جست‌وجوی استاد و پژوهشگر

Mia Minnesمشاهده پروفایل

استاد آموزشی

• Automata Theory
• Computability education
• Scholarship of Teaching and Learning
• +۷ مورد دیگر

Mia Minnes is a Teaching Professor and the Vice Chair for Undergraduate Education in the Computer Science and Engineering Department at UC San Diego's Jacobs School of Engineering. She teaches discrete math for CS, introduction to computability, and TA training classes, while leading initiatives that connect academic learning with professional development. Her research focuses on Automata Theory and Computability education, Scholarship of Teaching and Learning (SoTL), and projects supporting student professionalization pathways including industry internships, peer mentor development, and ethics in computing. She has pioneered initiatives like the Summer Internship Symposium and CSE-PACE (Peer-led Academic Cohort Experiences) to enhance student experiences in large computing programs. Minnes' publication portfolio reveals strong trends in computing education research, particularly in internship experiences, TA professional development, assessment methods, and interventions for large classes. Her work consistently bridges theoretical computer science with practical educational applications, demonstrating a commitment to evidence-based teaching practices and student success metrics. UC San Diego Academic Senate Distinguished Teaching Award (2020) Jacobs School of Engineering Teacher of the Year (2013-2014) Multiple NSF grants as PI including DUE-2337253 (2024-2027) UC San Diego Student Centeredness Award (2023-2024) Teaching+Learning Commons Faculty Fellow (2018-2019) She has advised numerous undergraduate and graduate students through research projects examining internship disparities, TA professional development, educational technology tools, and student experiences in computing programs. Her leadership extends to projects like FlapJS (an interactive visualization tool for formal computation), ComputingPaths (resources for computing career paths), and OCCTIVE (supporting computational problem solving in non-CS courses).

Dominique Unruhمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Cryptography
• Post-Quantum Cryptography
• +۵ مورد دیگر

Dominique Unruh is a Professor at RWTH Aachen University , leading the Chair for Quantum Information Systems . Additionally, they hold a Professorship in Cryptography at the Institute of Computer Science of the University of Tartu , Estonia. Their research spans quantum computing , quantum cryptography , post-quantum cryptography , and formal verification of cryptographic protocols and programs. Research Focus : Quantum programs, zero-knowledge proofs, lattice-based cryptography, and quantum random oracle model. Key Contributions : Advancements in NTRU encryption efficiency, quantum Hoare logic, and rewinding techniques for security proofs. Tools : Active development in the EasyCrypt framework for cryptographic verification. Email : unruh@cs.rwth-aachen.de

• Quantum Control Theory
• Quantum Dynamics
• Quantum Computing
• +۵ مورد دیگر

Xiuhao Deng is an Associate Research Fellow and PhD Supervisor at the Institute of Quantum Science and Engineering, Southern University of Science and Technology (SUSTech), with adjunct positions at Pengcheng Lab and Hefei Lab. He obtained his B.S. in Modern Physics from University of Science and Technology of China (USTC) in 2005, followed by an M.S. in Atomic and Molecular Physics from USTC (2009) and a Ph.D. in Physics from University of California, Merced (2015). Research Interests: Driven quantum systems Quantum control theory and open quantum systems Superconducting and spin qubits Quantum error correction Quantum simulation Quantum computing His work focuses on robust quantum gate engineering, scalable quantum control, and error mitigation in multi-qubit systems. Recent publications emphasize geometric correspondence methods, noise resilience, and hardware optimization. Academic Activities: Organized QIP 2020 (international quantum conference) Reviewer for Phys. Rev. X , Phys. Rev. Lett. , and other journals Transferred to Shenzhen International Quantum Academy in 2025 after tenure at SUSTech

• Software Engineering
• Model-Based Software Engineering
• Automated Reasoning
• +۵ مورد دیگر

