جست‌وجوی استاد و پژوهشگر

Eric Koskinenمشاهده پروفایل

دانشیار

• Concurrent Programming
• Formal Verification
• Programming Languages
• +۳ مورد دیگر

Eric Koskinen is the Charles Berendsen Chair Associate Professor in the Department of Computer Science at Stevens Institute of Technology. His research focuses on improving concurrent software development for multi-core and distributed systems through advances in programming languages, verification techniques, and formal methods. He holds a PhD from the University of Cambridge and has held roles at Yale, NYU, and industry positions at IBM, Microsoft, and Amazon. Education: PhD (2013) University of Cambridge, MS (2008) Brown University, BS (2001) William & Mary Research Interests: Concurrent programming, formal verification, programming language design, and distributed systems Recipient of over $5M in grants from NSF/ONR/DARPA. Active in conference organization (POPL, PLDI) and has developed verification tools like CityProver and Veracity. Advises PhD students in concurrency research and teaches courses on programming languages, discrete structures, and software verification.

Rachida Dssouliمشاهده پروفایل

استاد

• Software Engineering
• Quality Assurance
• Service Engineering
• +۷ مورد دیگر

Rachida Dssouli is a Professor at the Concordia Institute for Information Systems Engineering (Concordia University). Her research focuses on advanced software engineering methodologies, quality assurance systems, and distributed computing frameworks. She specializes in model-based testing, federated learning optimization, and big data quality management. Her work integrates formal verification techniques with modern machine learning approaches to address challenges in edge computing, IoT, and safety-critical systems. Key research areas include: Development of hybrid swarm intelligence algorithms for optimizing large language model deployment in edge-cloud environments Design of reinforcement learning frameworks for robotics motion planning and IoT device scheduling Creation of interpretable machine learning tools for fault detection in software systems Establishment of holistic big data quality frameworks for continuous monitoring and unstructured data analysis Formal verification methods for avionics systems using multi-agent models Her recent work demonstrates trends toward AI-driven solutions for testing methodologies (e.g., SHAP-Driven fault detection) and edge-cloud integration (e.g., MIMO-based computation offloading optimization). The 2025 publications highlight advancements in federated learning and trust-aware IoT scheduling. Earlier works (2018-2020) emphasize foundational contributions to cloud trust models, big data quality metrics, and safety-critical system testing. Her research also addresses emerging technologies for developing countries through frameworks like neurodegenerative disease monitoring systems and mobile application requirements engineering. She has contributed to service-oriented architectures for healthcare systems and cloud-based resource orchestration strategies.

Jinqiu Yangمشاهده پروفایل

دانشیار

• Software Engineering
• Automated Program Repair
• Software Testing
• +۴ مورد دیگر

Jinqiu Yang is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on software reliability, automated program repair, software testing, and quality assurance of machine learning systems, particularly in autonomous vehicles. He holds a PhD and MASc from the University of Waterloo and a B.Eng. from Nanjing University. Yang has been a tenure-track faculty member at Concordia since 2018, following research roles at IBM Watson and IBM CAS. Research Interests: Automated Program Repair Software Testing Machine Learning Systems Text Analytics of Software Artifacts Mining Software Repositories Autonomous Systems Quality Assurance Key Contributions: His recent work includes detecting concept drifts in ML systems (ICSE-25) and investigating social bias in LLM-generated code (AAAI-25). He leads the O-RISA Lab and has authored over 50 peer-reviewed publications, including distinguished papers at MSR-2018. Yang currently holds grants such as the NOVA FRQNT-NSERC Program (2024-2027) and the NSERC Discovery Grant (2019-2025). Service & Awards: Editorial Board Member of the Empirical Software Engineering Journal (EMSE) and active PC member in top venues like ICSE and FSE. Recipient of the IBM CAS Fellowship and ACM SIGSOFT Distinguished Paper Award. Teaching & Students: He mentors students in Master's and PhD programs, with funding available. His lab focuses on cutting-edge topics like secure code generation and autonomous vehicle reliability.

