جست‌وجوی استاد و پژوهشگر

Ken Satohمشاهده پروفایل

استاد

• Artificial Intelligence (AI) and Law
• Logical Foundations of AI
• Juris-Informatics
• +۶ مورد دیگر

Ken Satoh is a full Professor at the National Institute of Informatics (NII) and Sokendai (The Graduate University of Advanced Studies), Japan. He leads the Center for Juris-Informatics within the Joint Support-Center for Data Science Research (ROIS-DS). Previously, he worked at Fujitsu (1981-1995) and was an Associate Professor at Hokkaido University until 2001. He holds a law degree from the University of Tokyo (2006-2009) and passed the Japanese bar exam in 2017. Roles: Director of Center for Juris-Informatics, Principal Investigator in multiple AI/Law projects Research Focus: Juris-informatics (merging informatics and law), logical foundations of AI, legal debugging, and compliance mechanisms for AI systems His work bridges AI and legal systems, including developing the PROLEG framework for legal reasoning and organizing international workshops like JURISIN. Key contributions include applying logical inference to detect legal conflicts in algorithmic governance systems and advancing AI ethics through compliance checks with regulations like GDPR. He has authored over 130 publications, including works on legal norm reasoning, multi-agent systems, and formal methods in law. His research group collaborates globally, hosting competitions like COLIEE to advance legal AI technologies.

Silvia Mikschمشاهده پروفایل

استاد

• Visual Analytics
• Information Visualization
• Interaction Design
• +۶ مورد دیگر

Silvia Miksch is a Full University Professor of Visual Analytics at TU Wien's Faculty of Informatics, leading the CVAST Center. She holds a PhD from the University of Vienna and has held roles including Head of the Department of Information and Knowledge Engineering at Danube University Krems. Her research focuses on Visual Analytics, Information Visualization, Temporal Data Analysis, and Medical Informatics. She has supervised numerous PhD and Master’s students, with notable advisees including Ignacio Baltazar Pérez Messina and Davide Ceneda. Her work bridges theory and practice, addressing challenges in Visual Analytics for healthcare, business intelligence, and digital humanities. Awards include the IEEE VGTC Technical Achievement Award (2023) and induction into the IEEE Visualization Academy (2020). She actively contributes to conferences like IEEE VIS and EuroVis as program chair and steering committee member. Her projects, such as 'VisuExplore' and 'DisCo', have received recognition for advancing visualization in medical and cultural domains. Key research areas include guidance-enriched systems, network visualization, and temporal reasoning. She explores applications in fraud detection, cultural heritage analysis, and pandemic data visualization. Her lab's tools, like 'Hermes' and 'COVIs', exemplify task-driven design for real-world data challenges.

• Computational Optimization
• Global Optimization
• Mixed-Integer Nonlinear Programming
• +۹ مورد دیگر

Dr. Ruth Misener is a Professor in the Department of Computing at Imperial College London and holds the BASF/RAEng Research Chair in Data-Driven Optimization (2022-27). Her research focuses on computational optimization, including global optimization of mixed-integer nonlinear programs, optimization under uncertainty, and integration with machine learning. She leads the Computational Optimization Group, which develops open-source tools like GALINI, and collaborates with industry partners such as Royal Mail for logistics optimization. Her research interests span optimization challenges in engineering, bioprocess design, and healthcare, including bioreactor optimization and disease trajectory modeling for leukemia. She has been awarded the Royal Academy of Engineering Research Fellowship, supporting her work on hybrid computational/experimental platforms for biomedical applications. Recent projects include scheduling optimization under uncertainty, Bayesian methods for experimental design, and robust optimization for heat recovery networks. Her work emphasizes explainable optimization and safety-critical decision-making, with applications in energy systems, pharmaceuticals, and manufacturing. Ruth’s contributions include over 50 publications, with a focus on algorithm development and industrial impact. She actively participates in conferences and chairs workshops on optimization, such as the Mixed Integer Programming Workshop and the British-French-German Conference on Optimization.