Sebastián Uchitel is a Professor at the Department of Computing, Imperial College London, UK. His research focuses on foundational aspects of Software Engineering, particularly in modeling and analysis for automated reasoning, verification of probabilistic systems, controller synthesis, and adaptive systems. He has led major research projects, including the ERC-funded IDEAS StG project on Partial Behaviour Modelling and the European FP6 SENSORIA project. Research Interests: Model-Based Software Engineering, Controller Synthesis, Probabilistic Systems, Adaptive Systems, Requirements Engineering External Roles: General Chair, International Conference on Software Engineering (2017); Associate Editor, Elsevier Science of Computer Programming; Steering Committee, International Conference on Software Engineering His recent work explores intersections between Software Engineering and AI, including assured adaptive systems and logic-based learning. A Senior Member of IEEE and Distinguished Scientist of ACM , he has received awards like the Houssay Prize (2015) and Philip Leverhulme Prize (2005). Collaborators include institutions in Argentina, Canada, and the UK. Selected Publications: 150+ peer-reviewed works spanning controller synthesis, requirements engineering, and formal methods Students: Supervised 12 PhD students since 2003 Grants: Principal Investigator for 3 major grants (2005-2016) totaling over $3.7M USD, including: 2013-2016: Technology Platform in Software Engineering (ANPCYT, $1.6M) 2009-2014: ERC IDEAS StG on Partial Behaviour Modelling (€1.4M) 2005-2008: FP6 SENSORIA Project (€0.7M)

Aleksandra Radenovicمشاهده پروفایل

استاد

• Single molecule biophysics
• Solid State Nanopores
• 2-D materials
• +۶ مورد دیگر

Aleksandra Radenovic is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) holding multiple positions across the institution. She is a Full Professor at the Laboratory of Nanoscale Biology (LBEN) within the School of Engineering (STI), a Full Professor in Teaching at the School of Life Sciences (SV), and a Full Professor in Teaching at the School of Engineering (STI). Additionally, she serves as Co-Director of both the IBI-STI and IBI-SV administrative units, and is a Member of both the STI School direction and SV School direction. Dr. Radenovic received her PhD from the University of Lausanne in 2003, where she worked with Prof. Dietler in the Laboratory of Physics of Living Matter. Prior to that, she studied physics at the University of Zagreb from 1994-1999, and completed her baccalaureate at a Classical gymnasium in 1994. She conducted postdoctoral research at the University of California, Berkeley from 2004-2007 in the group of Prof. Liphardt. Her research focuses on single molecule biophysics, with particular emphasis on developing techniques and methodologies based on optical imaging, biosensing, and single molecule manipulation. Her laboratory works on three major research directions: (i) developing and using nanopores as platforms for molecular sensing and manipulation, particularly solid-state nanopores in glass nanocapillaries and 2D-material membranes; (ii) studying biomolecular function, especially protein and nucleic acid interactions, using force-based manipulation techniques like optical tweezers and Anti-Brownian Electrokinetic traps; and (iii) developing super-resolution optical microscopy based on single molecule localizations for quantitative cellular imaging. Her work bridges physics, engineering, and biology to create innovative tools for understanding molecular processes at the nanoscale. Analysis of her recent publications reveals a strong focus on nanofluidics, 2D materials (particularly MoS 2 and hBN), nanopore sensing, super-resolution microscopy, and the development of novel instrumentation for biophysical applications. Her research demonstrates increasing interdisciplinary collaboration, integrating materials science, nanotechnology, and biological applications to address fundamental questions in molecular biophysics. Dr. Radenovic has received numerous prestigious awards and grants, including: 2021: ERC Advanced Grant 2021: Optica Fellow 2016: CCMX Materials challenge award 2015: SNSF-ERC Consolidator Grant 2010: ERC Starting Grant 2003: SNSF Fellowship She has successfully advised numerous PhD students whose research spans single molecule biophysics, nanofluidics, and optical techniques. Her laboratory, the Laboratory of Nanoscale Biology (LBEN), is well-equipped for advanced biophysical research, with capabilities in nanopore fabrication, optical trapping, super-resolution microscopy, and 2D materials characterization. Dr. Radenovic has secured significant research funding through competitive grants, including multiple ERC grants, which have supported her innovative research program at the intersection of physics, engineering, and biology.

