جست‌وجوی استاد و پژوهشگر

Jana Hofmannمشاهده پروفایل

پژوهشگر

• Information Security
• Trust in Security Systems
• Microarchitectural Side Channels
• +۳ مورد دیگر

Jana Hofmann is a tenure-track faculty member at the Max Planck Institute for Security and Privacy (MPI-SP), leading the Foundations of Information Security and Trust group. Previously, she was a postdoctoral researcher at Microsoft Azure Research and completed her PhD at Saarland University (CISPA Helmholtz Center). Her research focuses on establishing strong security guarantees for systems through formal methods, with an emphasis on microarchitectural side channels and information leakage prevention. Education : PhD, Saarland University (2022), advised by Bernd Finkbeiner M.Sc., University of Edinburgh (2016–2017) B.Sc., Saarland University (2013–2016) Research Interests : Hofmann’s work combines formal methods, programming languages, and systems approaches to address information leakage in hardware/software systems. Key areas include: Microarchitectural side-channel detection/prevention Formal leakage models and verification techniques Smart contract synthesis and hyperproperties Publications : Her recent work emphasizes practical applications of formal methods to cloud CPU security, smart contracts, and automated testing. Notable contributions include Gaussian elimination-based memory coloring and isolation techniques for cloud CPUs. Awards : Dr.-Eduard-Martin Prize (2022) for best PhD thesis in computer science Distinguished Paper Awards at CCS’24 and CSF’23 Advising & Grants : Hofmann has advised five students on theses in formal verification and security. She actively contributes to program committees for conferences like CAV, CCS, and CSF. Labs/Teams : She leads the MPI-SP Foundations group, focusing on advancing trust in security-critical systems through interdisciplinary research.

Aïna Linn Georgesمشاهده پروفایل

پژوهشگر

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +۳ مورد دیگر

Aïna Linn Georges is a researcher affiliated with the Max Planck Institute for Software Systems (MPI-SWS) in Saarbrücken, Germany. Her work focuses on formal methods, programming languages, and system security. She specializes in program verification, capability-based systems, and secure compilation. Her research addresses challenges such as concurrency, memory safety, and security in distributed and cyber-physical systems. Her research interests include separation logic, modular verification frameworks, and the mechanization of proofs for systems like WebAssembly and capability machines. She explores robust security properties under diverse attacker models and contributes to foundational aspects of capability-based architectures. Recent work highlights include advancements in non-frame-preserving updates for separation logic, formal verification of compartmentalized C programs, and secure compilation techniques. Her publications reflect a strong emphasis on practical formal methods for real-world systems, with applications in both theoretical and applied computer science.

Mahmoud Salamatiمشاهده پروفایل

پژوهشگر ارشد

• Formal Methods in Control
• Learning in Control Systems
• Cyber-Physical Systems
• +۲ مورد دیگر

Dr. Mahmoud Salamati is a Research Fellow at the Max Planck Institute for Software Systems, working in the Rigorous Software Engineering group under Professor Rupak Majumdar. His research bridges formal methods, control theory, and machine learning with applications in cyber-physical systems, energy grids, and autonomous vehicles. Salamati's work develops formal verification techniques for stochastic systems and data-driven control synthesis methods. Recent publications focus on regret-free reinforcement learning for temporal logic specifications, metastable failure analysis in distributed systems, and abstraction-based controller synthesis. His research addresses fundamental questions about decidability and scalability in formal control synthesis while maintaining practical applications in energy management and autonomous systems. Key contributions include novel approaches to time-bounded reachability problems in continuous-time Markov chains, symbolic control methods for multi-agent systems, and hybrid optimization techniques for power plant control. Salamati's work demonstrates consistent integration of theoretical computer science foundations with practical engineering challenges in critical infrastructure systems.