Mehdi Norouziمشاهده پروفایل

دانشیار

• Computer Vision
• Video Analysis
• Deep Learning
• +۲ مورد دیگر

Mehdi Norouzi is an Associate Professor at the University of Cincinnati in the Department of Computer Science. His research focuses on video structure analysis and deep video understanding, with applications in medical imaging and social media analysis. Research interests include: Video temporal segmentation and scene detection Deep learning approaches for video summarization Language-guided video analysis frameworks Medical video processing applications His publications demonstrate a consistent focus on applying machine learning techniques to structural engineering problems through 2015-2018, shifting toward computer vision and transformer networks in recent years (2022-2023). This reflects an evolution from infrastructure diagnostics to advanced video analysis. Dr. Norouzi has secured multiple research grants from entities including the Federal Highway Administration and Department of Transportation, focusing on video analysis, structural monitoring, and machine learning applications. Current projects involve facial/skeletal tracking for medical applications and soil modulus prediction models.

• Cloud Computing
• High Performance Computer Architectures
• Parallel and Distributed Processing
• +۳ مورد دیگر

Dr. Robert K. Chun is a Professor in the Department of Computer Science at San José State University (SJSU), part of the College of Engineering. He holds a BSEE (1979), MSCS (1981), and Ph.D. (1989) from UCLA. With 20+ years in industry, he joined SJSU as a full-time faculty in 2001. His research focuses on Cloud Computing, parallel processing, high-performance architectures, and AI. He received NASA Faculty Fellowships (2002-2003) and holds a U.S. patent for real-time expert systems integration. Education: Bachelor of Science, Electrical Engineering, UCLA (1979) Master of Science, Computer Science, UCLA (1981) Doctor of Philosophy, Computer Science, UCLA (1989) Research Interests: Cloud Computing architectures and scalability High-performance computing and parallel algorithms Software engineering for distributed systems CAD tools for VLSI design verification Artificial intelligence and neural networks Publications highlight advancements in parallel processing, distributed systems, and compiler optimization. Notable works include adaptive transactional memory algorithms, wireless cluster computing frameworks, and EJB performance measurement tools. His NASA-funded research at Ames Supercomputing Center explored parallel computing applications. Advising and Grants: Advised 16 Master’s theses, including topics like dynamic clusters and intelligent debuggers Contributed to industry-university partnerships through NASA collaborations Labs/Teams: Active in SJSU’s parallel processing and computer architecture research groups, contributing to course development in advanced parallel processing and operating systems.

Jennifer K. Allenمشاهده پروفایل

دانشیار

• Literacy Education
• Writing Pedagogy
• Culturally Diverse Learners
• +۲ مورد دیگر

Jennifer K. Allen is Associate Professor in Literacy and Special Education at University of West Georgia's College of Education. Her research examines writing pedagogy, critical media literacy, and culturally responsive teaching. She holds B.S. and Ph.D. degrees from University of Georgia and M.Ed. from University of West Georgia. Allen's scholarship focuses on writing identity development, teacher self-efficacy, and literacy engagement strategies for multilingual learners. Her 15 most recent publications explore prosody instruction effects, media literacy education, and innovative writing approaches like writing marathons. Methodologically, her research employs mixed-methods designs examining classroom practices, teacher perceptions, and student outcomes. Recent collaborations investigate read-aloud frequency variations and digital storytelling for countering deficit perspectives. With ten years K-12 teaching experience, Allen connects research to classroom practice. She holds endorsements in Gifted Education, ESOL, and Reading Instruction. Her courses include Writing Development & Instruction and Trends in Language & Literacy Education.

Alexandre Violleمشاهده پروفایل

پژوهشگر

• Social studies of science
• Political sociology of public action
• Economic sociology
• +۵ مورد دیگر