Roberto Giacobazziمشاهده پروفایل

استاد

• Theory of computation
• Programming languages
• Abstract interpretation
• +۳ مورد دیگر

Roberto Giacobazzi is a Professor at the University of Arizona specializing in theoretical computer science with a focus on abstract interpretation, program analysis, and verification. His research bridges theoretical foundations with practical applications in software security and verification systems. Dr. Giacobazzi received his Ph.D. from the University of Pisa in Italy in 1993, establishing a long-standing academic career focused on the theoretical underpinnings of program analysis. His educational background forms the foundation for his contributions to abstract interpretation theory. His primary research interests center around abstract interpretation, a theoretical framework for approximating program semantics. This work spans theory of computation , programming languages , program analysis and verification , and logic in computer science . Giacobazzi has made significant contributions to understanding completeness and precision in abstract interpretation, with applications extending to code obfuscation, security analysis, and more recently, AI fairness in legal contexts. His work demonstrates how theoretical computer science concepts can address practical software engineering challenges. An analysis of his recent publications (2022-2025) reveals a consistent research trajectory with increasing sophistication in abstract interpretation theory. His work shows a growing emphasis on completeness properties, precision limitations, and security applications. Notably, his 2024 publication on "Fairness of AI Systems in the Legal Context" indicates an expansion of his theoretical expertise into AI ethics and regulatory compliance, demonstrating the versatility of abstract interpretation frameworks. Dr. Giacobazzi has contributed extensively to major conferences in programming languages and verification, including SAS (Static Analysis Symposium), POPL (Principles of Programming Languages), and VMCAI (Verification, Model Checking, and Abstract Interpretation). His publications reflect deep theoretical insights while maintaining relevance to practical software analysis challenges. His research has significant implications for software security, particularly in code obfuscation techniques based on abstract interpretation. The systematic approach to measuring incompleteness in abstract interpretations has provided new frameworks for understanding and improving program analysis tools. His work continues to influence both academic research and practical applications in program verification and security.

Sanjay Modgilمشاهده پروفایل

استاد

• Artificial Intelligence
• Argumentation Theory
• Non-monotonic Logic
• +۴ مورد دیگر

Sanjay Modgil is a Professor of Artificial Intelligence at King's College London's School of Informatics, specializing in argumentation theory, non-monotonic logic, and AI applications in medicine. He contributes to ethical AI research aligned with UN Sustainable Development Goals. Research Interests Argumentation Theory Non-monotonic Logic Normative Reasoning Agent Reasoning AI in Healthcare Human-AI Collaboration His recent publications focus on depth-bounded reasoning, ethical debates, and large language models. He leads EPSRC-funded projects like CONSULT and RESPECT, emphasizing responsible AI technologies and multimorbidity management systems.

Yan Congمشاهده پروفایل

استادیار

• Natural Language Processing (NLP)
• Semantics and Pragmatics
• Computational Linguistics
• +۴ مورد دیگر

Yan Cong is an Assistant Professor at Purdue University, focusing on Chinese linguistics and computational linguistics. Their work bridges natural language processing (NLP), semantics, and pragmatics, with applications in artificial intelligence (AI), language education, and healthcare. Research Focus: Developing text analysis models to quantify and improve language learning, assessing semantic/pragmatic competence in language models, and applying computational methods to speech and language fluency. Background: Former NLP researcher at the Feinstein Institutes, with a PhD in Linguistics from Michigan State University. Research Themes: Yan Cong integrates linguistic theory with AI to explore language understanding in humans and machines. Key areas include Computational modeling of semantics and pragmatics Application of NLP to second language acquisition Development of interpretable AI systems for education and healthcare Analysis of speech disturbances in clinical contexts (e.g., schizophrenia, aphasia) Awards: No specific honors mentioned in the provided text.