Percy Liangمشاهده پروفایل

دانشیار

• Machine Learning
• Natural Language Processing
• Foundation Models
• +۴ مورد دیگر

Affiliations Associate Professor at Stanford University's Computer Science Department within the School of Engineering. Director of the Center for Research on Foundation Models (CRFM) and core member of Stanford HAI . Also affiliated with the Artificial Intelligence Lab, Natural Language Processing Group, and Machine Learning Group. Education Ph.D. in Computer Science, UC Berkeley (2011), advisors: Michael Jordan and Dan Klein MEng in Computer Science, MIT (2005), advisor: Michael Collins B.S. in Computer Science, MIT (2004) Research Focuses on foundational aspects of AI, including: Foundation models and their societal implications (e.g., copyright, data attribution) Building scalable and interpretable AI systems Reproducible research via CodaLab Worksheets Formal methods for ensuring correctness in ML systems Key Contributions Pioneered work in: Automated reasoning for Olympiad-style problems Data Programming framework for rapid dataset creation Executable papers and experiment reproducibility AI ethics and model interpretability Grants & Awards Presidential Early Career Award (2019) IJCAI Computers and Thought Award (2016) Microsoft Research Faculty Fellowship (2014) Multiple patents and industry collaborations Labs & Teams Leads the CRFM team developing open foundation models. Collaborates with industry (e.g., Google, Meta, OpenAI) and co-founded xAI initiatives. Active in open-source projects like sfig for presentation tools.

• Artificial Intelligence
• Planning and Scheduling
• Reinforcement Learning
• +۵ مورد دیگر

Sheila A. McIlraith is a Professor in the Department of Computer Science at the University of Toronto, where she leads research at the intersection of artificial intelligence, knowledge representation, and formal methods. With an extensive publication record spanning over three decades, she has made significant contributions to planning, reinforcement learning, and epistemic reasoning in AI systems. Her research interests focus on developing formal frameworks for AI planning and decision-making, with particular emphasis on interpretable AI, reward specification in reinforcement learning, and multi-agent systems. She has pioneered work in reward machines for reinforcement learning, epistemic planning, and the application of formal methods to ensure safety and fairness in AI systems. Her recent work bridges symbolic AI with deep learning approaches to create more transparent and controllable intelligent agents. Analysis of her recent publications reveals a strong trend toward integrating formal specification languages with machine learning, particularly in reinforcement learning where she develops methods for specifying complex tasks using linear temporal logic and related formalisms. Her work increasingly addresses ethical considerations in AI, including fairness in sequential decision making and the impact of ethics education in computer science curricula. McIlraith has mentored numerous PhD students who have become prominent researchers in AI, including Rodrigo Toro Icarte, Toryn Q. Klassen, and Andrew C. Li. Her collaborative network spans major AI research institutions worldwide, with frequent collaborations with researchers at institutions including the Vector Institute and international universities. Her research group explores the theoretical foundations of AI planning while developing practical applications in areas including robotic assistance, ethics-aware AI, and interpretable decision systems. Current projects focus on language-guided reinforcement learning, multi-agent verification, and the development of tools for responsible AI development and deployment.

Julien Musolinoمشاهده پروفایل

استاد

• Cognitive Science
• Developmental Psychology
• Linguistics
• +۴ مورد دیگر

Julien Musolino is a Professor at Rutgers University, holding dual appointments in the Department of Psychology and the Rutgers Center for Cognitive Science (RuCCS). He is also a member of the Philosophy Department's graduate faculty. His research explores the foundations of human cognition, focusing on language, rationality, agency, memory, and belief formation, with a particular interest in their societal implications. Musolino has been recognized with multiple teaching awards for his outreach efforts, and his work has been supported by NIH and NSF grants. Education: University of Geneva, Switzerland University of North Wales, Bangor, UK University of Maryland University of Pennsylvania Research Interests: Musolino's work bridges cognitive science, linguistics, and philosophy. Key areas include belief dynamics, temporal binding mechanisms, supernatural concept memorability, and the cognitive underpinnings of religious thought. He actively engages in public discourse through lectures, podcasts, and media appearances, addressing topics like free will and the intersection of science and society. Recent Activities: Recent talks include presentations to employment lawyers, physics students, and humanist networks. He debated theologian Brian Brock (2025) and participated in Swiss media interviews (2023). His research has been featured in leading journals and interdisciplinary conferences. Grants & Funding: NIH and NSF grants support his studies on belief formation, temporal binding, and cognitive science outreach. Labs/Teams: Affiliated with RuCCS and collaborates with interdisciplinary teams on projects like the memorability of supernatural concepts and rethinking temporal binding.