Dr. Alexandre Violle is a sociologist specializing in the intersections of science and technology studies, economic sociology, and political sociology. He is currently coordinating the "Mapping Controversies" course at Sciences Po's School of Management and Innovation and has a research affiliation with the Center for the Study of Social Movements at the School for Advanced Studies in the Social Sciences (EHESS). Previously, he completed his PhD at the Center for the Sociology of Innovation (CSI) of PSL-Mines Paris University and conducted postdoctoral research funded by the Institut Francilien Recherche Innovation Société (IFRIS). His academic journey includes: Doctorate in sociology of science and technology from École des Mines de Paris Postdoctoral research at Centre d'étude des mouvements sociaux of École des Hautes Etudes en Sciences Sociales (2021-2023) PhD research at Center for the Sociology of Innovation (CSI) of PSL-Mines Paris University Dr. Violle's research examines how expertise drawing on economic or financial knowledge transforms public action in France and Europe across various sectors. His work spans the sociology of science and technology, economic sociology, and political sociology, with particular focus on: Social studies of science: knowledge production processes, controversies, science policy Political sociology of public action: instrumentation of public action, regulation, state and European action recomposition, energy and economic policies Economic/finance sociology: valuation, green finance, theories of money and currency, the role of economic expertise in shaping public action His current research focuses on the "Anticipation: the futures of French subsoil use" (ANTICIP) project, a five-year initiative examining how different actors conceptualize and plan for the future use of subsoil resources in France. This work builds on his previous research on the European Banking Union and climate stress testing in financial systems, revealing consistent patterns in how technical instruments shape governance approaches to complex societal challenges. Dr. Violle's scholarly contributions have been recognized through numerous publications in prestigious journals. His research has explored topics including: The political dimensions of financial supervision in the European context The material politics of climate stress tests in Europe The territorialization of industry during energy transitions Scaling imperatives in technological innovation Critical mineral supply chains and environmental governance As an educator, Dr. Violle has supervised numerous master's students through their thesis work and has been instrumental in developing innovative pedagogical approaches. He has coordinated the "Mapping Controversies" course at Sciences Po for several years, guiding students through complex analyses of science-society interactions. His teaching spans multiple institutions including École des Mines, IEP de Paris, and Sciences Po, demonstrating his commitment to bridging theoretical knowledge with practical application in understanding contemporary societal challenges. Dr. Violle is actively involved in collaborative research initiatives, currently working with teams from Ecole des Mines de Paris, IMT Mines Alès, and Bureau de Recherches Géologiques et Minières (BRGM) on the subsoil resources project. His interdisciplinary approach bridges sociology, political science, and economic analysis to address contemporary challenges in governance and public policy, with particular relevance to the energy transition and financial regulation in the European context.

• Inverse Problems
• Geometry
• Partial Differential Equations (PDEs)
• +۷ مورد دیگر

Sean Holman is a Senior Lecturer in Applied Mathematics at The University of Manchester, specializing in inverse problems, geometry, and partial differential equations. His research focuses on advancing theoretical frameworks and computational methods for imaging and material analysis, with applications in medical imaging, geophysics, and engineering. He is affiliated with the Industrial and Applied Mathematics and Inverse Problems research groups, contributing to the Digital Futures research beacon. His work integrates advanced mathematical techniques such as Radon transforms, tensor field analysis, and microlocal analysis to solve challenging inverse problems. Recent collaborations include studies on elastic strain reconstruction, electromagnetic parameter recovery, and agent swarm coordination under communication constraints. Dr. Holman has organized significant academic events like the 'Rich and Nonlinear Tomography' conference (2023) and the 'Microlocal Analysis meets Data Science' workshop (2018), fostering interdisciplinary research. His contributions span theoretical developments and practical applications in imaging modalities like SPECT and proton therapy range verification.

Kenneth Patersonمشاهده پروفایل

استاد

• Cryptography
• Information Security
• Applied Cryptography
• +۳ مورد دیگر

Prof. Kenneth Paterson is a Full Professor at ETH Zürich's Department of Computer Science, leading the Applied Cryptography Group. He has held academic positions at Royal Holloway, University of London, and Hewlett-Packard Laboratories. His research focuses on cryptographic protocol analysis, provably secure solutions, and real-world system vulnerabilities. Key contributions include the Lucky 13 TLS attack, analyses of Telegram and OpenPGP, and work on cryptographic transition strategies. He has been recognized with awards such as the Google Distinguished Paper Award, IACR Fellowship, and ETH Golden Owl Teaching Award. His leadership roles include Department Head at ETH Zurich and Programme Chair for EUROCRYPT 2011. Paterson actively engages in standardization efforts through IRTF's CFRG and co-founded the Real World Cryptography workshop series. Education: B.Sc. (Mathematics, University of Glasgow, 1990), Ph.D. (Mathematics, University of London, 1993). Career highlights include EPSRC Leadership Fellowship (2010–2015) and IACR Distinguished Lecture at EUROCRYPT 2025. Research Interests: Cryptography, Information Security, Applied Cryptographic Protocols, TLS Analysis, Post-Quantum Cryptography, and Privacy-Preserving Technologies. Notable projects include cryptographic analysis of TLS, SSH, and cloud storage systems. Awards and Recognition: Google Distinguished Paper Award (2012) Applied Networking Research Prize (2013) IACR Fellow (2017) ETH Golden Owl Teaching Award (2022) Multiple Best Paper Awards at ACM CCS, CHES, and IEEE Security & Privacy Advising and Grants: Supervised students like Francesca Falzon and led projects funded by EPSRC, IRTF, and industry collaborations. Contributions to cryptographic agility and transition strategies for Internet protocols. Labs/Teams: Founder and Head of ETH Zurich's Applied Cryptography Group, associated with the Institute for Information Security. Collaborates with industry on cryptographic protocol development and security audits.

