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Alexandru NicolauView profile

Professor

• Parallelizing compilers
• Supercomputing
• High Performance Computing (HPC)
• +5 more

Alexandru Nicolau is a Distinguished Professor and Chair of the Department of Computer Science at the University of California, Irvine (USA), where he has worked since 1992. He previously held positions as Associate Professor (1988–1992) and Assistant Professor (1984–1988) at UC Irvine and Cornell University, respectively. Education : B.A., Brandeis University (1980) MS (1981), Ph.D. (1984), Yale University Research Interests : A leading expert in parallelizing compilers , high-performance computing , and software-hardware co-design , Nicolau pioneered foundational techniques like Percolation Scheduling and Optimal Loop Parallelization . His work enables efficient exploitation of instruction-level parallelism in general-purpose programs, with applications in embedded systems , matrix algorithms , and GPU-based neural networks . He has also contributed to Electronic Design Automation (EDA) and lightweight synchronization protocols . Scientific Awards : IEEE Fellow (2014) ACM SIGPLAN Most Influential Paper (PLDI 20 years) EDAA/IEEE/ACM DATE Most Influential Paper (10 years) ACM ICS Most Influential Paper (25 years) 4 Best Paper awards (VLSI design 2003, ISHPC 2005, CASES 2008, IJCNN 2009) Advising & Grants : He has mentored notable scholars now at Stanford, McGill, and Google, and secured over $20M in funding from NSF , DARPA , and industry leaders like IBM and Intel . His professional service includes chairing ACM ICS’09 and PPOPP’13, and serving on steering committees for LCPC and ICS. Labs & Collaborations : His techniques have been adopted by IBM Watson, Siemens Munich, Fujitsu Labs Japan, and the open-source GCC compiler.

• Materials Science
• Mechanical Engineering
• Computational Modeling
• +3 more

Dr. Simone Falco is a Research Fellow at the Department of Engineering Science, University of Oxford, and a Lecturer at Oriel College. He holds a DPhil (Oxon) in Engineering Science. His research focuses on numerical modeling of polycrystalline materials, micromechanical behavior of ceramics, and multi-scale approaches. He has contributed to projects involving high-rate testing, explosive materials simulation, and flash sintering techniques. His work bridges computational methods with experimental validation, emphasizing practical applications in materials engineering. Education: Bachelor’s and Master’s in Aerospace Engineering, University of Naples Federico II (2006, 2009) PhD in Engineering Science, University of Oxford (2015) Research Interests: Generation of numerical models for real polycrystalline microstructures Numerical simulation of brittle material failure Multi-scale homogenization techniques High-rate material testing Modeling of material manufacturing processes Key Awards: Ross Coffin Purdy Award, American Ceramic Society (2019) JCS 2018 Award, Journal of the Ceramic Society of Japan (2019) Excellence Award, University of Oxford (2019) Lab/Team Affiliations: Impact Engineering and Materials Engineering groups at the University of Oxford.

Luke Zoltan KelleyView profile

Adjunct Assistant Professor

• Multi-messenger Astrophysics
• Gravitational Waves
• Massive Black Hole Binaries
• +5 more

Luke Zoltan Kelley is an Adjunct Assistant Professor of Astronomy at the University of California, Berkeley . He holds a PhD from Harvard University (2018) and previously served as a Lindheimer Prize Postdoctoral Fellow (Northwestern University) and Cottrell Fellow (CIERA). His research focuses on theoretical astrophysics at the intersection of gravitational waves and cosmological environments, particularly using pulsar timing arrays (PTAs) to study massive black hole binaries (MBHBs). He chairs the Astrophysics Working Group in the NANOGrav Pulsar Timing Array collaboration. Research Interests: Multi-messenger astrophysics, low-frequency gravitational waves from MBHBs, stellar tidal disruption events, active galactic nuclei dynamics, and LISA mission science. He also develops software tools like kalepy and holodeck for analyzing gravitational wave signals and simulating MBHB populations. Key Achievements: Lead author on 13 papers including breakthroughs in Pulsar Timing Array analysis Advises 15 student-led studies on MBHB dynamics and gravitational wave detection Recipient of prestigious postdoctoral fellowships (Cottrell, Lindheimer) Publications: Over 87 papers with 8,926 total citations. Recent work includes detecting gravitational wave signals in NANOGrav data and modeling MBHB evolution in cosmological simulations. Labs/Teams: Leads the NANOGrav Astrophysics Working Group and collaborates with teams at NASA, CERN, and international observatories.

