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Alex AikenView profile

Professor

• Programming Languages
• Compiler Construction
• Parallel Computing
• +2 more

Alex Aiken is the Alcatel-Lucent Professor of Computer Science at Stanford University and serves as the Computer Science Division Director at SLAC. He has been a faculty member at Stanford since 2003, after previously serving as a Professor in the EECS department at UC Berkeley (1993-2003) and as a Research Staff Member at IBM Almaden Research Center (1988-1993). Dr. Aiken received his Bachelors degree in Computer Science and Music from Bowling Green State University in 1983 and his Ph.D. from Cornell University in 1988. He previously served as chair of the Stanford Computer Science Department. Alex Aiken's research focuses primarily on programming languages, compilers, and parallel computing systems. He is renowned for his work on the Legion programming system for heterogeneous parallel machines, the FlexFlow system for deep learning parallelization, and the development of Moss, a widely-used plagiarism detection system. His research spans both theoretical foundations and practical implementations, with a strong emphasis on translating research into usable software tools. His work has significant applications in high-performance computing, software analysis, and compiler technology. His recent publications reflect a continued focus on parallel and distributed systems, with increasing attention to the intersection of programming systems and machine learning. The 15 most recent articles demonstrate his leadership in task-based programming models, verification techniques, and the application of AI to programming systems. His work spans from low-level GPU optimizations to high-level language design and verification. ACM Fellow Recipient of ACM SIGPLAN's Programming Languages Achievement Award Phi Beta Kappa's Teaching Award Professor Aiken has advised numerous Ph.D. students throughout his career, with eight current advisees including Benjamin Driscoll, Qiantan Hong, and Rupanshu Soi. His research group has received substantial funding for projects related to parallel programming systems, compiler technology, and software analysis tools. The group maintains several active open-source projects including Legion, FlexFlow, and Moss. Aiken leads the Legion research group, which focuses on developing programming models and runtime systems for heterogeneous and distributed parallel machines. The group has made significant contributions to the field of task-based parallelism and has developed several widely-used software systems that bridge the gap between theoretical research and practical implementation.

Hui ChenView profile

Research Fellow

• Arithmetic Circuits
• Integrated Circuits Design
• Reconfigurable Computing
• +3 more

Hui Chen is a Research Fellow at KTH Royal Institute of Technology, part of the School of Electrical Engineering and Computer Science (EECS), within the Department of Electrical Engineering. His current role is as a Digital Futures Postdoctoral Fellow, focusing on generalizing hardware acceleration for nonlinear functions. He completed his PhD in Information and Communication Engineering at Nanjing University (China) in 2022. Research Interests: Hui’s work centers on arithmetic circuits, integrated circuits for elementary functions, and reconfigurable computing. His postdoctoral project, supervised by Prof. Zhonghai Lu and Assoc. Prof. Masoumeh Ebrahimi, aims to develop a generalized design method for nonlinear function hardware acceleration, addressing challenges in digital chip efficiency for smart society applications. Project Context: The Digital Futures initiative, a cross-disciplinary research center involving KTH, Stockholm University, and RISE, focuses on digital technologies for societal challenges. Hui’s project (2023–2024) falls under the 'Digitalized Industry' theme, emphasizing sustainable and high-performance computational architectures. Publications: Hui has contributed to studies on transparent wood biocomposites, nanotechnology, and light scattering in biomaterials, with recent works exploring sustainable thermal energy storage and dual-stimuli-responsive materials. His research bridges materials science, optics, and computational engineering.

• Computing architectures
• Systems reliability
• Cyber-physical systems
• +3 more

Dr. Alexandru Amăricăi-Boncalo is a Lecturer at the Department of Computer Science, Politehnica University of Timisoara. He holds a Dr. Eng. degree and has served as Scientific Secretary of the Department from 2016 to 2023. His roles include academic instruction, research coordination, and administrative leadership in technical departments. Education: PhD in Computer Science (2009) and MSc in Computer Engineering (2006), both from Politehnica University of Timisoara Visiting researcher at University College Cork (2012) and ENSEA Cergy-Pontoise (2016) Senior Fulbright grant recipient at University of Arizona (2017) Research focuses on computing architectures, systems reliability, and FPGA-based signal processing implementations. His work addresses challenges in digital systems reliability, embedded architectures, and cyber-physical systems. Key publication themes: FPGA optimization (40%), digital arithmetic (30%), LDPC decoders (20%), image processing architectures (10%) Notable projects: CloudPUTing (high-performance cloud platform) and GEMSCLAIM (energy-efficient mobile systems) Scientific achievements include: Senior Fulbright Award (2017) Professional engagements span international collaborations, workshop organization, and participation in conferences like IEEE COMCAS and FPL. His technical expertise covers computer architecture, arithmetic algorithms, and hardware-software co-design.