Alberto L. Sangiovanni-Vincentelliمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Design Automation
• Embedded Systems
• +۷ مورد دیگر

Alberto L. Sangiovanni-Vincentelli holds the Edgar L. and Harold H. Buttner Chair of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He is a pioneer in Electronic Design Automation (EDA) and co-founder of Cadence and Synopsys. His research focuses on Cyber-Physical Systems (CPS), embedded systems, hybrid systems, and formal methods for AI. He has authored over 800 papers and 17 books, with major contributions to design automation and methodologies. Education: Dr. Ing., EECS, Politecnico di Milano (1971) Research interests include design methodologies, CPS, and AI integration. He has received numerous awards, including the IEEE James Clerk Maxwell Medal (2008) and ACM/IEEE A. Richard Newton Technical Impact Award (2009). He serves on multiple corporate boards and advisory councils, including the Strategic Committee of the Italian Strategic Fund and the Executive Committee of the Italian Institute of Technology. His work spans academia, industry, and policy, with a focus on innovation ecosystems and CPS design automation. Awards: Over 20 major honors, including Fellowships from IEEE and ACM.

• Automata Theory
• Formal Methods
• Tree Automata
• +۴ مورد دیگر

Christof Löding is an Adjunct Professor at the Department of Logic and Theory of Discrete Systems (Computer Science 7) at RWTH Aachen University. His research focuses on automata theory, formal verification, and logical foundations of computer science, with significant contributions to Büchi automata, tree automata, and stochastic games. Academic affiliation: RWTH Aachen University, Germany Research areas: Automata theory, Formal methods, Game theory, Logic in computer science Contact: loeding@informatik.rwth-aachen.de His recent work spans deterministic parity automata construction, finite-valued transducers, and algorithmic solutions for infinite games. Publications emphasize theoretical foundations and practical applications in program verification and XML processing. Articles analyze automata learning, uniformization problems, and lookahead degrees in infinite games, showing interconnections between automata theory and formal verification.

Nathanaël Fijalkowمشاهده پروفایل

پژوهشگر

• Games
• Machine Learning
• Automata Theory
• +۹ مورد دیگر

Nathanaël Fijalkow is a Researcher at CNRS in LaBRI (Bordeaux) and a Research Fellow at The Alan Turing Institute in London. His primary research fields include games , machine learning , automata theory , and dynamical systems , with a focus on synthesizing programs from logical specifications and probabilistic models. Research Interests span program synthesis (programming by example), controller synthesis (temporal logic specifications), games on graphs (parity/mean payoff games), probabilistic automata (bounded ambiguity), and invariants for linear dynamical systems. He bridges formal methods with machine learning through projects like DeepSynth . Scientific Contributions include: Undecidability results for probabilistic automata Advances in parity game algorithms (quasi-polynomial lower bounds) Foundations of probabilistic modal logics Efficient synthesis techniques using SMT solvers and distributional learning Supervision involves guiding postdocs and PhD students such as Guillaume Lagarde, Antonio Casares, and Pierre Ohlmann. He has secured grants like the Momentum DeepSynth project (2019-2021) , aiming to merge formal methods with ML for program synthesis.

Joshua Speagleمشاهده پروفایل

استادیار

• Astrostatistics
• Data Science
• Machine Learning
• +۷ مورد دیگر

Joshua Speagle is an Assistant Professor jointly appointed in the Department of Statistical Sciences and the David A. Dunlap Department of Astronomy & Astrophysics at the University of Toronto. He is also an Associate Member of the Dunlap Institute for Astronomy & Astrophysics and a Member of the Data Sciences Institute. His research lies at the intersection of statistics, astronomy, and computer science, focusing on astrostatistics and data-intensive astrophysics. His research interests include astrostatistics, data science, machine learning, statistical inference, and Bayesian methods. He develops novel statistical learning techniques to extract insights from large, complex datasets, particularly from astronomical surveys. His work emphasizes interpretability, robust inference, and computational efficiency, with applications to galaxy formation, stellar photometry, and 3D dust mapping. The trends in his recent publications reflect a strong focus on interdisciplinary methodologies, particularly in Bayesian inference, nested sampling, and machine learning applied to astrophysical problems. His work consistently bridges theoretical statistics with practical applications in astronomy, emphasizing open-source software and reproducible research. Banting Postdoctoral Fellowship Dunlap Fellowship Joshua Speagle is deeply committed to mentorship and collaboration. He co-leads the Astrostatistics Research Team (ART) with Gwen Eadie, mentoring students and postdocs across disciplines. He is involved in graduate and undergraduate research programs, including the Astronomy & Astrophysics Summer Undergraduate Research Program (SURP). He teaches courses in statistics and astronomy and serves on committees within the University of Toronto and professional societies such as the AAS, ASA-AIG, and SSC-DSA. He co-leads the interdisciplinary Astrostatistics Research Team (ART), which fosters a collaborative, inclusive environment focused on cutting-edge research at the intersection of statistics and AI. The team emphasizes open and accessible science, releasing open-source tools like dynesty and brutus , and mentoring the next generation of data scientists.