Sebastian SardinaView profile

Professor

• Artificial Intelligence
• Automated Planning
• Knowledge Representation
• +4 more

Professor Sebastian Sardina is a Professor in Artificial Intelligence at RMIT University's School of Computing Technologies. He holds a Bachelor's from South National University (Argentina) and a PhD from the University of Toronto (Canada). His research focuses on AI for dynamic systems, including automated planning, knowledge representation, and agent-oriented programming. He has contributed to enhancing agent programming languages with learning capabilities and advanced AI planning techniques. His work frequently appears in top AI venues like IJCAI and AAAI, with notable best paper nominations. Teaching interests include foundational CS courses such as Theory of Computation and Intro to AI. He actively promotes computational thinking through workshops for youth and educators, including roles in Victorian curriculum development (VCE Algorithmics). Supervision projects span hand gesture recognition, autonomous vehicle safety, and goal recognition in path-planning. His research has been presented globally and applied across domains like aviation safety, manufacturing systems, and healthcare. Recent trends in his publications emphasize goal recognition techniques (e.g., process mining applications), agent behavior modeling, and interdisciplinary AI applications in healthcare and automotive engineering. He has collaborated with industry and academic partners internationally, contributing to both theoretical advancements and practical AI solutions. Scientific Recognition: Multiple best paper nominations in AI conferences. Community Engagement: MAV conference presenter, VCAA Algorithmics curriculum panel member (2023). Supervision: Active mentor for 4+ research projects in AI planning and recognition.

• Biomedical Engineering
• Machine Learning
• Medical Imaging
• +3 more

Dr. Quoc Cuong Ngo is a Research Fellow in the School of Engineering at RMIT University, specializing in biomedical engineering and machine learning applications in healthcare. His research focuses on neurological disorders, particularly Parkinson’s disease, using advanced techniques such as facial expression analysis, speech assessment, and EEG signal processing. He also investigates medical imaging for conditions like leg ulcers and sleep apnea, contributing to automated diagnostic tools and healthcare technology innovations. Active in supervision, he mentors students on projects involving AI-based clinical symptom analysis and biometric authentication. His work bridges computer science and medicine, emphasizing interdisciplinary collaboration. Notable projects include developing NeuroDiag software for handwriting-based Parkinson’s diagnosis and pioneering chatbot-driven vocal screening systems. Despite no explicitly listed awards, his extensive publication record highlights contributions to medical diagnostics and biomedical engineering.

Wang ShirenView profile

Professor

• Additive Manufacturing
• Bio/nano-manufacturing
• Brain-inspired Artificial Intelligence
• +6 more

Professor Wang Shiren is a faculty member in the Department of Industrial & Systems Engineering at Texas A&M University, holding the Jill & Charles F. Milstead '60 Faculty Fellowship. He is affiliated with Biomedical Engineering and Materials Science & Engineering. His research focuses on additive manufacturing, bio/nano-manufacturing, brain-inspired AI, and decarbonization. He leads the Manufacturing Intelligence and Nanotechnology Innovation (MINI) Lab, emphasizing sustainable manufacturing and commercialization. Education: Ph.D. in Industrial & Manufacturing Engineering from Florida State University (2006) Research interests span advanced materials, energy-efficient manufacturing, and AI integration. Recent work includes low-carbon ceramics, thermoelectric materials, and nanozyme-based therapies. Over 100 peer-reviewed publications demonstrate expertise in additive manufacturing, nanocomposites, and energy harvesting. Awards include NSF CAREER Award (2010-15) and multiple faculty fellowships. Awards: NSF CAREER Award, AFOSR Fellowship, Texas A&M TEES Fellowship, and 3M Non-tenured Award. Grants and collaborations focus on AI-driven manufacturing, eco-friendly processes, and medical device innovation. The MINI Lab develops smart materials and sustainable solutions for industrial and biomedical applications. Labs/Teams: MINI Lab at Texas A&M, specializing in nanotechnology and manufacturing intelligence.

