جست‌وجوی استاد و پژوهشگر

Kai-Hsiung Changمشاهده پروفایل

استاد

• Software Testing
• Software Comprehension and Visualization
• Software Complexity Metrics
• +۷ مورد دیگر

Kai-Hsiung Chang is a Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering. He has been a faculty member since 1986, progressing from Assistant to Associate Professor in 1991, and to full Professor in 1998. He served as Department Chair from 2006 to 2016 and was honored with the Alumni Professorship from 2004 to 2009. Ph.D., Electrical and Computer Engineering, University of Cincinnati, 1986 M.S., Electrical and Computer Engineering, University of Cincinnati, 1982 Diploma, Electrical Engineering, Taipei Institute of Technology, 1977 Dr. Chang's research focuses on software testing, software comprehension and visualization, complexity metrics, information assurance education, computer supported cooperative work (CSCW), and artificial intelligence in software engineering. His work integrates formal methods and usage profiles to enhance software quality and safety. He has led research sponsored by the National Science Foundation (NSF) and the Department of Defense (DoD), particularly in pervasive and mobile computing and information assurance education. His recent publications reflect a strong focus on software testing methodologies, formal specification-based validation, collaborative systems, and intelligent software tools. Themes include object-oriented testing, complexity measurement, CSCW, and AI-driven test generation, indicating a long-standing commitment to improving software reliability and development processes. Alumni Professorship, Auburn University (2004–2009) ACM Certificate of Appreciation for Outstanding Service (1997) IEEE Senior Member INFOSEC Professional Certification (2005) Multiple Outstanding Teaching Awards at Auburn University (1989, 1992, 1997) Summer Faculty Fellowship at NASA Marshall Space Flight Center (1995) Dr. Chang has advised over 50 graduate students, including numerous Ph.D. and Master’s candidates, many of whom now hold academic and industry positions. He has served on NSF and DHS fellowship review panels, contributed to ABET accreditation as a commissioner and program evaluator, and participated in the IEEE-Computer Society/ACM Curriculum Committee for Software Engineering. He also served as Vice President of the International Society of Applied Intelligence. He has led significant research initiatives, including NSF-sponsored REU programs in pervasive computing, and has been deeply involved in curriculum development and professional service. His lab and research group have focused on software quality, intelligent systems, and collaborative environments, fostering interdisciplinary work in software engineering and AI.

Francois Sieweمشاهده پروفایل

عضو هیئت علمی

• Computer Security
• Pervasive Systems
• Formal Methods
• +۶ مورد دیگر

Francois Siewe is a Reader in Computer Science at De Montfort University (DMU), affiliated with the School of Computer Science and Informatics within the Faculty of Computing, Engineering and Media. He conducts research in the Software Technology Research Laboratory (STRL) and the Cyber Technology Institute (CTI). His work spans formal methods, pervasive systems, and cybersecurity. His research interests include: Computer Security Pervasive Systems Formal Methods Process Calculi Formal Verification The recent publications highlight a strong trend in applying formal techniques to software modeling and verification, integrating AI for health and environmental monitoring, and advancing software quality assessment. His work often bridges theoretical foundations with practical system design, particularly in context-aware and distributed environments. Scientific awards: Research Journal of Textile and Apparel (RJTA) Excellent Paper Award 2011 Francois Siewe actively supervises postgraduate research. He is first supervisor for Ahmed Mohammed Alalshuhai, Abdulgader Zaid Almutairi, Saud Maqed Almutairi, Muslit Awadh Alotaibi, Asma Abdulghani Qasem Al-Shargabi, Elena Chernikova, and Abdulghani Mahmoud Suwan. He serves as second supervisor for Abdullah Shawan Alotaibi and Amr Mohsen Jadi. While specific grants are not listed, his past involvement in EPSRC-funded projects (e.g., MELANGE) indicates experience with competitive research funding. He is a key member of the Software Technology Research Laboratory (STRL), contributing to its focus on software engineering, cybersecurity, and ambient intelligence.