Guowei Yangمشاهده پروفایل

مدرس ارشد

• Software Engineering
• Machine Learning
• Programming Languages
• +۱ مورد دیگر

Dr. Guowei Yang is a Senior Lecturer at the School of Electrical Engineering and Computer Science , The University of Queensland, Australia. He transitioned to this role in 2021 after serving as a tenured Associate Professor at Texas State University's Department of Computer Science. His research focuses on the intersection of Software Engineering Machine Learning Programming Languages Cybersecurity with an emphasis on system reliability and security. His recent publications (2022-2025) analyze: Android API compatibility challenges Symbolic execution optimizations Fuzzing techniques for JVM security Moving target defense strategies Automated patch generation Constraint classification in code analysis He leads a research group seeking students with backgrounds in software engineering, formal methods, and AI. Current funding includes a 2023-2026 Oracle Corporation grant for DevSecOps analysis. Dr. Yang supervises multiple PhD and Master's projects, often as principal advisor, focusing on topics like deep learning testing, IoT analysis, and DevSecOps integration.

Anirudh Sivaramanمشاهده پروفایل

استادیار

• Computer Networks
• Network Programmability
• Distributed Systems
• +۳ مورد دیگر

Anirudh Sivaraman is an Assistant Professor of Computer Science at New York University's Courant Institute, specializing in computer networks and programmability. He holds a PhD from MIT (2017) and a BTech from IIT Madras (2010). His research focuses on enabling ubiquitous network programmability through hardware-software systems, including compilers, runtimes, and applications like distributed consensus and financial exchanges. Education: Ph.D. in Computer Science, MIT (2012–2017) S.M. in Computer Science, MIT (2010–2012) B.Tech in CSE, IIT Madras (2006–2010) Research Interests: Network programmability (e.g., P4, Barefoot Networks) High-speed packet processing and compiler optimization Distributed systems and consensus protocols Cybersecurity in programmable networks Cloud computing and microservice autoscaling Notable Articles Trends: Focus on programmable networks (P4, NIC design) Hardware-software co-design for performance Security and isolation in multi-tenant environments Compiler-based solutions for bug detection Awards: ACM SIGCOMM Doctoral Dissertation (2017), SIGCOMM Best Paper (2017), and multiple teaching awards. Advising & Grants: PI on grants totaling $900K+ (Google, Amazon, NSF). Advises 8+ PhD/Master’s students. Serves on committees for SIGCOMM, NSDI, and HotNets. Labs/Teams: Technical advisor at Clockwork. Co-organizes workshops on programmable networks and P4 standards.

Siraj Shaikhمشاهده پروفایل

استاد

• Cybersecurity
• Systems Engineering
• Cyber-Physical Systems
• +۲ مورد دیگر

Professor Siraj Shaikh is a Professor in Systems Security at Swansea University (UK) with joint appointment as Visiting Professor at Nebrija University (Spain). His research specializes in cybersecurity for automotive and transport systems, focusing on cyber-physical systems security. He co-founded CyberOwl, a maritime security analytics company. His research explores the intersection of cybersecurity, systems engineering and computer science, particularly addressing security challenges in connected vehicles and transportation infrastructure. Current work examines threat modeling, risk assessment frameworks, and security validation methods for automotive systems. Professor Shaikh's publications demonstrate consistent focus on automotive cybersecurity, evolving from fundamental security frameworks to specialized applications in vehicular networks and hardware security. Recent work shows increased emphasis on practical implementations and supply chain security. Honors include: Royal Academy of Engineering Industry Fellowship (hosted at HORIBA MIRA) His research has been funded by EPSRC, ESRC, Lloyds Register Foundation, DSTL, British Council and Royal Academy of Engineering. He has authored the book Formal Methods for Software Engineering (Springer, 2022) and leads the Systems Security research group.