• Cyber-Physical Systems
• Autonomous Systems
• Formal Methods
• +4 more

Josefine B. Graebener is a Postdoctoral Scholar Research Associate in the Department of Computing & Mathematical Sciences at the California Institute of Technology (Caltech). Her research focuses on formal methods for test and evaluation of autonomous systems, including cyber-physical systems and reactive systems. She holds an office at the Annenberg IST Center (Mail Code 305-16) and can be reached at jgraeben@caltech.edu . Her work emphasizes assume-guarantee contracts for compositional system analysis, automated test synthesis, and failure-tolerant design for applications like autonomous vehicles and spacecraft computers. Key contributions include the development of the Pacti framework for scalable system analysis and the study of thermal stabilization in space telescopes using phase change materials. Josefine’s publications span topics such as reach-avoid specifications for autonomous systems, trade-off analysis in spacecraft computer design, and directive-response architectures for automated systems. While no formal awards are listed, her research demonstrates significant contributions to system reliability and formal verification methodologies.

• Theoretical Computer Science
• Logic in Computer Science
• Programming Languages
• +5 more

Dr. Cécilia Pradic is a Lecturer in Computer Science at Swansea University's School of Mathematics and Computer Science. Her research focuses on theoretical computer science, logic, and automata theory with applications in programming languages and database systems. She is affiliated with the Computational Foundry at Bay Campus and holds an ORCID identifier (https://orcid.org/0000-0002-1600-8846). Her recent work emphasizes nested relational query synthesis, implicit automata in λ-calculi, and Weihrauch reducibility for computational problems. She teaches modules including Declarative Programming (CS-205), Software Concepts and Efficiency (CSCM12), and Problem Solving & Software Efficiency (CSCM712), using Java and Python as primary tools. Pradic's publications span topics like proof theory applications to database systems, formal methods for string transformations, and computational complexity analysis. She has supervised multiple graduate research students, including a current PhD candidate and an MRes graduate (2024). Her research bridges foundational theory with practical algorithm design, contributing to advancements in both academic and applied computing domains.

• Medical Imaging
• MRI Reconstruction
• Real-Time MRI
• +4 more

Martin Uecker is a Professor at the Institute of Biomedical Imaging at TU Graz. His research focuses on advanced MRI reconstruction techniques, real-time imaging, and open-source software tools like the Berkeley Advanced Reconstruction Toolbox (BART). He specializes in developing methods for fast and accurate medical imaging, including applications in cardiac MRI, fetal brain imaging, and disease monitoring. His work emphasizes reproducibility, quantitative imaging, and clinical translation. Key research areas include generative models for MRI reconstruction, model-based inversion of the Bloch equations, and interactive real-time MRI systems. His team collaborates on projects involving hardware-software integration, such as portable MRI scanners and MRI-guided interventions. Notable contributions include advancements in multi-echo radial FLASH techniques, motion-resolved T1 mapping, and Bayesian uncertainty estimation in imaging. Uecker’s publications highlight innovations in accelerating MRI acquisition and reconstruction, with applications in pulmonary function assessment, neonatal imaging, and cardiovascular diagnostics. His work bridges theoretical physics, computational methods, and clinical practice, fostering open-source frameworks to democratize access to cutting-edge imaging tools.