Joel Grodsteinمشاهده پروفایل

مدرس

• VLSI Design
• Computer Architecture
• Computer-Aided Design (CAD)
• +۴ مورد دیگر

Joel Grodstein is a Lecturer in the Department of Electrical Engineering at Tufts University's College of Engineering. He holds a BSEE from Case Western Reserve University (1981) and an MSCS from the University of Utah (1986). His research spans VLSI design, computer architecture, and interdisciplinary bioelectricity studies, focusing on the intersection of hardware-software systems and biological applications. He teaches courses on real-time embedded systems, parallel computing, bioelectricity, and digital design verification. His career includes roles at Digital Equipment Corporation, Compaq, Intel, and now academia. His recent work bridges computational modeling of bioelectric networks with traditional hardware design, as seen in collaborations with Mike Levin's lab at Tufts. Courses like EE 123 (Bioelectricity) and new offerings like EE 152 (Real-Time Embedded Systems) reflect this dual focus. Publications emphasize symbolic timing analysis, CAD tools for VLSI, and bioelectric systems. He has advised no listed students but collaborates actively with industry partners (e.g., NVIDIA for EE 165). His lab work involves biophysical modeling and synthetic biology projects, as detailed in his recent bioelectricity-related papers.

Aviral Kumarمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Reinforcement Learning
• +۳ مورد دیگر

Aviral Kumar is an Assistant Professor in the School of Computer Science at Carnegie Mellon University (CMU), jointly appointed in the Computer Science Department (CSD) and Machine Learning Department (MLD). He earned his PhD from UC Berkeley in 2023, where he received prestigious awards including the CV Ramamoorthy Distinguished Research Award, Apple PhD Fellowship, and Facebook PhD Fellowship. His research focuses on reinforcement learning (RL), particularly offline RL, scaling RL methods, and their intersection with foundation models. He leads the CMU AI & Reinforcement Learning (AIRe) lab, exploring core RL algorithms, robotics applications, and AI foundation models. Education: PhD in Computer Science from UC Berkeley (2023) Research Interests: Reinforcement Learning Offline Reinforcement Learning Robotics Foundation Models His lab emphasizes scalable RL techniques and real-world applications. Current advisees include Bhavya Kumar Agrawalla and Max Sobol Mark. Notable awards include the CV Ramamoorthy Distinguished Research Award for pioneering contributions to CS research. Lab activities and future work focus on advancing RL for autonomous systems and integrating foundation models into decision-making frameworks. The lab recruits PhD students annually from CMU SCS programs (CS, ML, RI). Undergraduates and MS students can apply via a dedicated form for research opportunities.

• Software Engineering
• Cyber-Physical Systems
• Real-Time Systems
• +۴ مورد دیگر

Seung Yeob SHIN is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg. He holds a PhD from the University of Massachusetts Amherst (2016), specializing in software engineering with a focus on system modeling and analysis through simulation and model checking frameworks. His work is centered at the Software Verification and Validation (V&V) Lab , led by Prof. Lionel Briand. Research Interests: Software Engineering Methodologies Cyber-Physical Systems Testing Real-Time Systems Analysis AI-Driven Testing Techniques Model Checking & Simulation Key Contributions: Pioneering work on fuzzing techniques for SDN controllers Development of probabilistic WCET estimation methods Advancements in metamorphic testing for CPS Control theory-based stress testing frameworks Publications: Over 30 peer-reviewed articles focusing on testing methodologies for real-time systems, cyber-physical systems, and quantum programming analysis. Recent trends emphasize AI integration in software validation and uncertainty-aware system design. Labs & Teams: Active member of the V&V Lab, collaborating on hardware-in-the-loop testing and embedded system validation projects.

Ben Greenmanمشاهده پروفایل

پژوهشگر

• Gradual Typing
• Formal Methods
• Programming Languages
• +۳ مورد دیگر

Ben Greenman is a Researcher at Brown University , specializing in Gradual Typing , Formal Methods , and Programming Language Design . He has developed tools like Forge for teaching formal methods FlowFPX for floating-point exception debugging CnD for specification visualization His work bridges theoretical advancements and practical software engineering challenges. Research Trends: Recent publications focus on Temporal logic misconceptions (2024-2025) Gradual typing performance (2023-2025) Tool-driven formal methods education (2023) Language design for macro systems (2023) Numerical computation reliability (2023) Key Contributions: Unified deep/shallow type systems Blame assignment strategies Collapsible contracts Corpus studies for type analysis Visual debugging frameworks

