research focuses on computer architecture, parallel computing, memory models, and hardware synthesis. He pioneered dataflow architectures and developed the pH programming language. Notable projects include the Monsoon dataflow machine and Sandburst, a semiconductor company for 10G-bit Ethernet routers. Arvind has received prestigious awards like the IEEE Harry H. Goode Memorial Award (2012) and ACM Fellow (2007). He co-founded Bluespec Inc. and managed collaborations like Nokia-CSAIL (2006-2010). His work spans academia and industry, emphasizing scalable systems and secure computing. Research interests include synthesis/verification of digital systems, graph algorithms, and weak memory models. Current projects explore next-gen Graph AI systems and financial security applications.
Rohan Basu Roy is an Assistant Professor (tenure-track) at the University of Utah, affiliated with the Kahlert School of Computing and the SCI Institute. His research focuses on optimizing parallel and distributed computing systems, including cloud, serverless, and HPC environments, with an emphasis on sustainability and cost-effectiveness. He holds a Ph.D. in Computer Engineering from Northeastern University, advised by Prof. Devesh Tiwari. Affiliations: University of Utah (Kahlert School of Computing), SCI Institute. His research interests include scheduling algorithms, energy efficiency, and environmental sustainability in computing systems. He has pioneered open-source tools like GreenMix and ECOLIFE , widely adopted in the systems research community. Awards: ACM-IEEE CS George Michael Memorial HPC Fellowship (2023), MLCommons ML and Systems Rising Star (2023), Northeastern University Excellence in Research Award (2023). Rohan has served as a program committee member for top-tier conferences (ASPLOS, HPCA, SC) and co-chaired tracks such as AI/ML for Systems at HiPC 2025. He has also delivered invited talks at Google Brain and ParslFest 2023.
Manuel Alejandro Pajuelo González is a researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture and the School of Computer Science. His research focuses on Performance measurement Operating systems Virtualization Thread assignment in multithreaded processors Recent publications show strong trends in RISC-V architectures, cybersecurity, and performance optimization. Key themes include Hardware virtualization Intrusion detection frameworks Statistical thread assignment approaches Spin-lock overhead analysis Scientific awards include BDigital Global Congress 15ª Edició Computación de Altas Prestaciones VI HiPEAC Paper Award He participated in multiple competitive R&D projects, including the DRAC project focused on RISC-V accelerators for next-generation computing.
Dustin Richmond is an Assistant Professor in the Department of Computer Science and Engineering at the Baskin School of Engineering, University of California, Santa Cruz. His work focuses on secure, usable hardware systems with applications in FPGA acceleration, RISC-V architectures, and side-channel analysis. Email: drichmond@ucsc Office: Engineering 2, Room 221 Research Interests: Secure hardware systems FPGA-based computing Manycore processors High-level synthesis Side-channel vulnerabilities Notable Article Trends: Recent publications emphasize cloud FPGA security, manycore design optimization, and hardware security. Earlier works focus on RISC-V acceleration, OpenCL compiler enhancements, and heterogeneous computing systems. GitHub Contributions: Maintains open-source projects like RISC-V-On-PYNQ and PYNQ-HLS, addressing FPGA programming challenges and RISC-V integration. Active in resolving community issues related to toolchain compatibility and hardware-software interfaces.
Sumeet Syal is a Lecturer and Faculty & Academic Programs Lead at San José State University's College of Information, Data & Society. He also serves as Adjunct Faculty at Santa Clara University's Graduate School of Engineering and teaches at UC Santa Cruz. His academic roles focus on Management of Tech & AI Innovations, Leadership, and Marketing, drawing from his extensive executive background in Silicon Valley. UC Berkeley-Haas: Executive Coaching Certification (2021) Stanford Graduate School of Business: Leading Change & Org Renewal (2010) UCLA Anderson & National University of Singapore: Executive MBA (2007) Cal Poly, SLO: B.S. in Computer Engineering (1996) Sumeet’s research and teaching interests span a broad spectrum of technology and society, including Data Analytics, Health Informatics, Human-Computer Interaction, Information Policy, Technology Integration, and Strategic Marketing. His work emphasizes multicultural engagement, storytelling in tech, and leadership in innovation. As a tech executive, he brings practical insights into how information systems transform enterprise strategies. His recent publications, featured in TechCrunch, Engadget, and Business Insider, center on mobile chip technologies, LTE integration, and Intel’s strategic roadmap. These reflect his deep involvement in semiconductor innovation and mobile computing, highlighting trends in processor design, wireless communication, and Silicon Valley’s evolving tech ecosystem. Award-winning coaching & consulting company (3Doshas.com) featured on Bloomberg TV and Apple TV Sumeet has advised and mentored global teams at Intel, guiding leadership development and high-performance culture. Though no formal PhD students are listed, his role as an educator and coach involves significant advising of startup founders and executives. He has not received public research grants, but his industry leadership includes forging multi-billion-dollar partnerships with Google, Apple, Dell, and HP. He leads academic programming initiatives at SJSU and is building educational bridges between academia and Silicon Valley through experiential learning and industry-aligned curriculum development.
