Herman Bruyninckx is a Part-Time Full Professor at Eindhoven University of Technology (TU/e) in the Mechanical Engineering department, specifically within the Control Systems Technology group and EAISI High Tech Systems initiative. He also serves as a professor (Hoogleraar) at KU Leuven in Belgium. Academic focus on robotics, control systems, and multi-agent coordination Active research in model predictive control , semantic mapping , and dynamic constraint algorithms Recent publications address industrial automation , agro-food robotics , and haptic technology Research Highlights : Developed hybrid decision-making frameworks for multi-agent navigation Innovated swing-free control methods for robotic pick-and-place operations Formulated constrained dynamics algorithms with LQR-Gauss principle integration Created ExoTen-Glove for haptic feedback in virtual environments Collaborative Projects : Coordinated with researchers like René van de Molengraft , Elena Torta , and Koen de Vos Contributed to NWO/TTW FlexCRAFT project for cognitive robotics in agro-food technology
Mirella Lapata is a Professor of Computer Science at the University of Edinburgh , affiliated with the School of Informatics and the EdinburghNLP group. Her research focuses on developing AI systems that reason, generalize, and handle long contexts, with specific interests in compositional generalization, cross-lingual transfer, and verifiable generation. She leads projects funded by UKRI and ERC , including the UKRI AI Centre for Doctoral Training in Responsible NLP and Turing AI Fellowship for human-like reasoning in models. Research Emphasis : Coarse-to-fine decoding in semantic parsing, parameter-efficient LLMs, collaborative writing frameworks, and multimodal summarization. Advising : Supervises current PhD students and has mentored 23 PhD graduates since 2007, including notable alumni like Li Dong and Siva Reddy. Labs & Teams : Co-leads the Generative AI Laboratory (GAIL) and contributes to the Edinburgh Laboratory for Integrated Artificial Intelligence (ELIAI). Her recent work addresses hallucinations in generative models, cross-lingual semantic parsing, and structured reasoning in text-to-SQL tasks. She has co-authored 15+ publications in 2024 alone, spanning journals like TACL , NeurIPS , and ACL .
Li-Yang Tan is an Assistant Professor of Computer Science at Stanford University , focusing on theoretical computer science. His research emphasizes computational complexity, machine learning theory, and algorithm design. Education: Ph.D. in Computer Science from Columbia University , advised by Rocco Servedio His work explores: Boolean function complexity Decision tree learning algorithms Circuit lower bounds Computational-statistical tradeoffs Query complexity Massively parallel algorithms Recent publications analyze computational-statistical tradeoffs via NP-hardness, improve decision tree learning techniques, and establish direct sum theorems for query complexity. His research often bridges complexity theory, learning theory, and algorithm design, with applications in pseudorandomness and correlation clustering. Awards: Best Paper Award at FOCS Best Paper Award at CCC Best Paper Award at SAT Sloan Fellowship Li-Yang collaborates with students and researchers including Guy Blanc, Caleb Koch, and Carmen Strassle. He has delivered invited special issue papers at FOCS, CCC, and SAT conferences.
Jacqui Webster is a Professor of Public Health at the University of Technology Sydney (UTS), leading the WHO Collaborating Centre on Nursing, Midwifery and Health Development. She serves as the Secretariat for the South Pacific Chief Nursing and Midwifery Officers Alliance (SPCNMOA) and continues collaborating with The George Institute for Global Health on salt reduction research. Key Grants: NHMRC Investigator Grant (Leadership 2), NHMRC IDEAS Grant, Global Alliance for Chronic Diseases grants Collaborations: Fiji National University, Deakin University, University of Sydney, UNSW, Northwestern University Her research focuses on reducing cardio-metabolic diseases through food/water security programs and salt reduction policies. Recent articles analyze potassium-enriched salt adoption barriers, global water sodium standards, ultra-processed food impacts in Fiji, and pandemic-related dietary shifts in Australia. She authored the public health-themed book Two Bugs on Bikes (Hembury Books 2025) based on her cycling journey across Europe and Africa. At UTS, she mentors early-career researchers and supports strategic operations for the WHO Collaborating Centre.