• Formal analysis
• Software testing
• Programming languages
• +6 more

Alastair Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he has been a faculty member since 2011. He leads the FastPL research group (formerly Multicore Programming Group), focusing on formal analysis, software testing, and programming languages techniques for improving software reliability, with special emphasis on high-performance systems. Donaldson earned his BSc (First Class Honors) in Computing Science and Mathematics from the University of Glasgow in 2003, followed by a PhD in Computing Science from the same institution in 2007 under Alice Miller. His academic journey includes positions as an EPSRC Postdoctoral Research Fellow at Oxford, Visiting Researcher at Microsoft Research Redmond, and Research Engineer at Codeplay Software Ltd. His research spans automated reasoning, compiler verification, and GPU programming with significant contributions to software reliability. He pioneered metamorphic testing for graphics drivers through GraphicsFuzz (acquired by Google in 2018) and developed innovative compiler fuzzing techniques. His work addresses critical challenges in memory models, concurrency, and verification of complex systems. Recent publications show increasing focus on applying these techniques to modern challenges including AI-generated code and verification-aware programming languages like Dafny. Donaldson's scientific contributions have been recognized with the 2017 BCS Roger Needham Award, an EPSRC Early Career Fellowship, and multiple best paper awards including EuroSys 2024 (Best Paper), ICST 2024 (Best Industry Paper), and ISSTA 2023 (Distinguished Paper). His 2012 GPUVerify paper received the ACM SIGPLAN Most Influential OOPSLA Paper Award in 2022. As an advisor, Donaldson has mentored numerous PhD students and postdocs, many now in prominent academic and industry positions. His research is supported by Amazon Research Awards (2022-2023) for Dafny ecosystem testing and compiler validation. He previously served as Senior Software Engineer and Visiting Researcher at Google following the GraphicsFuzz acquisition. The FastPL group maintains strong industry connections with Google, Microsoft, and Amazon, ensuring practical relevance of their theoretical work. Donaldson currently serves as Editor-in-Chief of ACM TOPLAS (2025-present) and on program committees for major conferences including PLDI, ICSE, and ASPLOS.

• Static Analysis of Programs
• Formal Verification
• Concurrency
• +12 more

Tomáš Vojnar is a Professor at the Department of Intelligent Systems, Faculty of Information Technology, Brno University of Technology (FIT BUT), Czech Republic. He has been a faculty member since 1999, promoted to Associate Professor in 2007 and full Professor in 2012. He leads the VeriFIT research group and has extensive experience in academic leadership, including candidacy for Dean of FIT BUT in 2023 and chairing major conferences such as TACAS'19 and SV-COMP 2018. Research Interests: Static and dynamic analysis of programs, especially those with pointers and dynamic data structures Formal verification of concurrent and infinite-state systems Automata-theoretic and logical methods in verification Binary code analysis and performance analysis His recent publications show a strong trend in developing and applying static analysis tools for verifying memory safety, concurrency, and semantic equivalence in C programs. He has made significant contributions to tools like Predator, 2LS, and DiffKemp, which are widely used in the verification community and have achieved top rankings in international competitions such as SV-COMP. His work bridges theoretical foundations in automata and logic with practical software verification applications. Scientific Awards: Best theory paper award of ETAPS'10 (EATCS) Best paper awards at CADE'19 and CIAA'08 Best tool paper awards at ISSTA'18 and RV'12 Multiple gold, silver, and bronze medals in SV-COMP (Predator, 2LS, Symbiotic) Bronze Humies award for automated design of approximate circuits Gödel prize from FLoC 2014 Olympic Games 1 gold and 3 silver medals at SL-COMP'14 Siemens prize for outstanding PhD thesis (2001) Advising and Grants: He has supervised numerous PhD and Master's students who have contributed to major verification tools and publications. He has been actively involved in national and international research projects, including the Czech Science Foundation panel P103 (2019–2023), and has secured funding for research in formal methods and software verification. His collaborations span institutions in France (LIAFA, CNRS), Austria (TU Vienna), and beyond. Labs and Teams: He leads the VeriFIT research group at FIT BUT, which focuses on formal methods and software verification. The group develops state-of-the-art tools such as Predator (shape analysis), 2LS (heap verification), DiffKemp (semantic diffing), and others used in both academia and industry. The team actively participates in international verification competitions and collaborates with researchers worldwide.