Resit Sendag is a Professor and Director of Graduate Studies in the Department of Electrical, Computer and Biomedical Engineering at the University of Rhode Island. He serves as Director of both the URI Computer Architecture Laboratory and the URI Generative AI Development Group, leading cutting-edge research in computer architecture and high-performance computing. His academic credentials include: Ph.D. in Computer Engineering from the University of Minnesota (2003) B.Sc. in Electrical Engineering from Hacettepe University, Ankara (1994) Professor Sendag specializes in computer architecture with research interests spanning processor design, memory systems, parallel computing, and hardware acceleration. His work focuses on improving computational performance through innovative techniques in cache management, prefetching, branch prediction, and specialized hardware implementations using FPGAs and GPUs. Recent research has expanded into applying these architectural principles to solve complex optimization problems like vehicle routing. His publication record demonstrates a consistent evolution from fundamental computer architecture research toward practical applications of architectural techniques. The most recent work shows strong emphasis on implementing genetic algorithms for vehicle routing problems using specialized hardware platforms (FPGAs and GPUs), while maintaining his foundational research on memory access optimization through sophisticated prefetching techniques. Professor Sendag has secured research funding from the Office of Naval Research through collaborative projects with the University of Connecticut focused on advanced manufacturing, shipbuilding processes, and material tracking systems. He actively mentors graduate students, with current advisees working on challenging computer architecture projects. His former students have achieved notable success at leading technology institutions including ETH-Zurich, Intel, NVIDIA, AMD, and various research laboratories. Professor Sendag leads key research initiatives including the URI Computer Architecture Laboratory, the Generative AI Development Group, and the PatternFinder project (an NSF-funded open-source tool for program behavior analysis).
Lecturer Rok Češnovar is affiliated with the Laboratory for Adaptive Systems and Parallel Processing (LASPP). His work focuses on computational methods in adaptive systems and parallel processing. Teaches classes in Computer Systems Organisation, Input-Output Systems, and Embedded Systems Active in research projects related to computationally intensive statistical analysis, sensor networks, and RISC-V vector processors Research Focus Rok Češnovar specializes in embedded systems and signal processing , with emphasis on computationally intensive methods and approximate computing . His work bridges theoretical statistics with practical implementation in adaptive systems. Project History He has contributed to projects including: ARRS-funded research on computationally intensive statistical methods (2016-2019) Decomposing cognition in working memory studies (J3-9264, 2018-2021) High-performance RISC-V vector processor computing (BI-HR/23-24-009, 2023-2025)
Bruno Gaujal is a Research Professor at Inria Grenoble-Rhône-Alpes, affiliated with Université Grenoble Alpes. He obtained his PhD from the University of Nice in 1994 under François Baccelli's supervision and has held positions at AT&T Bell Labs, INRIA, and École Normale Supérieure de Lyon. He previously led the MESCAL (now POLARIS) research group focused on large-scale computing until 2015. His research interests center on performance evaluation, optimization, and control of discrete event dynamic systems with stochastic inputs. Specific areas include: Markov Chains and Markov Decision Processes Reinforcement Learning and stochastic optimization Queueing theory and scheduling algorithms Energy-efficient computing in distributed systems Game-theoretic approaches in network optimization Gaujal's recent publications show strong emphasis on reinforcement learning applications in queueing networks, energy optimization for real-time systems, and scalable algorithms for Markov Decision Processes. His work bridges theoretical frameworks like Whittle indices with practical implementations in cloud computing and distributed systems. He has supervised numerous PhD students including Nicolas Gast (now Inria researcher), Anne Bouillard (Huawei researcher), and Emmanuel Hyon (Paris Nanterre professor). Current students include Hélène Arvis and Romain Cravic. Gaujal co-founded RTaW, a startup specializing in real-time network design tools. At Inria, he leads research in the POLARIS group, focusing on optimization methods for large-scale distributed computing infrastructures. His work involves collaborations with 85+ co-authors across institutions globally.
