جست‌وجوی استاد و پژوهشگر

Anantaa Kotalمشاهده پروفایل

استادیار

• Generative AI
• Privacy-Preserving Data Sharing
• Cybersecurity
• +۲ مورد دیگر

Anantaa Kotal is an Assistant Professor of Computer Science at The University of Texas at El Paso (UTEP), commencing her position in Fall 2024. Previously, she completed her PhD at the University of Maryland, Baltimore County (UMBC) and gained industry experience at Amazon and IBM. Her academic credentials include: PhD in Computer Science, University of Maryland Baltimore County (UMBC), 2024 B.E. in Computer Science and Engineering, Jadavpur University, 2017 Dr. Kotal's research centers on Generative AI applications for privacy and security, with emphasis on privacy-preserving data sharing, synthetic data generation, and policy compliance verification. She integrates knowledge graphs, reinforcement learning, and neurosymbolic approaches to develop frameworks for secure data synthesis in healthcare, agriculture, and cybersecurity domains. Her work addresses critical challenges like policy ambiguity resolution and trustworthy AI code generation. Analysis of her 15 most recent publications (2021-2025) reveals a strong trajectory toward knowledge-infused generative models for privacy preservation, with increasing focus on large language models (LLMs) and real-world applications in distributed systems. Key thematic clusters include policy-aware data synthesis (12 publications), healthcare data security (7 publications), and knowledge-graph-enhanced cybersecurity (5 publications). Dr. Kotal is actively recruiting graduate students for her research lab at UTEP and currently teaches Data Mining (CS 5362/6362) in Fall 2024. She maintains active research collaborations with her doctoral advisor Dr. Anupam Joshi at UMBC and industry partners including IBM. She leads a research laboratory at UTEP focused on developing next-generation privacy-preserving AI systems, with current projects spanning healthcare data anonymization, agricultural data sharing frameworks, and policy-compliant synthetic data generation for cybersecurity applications.

• Runtime Verification
• Formal Methods
• Concurrency Theory
• +۷ مورد دیگر

Adrian Francalanza is a Professor in the Department of Computer Science at the Faculty of Information and Communication Technology, University of Malta. His research is centered on formal methods, runtime verification, and concurrency, with a focus on monitorability and distributed systems. His research interests include: Runtime Verification and Monitor Synthesis Session Types and Protocol Safety Concurrency and Actor-Based Systems Branching and Linear-Time Temporal Logics Probabilistic and Decentralized Monitoring Formal Tools for Cyber-Physical and Distributed Systems The recent publications highlight a strong trend in theoretical and practical advances in monitorability, especially for branching-time and probabilistic systems. His work bridges theory with implementation, often resulting in tools like STMonitor and DetectEr. There is a clear emphasis on session types, runtime enforcement, and the verification of communication protocols in real-world systems such as REST APIs and SMTP. Scientific awards include: Distinguished Paper Award at ECOOP 2025 Best Paper Award at DisCoTec 2022 He has been actively involved in advising and organizing major academic events. He served as Program Chair for GandALF 2024 and 2025, FORTE 2024, and VORTEX workshops. He led a three-year project funded by Rannis on Theoretical Foundations for Monitorability in collaboration with Reykjavik University. He has received grants and recognition for developing practical tools such as DetectEr and STMonitor, which support runtime monitoring of Erlang and session-typed systems. He is associated with several research teams and labs, including: Runtime Verification and Monitorability Research Group at University of Malta Collaborators on the DetectEr project Developers of STMonitor and polyLarva tools International collaborators at Reykjavik University and beyond

Iain Macgillمشاهده پروفایل

دانشیار

• Renewable Energy Integration
• Electricity Market Design
• Distributed Energy Systems
• +۴ مورد دیگر

Associate Professor Iain MacGill at the University of New South Wales leads interdisciplinary research at the intersection of renewable energy integration , electricity market design , and policy frameworks for low-carbon transitions. As a core member of the Centre for Energy and Environmental Markets , he develops computational models for coordinating distributed energy resources in restructured power systems. PhD in Electrical Engineering (UNSW) B.Eng. & M.Eng.Sci. (University of Melbourne) His work examines technical-economic-commercial challenges of renewable integration, with recent focus on: 24/7 zero-emission energy tracking frameworks Temporal matching in renewable procurement Open-source tools for green hydrogen value chains Residential solar-battery interaction dynamics Current research projects involve smart grid technologies , community microgrid economics , and climate-resilient energy systems . He collaborates with institutions like ARENA , CSIRO , and ARC on grants addressing grid stability, cost allocation, and policy innovation.