Peter Popovمشاهده پروفایل

پژوهشگر

• Software Reliability
• System Dependability
• Software Fault-Tolerance
• +۵ مورد دیگر

Peter Popov is a Reader at the Centre for Software Reliability (CSR) , City St George's, University of London , where he has been employed since 1997. He specializes in software dependability , fault tolerance , and stochastic modeling of critical infrastructures. Before his current position, he was an Associate Professor at the Bulgarian Academy of Sciences (1990-1997) and a Research Fellow at City St George's. Peter's academic journey began with a PhD in Computer Science from the Kiev National University of Technologies and Design (1989), following his BEng in Computer Engineering from the National Technical University of Ukraine (KPI, 1982). He has worked as a visiting scientist at renowned institutions including the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign , LAAS-CNRS in Toulouse, and Duke University . His research interests span Software reliability assessment System dependability Software fault-tolerance Performance evaluation Interdependencies of critical infrastructures He has contributed extensively to projects such as ReSIST , IRRIIS , DISPO , and AFTER , focusing on the dependability of composite systems and critical infrastructure resilience. Key publication trends reveal expertise in Stochastic modeling of autonomous vehicle safety Software diversity for fault tolerance Interdependency analysis in critical systems Bayesian reliability assessment Performance evaluation of distributed protocols Security implications in cyber-physical systems Peter has supervised several PhD students , including those researching autonomous vehicle resilience , safety assurance with ML components , and adaptable web services . His professional activities include serving on program committees for ISSRE , SAFECOMP , and EDCC conferences, as well as editorial contributions to CEUR Workshop Proceedings . He is proficient in Bulgarian , English , and Russian , with peer-review capabilities in all three languages.

• Software Engineering
• Code Readability
• API Compatibility
• +۵ مورد دیگر

Rocco Oliveto is a prominent researcher in software engineering with extensive contributions across multiple domains including code quality assessment, smart contracts, Docker configuration analysis, and healthcare applications of AI. His collaborative work spans numerous institutions, with frequent co-authorship with researchers such as Simone Scalabrino, Gabriele Bavota, and Emanuela Guglielmi. Dr. Oliveto's research interests focus on practical software engineering challenges with emphasis on code readability, API compatibility, bug prediction, and smart contract maintenance. His work bridges theoretical research with practical applications, particularly evident in recent projects applying machine learning to healthcare diagnostics and video game quality analysis. His research demonstrates a consistent trajectory toward addressing real-world software engineering problems with innovative methodological approaches. Analysis of his recent publications reveals a strong trend toward interdisciplinary research, particularly at the intersection of software engineering and healthcare applications. His work shows increasing focus on practical applications of AI in medical diagnostics, rehabilitation technology, and patient monitoring systems, while maintaining strong contributions to core software engineering topics like code quality and developer productivity. The diversity of publication venues—from top software engineering journals like Empirical Software Engineering and ACM TOSEM to healthcare conferences like BIOSTEC—demonstrates the breadth of his research impact. Dr. Oliveto has demonstrated significant research leadership through numerous collaborative projects, particularly evident in his participation in the QualAI project focused on continuous quality improvement of AI-based systems. His work shows consistent funding support through collaborative research initiatives that bridge academic and practical software engineering concerns.

• Database Systems
• Transaction Processing
• Distributed Database Systems
• +۵ مورد دیگر