• Mobile Crowd Sensing
• Visual Information Processing
• Medical Imaging Analysis
• +۵ مورد دیگر

Huihui Chen is an Associate Professor in the Department of Computer Science and Engineering at Northwestern Polytechnical University, specializing in mobile crowd sensing, medical imaging analysis, and control systems for autonomous vehicles. With over 50 publications spanning from 2013 to 2025, Dr. Chen has established a significant research presence in interdisciplinary areas combining computer science, engineering, and medical applications. Dr. Chen's research interests focus on mobile crowd sensing systems , particularly visual crowdsensing applications for smart cities and transportation. Their work extends to medical imaging analysis for conditions like Fragile X syndrome and granulosa cell tumors, as well as control systems for unmanned surface vehicles. The research demonstrates a progression from fundamental crowd sensing frameworks to sophisticated applications in medical diagnostics and autonomous systems. Key methodological approaches include sensor fusion techniques, neural network modeling, and optimization algorithms for dynamic environments. Recent publications reveal a growing emphasis on interdisciplinary applications, particularly at the intersection of computer vision and medical diagnostics. The 15 most recent articles demonstrate expertise across multiple domains including transportation systems optimization, neural network synchronization, and medical imaging analysis. This diverse portfolio shows a research trajectory that bridges theoretical computer science with practical applications in healthcare and autonomous systems. Dr. Chen actively collaborates with researchers including Bin Guo (31 joint publications), Zhiwen Yu, Chundi Zheng, and Aiguo Wang, forming a productive research group focused on mobile sensing technologies. The collaborative network extends across multiple Chinese institutions, with significant contributions to IEEE journals and international conferences in computer science and engineering.

Chana Weil-Kennedyمشاهده پروفایل

پژوهشگر

• Formal Verification
• Distributed Systems
• Petri Nets
• +۳ مورد دیگر

Chana Weil-Kennedy is a Researcher at CEA List in Paris, focusing on formal verification of distributed systems, Petri nets, and theoretical computer science. Previously, she was a Postdoctoral Researcher at the IMDEA Software Institute (2023–2024) and completed her PhD at the Technical University of Munich (TUM), supervised by Javier Esparza. Her PhD thesis, Observation Petri Nets , explores parameterized verification and Petri net reachability under the ERC-supported PaVeS project. Education: PhD in Computer Science, TUM (2023) Master’s in Computer Science, École Normale Supérieure Paris-Saclay (2018) Bachelor’s in Mathematics, Université Paris-Sud (formerly Orsay) Research Interests: Runtime verification, distributed systems, formal methods, Petri nets, and mathematical reasoning in computer science. Her work emphasizes parameterized verification of protocols and systems, with applications to population protocols and distributed computations. Teaching & Supervision: Tutored courses at TUM including Automata and Formal Languages, Petri Nets, and Fundamental Algorithms. Co-supervised three Bachelor’s theses and a Master’s thesis on distributed systems and verification tools. Awards: Best Paper Award at Petri Nets 2019 for Parameterized Analysis of Immediate Observation Petri Nets . Labs/Teams: Active at CEA List, collaborating on runtime verification and distributed system analysis. Formerly part of Pierre Ganty’s group at IMDEA and Javier Esparza’s team at TUM.