Koushik Senمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Formal Methods
• +۸ مورد دیگر

Koushik Sen is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He holds a B.Tech from IIT Kanpur and M.S./Ph.D. from UIUC. His research focuses on Software Engineering, Programming Languages, and Formal Methods, emphasizing tools like DART, CUTE, and Jalangi for improving software reliability. He leads projects such as CORVETTE and Sky Computing Lab, and collaborates with Samsung Research America on JavaScript analysis. Sen has received prestigious awards including the Sloan Fellowship and ACM SIGSOFT Impact Award. Education: B.Tech, Indian Institute of Technology, Kanpur M.S. and Ph.D., University of Illinois at Urbana-Champaign Research Interests: Software Testing, Verification, Symbolic Execution, Security, and Quantum Computing. His work bridges automated testing (e.g., concolic testing) with machine learning for bug detection and program synthesis. Projects include Hindsight Logging for ML reproducibility and quantum circuit optimization (QFAST). Awards: NSF CAREER, IFIP Manfred Paul, ACM SIGSOFT Distinguished Paper (multiple), and Sloan Fellowship. Advising: Supervised over 30 students/postdocs, leading to faculty roles at UBC, CMU, and industry positions at Google, Facebook, and Samsung. Labs/Teams: Berkeley Center for Responsible, Decentralized Intelligence (RDI), EPIC Data Lab, and Sky Computing Lab. Active in quantum computing and hardware fuzzing (RTL-FuzzLab).

Joanna Cecilia da Silva Santosمشاهده پروفایل

استادیار

• Software Engineering
• Software Security
• Code Generation
• +۴ مورد دیگر

Joanna Cecilia da Silva Santos is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame , where she leads the Security and Software Engineering research lab (S 2 E) . She earned her Ph.D. and M.Sc. in Computing and Information Sciences from Rochester Institute of Technology (RIT) and a B.Sc. in Computer Engineering from Federal University of Sergipe (UFS) . Research Interests: Her work focuses on the intersection of Software Engineering and Software Security , with specific emphasis on Code Generation , Program Analysis , Software Architecture , and Quantum Software Engineering . Recent projects include evaluating large language models for code generation, detecting regular expression denial-of-service vulnerabilities, and creating taint-based analysis tools for Java security. 2025: Code generation benchmarks, LLM performance in programming assignments 2024: Frameworks for secure code generation, ReDoS analysis, static analysis of deserialization 2023: GitHub Copilot complexity prediction, vulnerability characterization 2022: Transformer-based code smell detection, security evaluation datasets Scientific Awards: 2017 Best Paper Award at ICSA 2020 JOBS Workshop Research Pitch Competition Winner 2023 Distinguished Reviewer at ESEC/FSE 2014 CAPES Scholarship for Masters at RIT 2013 3rd Place Paper at XIII ERBASE Her research group engages in empirical studies of code vulnerabilities, automated security tools, and educational applications of language models, with funding reflected in multiple peer-reviewed publications.

Jürgen Gieslمشاهده پروفایل

استاد

• Program Verification
• Automated Deduction
• Termination Analysis
• +۱۲ مورد دیگر