Giulio Tiozzoمشاهده پروفایل

دانشیار

• Dynamical Systems
• Ergodic Theory
• Complex Analysis
• +۵ مورد دیگر

Giulio Tiozzo is an Associate Professor in the Department of Mathematics at the University of Toronto, affiliated with both the St. George and Scarborough campuses. His research lies at the intersection of dynamical systems, ergodic theory, and geometry, with strong connections to complex analysis, probability, and group theory. Institution: University of Toronto School: Faculty of Arts and Science Department: Department of Mathematics Rank: Associate Professor Campus Offices: BA 6206 (St. George), IC 495 (Scarborough) Email: tiozzo@math.utoronto.ca His research focuses on dynamical systems and ergodic theory , particularly entropy in complex and real dynamics, random walks on groups, and thermodynamic formalism. He investigates the structure of the Mandelbrot set, core entropy of polynomials, and geometric group actions. His work combines deep theoretical insights with algorithmic and computational approaches, as seen in his exploration of Thurston’s master teapot and entropy algorithms. The 15 most recent publications reveal a sustained focus on entropy, fractal geometry, and probabilistic group actions. Themes include the continuity and computation of core entropy, thermodynamic formalism for expanding systems, boundary theory for random walks on hyperbolic groups, and metric properties of group actions. His work spans pure mathematics with links to computer science and statistical mechanics. Scientific Awards: 2018 Sloan Research Fellowship (Alfred P. Sloan Foundation) Research and Advising: Giulio Tiozzo leads an active research program supported by NSERC and the Sloan Foundation. He mentors graduate students and postdoctoral researchers, and contributes to academic life through seminars, public lectures, and participation in programs at the Fields Institute. He has delivered invited talks and lecture series internationally, including at ICTS-TIFR, ICERM, and Warwick. Labs and Teams: While not leading a formal lab, Tiozzo collaborates extensively with researchers in dynamical systems and geometry. He is involved in thematic programs at the Fields Institute, such as the 2024 program on Randomness and Geometry, and contributes to the academic community through organized seminars and collaborative research projects.

Andrea Maranzoniمشاهده پروفایل

دانشیار

• Hydraulics
• Numerical Modelling of Free Surface Flows
• Flood Hazard Assessment
• +۷ مورد دیگر

Andrea Maranzoni is an Associate Professor of Hydraulics at the Department of Engineering and Architecture, University of Parma, Italy, where he has been serving since February 2019. He previously held assistant professor positions at the University of Parma and the University of Brescia, and has been actively involved in teaching and research in hydraulic and environmental engineering. Education: Ph.D. in Civil Engineering (Hydraulic Engineering), University of Parma, 2004 Degree in Civil Engineering (cum laude), University of Parma, 2000 His research focuses on the numerical and physical modeling of unsteady free surface flows, flood hazard assessment due to dam-breaks and levee breaches, probabilistic flood mapping, shallow water equations, and finite volume methods. He also investigates hydrodynamic actions on structures, mixed flow modeling, and imaging techniques for water surface measurement. His work bridges theoretical hydraulics with practical flood risk mitigation strategies. The recent publications (2023–2024) reflect a strong trend in dam-break modeling, flood hazard quantification, and theoretical advances in fluid mechanics. Key themes include probabilistic risk assessment, extension of classical equations like Bernoulli’s under non-inertial frames, and experimental analysis of hydrophobic sphere impacts. These works demonstrate a consistent focus on improving flood prediction accuracy and safety through advanced numerical and experimental methods. Scientific Awards: None listed in the provided text. Maranzoni has advised one Ph.D. student, Susanna Dazzi, and has supervised approximately 30 Bachelor’s and Master’s theses. He has received research funding from MIUR’s FFABR program (€3,000) and is a participant in the RELAID project (€600,000 total, 2020–2022). He also serves as Vice Coordinator of the Ph.D. Programme in Civil Engineering and Architecture at the University of Parma. He is involved in the research community through editorial roles, notably as Guest Editor for a special issue in Water (MDPI) on dam-break modeling, and as a reviewer for leading journals such as Journal of Hydraulic Engineering (ASCE) and Advances in Water Resources . He is a member of the Italian Hydraulic Group (GII), the Faculty Board of the Ph.D. program, and the CIDEA Interdepartmental Center for Energy and the Environment.