Bruce Jacob is a Keystone Professor and Full Professor in the Department of Electrical & Computer Engineering at the University of Maryland College Park's College of Engineering. His research primarily focuses on memory systems design and exascale computing architectures, with significant contributions to DRAM simulation and high-performance computing systems. Dr. Jacob received his A.B. in Mathematics from Harvard University (1988), followed by his M.S. and Ph.D. in Computer Science & Engineering from the University of Michigan (1995 and 1997 respectively). His research interests include memory systems design, exascale computing architectures, embedded systems, circuit integrity, and algorithmic composition. His recent publications demonstrate a strong focus on next-generation memory technologies, particularly ReRAM and advanced DRAM architectures. His work bridges the gap between theoretical modeling and practical implementation, with significant contributions to memory system simulation through projects like DRAMsim. His research shows a consistent trajectory toward solving the memory bottleneck problem in high-performance computing systems. Named Fellow, IEEE (2021) Multiple University of Maryland Research Leader awards (2006, 2010, 2012, 2016, 2017) Clark School of Engineering Keystone Professor (2006) National Science Foundation CAREER Award (2000) University of Maryland Award for Teaching Excellence (2004) Dr. Jacob has led significant research initiatives including the University of Maryland Exascale Systems Research and Memory-Systems Research groups. He has developed important computational artifacts such as DRAMsim (a public-domain DRAM-system simulator) and BioBench (a set of bioinformatics workloads). His work has influenced both academic research and industry practices in memory system design.
Chuchu Fan is the Leonardo Career Development Professor and Director of the REALM Lab (REliable Autonomous system Lab) at MIT's School of Engineering , with a primary appointment in the Department of Aeronautics and Astronautics and Laboratory for Information and Decision Systems . Her work bridges formal methods , control theory , and machine learning to ensure safety in autonomous systems. Ph.D., University of Illinois at Urbana-Champaign (2019) B.E., Tsinghua University (2013) Her research focuses on rigorous safety verification of autonomous systems through neural Lyapunov-barrier functions , control contraction metrics , and formal logic specifications . Recent work emphasizes LLM integration for symbolic planning, multi-robot collaboration , and robustness against model uncertainties . The 15 most recent articles highlight trends in safety-critical control using graph neural networks , reinforcement learning , and temporal logic . Key themes include collision avoidance , multi-agent coordination , and runtime safety filters applied to drones, self-driving cars, and microgrids. Scientific Awards & Honors : 2025 ONR YIP Award 2023 NSF CAREER & AFOSR YIP Awards 2020 ACM Doctoral Dissertation Award 2016 Rising Stars in EECS As head of the REALM Lab, she leads projects on autonomous air taxis , safety verification , and neural certificates for robotic systems. Her teaching includes courses on feedback control and formal methods for autonomous systems.
Brandon Schmandt is a Professor in the Department of Earth, Environmental and Planetary Sciences at Rice University, where he leads research using seismology to investigate Earth systems. His work integrates interdisciplinary approaches, data science, and numerical modeling to study tectonic processes, magmatic systems, and environmental interactions. His educational background includes a PhD in Geological Sciences from the University of Oregon (2011) and a BA in Environmental Studies from Warren Wilson College (2006). Dr. Schmandt's research focuses on seismology, tectonics, volcanology, and surface processes , with emphasis on seismic imaging of subsurface structures. His group employs innovative time-series analysis and field projects to resolve geologic history and contemporary Earth dynamics, particularly examining fault zones, magmatic reservoirs, and deep convective processes. Key methodologies include dense seismic arrays and machine learning applications. Analysis of his recent publications (2023-2025) reveals dominant trends in seismic event discrimination (earthquakes vs. explosions), magmatic system imaging (Yellowstone, Cascades), and global mantle structure studies. There is strong emphasis on induced seismicity, machine learning applications, and high-resolution imaging of Earth's discontinuities using dense arrays. His distinguished honors include: Aki Award of the AGU Seismology Section GSA Donath Medal AGU Macelwane Medal Body Dr. Schmandt directs an active research group conducting field projects across diverse settings including the Raton Basin, Yellowstone, Antarctica, and the Caribbean. While specific student advisees and grant details aren't provided in available materials, his group's work involves collaborative data collection, advanced computational modeling, and development of novel seismic analysis techniques applicable to both natural and anthropogenic seismic sources. The research program maintains focus on magmatic systems beneath volcanic regions, induced seismicity mechanisms, and global mantle structure using dense node arrays and interdisciplinary approaches to address fundamental questions in Earth dynamics.