Ataberk Olgunمشاهده پروفایل

مدرس

• Computer Architecture
• Memory Systems
• DRAM Reliability
• +۵ مورد دیگر

Ataberk Olgun is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich, where he conducts research in the SAFARI Research Group under Professor Onur Mutlu. His work focuses on computer architecture with particular emphasis on memory systems, DRAM reliability, and security vulnerabilities such as RowHammer. His educational background includes BSc and MSc degrees from TOBB ETÜ (Ankara University of Economics and Technology) under Professor Oğuz Ergin's supervision. Prior to his doctoral work at ETH Zürich, he worked at Kasirgalabs until 2021, leading the design of a RISC-V system-on-chip manufactured using SKY130 technology, and previously developed authentication methods based on behavioral biometrics with Professor Kemal Bicakci. Olgun's research interests center on designing reliable and energy-efficient memory systems. He has developed FPGA-based testing platforms for DDR3/4 and HBM2 DRAM chips, created end-to-end systems for processing-in-memory techniques, and made significant contributions to understanding and mitigating the RowHammer problem. His work often combines hardware design with system-level considerations to address fundamental challenges in modern memory technology. His publication record shows consistent output in top-tier venues including ACM TACO, USENIX Security, ISCA, MICRO, and HPCA, with a clear trend toward increasingly sophisticated investigations of DRAM vulnerabilities and innovative mitigation strategies. Recent work focuses on fine-grained DRAM architectures, scalable RowHammer mitigation techniques, and experimental characterization of emerging memory technologies. As part of the SAFARI Research Group at ETH Zürich, Olgun collaborates extensively with Professor Onur Mutlu and other researchers on memory systems research. His technical expertise spans FPGA-based prototyping, DRAM characterization, hardware security, and memory controller design. Olgun maintains an active research presence with numerous ongoing projects investigating next-generation memory technologies, security vulnerabilities in modern DRAM, and energy-efficient memory system designs. His work bridges theoretical understanding with practical implementation through FPGA-based experimental platforms.

• Computer Security
• Formal Verification
• Networking Protocols
• +۳ مورد دیگر

Dr. Christoph Sprenger is a Lecturer at the Department of Computer Science at ETH Zürich, specializing in formal verification of security protocols and networking systems. His work focuses on ensuring the correctness and security of distributed systems, databases, and network infrastructure through rigorous mathematical methods. His research addresses challenges such as verified isolation guarantees for database transactions, formal verification of router implementations, and secure data plane protocols in next-generation internet architectures. He has contributed to frameworks like IsaNet and N-Tube, emphasizing practical applications of formal methods in real-world systems. Key themes in his publications include protocol design, cryptographic security, and compositional verification techniques. Recent work explores the intersection of formal verification with path-aware networking and distributed system reliability. His research maintains a strong emphasis on bridging theoretical foundations with deployable solutions. Current projects involve advancing formal verification tools for critical infrastructure components, such as transactional memory managers and secure service architectures. His work consistently bridges gaps between abstract protocol specifications and their secure, interoperable implementations.

Viktor Kuncakمشاهده پروفایل

دانشیار

• Formal Verification
• Automated Reasoning
• Programming Languages
• +۳ مورد دیگر

Viktor Kuncak is an Associate Professor and head of the Laboratory for Automated Reasoning and Analysis (LARA) at EPFL. He joined EPFL in 2007 after completing his PhD at MIT. His research focuses on formal verification, automated reasoning, programming languages, and program synthesis. He has led significant initiatives such as the European COST Action on automated reasoning formats and secured a 5-year ERC grant (2012–2017). Education: PhD in Computer Science from MIT (2007), MSc in Computer Science and Physics from MIT (2001), BSc in Computer Science from University of Novi Sad (2000). Research Interests: Formal methods, automated theorem proving, program analysis, and tools for software verification. His work bridges theoretical foundations and practical systems, with contributions to verifiers like Leon and Stainless. Recent work emphasizes verified compilers, set theory formalisms, and education tools like Lisa. His publications address challenges in SMT solving, equivalence checking, and functional programming. Scientific Awards: ERC Starting Grant (2012), ACM SIGSOFT Distinguished Paper (2010), CAV Best Paper (2010). Advising: Supervised 16 completed PhD theses, with current students working on proof assistants and formal verification frameworks. Grants include SNSF and EU-funded projects. Labs/Teams: Directs LARA lab at EPFL, collaborating with global researchers in formal methods and programming languages.

• Biomedical Circuits
• Ultra-Wideband Communication
• Robotics
• +۳ مورد دیگر

Marco Crepaldi is an active researcher with a focus on biomedical circuits, wearable systems, and machine learning applications. His work spans collaborations with institutions and researchers globally, contributing to fields such as multisensory rehabilitation devices, ultra-wideband communication, and neuromorphic computing. Research Interests: Biomedical circuits for rehabilitation, wireless sensing, machine learning hardware, and human-robot interaction. Recent publications highlight his innovation in: Transformer and graph neural networks for fall detection Reservoir computing for seizure control Low-power 8-bit neural processors Wearable multisensory systems for visually impaired infants He has co-authored 73+ peer-reviewed publications since 2007, with a technical focus on ultra-wideband systems, asynchronous logic, and embedded biomedical devices.