Panagiotis E. Hadjidoukas is an Adjunct Assistant Professor at the Department of Computer Science, University of Ioannina, Greece. He currently holds a Visiting Scientist position at IBM Research Zurich. His work bridges parallel computing with applications in medical physics, computational biology, and high-performance numerical optimization. His research focuses on parallel and distributed computing, runtime support for parallel programming models, and thread libraries. He has contributed to hybrid programming frameworks and task-parallelism deployment in multicore environments. The articles in his portfolio highlight a strong trend in Monte Carlo simulations applied to radiation biology, parallelization techniques for hierarchical data clustering, and performance optimization in multicore systems. His work often integrates OpenMP and hybrid MPI/OpenMP models for distributed computing. He has developed notable software projects like PSthreads (a runtime library for lightweight threads) and UthLib (a portable non-preemptive user-level threads package).
Nicholas Morse is a Postdoctoral Researcher in the Engineering Mechanics Department at KTH Royal Institute of Technology in Stockholm, Sweden. He joined KTH in May 2025 and is supervised by Professors Philipp Schlatter (FAU Erlangen, KTH), Ramis Örlü (OsloMet, KTH), and Mihai Mihaescu (KTH). Dr. Morse earned his PhD in Aerospace Engineering & Mechanics from the University of Minnesota in 2023 under Professor Krishnan Mahesh. Prior to KTH, he served as a Senior Scientist at the Research Center Pharmaceutical Engineering in Graz, Austria (2023-2025), where he led simulation strategy for an EU Horizon 2020 project and developed computational methods for droplet breakup analysis. Nicholas Morse's research centers on: Curvature and rotational effects on turbulent flows Turbulent boundary layers on curved surfaces and spinning cones Eccentric Taylor-Couette-Poiseuille flow transition High-fidelity simulation of complex turbulent flows using DNS and LES His technical expertise spans: High-performance computing infrastructure Direct numerical and large-eddy simulation methodologies Adaptive mesh refinement algorithms Heterogeneous (GPU) computing implementations Multiphase flow modeling Academic recognition includes: John A. & Jane Dunning Copper Fellowship for Aerospace Engineering & Mechanics (2019) Donald & Shirley Gorence Scholarship (2018) Robert H. & Marjorie F. Jewitt Fund Scholarship (2017) Dr. Morse has extensive experience in computational fluid dynamics, having conducted large-scale simulations (>10,000 processors) at the University of Minnesota and developed the Multi-Element Wing Generator MATLAB application for Formula SAE aerodynamics design. His work bridges theoretical fluid mechanics with practical engineering applications across aerospace and pharmaceutical domains.
Dr. hab. Beata Bylina is a Professor at the Faculty of Mathematics, Physics and Computer Science , Maria Curie-Skłodowska University (UMCS) , affiliated with the Department of Information Systems Software . She specializes in high-performance computing, numerical methods, and energy-efficient parallel programming. ORCID ID : 0000-0002-1327-9747 Contact : beata.bylina@umcs.pl / beata.bylina@mail.umcs.pl Office : Room D-522 (Institute of Computer Science) or Room B-2, Akademicka Street 9, Lublin Consultations : Wednesdays 10:00–12:00 (in-person or remote via Microsoft Teams) Her research focuses on: Parallelization and vectorization techniques for multicore architectures Energy consumption optimization in numerical algorithms Matrix factorization methods (WZ, LU, QR) for CPU/GPU hybrid systems Markov chain modeling for network performance analysis Compiler optimization impact on performance and energy metrics Recent publication trends show emphasis on: Time-energy correlations in multithreaded algorithms OpenMP/OpenACC for hybrid CPU-GPU implementations Efficient sparse matrix storage schemes for GPUs Impact of hardware-specific optimizations (Xeon Phi, frequency scaling) Comparative studies of parallelization strategies
Bartłomiej Kotyra serves as an Assistant Professor in the Department of Information Systems Software at the Institute of Computer Science and Mathematics, Faculty of Mathematics, Physics and Computer Science, Maria Curie-Skłodowska University in Lublin, Poland. His research spans interdisciplinary domains with emphasis on: Parallel algorithms implementation using OpenMP and GPU architectures Hydrological modeling including watershed delineation and flow accumulation analysis Financial market applications focusing on forex indicators and technical analysis Dr. Kotyra has published 5 scholarly articles with a Scopus/Web of Science h-index of 3. His computational research demonstrates expertise in applying high-performance computing techniques to geospatial problems and financial market analysis, particularly in longest flow path calculations and multicore processor optimizations. His scholarly impact is reflected in a total impact factor of 14.768, SNIP of 4.92, and CiteScore of 26.3, accumulating 485 points in the Polish ministerial scoring system. Dr. Kotyra maintains regular consultation hours on Mondays from 12:15-14:15 and can be reached at room 306 (phone: 81 537 29 35) or via email.