• Nanoscale CMOS architectures and circuits
• Frequency synthesizers
• Transmitters and receivers
• +3 more

Prof. Robert Staszewski is a Full Professor at the School of Electrical and Electronic Engineering, University College Dublin (since 2014) and a Visiting Full Professor at Delft University of Technology (since 2009). His academic journey began with a PhD from University of Texas at Dallas (2002), preceded by MSEE (1992) and BSEE (1991) degrees. He previously worked at Alcatel (1991–1995) and Texas Instruments (1995–2009), where he co-founded the Digital RF Processor (DRP) group and served as CTO (2007–2009). Research Focus : Nanoscale CMOS architectures, quantum computing hardware, millimeter-wave PLLs, and low-power IoT RF circuits. Recent Publications : 15 most recent works span quantum dots in 22nm FDSOI, harmonic predistortion in ADPLLs, ultra-low-jitter charge-sharing PLLs, and RF reuse strategies for IoT. Scientific Contributions include 6 books, 11 book chapters, 150+ journal papers, and 210 US patents. His Equal1 Labs co-founded in 2014 aims to build the first single-chip CMOS quantum computer. Awards: 2012 IEEE Circuits and Systems Industrial Pioneer Award IEEE Fellow (2009) Teaching Leadership : Coordinates advanced modules in Analogue Integrated Circuits , Mixed-Signal Circuits , and Quantum Computing (2014–2025). Supervises PhD thesis projects in nanoscale RF and quantum systems.

Afsaneh RahbarView profile

Assistant Professor

• Compilers
• High-Performance Computing
• Compute Clusters
• +2 more

Afsaneh Rahbar is an Assistant Professor at Duke University's Department of Electrical and Computer Engineering within the College of Engineering. Her research focuses on compilers, high-performance computing, and distributed systems, with particular emphasis on mobile ad hoc networks and data communication protocols. M.S., Rice University (2018) Ph.D., Rice University (2021) Rahbar's work spans both theoretical and applied aspects of computing systems, including contributions to MANET protocols, distributed learning automata, and fault-tolerant circuit design. Her publications from 2009–2010 reflect early-career expertise in system architecture and network optimization. While no scientific awards are highlighted in available records, her research has been presented at major international conferences like IEEE ACS and ITNG. Rahbar actively contributes to academic training through courses in software engineering and systems programming.

• Computational Fluid Dynamics
• Aerospace Engineering
• Quantum Computing Applications
• +7 more

Rene Steijl serves as a Senior Lecturer in Aerospace Engineering within the James Watt School of Engineering at the University of Glasgow, specializing in Autonomous Systems & Connectivity. His academic profile demonstrates a sustained research career focused on computational fluid dynamics with increasing emphasis on quantum computing applications in recent years. Dr. Steijl's research interests center on modeling and simulation of complex flows for aerospace applications, particularly focusing on multi-physics/multi-scale methods for challenging flow regimes including strong shock waves and expansions in supersonic and hypersonic flows. His work spans computational aerodynamics for high-speed transport aircraft, unmanned aerial vehicles, space launch systems, re-entry vehicles, and helicopters. Since approximately 2020, his research has significantly expanded into quantum computing applications for fluid dynamics, with numerous publications exploring quantum algorithms for computational fluid dynamics, quantum circuit implementations, and quantum simulation of fluid phenomena. This represents a strategic evolution of his expertise in advanced computational methods toward emerging quantum computing paradigms. Analysis of his recent publications reveals a clear trajectory from traditional computational fluid dynamics toward quantum computing applications, with nearly half of his 2023-2024 publications focusing on quantum algorithms and implementations. His work bridges fundamental fluid dynamics with cutting-edge computational approaches, maintaining relevance to practical aerospace applications while exploring next-generation computing technologies. The publications demonstrate consistent collaboration with colleagues at Glasgow and internationally, particularly with George Barakos and Craig White. Dr. Steijl maintains active research in both conventional computational fluid dynamics and emerging quantum computing applications, with recent work addressing challenges in shock wave interactions, gas kinetic modeling, rotorcraft aerodynamics, and quantum circuit optimization. His ORCID profile (0000-0002-1872-8687) documents over 100 publications spanning two decades of research contributions to aerospace engineering and computational science.