Manikandan Palanichamyمشاهده پروفایل

دانشیار

• Green Energy Transitions
• Smart Energy Systems
• Industry 5.0
• +۵ مورد دیگر

Manikandan Palanichamy is an Associate Professor at Østfold University College, specializing in green energy transitions, smart energy systems, and emerging ICT technologies. He holds a PhD in Electronics and Telecommunications Engineering from NTNU, Norway, and has extensive international academic and industry experience. Education: PhD (2013): NTNU, Norway Master’s (2006): National Cheng Kung University, Taiwan Bachelor’s (2004): MKU, India Engineering Diploma (2001): Alagappa Polytechnic, India Research Interests: His work focuses on green energy, Industry 5.0, circular economy, IoT integration, and hardware security. He has pioneered novel CAM cell designs, path delay fault testing methodologies, and sustainable energy solutions. Recent projects include bilateral collaborations on renewable energy and smart industrial IoT systems. Publications: Over 30 peer-reviewed articles in journals like IEEE Proceedings and International Journal of Engineering and Advanced Technology. Key themes include AI integration in networks, LoRaWAN for industrial IoT, and hardware security. Awards: IEEE Best Paper Award (2006) Roles: International Coordinator at Østfold University College, managing student exchanges and partnerships. He also advises industrial projects in software development and IIoT integration. Labs/Teams: Involved in the Green Energy Research Hub and collaborates with institutions globally on projects like BioSolar Hydrogen and ReSAG (Remote Sensing for Agriculture).

Jaco van de Polمشاهده پروفایل

استاد

• Model Checking
• Quantum Computing
• Symbolic Computation
• +۵ مورد دیگر

Jaco van de Pol is a Professor at the Department of Computer Science, Aarhus University. His research focuses on formal methods, quantum computing, and symbolic computation. He specializes in model checking, timed automata, decision diagram algorithms, and quantum circuit synthesis. Education background includes expertise in computer science with a strong foundation in theoretical computer science and formal verification techniques. Key research interests include: Development of scalable symbolic algorithms for large systems Quantum circuit optimization using SAT-based approaches External memory implementations of decision diagrams Formal verification of real-time and parametric systems Recent work emphasizes quantum computing applications, such as layout-aware CNOT circuit synthesis for NISQ processors, and novel algorithms for parametric timed games. His contributions include the Adiar framework for external memory BDD manipulation and the Sylvan decision diagram library. No academic awards or grants are explicitly mentioned in the provided materials. He has advised multiple collaborations but no specific student names are listed. His research group focuses on advancing formal methods through practical tools and theoretical advancements.

• Linguistics
• Digital Communication
• Historical Linguistics
• +۳ مورد دیگر

Francesca Chiusaroli is a Full Professor of Linguistics at the University of Macerata, specializing in Glottology (GLOT-01/A). She holds a PhD in Linguistics from the University of Pisa and has held academic positions at institutions like the University of Udine and Roma Tor Vergata. Her research focuses on historical linguistics, digital communication, and emoji semiotics, particularly exploring shorthand systems, medieval language evolution, and modern digital writing practices. Education: Laurea (BA) and PhD in Linguistics from University of Macerata and Pisa Post-doctoral fellowship at University of Naples 'L'Orientale' Research Interests: Orality and literacy processes in Old English Short writings and digital communication (emojis, hashtags) Historical shorthand systems and their linguistic analysis Social media's impact on language use Recent Work Trends: Her articles analyze emoji usage, AI-driven language translation, and pandemic-era communication patterns. Collaborations include projects on Emojitaliano and sentiment analysis of student writing during the pandemic. Teaching: She teaches courses like 'Linguistics of Media' and 'History of Translation', emphasizing digital tools and historical language studies.