Andreas Lööw is a Lecturer at Royal Holloway, University of London , focusing on hardware and software verification. Previously, he was a postdoctoral researcher at Imperial College London under Philippa Gardner , contributing to the Gillian Platform . He completed his PhD at Chalmers University of Technology under Magnus Myreen , specializing in interactive theorem proving and hardware verification. His research explores symbolic execution, separation logic, and formal verification of hardware/software systems. Key projects include Betterlog (Verilog semantics reformulation) and foundational work on the Gillian Platform . 2025 : Compositional Symbolic Execution for Memory Models 2025 : Simulation Semantics of Synthesisable Verilog 2024 : Compositional Symbolic Execution for Correctness/Incorrectness 2023 : Exact Separation Logic (Distinguished Paper at ECOOP'24) 2023 : Hardware Verification of Pipelined Processors 2022 : Verilog Concurrency Analysis 2021 : Verified Verilog Compiler (Lutsig) Scientific Awards : Distinguished Paper at ECOOP 2024 He maintains the vv Verilog visualization tool and collaborates on the Gillian Platform . Contact: andreas.loow@rhul.ac.uk
Fabrício Benevenuto is an Associate Professor in the Computer Science Department at Federal University of Minas Gerais (UFMG), where he conducts interdisciplinary research at the intersection of social media analysis, data science, and computational journalism. His work spans complex networks, machine learning, and natural language processing with strong societal impact. His research focuses on social media dynamics, particularly in Brazilian contexts, with major contributions to hate speech detection, fake news analysis, and political discourse monitoring. He leads large-scale projects against misinformation, including development of systems like WhatsApp Monitor, Media Bias Monitor, and Purple Feed. His work combines technical innovation with real-world applications for election transparency and public discourse integrity. Benevenuto's recent publications demonstrate strong trends in multilingual NLP for social media analysis, with emphasis on Brazilian Portuguese contexts. His team produces both theoretical contributions and practical systems addressing hate speech, misinformation, and media bias. Notable methodological approaches include combining network analysis with linguistic features, developing culturally-aware detection systems, and creating large annotated datasets for understudied languages. CAPES award for best Brazilian computer science thesis (2010) Humboldt Foundation scholarship recipient (2017-2018) Member of TikTok Safety Advisory Council WWW'20 Best Paper Nominee & CNIL-INRIA Privacy Protection Prize winner Multiple best paper awards at CEAS, WBC, and ICWSM conferences Test-of-Time Award at ICWSM'20 Benevenuto actively mentors PhD and MSc students, with numerous advisees securing academic positions at Brazilian universities and research roles at institutions like Max Planck Institute. His projects often receive funding supporting interdisciplinary collaborations across computer science and social sciences. Current work includes large-scale analysis of Telegram political groups, real-time election monitoring systems, and developing culturally-aware NLP tools for Portuguese. He leads research teams working on social media analysis systems with societal impact, particularly focused on Brazilian digital ecosystems. Projects involve cross-institutional collaborations with researchers from MPI-SWS, Max Planck Institute, and various Brazilian universities, emphasizing practical applications for public discourse integrity.
José Luiz Fiadeiro is a Professor at Royal Holloway, University of London , affiliated with the Centre for Distributed and Global Computing. He previously held positions at the University of Leicester (including Head of Department), University of Lisbon, and Technical University of Lisbon. He has conducted visiting research at Imperial College London, King’s College London, PUC-Rio, University of Pisa, SRI International, UPC Barcelona, and NASA Ames. Research Interests: Formal aspects of software system modeling and analysis in global ubiquitous computing, with emphasis on distributed systems, formal verification methods, and service-oriented architectures. His work integrates theoretical computer science with practical software engineering challenges. Editorial & Leadership: Associate Editor: SN Computer Science Board Member: Information Processing Letters, EPTCS Steering Committee: CALCO (co-founder), ETAPS, FASE, WADT, WS-FM Scientific Board: INESC-TEC (Portugal) Awards & Honors: Elected Member, Academia Europaea Fellow, British Computer Society Grants & Projects: Leverhulme Trust Visiting Professorship (2018) Semantic Completions: Unifying Wave/Particle Information Views (AFOSR, 2016) Modeling and Analysis of Dynamic Interaction Networks (Royal Society, 2013–2015) Verification of Service-Oriented Systems (EPSRC, 2012) Professional Service: Extensive panel membership for research assessment in Portugal, Romania, Belgium (AEQES), France (AERES), and Lithuania (SKVC).