• Differential-Algebraic Equations (DAEs)
• Interval Methods
• Structural Analysis
• +7 more

Nedialko Nedialkov is a Professor in the Department of Computing and Software at McMaster University, Faculty of Engineering. His research centers on differential-algebraic equations (DAEs) , interval methods , and computational science , with a focus on rigorous numerical solutions and structural analysis. Contact: nedialk@mcmaster.ca Teaching: Courses include Scientific Computing, Advanced Topics in Computing and Software, and Principles of Programming. Research Highlights: Nedialkov has developed symbolic-numeric methods for DAEs, improved verified ODE integration, and created tools like DAETS for structural analysis. His work spans applications in hybrid systems , control theory , and biomedical computing . Publications Trends: Over the past 15 years, his scholarship emphasizes DAEs, validated numerical methods, and computational modeling. Key subfields include Port-Hamiltonian systems , block triangularization , interval constraints , and automatic differentiation . Labs & Teams: Collaborates with McMaster Experts and contributes to open-source projects for validated numerical computing.

Moritz WeißbrichView profile

Researcher

• Processor Architecture
• Low-power Electronics
• Approximate Computing
• +3 more

M.Sc. Moritz Weißbrich is a Researcher at the Chair for Chip Design for Embedded Computing , part of the Institute of Theoretical Computer Science at Technische Universität Braunschweig. Holding an M.Sc. in Electrical Engineering and Information Technology from Leibniz Universität Hannover, his academic focus spans high-performance/low-power processor architectures , approximating arithmetic circuits , and stochastic computation techniques for fault-tolerant systems. His research portfolio includes 20+ peer-reviewed publications since 2017, with recent work on Nano-scale controllers for FPGA systems Biomedical sensor design in 22nm FDSOI Energy-aware VLIW processor optimization Stochastic timing analysis frameworks He has been developing ultra-low-power embedded solutions since 2021, following prior research assistant roles at Leibniz Universität Hannover's Institute of Microelectronic Systems (2017-2021). Key technical contributions appear in venues like Springer LNCS , IEEE RFIC Symposium , and Journal of Systems Architecture , focusing on processor customization , energy harvesting systems , and radiation-hardened circuit design . His work addresses challenges in autonomous computing, harsh environment electronics, and precision agriculture applications.

• Neuromorphic Computing
• Neural Networks
• Machine Learning
• +4 more

Dr. Denis Kleyko is a Visiting Research Fellow at La Trobe University's Business Analytics department. His work focuses on neuromorphic computing, hyperdimensional computing, and neuro-inspired algorithms. He has contributed to frameworks like NeuroBench for benchmarking neuromorphic systems and authored comprehensive surveys on vector symbolic architectures. Key research interests include neuromorphic reservoir computing, sparse randomized embeddings, and cognitive mapping through neural circuits. His publications span journals such as Nature Communications and IEEE Transactions, emphasizing interdisciplinary approaches in machine learning and neuroscience. Collaborations include international teams addressing challenges in seizure prediction, compositional learning, and high-dimensional data processing. Notable outputs include foundational work on HyperSEED and efficient optimization using Ising machines.

• High-performance computing
• Decimal arithmetic
• Parallel programming
• +4 more

Alvaro Vazquez Alvarez is an Assistant Professor at the Higher Technical School of Engineering, University of Santiago de Compostela. He holds a PhD in Computer Engineering (2009) from the same institution, focusing on High-performance decimal floating point units under the supervision of Dr. Elisardo Antelo Suárez. His research interests span high-performance computing, decimal arithmetic hardware design, parallel programming models, and LiDAR data processing. His work emphasizes FPGA implementation of arithmetic units, numerical algorithms optimization, and compiler/runtime systems for parallel environments. He leads the CograDe Research Group (Computer Graphics and Data Engineering), exploring advanced topics in parallel computing and data engineering applications. Key contributions include universal MPI binding frameworks for new languages and efficient LiDAR point cloud processing algorithms. Notable technical expertise includes: digit-by-digit algorithms, redundant number systems, CORDIC-based computations, and multi-operand decimal arithmetic implementations. His publications bridge theoretical numerical methods with practical hardware/software co-design solutions. Current research focuses on extending parallel programming interfaces, improving decimal arithmetic precision in modern architectures, and applying advanced geometric processing techniques to 3D data challenges.