Grégory BattView profile

Researcher

• Systems biology
• Synthetic biology
• Quantitative modeling
• +15 more

Grégory Batt is a Researcher and Head of the InBio joint research group at the Institut Pasteur and Inria Paris. The lab operates at the intersection of wet and dry biology, focusing on systems and synthetic biology with an emphasis on automation, modeling, and real-time control of cellular processes. The team is affiliated with both institutions and hosts a multidisciplinary group of researchers, engineers, and students. The research interests of Grégory Batt span systems biology, synthetic biology, quantitative modeling, lab automation, bioproduction, and single-cell analysis . His work integrates computational and experimental approaches to develop frameworks for understanding and controlling cellular behavior. Key methodologies include the use of synthetic biology, microfluidics, optogenetics, and robotics. The lab has developed innovative software tools such as ReacSight and MicroMator to enable automated and reactive experimentation. Recent publications highlight trends in real-time control of bioproduction, optimization of protein secretion, parameter inference in stochastic models, and ecological frameworks for antibiotic resistance . These works demonstrate a strong focus on integrating modeling with high-throughput experimentation to solve problems in biotechnology and medicine. Scientific contributions include: Development of ReacSight for bioreactor automation and reactive control Creation of MicroMator for reactive microscopy Application of ecological concepts to bacterial antibiotic responses Modeling stochastic kinetics coupled with auxiliary processes Batt advises several PhD students and postdoctoral researchers, including Henri Galez, Alicia Da Silva, Cecilia Capela, and Viktoriia Gross. His lab has received support from ANR, Inria, and other funding bodies. The InBio team operates a state-of-the-art laboratory equipped with bioreactors, liquid handling robots, flow cytometers, automated microscopes, and high-performance computing resources, enabling advanced research at both population and single-cell levels. The lab, located at the Yersin and Lwoff buildings of the Institut Pasteur in Paris, fosters a collaborative environment integrating molecular biology, microbiology, and computational modeling to advance quantitative understanding of cellular systems.

Woosuk LeeView profile

Researcher

• Program Analysis
• Program Synthesis
• Computer Science
• +1 more

Woosuk Lee is a researcher at Hanyang University in South Korea, specializing in Program Analysis and Program Synthesis . He has been actively involved in academic activities since 2015, contributing to major conferences like OOPSLA, PLDI, POPL, and ESEC/FSE. Current affiliation: Hanyang University Research interests: Program Analysis, Program Synthesis His research focuses on automating program generation through inductive methods and abstract interpretation. Key contributions include: Advancing iterative forward-backward abstract interpretation for program synthesis (2023) Structurally recursive functional program synthesis (2023) Homomorphic encryption circuit optimization via term rewriting (2020) Data-driven feedback systems for programming education (2021) He has served on program committees for PLDI (2024), POPL (2022), and SPLASH (2025), while also chairing workshops at PLDI 2026. His work bridges theoretical computer science with practical software engineering applications.

Ruhul AminView profile

Assistant Professor

• Artificial Intelligence
• Bioinformatics
• Data Science
• +5 more

Ruhul Amin is an Assistant Professor at Fordham University's Department of Computer and Information Science, where he explores the intersection of Artificial Intelligence , Data Science , and Public Health . His work spans multiple domains including Bioinformatics , Natural Language Processing , and Computational Social Science . PhD in Computer Science (Stony Brook University, 2019) MS in Computer Science (Stony Brook University, 2015) BSc in Computer Science (Shahjalal University, 2007) His research focuses on developing deep learning algorithms for genome annotation, anomaly detection in high-cardinality spaces, and assistive technologies for visually impaired users. Notably, he designed the Mongol Dip bilingual screen reading software and the Pipilika Bengali text search engine. Recent publications (2025-2024) demonstrate his expanding interests in large language model alignment , sentiment analysis across languages, and distributed reinforcement learning for cybersecurity applications. His work frequently appears at IEEE conferences and in journals like PLOS One. Scientific Recognition BASIS National ICT Award (Bangladesh) Best Poster Awards at IEEE R10 HTC and CEWIT conferences Bangladesh Prime Minister’s Award (2012) mBillionth South Asia Award (2010) He maintains active collaborations with research teams at University of Toronto , University of British Columbia , and Stony Brook University . Contact: moamin@cs.stonybrook.edu