Sara Magliacane is an Assistant Professor at the University of Amsterdam , affiliated with the Amsterdam Machine Learning Lab (AMLab) and the Informatics Institute . She also holds a Research Scientist position at the MIT-IBM Watson AI Lab and has been an ELLIS Scholar since 2022. Education PhD in Artificial Intelligence (2017), VU Amsterdam MSc in Computer Engineering (2011), Politecnico di Milano BSc in Computer Engineering (2008), Università degli Studi di Trieste Research Focus : At the intersection of Causality and Machine Learning , her work addresses Causal Representation Learning from high-dimensional data (images, sequences) Causal Discovery in latent confounder scenarios Causality-inspired Reinforcement Learning for robustness and adaptability Neurosymbolic AI for theoretical guarantees Publication Trends : Her recent work explores Factored adaptation in non-stationary environments (NeurIPS 2022) Temporal causal identifiability (ICML 2022) Binary interaction-based causal discovery (UAI 2023) Safe exploration in visual RL (HSCC 2021) Structure learning lower bounds (NeurIPS 2020) Scientific Recognition : ELLIS Scholar (2022–present) Spotlight presentations at ICML 2022 and ICLR 2022 Advising & Collaborations : Currently supervising 6 PhD students at the University of Amsterdam and AUMC, with 12 alumni advisees. Collaborates with researchers at MIT-IBM Watson AI Lab, Simons Institute, and TUM.
Mark Batty is a Professor in the School of Computing at the University of Kent, specializing in formal methods for concurrent systems. His work bridges hardware-software interfaces, focusing on memory models for C/C++, OpenCL, and architectures including x86, ARM, POWER, and GPUs. As a member of the Programming Languages and Systems Research Group, he develops mathematical specifications and verification tools for real-world concurrency challenges. His research centers on empirical testing of hardware/compiler behavior, formal modeling of system components, and verification of fine-grained concurrent algorithms. Key contributions address relaxed memory semantics, transactional memory, and compositional reasoning for concurrent data structures. His work combines theoretical rigor with practical tool development to ensure correctness in complex concurrent environments. Analysis of his 2015-2025 publications reveals consistent focus on memory consistency models, formal verification of weak memory concurrency, and compiler optimizations. Dominant themes include C/C++11 standards, GPU concurrency semantics, and mechanized verification techniques. His research demonstrates strong industry relevance through collaborations with hardware vendors and contributions to language standards. Mark Batty has received significant recognition: John C. Reynolds Doctoral Dissertation Award (2015) from ACM SIGPLAN CPHC and BCS Distinguished Dissertation Award (2015) Lloyds Register Foundation and Royal Academy of Engineering Research Fellowship (2016) He actively leads major research initiatives and mentors next-generation researchers: Current Funding: EPSRC Standard Grant 'Verifiably Correct transactional memory' (2018), VeTTS Grant 'Specification and verification of C++ data structure libraries' (2018), EPSRC First Grant 'Compositional, dependency-aware C++ concurrency' (2018) PhD Recruitment: Actively seeking candidates for UKRI-funded studentship in Verified Trustworthy Software Systems Batty drives community engagement through Kent Concurrency Workshop (2016) and South of England Programming Language Seminars, fostering national collaboration in programming languages research. His leadership in organizing Royal Society discussions underscores his influence in trustworthy systems verification.