Jürgen Giesl is a Professor at the Teaching and Research Area Computer Science 2 within the Department of Computer Science at RWTH Aachen University , Germany. He leads research in programming languages, formal verification, automated deduction, and term rewriting systems. Research Interests: Automated Termination and Complexity Analysis of Programs Dependency Pairs and Term Rewriting Systems Verification of Probabilistic and Integer Programs Static Analysis and Symbolic Execution Model Checking and Constrained Horn Clauses Development of Automated Tools (AProVE, LoAT) His recent research, reflected in the latest publications, focuses on termination and complexity analysis for probabilistic programs, polynomial loops, and integer programs, using advanced techniques such as dependency pairs, loop acceleration, and semiring semantics. He also contributes to SMT solving and transitive relation learning for infinite-state model checking. Scientific Awards: Best Tool Paper Award at iFM 2017 Silver Medal (Second Best Paper) at SEFM '16 Best Paper Honourable Mention at IJCAR 2024 Best Student Paper Honourable Mention at IJCAR 2024 Advising and Grants: Giesl has supervised numerous PhD and Master’s students, including prominent researchers such as Fabian Frohn, Jens Hensel, Nils Lommen, and Marcel Hark. He leads a large research group focused on automated verification and has contributed extensively to international verification competitions. His work is supported by ongoing research grants and collaborations with leading institutions in formal methods. Labs and Teams: He leads the Programming Languages and Verification research group at RWTH Aachen, which develops and maintains the AProVE and LoAT tools. These tools are central to automated termination and complexity analysis and are regularly submitted to international competitions such as TERMCOMP and VBS.

• Computer Science
• Formal Methods
• Model Checking
• +۳ مورد دیگر

Gethin Norman is a Senior Research Fellow at the Department of Computer Science, University of Oxford, where he contributes to advanced research in formal verification and system modeling. He is based at the Wolfson Building, Parks Road, Oxford. His research focuses on formal methods for computer systems, particularly in the areas of probabilistic model checking and concurrency. His work supports the rigorous analysis of complex software and hardware systems to ensure correctness and reliability. The research activities Gethin is involved in, such as the FUN2MODEL project, emphasize automated reasoning and system verification techniques. These efforts align with broader trends in dependable computing and safety-critical system design. He supervises research under the guidance of Professor Marta Kwiatkowska, a leading figure in probabilistic verification and autonomous systems. No scientific awards or honors are mentioned in the available text. Gethin Norman advises research within the formal methods group at Oxford, contributing to collaborative academic supervision. While no specific grants are listed, his position suggests involvement in externally funded research initiatives. He is part of the research team engaged in the FUN2MODEL project, which aims to advance modeling and analysis techniques for complex computational systems.

Ganesh Lalitha Gopalakrishnanمشاهده پروفایل

استاد

• Computer Science
• Formal Methods
• High-Performance Computing (HPC)
• +۶ مورد دیگر

Ganesh Gopalakrishnan is a Professor of Computer Science at the University of Utah's School of Computing. His research focuses on software correctness, floating-point arithmetic, and formal methods for HPC applications. He leads the ComPort DOE project and NSF REU Site on Trust and Reproducibility. He has advised 26 PhD students and holds seven active NSF grants and a DOE award. Education: B.Sc.(EE), National Institute of Technology Calicut (1978) M.Tech (EE), Indian Institute of Technology Kanpur (1980) PhD in Computer Science, Stony Brook University (1986) Research Interests: Formal methods, HPC correctness, GPU debugging, floating-point error analysis, neural network compression, and reproducible scientific computing. His tools include FPBoxer, HiRace, and FPDetect. Awards & Recognition: ACM Distinguished Scientist IEEE Senior Member University of Utah Beacon of Excellence Award (2012) NSF and DOE funding leadership Labs & Projects: Principal Investigator of the ComPort project (DOE) and NSF REU Site. Co-developed the Jove system for automata education and the Flit floating-point testing framework.