• Functional Safety
• Safety Instrumented Systems (SIS)
• Cybersecurity in Industrial Systems
• +۵ مورد دیگر

Mary Ann Lundteigen is a Professor in instrumentation systems and safety at NTNU’s Department of Engineering Cybernetics, part of the Faculty of Information Technology and Electrical Engineering. She holds an MSc (1993) and PhD (2009) in Engineering Cybernetics from NTNU, with 15+ years of industry experience across Phillips Petroleum, Nidar AS, DNV, and SINTEF. She has led major research initiatives including SFI SUBPRO (2014–2023) and SFI Autoship (2019–2022), focusing on subsea production, autonomous ships, and cybersecurity for safety-critical systems. Her research emphasizes functional safety of industrial control systems, cybersecurity compliance with standards like IEC 62443, and the integration of AI in safety-critical environments. She leads projects such as APOS 2.0 (digital lifecycle management) and CyberBarrier Management, while supervising multiple PhD students and postdocs. Lundteigen co-authored over 100 publications and received the ExxonMobil Doctoral Prize (2009) for her thesis on SIS reliability. Professional roles include: Co-director of SFI SUBPRO Director of SFI Autoship’s initial phase Adjunct Professor at NTNU (2013) Member of IEC 61511 maintenance team and PDS forum organizing committee Current research focuses on: Cybersecurity threats to SIS AI applications in safety systems Digital twins for safety demonstration Industry 4.0 frameworks like OPC UA Her work bridges academia and industry, with active projects funded by the Norwegian Research Council and industrial partners like Equinor and DNV.

James Caverleeمشاهده پروفایل

استاد

• Machine Learning
• Recommender Systems
• Information Retrieval
• +۷ مورد دیگر

James Caverlee is a Professor in the Department of Computer Science and Engineering at Texas A&M University, and a Visiting Researcher at Google DeepMind. He holds a Ph.D. from Georgia Institute of Technology (2007), and degrees from Stanford University and Duke University. His research focuses on trustworthy, efficient, and personalized machine learning systems, including Recommender Systems, Large Language Models (LLMs), and bias mitigation. Recent work emphasizes fairness, efficiency, and transparency in AI, with applications in conversational systems, speech, and medical QA. He has been recognized with an NSF CAREER Award, AFOSR Young Investigator Award, and DARPA Young Faculty Award. His group has published extensively at top venues like KDD, EMNLP, WWW, SIGIR, and WSDM. Education: Ph.D., Computer Science, Georgia Tech, 2007 M.S., Computer Science & Engineering-Economic Systems, Stanford University, 2001–2000 B.A., Economics, Duke University, 1996 Research Interests: Machine Learning, Recommender Systems, NLP, LLMs Bias Mitigation, Efficiency, Personalization Social Computing, Information Retrieval Awards: NSF CAREER Award (2012) AFOSR Young Investigator (2012) SIGIR Test of Time Honorable Mention (2022) Grants: Supported by NSF, AFOSR, DARPA, and industry (Google, Amazon). Labs/Teams: InfLab research group at Texas A&M, collaborating with Google DeepMind. His publications address topics like adversarial attacks on LMs, gender bias in podcasts, and efficient recommendation algorithms. Recent trends show focus on generative AI for personalization and ethical AI challenges.

• Static Analysis
• Logic Programming
• Program Verification
• +۴ مورد دیگر

Manuel V. Hermenegildo is a Professor at the Universidad Politécnica de Madrid, Spain. He is a prominent researcher in the field of programming languages and static analysis, with significant contributions to logic programming, program verification, and formal methods. His work focuses on advancing static analysis techniques, compiler optimization, and energy-efficient computing. He has co-authored numerous papers and organized international conferences such as LOPSTR and SAS, demonstrating his leadership in academic and research communities. His research explores topics including abstract interpretation, runtime checking, and parallel logic programming systems. He is a key contributor to the Ciao Prolog system, emphasizing comprehensive tool integration and formal methods. His research interests span static analysis frameworks, program verification, resource usage analysis, and energy efficiency in computing. He has developed methodologies for optimizing program performance while ensuring correctness, with applications in both theoretical and applied domains. His work often bridges the gap between high-level program analysis and low-level hardware constraints, particularly in embedded systems. Recent trends in his publications include advancements in static cost analysis, dynamic inference of invariants, and tools for incremental assertion checking. His collaborations with institutions like the University of Copenhagen and the University of Kent reflect a global network in advancing computational logic and software engineering. He has been actively involved in academic service, including editorial roles for conference proceedings and journals. His contributions highlight a commitment to both foundational research and practical tools for the programming language community.