• Fuzzy Logic
• Soft-Computing
• Health Monitoring
• +۹ مورد دیگر

Nishchal K. Verma is a Professor at the Department of Electrical Engineering, Indian Institute of Technology Kanpur. He holds a PhD from IIT Delhi (2007), an M.Tech from IIT Roorkee (2003), and a B.Tech from DEI Agra (1996). His postdoctoral research includes work at the University of Tennessee (2009) and Louisiana Tech University (2008). Specialization: Fuzzy Logic, Health Monitoring, Intelligent Informatics Current Research Interests: Intelligent Data Mining, Computer Vision, Smart Grids, Biomedical Applications His research focuses on Fuzzy Systems , Machine Learning , and Health Monitoring with applications to power systems, biomedical data, and wireless sensor networks. He has developed technologies like the Transducers and Instrumentation Virtual Laboratory and Brain Computer Interface Laboratory , emphasizing predictive modeling and fault diagnosis. Key sponsored projects include DST-funded Fuzzy Rule-Based Image Prediction and DRDO-supported Visual Surveillance Systems . His work spans 15+ years of interdisciplinary publications in journals and conferences. Scientific Awards : Devendra Shukla Young Faculty Research Fellowship (2013-16) He has served as Associate Editor for journals and Chairman of IEEE chapters, with leadership roles in academic administration at IIT Kanpur.

Jia Diمشاهده پروفایل

استاد

• Asynchronous Integrated Circuit Design
• Hardware Security
• Extreme Environment Electronics
• +۳ مورد دیگر

Jia Di serves as Professor and Department Head of the Department of Electrical Engineering and Computer Science at the University of Arkansas, holding the Rodger S. Kline Endowed Leadership Chair. He has been with the institution since 2004, progressing from Assistant Professor to his current leadership position within the College of Engineering. Education: B.S. in Automatic Control, Tsinghua University (1997) M.S. in Automatic Control, Tsinghua University (2000) Ph.D. in Electrical and Computer Engineering, University of Central Florida (2004) Research Focus: Dr. Di's work centers on asynchronous integrated circuit design and hardware security , with emphasis on Multi-threshold Null Convention Logic (MTNCL) for ultra-low-power secure systems. His research spans hardware Trojan detection, polymorphic logic gates, extreme environment electronics, and security solutions for IoT infrastructure. His Trustable Logic Circuit Design Lab has pioneered techniques for side-channel attack mitigation and cold boot attack prevention through self-destructive memory mechanisms. Publication Trends: Recent publications reveal a strategic shift toward hardware security applications for renewable energy systems and IoT edge devices, while maintaining core expertise in asynchronous circuit design. His work increasingly integrates machine learning (e.g., graph neural networks for hardware Trojan detection) and cross-platform verification frameworks, demonstrating evolution from pure circuit design to holistic cybersecurity solutions for critical infrastructure. Scientific Recognition: Senior Member of IEEE Eminent Member of Tau Beta Pi Elected Member of the National Academy of Inventors Research Leadership: Dr. Di has secured over $23 million in research funding for his Trustable Logic Circuit Design Lab, supporting development of 6 U.S. patents and two authoritative books. His lab collaborates with federal agencies and industry partners on hardware security challenges, with recent grants focusing on photovoltaic system protection and extreme-environment electronics. While specific student names aren't documented here, his extensive publication record indicates significant graduate mentorship in hardware security and asynchronous design. Lab Infrastructure: The Trustable Logic Circuit Design Lab maintains specialized capabilities for testing circuits in extreme environments (high temperature/radiation) and developing polymorphic security mechanisms. Current projects include RF aperture security, hardware-based IoT verification systems, and digital twin implementations for power electronics with integrated trust verification.

Heather Millerمشاهده پروفایل

استادیار

• Distributed Systems
• Concurrent Programming
• Programming Languages
• +۴ مورد دیگر