James C. Davis is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. He leads the Duality Lab, which focuses on the engineering of software-intensive computing systems with particular interest in how these systems fail and how those failures can be mitigated. His research takes a socio-technical approach, considering both human and technical perspectives in system engineering. Dr. Davis received his PhD in Computer Science from Virginia Tech, where he was advised by Dongyoon Lee. His research interests span empirical software engineering, security, safety, testing, and web technologies, with a strong emphasis on practical impact and measurement. He applies a socio-technical philosophy to his work, believing high-quality systems must be engineered considering both human and technical perspectives. His recent research focuses on software supply chain security, regular expression vulnerabilities (particularly ReDoS), pre-trained model security, and failure analysis in software systems. His work often involves empirical studies of real-world software systems and security practices, with a strong emphasis on practical impact and measurable results. Dr. Davis has received significant funding from the National Science Foundation, Google, Cisco, and Rolls Royce for his research. His publications appear in top-tier venues including ICSE, FSE, ASE, and USENIX Security. He has served on program committees for many major software engineering and security conferences. Among his notable achievements are being elevated to IEEE Senior Member in 2022, receiving the Ruth and Joel Spira Outstanding Teacher Award from ECE@Purdue in 2022, and multiple Best Paper and Best Poster awards. He has successfully mentored numerous PhD and Master's students, with several completing their theses on topics related to software security and engineering. Dr. Davis actively recruits graduate and undergraduate research assistants for his Duality Lab, which has produced influential work on software failure analysis, regular expression security, and machine learning supply chain security. His lab is supported by multiple federal and industry grants focused on improving the security and reliability of software systems.
Maneesh Agrawala is the Forest Baskett Professor of Computer Science and Director of the Brown Institute for Media Innovation at Stanford University. He is also a consulting AI Scientist at Roblox. His research lies at the intersection of computer graphics, human-computer interaction (HCI), and visualization, with a focus on cognitive design principles for improving audio/visual media. He leads a vibrant research group and has advised numerous PhD students and postdocs. His research interests include: Computer Graphics Human-Computer Interaction Visualization and Visual Communication Cognitive Design Principles Generative AI and Diffusion Models Interactive Video and Sketch-based Interfaces Data and Information Visualization His recent publications (2023–2025) reflect a strong trend toward leveraging generative models—particularly diffusion models—for video and image synthesis, editing, and personalization. Key themes include controllable generation (e.g., SparseCtrl, ControlNet), sketch-to-image translation, relightable texturing, and tools that enhance visual storytelling and data communication. His work integrates cognitive science with computational tools to build systems that support human creativity and understanding. His scientific honors include: MacArthur Foundation Fellowship (2009) Alfred P. Sloan Foundation Fellowship (2007) NSF CAREER Award (2007) SIGGRAPH Significant New Researcher Award (2008) Allen Distinguished Investigator Award (2014) Induction into the SIGCHI Academy (2021) ACM Fellow (2022) Okawa Foundation Research Grant (2006) A dedicated mentor, Agrawala has advised a large cohort of students and postdocs, many of whom have gone on to influential positions in academia and industry. His lab develops tools for video editing (e.g., AnimateDiff, ControlNet), sketch-based design, and visualization (e.g., EmphasisChecker), often bridging theory with practical applications in media and education. He continues to be a leading figure in visual computing and interactive systems.
Professor L.J. Sluys is a Full Professor and Chair of Computational Mechanics at the Faculty of Civil Engineering and Geosciences, Delft University of Technology (TU Delft). He has been a leading figure in computational mechanics since 1999, heading the Computational Mechanics group and serving as head of the Department of Materials, Mechanics, Management and Design (3MD) from 2018 to 2024. His research is centered on the computational modeling of material behavior, particularly focusing on failure processes and high-performance materials. His research interests include computational mechanics of materials, modeling of failure and fracture processes, multi-scale methods, and the computational modeling of high-performance materials such as composites and concrete. He employs advanced numerical techniques including the finite element method, extended finite element method (XFEM), level-set methods, and cohesive zone modeling to simulate complex mechanical behaviors under static and dynamic loading conditions. His work spans civil, mechanical, and materials engineering domains, with applications in infrastructure, energy, and sustainable materials. The recent publications highlight a strong trend in modeling fracture, fatigue, and degradation in heterogeneous materials such as composites, concrete, and geological formations. His work integrates multi-physics and multi-scale approaches, often coupling mechanical, thermal, and chemical effects. There is a consistent focus on numerical robustness, model validation, and the development of adaptive computational frameworks for simulating progressive damage and failure. Research Fellow of the Netherlands Academy of Arts and Sciences (KNAW) Professor Sluys has taught core courses such as Introduction to the Finite Element Method and Computational Methods in Non-linear Solid Mechanics for over a decade, indicating a strong commitment to academic education. He has supervised numerous students, though specific names are not listed in the provided texts. He leads an active research group in computational mechanics, contributing to both fundamental and applied research in solid mechanics. His work involves collaboration with international institutions and industry partners, particularly in the areas of infrastructure durability and advanced materials.