Pierre-Yves Lajoieمشاهده پروفایل

استادیار

• Robotics
• Computer Vision
• Artificial Intelligence
• +۵ مورد دیگر

Pierre-Yves Lajoie is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, a leading engineering school affiliated with Université de Montréal. His research focuses on robotics and artificial intelligence, with specialization in robotic perception for single and multi-agent systems. He has held research positions at prestigious institutions including the Massachusetts Institute of Technology (2019), Samsung AI Center (2023), and University of Oxford (2024). Education: Ph.D. in Computer Engineering, Polytechnique Montréal Dr. Lajoie's research interests span across robotics, computer vision, and distributed systems. He specializes in developing algorithms for robotic perception in challenging environments, with applications in aerial, underground, indoor, and space robotics. His work focuses on enabling robots to understand their surroundings through visual and sensor data, particularly in collaborative multi-robot scenarios where communication may be limited or unreliable. His primary research center of excellence is the Industry of the Future and Digital Society, with secondary centers in Modeling and Artificial Intelligence and New Frontiers in Information and Communication Technologies. His publication record demonstrates a strong focus on collaborative SLAM (Simultaneous Localization and Mapping) systems, with recent work addressing challenges in planetary exploration, swarm robotics, and pedestrian positioning. His research combines computer vision, machine learning, and distributed systems to create robust solutions for real-world robotic applications, particularly in environments with communication constraints. Scientific Awards: Vanier Canada Scholarship Best Paper Award at IEEE ICC 2024 Dr. Lajoie is actively recruiting graduate students for PhD and Master's programs, with openings for Fall 2025 and Spring 2026. He encourages students to apply for various scholarship opportunities including NSERC, FRQ, and IVADO scholarships at multiple academic levels. His research is supported by collaborations with academic and industrial partners, focusing on applications in space robotics, automated manufacturing, and service robotics. He has supervised research projects in areas such as search and rescue with sparsely connected swarms and distributed risk-aware exploration systems.

Hamed Nematiمشاهده پروفایل

استادیار

• Security of systems software
• Formal methods and program logics
• Interactive theorem proving
• +۲ مورد دیگر

Hamed Nemati is an Assistant Professor at the Division of Network and Systems Engineering under the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology in Stockholm, Sweden. He was previously a Visiting Assistant Professor at Stanford University and a Research Group Leader at the Helmholtz Center for Information Security (CISPA) , where he also worked as a PostDoc and Research Fellow. Education : PhD in Computer Science from KTH Royal Institute of Technology Research Interests : Security of systems software, formal methods and program logics, interactive theorem proving, machine code analysis, applied machine learning Current Projects : Systematic verification of multi-language security protocols, hardware-software co-design for Spectre mitigation, capability-based access control models Scientific Awards : WASP (Wallenberg AI, Autonomous Systems and Software Program) faculty member Teaching Activities : Formal Methods in Security (Fall 2020-2023) at CISPA/Saarland University Digital Forensics and Incident Response (EP2780) (Fall 2024) at KTH

• Computational physiology
• Software testing, verification and validation
• Computational logic and formal languages
• +۲ مورد دیگر

Dr. Weiwei Ai is a Research Fellow at the Auckland Bioengineering Institute , University of Auckland, New Zealand. With a multidisciplinary background in biomedical engineering and computational modeling, he focuses on developing energy-consistent physiological models and closed-loop validation frameworks for implantable medical devices. Education PhD in Bioengineering, University of Auckland (2019) Master of Engineering (ME) in Electrical Engineering, Beijing University of Technology (2005) BSc in Electronic Engineering, Qingdao University (2002) Dr. Ai's research centers on computational physiology and medical device validation , utilizing bond graph formalisms and hybrid automata to create thermodynamically consistent models for glucose transport, cardiac pacemakers, and gastrointestinal systems. His work bridges mathematical modeling with clinical applications through formal verification techniques. His recent publications highlight trends in closed-loop biomedical device design and energy-based physiological modeling , including: (1) bond graph models for SLC transporter dynamics, (2) adaptive respiratory pacemaker frameworks with biofeedback, (3) formal verification of cardiac devices using timed automata, and (4) compositional cyber-physical epidemiology models. He also explores AI-driven integration of digital twins in healthcare through FAIR data principles. Supervision Opportunities : Dr. Ai is an accredited PhD supervisor at the University of Auckland, offering projects on AI-driven energy-based platforms for credible digital twins in healthcare. Labs : Affiliated with the Auckland Bioengineering Institute, focusing on computational models and in-silico validation systems.