Heather Miller is a tenure-track Assistant Professor in the Software and Societal Systems Department within Carnegie Mellon University's School of Computer Science. Her academic journey includes prior roles as an Assistant Clinical Professor at Northeastern University's College of Computer and Information Science and as Executive Director of the Scala Center at EPFL. Miller's research centers on distributed and concurrent computation through the lens of programming languages, with particular emphasis on data-centric systems, big data processing, and edge computing. A defining theme throughout her work is composability - enabling construction of complex distributed systems through composition of components that are correct by construction. Her projects span distributable closures, flexible serialization techniques, futures and promises for asynchronous programming, and deterministic concurrent dataflow models. Her recent publications demonstrate strong trends in applying programming language theory to practical distributed systems challenges, with increasing focus on WebAssembly instrumentation, microservice resilience, and language model pipelines. This evolution reflects her commitment to bridging theoretical foundations with real-world system requirements. Dahl-Nygaard Junior Prize (2023) Mentorship forms a significant component of Miller's academic work. She actively supervises multiple PhD, MS, and undergraduate researchers at CMU, including Christopher Meiklejohn, Matthew Weidner, Huairui Qui, Ria Pradeep, and Luke Dramko. Her service contributions span numerous top-tier conferences including PLDI, SPLASH, ECOOP, and ICSE where she has served as committee member, chair, and keynote speaker. Miller co-founded the Curry On conference to foster industry-academia dialogue, hosting successful editions in Prague, Rome, Barcelona, Amsterdam, and London. She leads research groups focused on distributed programming models and maintains strong industry connections through Two Sigma, where she holds an affiliation. Her work consistently emphasizes practical open-source implementations, primarily within the Scala ecosystem where she's been a core contributor since 2011.

Benjamin Lucien Kaminskiمشاهده پروفایل

استاد

• formal verification
• semantics
• probabilistic programs
• +۱۰ مورد دیگر

Benjamin Lucien Kaminski is a Professor at Saarland University and a Lecturer at University College London . He specializes in quantitative aspects of formal program verification , with a focus on probabilistic and quantum programs , incorrectness logic , and non-classical computation models . His research includes semantics , probabilistic program verification , expected runtimes , and explainable verification . He leads the Examination Board for B.Sc. Computer Science (English) and actively mentors PhD, Master’s, and Bachelor’s students in logic and verification. 2025 : A Taxonomy of Hoare-Like Logics (POPL), Partial Incorrectness Logic (TPSA) 2024 : Quantitative Weakest Hyper Pre (OOPSLA), Caesar: A Verifier for Probabilistic Programs (Dafny), Hoare-Like Triples (Incorrectness-track) 2023 : A Deductive Verification Infrastructure (OOPSLA), Lower Bounds (OOPSLA), A Calculus for Amortized Expected Runtimes (POPL) He has received notable awards including the Ackermann Award (2020), Best Paper at LOPSTR 2020 , and EATCS Best Paper Award at ETAPS 2016 . He has also served on program committees for leading conferences like CAV , POPL , and LICS , and reviewed for prestigious journals such as Journal of the ACM and TOCL .

Jamal Atifمشاهده پروفایل

استاد

• Artificial Intelligence
• Responsible AI
• Privacy Preservation in Machine Learning
• +۴ مورد دیگر

Jamal Atif is a Professor at Paris-Dauphine University and holds multiple significant leadership positions including Project Manager for 'Data Science and Artificial Intelligence' at the Institute of Information Sciences and their Interactions (INS2I) of the CNRS, Deputy Scientific Director of 3IA PRAIRIE, Head of the MILES team/project at LAMSADE (UMR CNRS-Université Paris-Dauphine), Co-leader of the Transverse Artificial Intelligence Program at PSL University, and Director of the Dauphine Numérique program. Professor Atif's primary research focuses on the foundations of responsible artificial intelligence, with specific expertise in privacy preservation in machine learning, robustness of deep learning algorithms to malicious attacks, causality, and explainability. His work bridges theoretical foundations with practical applications in security and reliability of AI systems. He has developed innovative approaches to address adversarial vulnerabilities in machine learning models and has made significant contributions to privacy-preserving techniques in data analysis. His publication record demonstrates a consistent focus on robust and trustworthy AI systems, with recent work exploring differential privacy in clustering, adversarial robustness, and explainable AI. The research spans theoretical foundations in logic and knowledge representation to practical applications in finance, healthcare, and computer vision. His publications appear in top-tier venues including Machine Learning journal, Neural Information Processing Systems, and International Joint Conferences on Artificial Intelligence. Scientific Awards: Recipient of two awards from the North American Society of Radiology for his thesis work Professor Atif has co-supervised or is currently supervising around fifteen doctoral students, demonstrating his commitment to mentoring the next generation of AI researchers. His leadership extends to directing major institutional programs including Dauphine Numérique and the Transverse Artificial Intelligence Program at PSL University, where he shapes strategic research directions in AI. He leads the MILES team/project at LAMSADE, which focuses on foundational aspects of machine learning and artificial intelligence. The team's research spans theoretical aspects of learning algorithms to practical applications requiring robust and reliable AI systems, with particular emphasis on security and privacy considerations in modern machine learning deployments.