Vladimir MilovanovićView profile

Associate Professor

• Electrical Engineering
• Computer Science
• Signal Processing
• +7 more

Dr. Vladimir Milovanović is an Associate Professor at the Faculty of Engineering, University of Kragujevac, Serbia, holding a position as Chair of the Department of Electrical Engineering and Computer Sciences. His academic career is anchored in interdisciplinary research at the intersection of electrical engineering, computer science, and biomedical applications. His research focuses on hardware design, radar sensor systems, biomedical signal processing, and machine learning applications. Notable areas include CMOS circuit design, FPGA-based implementations, and parameterizable hardware generators for signal processing tasks. He also explores medical imaging analysis using deep learning techniques for conditions like disc hernia diagnosis. Recent work emphasizes radar technology (FMCW transceivers, signal processing architectures), embedded systems (FPGA development, IP core utilization), and high-performance streaming data algorithms. His publications span over two decades, demonstrating expertise in analog/digital circuit design, comparative classifier analysis in biomedical contexts, and hardware-software co-design methodologies. Dr. Milovanović collaborates with industry on energy-efficient MIMO arrays and semiconductor gas sensors. His contributions include open-source HDL models for digital signal processors and comparator circuits optimized for low-power and high-speed applications.

Yiorgos TsiatouhasView profile

Professor

• Analog and Digital VLSI Design
• Integrated Circuit Reliability
• Secure Computing Systems
• +4 more

Yiorgos Tsiatouhas is a Professor in the Department of Computer Science and Engineering at the University of Ioannina. He holds a B.Sc. in Physics (University of Athens, 1990), M.Sc. in Informatics and Telecommunications (University of Athens, 1993), and Ph.D. in Informatics and Telecommunications (University of Athens, 1999). His research focuses on VLSI circuit design, reliability engineering, and secure computing. He teaches courses such as 'Electronics' (MYY404), 'VLSI Circuits' (MYE018), and 'Reliable Integrated Systems' (Y2), emphasizing topics like CMOS technology, radiation-hardened electronics, and testing methodologies. His research interests span secure computing architectures, fault-tolerant systems, and aging monitoring in integrated circuits. Recent work includes developing radiation-hardened latches, PUF-based security solutions for SoCs, and novel testing algorithms for phase-change memories. He has also contributed to visible light communication (VLC) systems, addressing challenges like anti-reflective obstacle detection and adaptive signal decoding in non-line-of-sight (NLOS) environments. Teaching activities include supervising student projects, maintaining an active lab for SPICE-based circuit simulation, and integrating industry-standard tools like Cadence into coursework. His lab focuses on designing and testing analog/digital circuits, emphasizing practical skills in SPICE simulation and layout design.

Majid HaghparastView profile

Associate Professor

• Software Engineering
• High Performance Computing
• Quantum Computing
• +10 more

Majid Haghparast serves as an Associate Professor in the Faculty of Information Technology at the University of Jyväskylä, Finland, with a sabbatical research fellowship at Johannes Kepler University (Linz, Austria) from April 2017 to January 2018. His research spans Software Engineering, Quantum Computing, and High Performance Computing, with concentrated expertise in Quantum Algorithms, Reversible Computation, Quantum dot Cellular Automata, and Multiple-Valued Logic. He investigates fault-tolerant quantum systems, ternary logic implementations, and quantum software development frameworks, bridging theoretical quantum principles with practical nanoscale computing applications. Recent publications (2024-2025) reveal dominant trends in quantum circuit optimization, reversible logic design for ternary/qutrit systems, and quantum software tool development. Key contributions include efficient quantum hardware components (comparators, multiplexers, flip-flops) using quantum-dot cellular automata, alongside advancements in quantum communication protocols and algorithm simulation tools. Professor Haghparast has supervised over 10 PhD and 150 MSc theses. He leads the SeQuSoS project (Securing the Quantum Software Stack) and DEQSE (Developer Experience in Iterative Quantum Software Engineering), addressing quantum software security and programming usability challenges. He co-leads the Empirical Software Engineering Research group and heads the Quantum Information and Computation Team, which actively explores quantum computational boundaries through projects like SeQuSoS and DEQSE.