Andrew Jirasekمشاهده پروفایل

استاد

• Medical Physics
• Radiation Oncology Physics
• Raman Spectroscopy
• +۳ مورد دیگر

Andrew Jirasek is a Professor at the Irving K. Barber Faculty of Science , University of British Columbia Okanagan , and serves as the Associate Dean for Graduate and Postdoctoral Training . He leads the Analytics in Medical Sciences (AiMS) Institute with a focus on Medical Physics and Radiation Oncology Physics , particularly utilizing Raman spectroscopy and 3D radiation dosimetry for cancer treatment verification. PhD from University of British Columbia His research involves developing polymer gel dosimeters for 3D radiation dose verification in complex therapies like volumetric modulated arc therapy (VMAT) , collaborating across physics, oncology, and engineering . He also investigates optical technologies to monitor biological responses during radiotherapy using Raman spectroscopy with machine learning for data analysis. Recent publications highlight advancements in 3D gel dosimetry , Raman spectroscopy for metabolic profiling , and iterative image reconstruction algorithms . His work spans dosimeter technology development , radiation therapy quality assurance , and clinical applicability studies for novel treatment verification methods.

Robert Y. Lewisمشاهده پروفایل

مدرس

• Formal Methods
• Logic
• Theoretical Computer Science
• +۳ مورد دیگر

Robert Y. Lewis is a Lecturer in the Department of Computer Science at Brown University, specializing in formal methods, logic, and interactive theorem proving. His work bridges computer science and mathematics, focusing on the verification of mathematical proofs and program correctness. Education: PhD in Pure and Applied Logic (2018), Carnegie Mellon University MS in Pure and Applied Logic (2015), Carnegie Mellon University BA in Mathematics (2010), Rice University Research Interests: Lewis’s research spans formal verification, logic, type theory, and automated reasoning. He explores the application of logical tools like the Lean proof assistant in mathematics education and software verification. Teaching: At Brown, he teaches courses such as Introduction to Discrete Structures and Probability and Formal Proof and Verification . Prior to Brown, he taught Logic and Modeling at Vrije Universiteit Amsterdam and served as a teaching assistant at Carnegie Mellon University. Publications: His recent work includes advancements in formalizing mathematical structures (e.g., Witt vectors, Cap Set Problem), integrating proof assistants with computational tools (Lean-Mathematica interface), and developing educational resources for logic and formal methods. Contact: Email: robert_lewis@brown.edu Office: Center for Information Technology 203, Brown University

• Natural Language Processing
• Semantic Parsing
• Large Language Models
• +۳ مورد دیگر

Rui Zhang is an Assistant Professor in Computer Science and Engineering , with research expertise spanning Natural Language Processing , Large Language Models , and Semantic Parsing . His recent work focuses on enhancing multimodal consistency , fairness in summarization , and mathematical reasoning capabilities of LLMs. Key Research Themes: Text-to-SQL and cross-domain semantic parsing Multimodal learning (vision-language models) Fairness and bias mitigation in NLP tasks Efficient model training and prompt optimization Scientific Awards: National Science Foundation CAREER Award (2024) Grants & Projects: CAREER: Trustworthy Human-Centered Summarization (NSF, 2024-2029) addressing LLM trustworthiness through user-centric summarization frameworks. Article Trends: Recent publications emphasize LLM collaboration , compressed reasoning models , and cross-domain knowledge alignment . He explores multi-agent systems , mathematical reasoning , and vision-language limitations , particularly in geometric perception. Applications span bioinformatics (Alzheimer's biomarker discovery) and democratic AI frameworks.

• Artificial Intelligence
• Medical Informatics
• Software Engineering
• +۴ مورد دیگر

Dr. rer. nat. Joscha Grüger is a researcher at the Experience-based Learning Systems department of the University of Trier . His work bridges artificial intelligence, medical informatics, and software engineering, focusing on AI-driven solutions for healthcare and data-intensive applications. Current research projects include: KI-AIM : AI-based anonymization in medicine KIAFlex : Interactive AI assistance for predictive and flexible control in discharge management DaTreFo : Encrypted data stewardship for medical research Pre-OnkoCase : Case-oriented decision support for skin cancer treatment His publications highlight expertise in probabilistic programming, IoT-enhanced event logs, and clinical decision support systems. Collaborations span international conferences like Petri Nets 2025, ICCBR, and RCIS. Contact: Joscha.Grueger@dfki.de .