Panagiotis Hadjidoukasمشاهده پروفایل

دانشیار

• Parallel Computing
• Distributed Systems
• High Performance Computing
• +۳ مورد دیگر

Panagiotis Hadjidoukas is an Associate Professor and Head of the Laboratory for Computing at the Computer Engineering and Informatics Department, University of Patras, within the School of Engineering. His work focuses on high-performance computing systems and parallel programming models. His research spans parallel and distributed computing , runtime support for parallel programming models , and automation of AI/ML workloads . Key contributions include developing the torc runtime system for task parallelism and pioneering work in extreme-scale scientific simulations. His interests bridge theoretical computer science with practical applications in scientific computing and AI acceleration. Notable achievements include the ACM Gordon Bell Prize Winner (2013) for 11 PFLOP/s cloud cavitation simulations and Finalist (2015) for in-silico lab-on-a-chip microfluidics. His software tools ( torc_lite , torcpy ) enable efficient parallelism across diverse architectures. Doctor of Philosophy (2003), University of Patras Master of Science (2001), University of Patras Diploma in Computer Engineering (1998), University of Patras As Head of the Laboratory for Computing, he leads infrastructure development while maintaining active research collaborations with IBM Research and ETH Zurich. His teaching portfolio includes graduate courses on high-performance computing for data sciences and parallel processing principles.

Guangya Yangمشاهده پروفایل

دانشیار

• Power System Stability
• Offshore Wind Energy
• Cyber-Physical Power Systems
• +۷ مورد دیگر

Guangya Yang is an Associate Professor at the Department of Wind and Energy Systems, Technical University of Denmark (DTU), with expertise in power system stability, control, and protection of low-inertia systems, particularly in offshore wind applications. He has worked full-time as an electrical design and simulation specialist at Ørsted (2020-2021) and maintains active roles in IEEE, IEC standardization, and editorial work as lead editor for IEEE Access PES. PhD in Electrical Engineering (University of Queensland, 2008) Senior Member of IEEE Former expert member of European Technology & Innovation Platform for solar PV His research focuses on electromagnetic transient simulation, cyber-physical energy systems, and grid compliance for wind power plants. He leads the Horizon 2020 InnoCyPES project (€12m+ grants), training 15 early-stage researchers in cyber-physical energy systems. Key contributions include validating synchronous condensers for low-inertia systems and developing industry training programs on offshore wind control strategies. Coordinated Hardware-in-the-Loop test bench standards (IEC61400-21-5) Advances in grid-forming converter stability and fault ride-through assessment Developed digital twins for power grid validation Scientific Recognition: World’s Top 2% Scientists (Elsevier/Stanford, 2024) Advising & Grants: Supervises 5 PhD students in projects related to machine learning, digital twins, and predictive maintenance. Coordinates €12m+ in research grants, including Horizon 2020’s InnoCyPES. Labs & Collaborations: Works with Ørsted, industry partners, and international universities on offshore wind validation and digitalization.

• Verification of Secure Systems
• Software Security
• Web Security
• +۵ مورد دیگر

Pedro Adão is an Assistant Professor at the Department of Computer Science and Engineering (DEI) of the Instituto Superior Técnico (IST) , University of Lisbon . He is affiliated with the SQIG - Security and Quantum Information Group at the Institute of Telecommunications , formerly part of CLC - Logic and Computation Centre . His work bridges formal methods and computational cryptography , focusing on security protocols , software security , and quantum information security . PhD in Mathematics (2006, IST) with thesis "Formal Methods for the Analysis of Security Protocols" Graduated in Applied Mathematics and Computation (2002, IST) with thesis "Electronic Money" His research interests include verification of secure systems, composition of secure systems, mathematical foundations of cryptography, and physical/day-life security. His publications span topics like firewall configuration tools , smart contract verification , quantitative protocol analysis , and computationally sound symbolic cryptography . He has collaborated with institutions such as the University of Pennsylvania, Microsoft Research Cambridge, and INRIA-Microsoft Research Paris. Key teaching contributions include courses in Introduction to Algorithms and Data Structures , Computational Models in Security , and Software Security . He is a member of the SQIG research group and has organized the SQIG Information Security Seminar . Past teaching roles include lecturing at the Catholic University of Portugal and the Air Force Academy.

