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Rakesh Kumar is an Associate Professor in the Department of Computer Science (IDI) at the Norwegian University of Science and Technology (NTNU) , affiliated with the Computer Architecture Lab (CAL) within the Faculty of Information Technology and Electrical Engineering . Prior to joining NTNU, he held postdoctoral and research associate positions at Uppsala University and the University of Edinburgh, and interned at Intel Barcelona Research Center. Research Interests include improving large-scale datacenter efficiency through microarchitecture and memory system optimizations, hardware/software co-designed processors, dynamic code translation, vectorization, and serverless function execution. His work explores ready-aware instruction scheduling, branch prediction organization, and address translation mechanisms. Scientific Contributions span publications at top-tier conferences like MICRO (2024, 2023, 2018, 2016) HPCA (2020, 2019, 2023, 2022) ASPLOS (2018) DATE (2019, 2021) Journal articles appear in ACM Transactions on Computer Systems and IEEE Computer Architecture Letters . Awards include Intel Spontaneous Level II/Excellence Award (2014) Best Presentation Award at HiPC-SS08 (2008) Best Paper Award at National Conference on High Computing Technologies (2008) Distinguished Artifact Award at MICRO 2023 PhD Supervision involves advising students like Roman Kaspar Brunner, Elias Orrem, and Truls Asheim on topics spanning microarchitecture, vector units, and runahead execution policies.

• Computer Architecture
• Microarchitecture
• Memory Systems
• +4 more

Prof. Anne C. Elster is a Professor of Computer Science at NTNU's Department of Computer & Information Science (IDI), leading the HPC-Lab. She specializes in High-Performance Computing (HPC), GPU acceleration, and heterogeneous systems. Her work spans HPC applications in medical imaging, seismic processing, and oil & gas simulations, with collaborations at CERN, NVIDIA, and Schlumberger. Elster holds a PhD in Electrical Engineering from Cornell University (1994) and is an IEEE Senior Member since 2000. She has supervised over 70 master students and numerous PhD candidates, emphasizing GPU computing. Her teaching includes courses like Parallel Computing and Compilers , with a focus on programming and problem-based learning. She leads EU projects like CLOUDLIGHTNING (2015–2018) and has organized major conferences (e.g., ISC, SC, PARA). Her HPC-Lab is a CUDA Research and Teaching Center, and she advocates for HPC infrastructure investments in Norway through policy engagement.

• High-Performance Computing (HPC)
• Parallel Computing
• GPU Computing
• +6 more

Dr. Zhang Qixia is a Postdoctoral Research Fellow in Computer Science at UiT The Arctic University of Norway and a guest researcher at the University of Oslo. She actively contributes to cutting-edge research in cloud/edge computing , machine learning , and energy-efficient IoT systems , with particular focus on air pollution monitoring and wind energy optimization . Current roles: Postdoctoral Research Fellow (UiT), Guest Researcher (University of Oslo) Research projects: HAPADS, MISO, EMLEMS, DILUTE, AirQMan Research group: Arctic Green Computing (AGC) Contact: qixia.zhang@uit.no , +47 96 64 67 05 Her research integrates artificial intelligence with distributed systems to enhance environmental monitoring technologies and renewable energy systems. Recent work demonstrates expertise in autonomous data collection , vehicular edge computing , and machine learning-driven wind energy modeling . Publication Trends reveal a focus on IoT/5G network optimization (2019-2021), wind energy analytics (2022-2023), and intelligent environmental monitoring (2024-2025). Her work bridges computer science with climate science through interdisciplinary applications of transfer learning and control theory . Teaching : Instructor for INF-2300 Computer Communication at UiT.

• Cloud Computing
• Edge Computing
• Artificial Intelligence
• +7 more

Rakesh Kumar is an Associate Professor in the Department of Computer Science at NTNU, affiliated with the Computer Architecture Lab (CAL). He received his PhD from UPC Barcelona in 2014 and previously worked at Uppsala University, the University of Edinburgh, and Intel Barcelona Research Center. His research focuses on improving datacenter efficiency through microarchitecture and memory systems, hardware/software co-design, and dynamic code translation. Education: PhD in Computer Architecture, UPC Barcelona (2014) MEng in Microelectronics, BITS Pilani (2008) BTech in Electronics and Communications, Kurukshetra University (2005) Research Interests: His work emphasizes processor microarchitecture, memory systems, and energy-efficient designs. Key areas include hardware/software co-design (e.g., Nvidia Denver alternatives), dynamic vectorization, and server optimization. Recent projects target server front-end bottlenecks, address translation efficiency, and BTB organization for data centers. Publications: Recent work includes contributions to IEEE/ACM MICRO, HPCA, and ISCA, focusing on topics like uneven block size instruction caches, address translation optimizations, and server architecture improvements. Awards: Intel Spontaneous Level II/Excellence Award (2014) Distinguished Artifact Award at IEEE/ACM MICRO 2023 Teaching & Advising: Teaches courses like TDT4258 Low Level Programming and advises students on projects such as vector unit design and microarchitecture optimization. Active in mentoring PhD candidates and leading the Computer Architecture Lab. Labs/Teams: Affiliated with the Computer Architecture Lab (CAL) and collaborates on projects like DARCO, an infrastructure for HW/SW co-designed virtual machines.

• Computer Architecture
• Processor Microarchitecture
• Memory Systems
• +4 more

Kristjon Ciko is a Research Fellow at the University of Oslo's Faculty of Mathematics and Natural Sciences, affiliated with the Department of Informatics under the Networks and Distributed Systems group. His work focuses on advancing network architectures and distributed systems. Research Interests: Ciko's research spans network architecture, particularly Recursive InterNetwork Architecture (RINA), congestion control mechanisms, and energy-efficient computing. His studies address challenges in next-generation network design, throughput optimization, and sustainable computing systems. Publications: Recent work includes innovations in energy efficiency for throughput computing, software-based server energy management, and congestion control solutions for datacenter networks. His research bridges theoretical advancements with practical implementations.

• Network Architecture
• Distributed Systems
• Recursive InterNetwork Architecture (RINA)
• +3 more