Ioannis Venetis is an Assistant Professor at the University of Piraeus, School of Information and Communication Technologies, Department of Informatics, specializing in Operating Systems and Parallel Computing. He earned his PhD from the Department of Computer Engineering and Informatics at the University of Patras. His research spans programming models for parallel systems, scheduling optimization, and applications in computational neuroscience and seismology. Research Interests Operating Systems Parallel Computing Scheduling Algorithms High-Performance Computing Computational Neuroscience Seismology Projects Participation in European and national research programs Development of Gisola (GPU-accelerated seismic inversion tool) His teaching portfolio includes courses like Operating Systems, Parallel Processing, and Symbolic Programming. Articles highlight expertise in GPU acceleration, tridiagonal solvers, sensor networks, and many-core architectures. Notable contributions include work on Chimera states in neuronal dynamics and hierarchical workload scheduling frameworks.
Borut Robič is a Full Professor and Head of the Theoretical Computer Science Chair at the Faculty of Computer and Information Science, University of Ljubljana . He also serves as Head of the Laboratory for Algorithmics and President of the Faculty's Academic Assembly since 2005. His work spans computability theory, algorithms, and parallel computing, with notable contributions to foundational concepts and educational literature. University: University of Ljubljana School: Faculty of Computer and Information Science Roles: Professor, Head of Theoretical Computer Science Chair, Head of Laboratory for Algorithmics, President of Academic Assembly Robič's research interests focus on computability and complexity theory, algorithm design, and parallel computing frameworks. His publications emphasize historical context, formal methods, and modern computational paradigms like hypercomputing. Publication trends reveal a progression from foundational algorithmic theory (1999) to advanced computability research (2020), with a 2018 work bridging parallel programming and practical implementation. Projects include leadership in ARRS research programmes on parallel systems (2020-2026) and past collaborations on graph optimization and big data initiatives. Laboratory affiliations: Head of the Laboratory for Algorithmics and active member of its research team.
Mainak Chaudhuri serves as a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur, where he specializes in computer architecture research and teaching. Doctor of Philosophy, Cornell University, 2004 Master of Science, Cornell University, 2001 Bachelor of Technology, Indian Institute of Technology Kharagpur, 1999 Professor Chaudhuri's research focuses exclusively on computer architecture, with particular expertise in cache management systems, memory hierarchy optimization, and processor design. His work addresses critical challenges in modern computing systems where efficient memory access patterns significantly impact overall system performance across various computing platforms. His recent publications demonstrate consistent contributions to cache management research, particularly in last-level cache algorithms for both traditional processors and graphics processing units. The publications show an evolving research trajectory from general cache algorithms toward specialized implementations for graphics workloads, indicating strategic expansion of his research domain while maintaining core expertise in memory systems. Best paper award in the 11th IEEE International Symposium on High-Performance Computer Architecture, February 2005 While specific details about graduate student supervision aren't provided in the available documentation, his publication record suggests active research mentorship within computer architecture. The absence of explicit grant information in the source material prevents detailed commentary on funded research projects, though his award-winning work indicates successful research proposal development. Though not explicitly mentioned in the source documents, his specialization in computer architecture suggests potential involvement with computer systems laboratories at IIT Kanpur where architectural simulations and hardware implementations would be conducted, supporting both his research and educational mission in advanced computing systems.