R. Iris Baharمشاهده پروفایل

استاد

• Computer Architecture
• Low Power Design
• Machine Learning
• +۵ مورد دیگر

R. Iris Bahar is a Professor of Computer Science and Engineering at Colorado School of Mines, where she serves as Department Head of Computer Science since 2022. Previously, she held dual appointments as Professor of Engineering and Computer Science at Brown University for 26 years. Her research focuses on energy-efficient and reliable computing across system-level to device-level domains, with applications in near-data processing, robust machine learning for robotics, and noise-immune nanoscale circuit design. Research Interests include computer architecture, low-power design, and robotic system optimization. She pioneers hybrid generative-discriminative inference techniques for robot scene perception, achieving 40% accuracy improvements in occluded environments through FPGA-based Monte-Carlo sampling implementations. Her work on subthreshold CMOS noise modeling provides 1000x simulation speedups over SPICE-based methods. Near-Data Processing Architectures Approximate Computing Hardware/Software Co-design Nanoscale Noise Modeling Robust AI for Robotics Scientific Awards include the 2024 IEEE Undergraduate Teaching Award, 2019 Marie R. Pistilli Women in Engineering Achievement Award, and NSF CAREER award. She is an IEEE Fellow and ACM Distinguished Scientist. Funded Research spans NSF grants on thermal noise effects ($360k), durable data structures ($500k), and Brown SEED grants for autonomous robotics. Her lab trains 12+ students in hardware acceleration and probabilistic computing.

Daniel Wichsمشاهده پروفایل

دانشیار

• Cryptography
• Computer Security
• Algorithms
• +۵ مورد دیگر

Daniel Wichs is an Associate Professor at the Khoury College of Computer Science , Northeastern University , and Senior Scientist at NTT Research . His work focuses on Cryptography , particularly in computing on encrypted data, lattice-based cryptography, and information-theoretic security. Education: PhD in Computer Science (NYU, 2011), BS/MS in Mathematics and Computer Science (Stanford, 2005). His research spans Cryptography , with emphasis on theoretical foundations , program obfuscation , and secure computation . Recent work explores computationally bounded error correction , succinct arguments , and RAM-based cryptographic systems . He has received the Alfred P. Sloan Foundation Fellowship (2018), NSF CAREER Award (2018), and IBM Josef Raviv Fellowship (2011-2013). His students include Manu Kondapaneni , LaKyah Tyner (co-advised), and Ethan Mook , many of whom now hold academic positions. He leads the Cryptography and Privacy Group at Northeastern and has organized major conferences like the Simons Summer Program in Cryptography (2025). His teaching includes advanced courses on Foundations of Cryptography and Theory of Computation .

• Automata Theory
• Formal Verification
• Logic in Computer Science
• +۳ مورد دیگر

Christof Löding , currently an Adjunct Professor at the Lehrstuhl für Logik und Theorie diskreter Systeme (Informatik 7) department of RWTH Aachen University , is a leading researcher in Automata Theory , Formal Verification , and Logic in Computer Science . His work bridges theoretical foundations with practical applications in software verification, automata minimization, and game theory. Research Interests include automata theory, formal verification, logic, tree automata, game theory, and computational models. Publications span topics like Finite-valued Streaming String Transducers , Deterministic Parity Automata , and Stochastic Game Strategies . Collaborations with researchers like Emmanuel Filiot , Sarah Winter , and León Bohn highlight his contributions to automata and verification. Email : loeding@informatik.rwth-aachen.de He has actively published in venues such as ICALP , LICS , and STACS , focusing on deterministic automata, transducers, and logic-based computational systems. His work on Hyperlogic for Strategies in Stochastic Games (2025) and Minimal History-Deterministic Automata (2025) showcases his ongoing influence in formal methods and automata theory.