Alexandre Bartelمشاهده پروفایل

استاد

• software security
• software engineering
• system security
• +۵ مورد دیگر

Alexandre Bartel is a Professor in the Department of Computing Science at Umeå University, Sweden, specializing in software security and software engineering. His research focuses on system security and analysis of permission-based software stacks, particularly Android. With numerous publications in top-tier security and software engineering conferences and journals, Bartel has established himself as a leading researcher in vulnerability analysis and software security. Bartel's research interests primarily center around software security, with a particular emphasis on Java and Android ecosystems. His work delves into vulnerability analysis, deserialization attacks, control flow integrity, and security mechanisms for complex software systems. He investigates how to verify security properties through efficient algorithms and examines existing software layers from a security perspective. His research bridges theoretical security concepts with practical implementation challenges in real-world systems. Analysis of Bartel's recent publications reveals a strong focus on Java deserialization vulnerabilities, control flow integrity mechanisms, and Android security. His work demonstrates a consistent trajectory from fundamental vulnerability analysis to developing practical security solutions and benchmarks. The research spans both theoretical frameworks and empirical evaluations, with significant contributions to understanding long-term security adoption patterns and developing tools for vulnerability detection. Scientific Awards: Most influential Paper ICSE N-10 Award for IccTA: Detecting Inter-Component Privacy Leaks in Android Apps Bartel actively contributes to the academic community through service roles, having served on program committees for major conferences including ASE, ESEC/FSE, ICSE, and FSE. His research has practical implications for software developers and security practitioners, particularly in the areas of vulnerability detection and security mechanism implementation. While specific grant information isn't detailed in the provided materials, his extensive publication record suggests successful funding for his research initiatives. Though not explicitly detailed in the provided information, Bartel's research likely involves collaboration with students and researchers on projects related to software security analysis. His work on benchmarks like Gleipner and CONFUZZION suggests involvement in developing tools and resources for the security research community.

• Bioinformatics
• Computational Biology
• Pharmaceutical Drug Discovery & Development
• +۱۳ مورد دیگر

Leonard Wesley is an Associate Professor in the Department of Computer Science at the College Of Science, San Jose State University. His research spans interdisciplinary domains at the intersection of Bioinformatics , Computational Biology , and Machine Learning , with specific applications in Pharmaceutical Drug Discovery , Genomic Data Analysis , and Autonomous Robotics . Education: Ph.D. in Computer Science, University of Massachusetts M.S. in Computer Science, University of Massachusetts B.A. in Physics and Math, Northeastern University Research Interests include Approximate Reasoning (probabilistic, evidential, and fuzzy logic), Agent-Oriented Systems , and Sensor Fusion . His work applies these methodologies to Drug Portfolio Management , Protein Structure Scoring , and Medical Diagnostics . Publication Trends show a consistent focus on Computational Biology , Robotics , and Uncertainty Quantification over four decades. Early work in Computer Vision evolved into modern applications in Pharmaceutical Analytics and AI in Aerospace . Key Projects include SVM-based drug affinity prediction, evidence-driven decision support systems for biopharma, and real-time agent development frameworks like ROADS. He has contributed to CFD code control and Mobile Network Congestion solutions. Collaborations with institutions like NASA, Los Alamos National Laboratory, and international conferences (WMSCI, ICINCO, AIAA) highlight his cross-disciplinary impact. His teaching includes Artificial Intelligence and Bioinformatics courses.