• Software Engineering
• Cryptography & Blockchain
• Internet of Things
• +1 more

Dr Nguyen Tran is a Researcher at the School of Computer and Mathematical Sciences , part of the Faculty of Sciences, Engineering and Technology at the University of Adelaide . His work focuses on developing software systems that are correct, efficient, and secure, particularly through the application of blockchain and related technologies. Nguyen Tran's research spans four key domains: Software Engineering for large-scale systems, Cryptography & Blockchain for security, Internet of Things for physical-digital integration, Machine Intelligence for automation. He is eligible to co-supervise Masters and PhD students and contributes to the Centre for Research on Engineering Software Technology . His publications highlight advancements in blockchain metadata management, IoT search engines, and decentralized provenance systems.

• Game Development
• Serious Games
• Game Analytics
• +7 more

Henrik Engström is a Professor of Informatics at the University of Skövde, affiliated with the School of Informatics and Department of Information Technology. He holds a PhD in Computer Science from the University of Exeter. His research focuses on game development processes, serious games, and interdisciplinary collaboration in game design. Engström has led multiple projects, including the Game Tech Academy and Sweden Game Arena initiative, aiming to leverage game technology for societal challenges in health, education, and industry. He coordinates the Game Development Master's Programme and has published extensively on topics like game analytics, inclusive design, and mobile game publishing strategies. His work often bridges academia and industry, emphasizing practical applications in training simulations and healthcare. Education: PhD in Computer Science (University of Exeter) Key Projects: Sweden Game Arena, Game Hub Scandinavia, Digital Parental Support Tools Research Interests: Game design processes, serious games for health, inclusive game development, and mobile game business models Engström’s research outputs span over two decades, with notable contributions to understanding game development challenges, stress detection in games, and the application of AI in game narratives. His book Game Development Research (2020) synthesizes empirical insights from industry practices. He collaborates internationally, including with Japanese and Scandinavian institutions, to advance educational game models and industry-academia partnerships. His articles highlight trends in data-driven decision-making for indie game publishers, the psychological impact of game design on player experiences, and leveraging game jams for addressing heavy societal topics. Engström also leads grants focused on digital health tools for expecting parents and sustainable urban planning via game-based participation. Labs/Teams: Key contributor to the Sweden Game Conference and collaborator with Game Tech Academy, fostering innovation in game-based solutions for societal challenges.

Christian FibichView profile

Researcher

• Fault-Tolerant FPGA Design
• Reliability Analysis of SRAM-Based FPGAs
• High-Level Synthesis

Christian Fibich is a Researcher and Lecturer at the Department of Electronic Engineering, University of Applied Sciences Technikum Wien, Austria. He leads the Research Group Embedded Systems, focusing on FPGA reliability and high-level synthesis. His roles include project management for R&D initiatives like VECS (2013-2018), INES (2018-2023), and the 2024 Drohnentechnik integration project. Fibich holds an MSc in Embedded Systems from Technikum Wien and has been active in the field since 2010. Research interests include fault-tolerant FPGA design, reliability analysis of SRAM-based FPGAs, and high-level synthesis optimization. His work emphasizes practical applications of open-source tools and automated design exploration. Recent projects explore temperature-dependent fault effects and drone integration in academic programs. Publications span FPGA reliability, fault injection methods, and embedded systems design, with a focus on open-source IP cores and hardware security. His contributions include Fiji (a fault injection tool) and HLShield (a reliability framework for HLS).