Rong Zhang is a Professor at East China Normal University's School of Computer Science and Software Engineering in Shanghai, China. With a PhD from Fudan University's Department of Computer Science and Engineering (2007), Dr. Zhang has established himself as a leading researcher in database systems, particularly in transaction processing, performance evaluation, and distributed database technologies. His extensive collaboration network includes prominent researchers like Aoying Zhou, Weining Qian, and Xiaofeng He. Dr. Zhang's research primarily focuses on database performance evaluation, transaction processing systems, workload generation, and isolation level verification. His work addresses critical challenges in modern database systems including generating realistic test databases, benchmarking transactional performance, verifying isolation levels in distributed environments, and optimizing query processing. His research has significant practical applications for database vendors and users who need reliable performance metrics and verification tools. Analysis of Dr. Zhang's recent publications (2022-2025) reveals a strong focus on database benchmarking and verification. His work on the Leopard test suite for isolation level verification represents a major contribution to ensuring database correctness. The Mirage and Touchstone projects demonstrate innovative approaches to generating enormous, query-aware databases for comprehensive performance evaluation. His research increasingly incorporates machine learning techniques, as seen in SPQO for query plan reuse and functionality-aware database tuning. Dr. Zhang has mentored numerous researchers who appear as co-authors on his papers, including Xiaotong Wang, Siyang Weng, Yuming Li, and Qingshuai Wang. His research has been supported by projects focused on database performance evaluation, transaction processing, and distributed systems. While specific grant details aren't provided in the source material, his extensive publication record across top database venues suggests sustained research funding. Dr. Zhang appears to lead or be a key member of a research group focused on database systems at East China Normal University. This group has developed several significant tools and frameworks including Leopard for isolation verification, Mirage for database generation, and Lauca for workload duplication. Their work bridges theoretical database concepts with practical system implementation, producing tools that have become influential in database research and development.

• Empirical Software Engineering
• Software Process Improvement
• Requirements Engineering
• +۷ مورد دیگر

Andreas Jedlitschka is a researcher at Fraunhofer IESE in Kaiserslautern, Germany, affiliated with the University of Kaiserslautern. He has made significant contributions to empirical software engineering, software process improvement, and experience management. His research focuses on evidence-based decision support, technology transfer, and quality in agile and AI-driven software development. PhD, University of Kaiserslautern (2009) His research interests include empirical software engineering, requirements engineering, software quality, experience management, and AI in software development. He investigates how to improve software processes through data-driven methods, empirical validation, and knowledge reuse. His work often bridges industry and academia, emphasizing practical applicability. The recent articles highlight a growing focus on AI-enabled systems, sustainability in software engineering, and data-driven technical debt management. His work spans both theoretical frameworks and industrial case studies, particularly in agile environments and safety-critical systems. He has co-organized workshops and edited conference proceedings, indicating active participation in the research community. He mentors researchers through collaborative projects and has contributed to doctoral research frameworks. His work is supported by collaborations across Europe, particularly in EU-funded projects related to software quality and AI. He is involved in initiatives like the Q-Rapids project, which supports decision-makers in managing quality in rapid software development, and contributes to building AI innovation labs with industry partners.

Jörn Müller-Quadeمشاهده پروفایل

استاد

• Cryptography
• IT Security
• Cybersecurity
• +۶ مورد دیگر

Professor Jörn Müller-Quade is a leading expert in cryptography and IT security at the Karlsruhe Institute of Technology (KIT). He serves as Director of the KASTEL — Institute for Information Security and Reliability at KIT and heads the Cryptography and Security research group. Müller-Quade is also the head of the "IT Security, Privacy, Law and Ethics" working group at the Learning Systems Platform initiated by the Federal Ministry of Education and Research. His work focuses on developing secure systems that can withstand intelligent attackers through rigorous mathematical models and cryptographic methods. Professor Müller-Quade's research spans multiple critical areas of modern digital security. His primary interests include cryptography, secure multi-party computations, privacy-preserving analytics, and the intersection of artificial intelligence with security systems. He investigates how to develop security properties that can be mathematically proven, particularly against intelligent adversaries who constantly develop new attack methods. His work on cryptographic voting procedures demonstrates how seemingly contradictory requirements like ballot secrecy and verifiable counting can be simultaneously achieved. Müller-Quade also explores how AI systems change IT security landscapes, creating both new vulnerabilities and potential defense mechanisms. Analysis of Professor Müller-Quade's publications reveals consistent focus on practical security applications with societal impact. His work spans election security, patient data protection, surveillance debates, and industrial espionage prevention. A recurring theme is the need for security systems that remain robust against previously unknown attacks. His publications show increasing attention to AI's dual role in security - both as a tool for attackers and defenders. The evolution of his work demonstrates growing emphasis on European digital sovereignty and the need for mandatory cybersecurity standards. Professor Müller-Quade's notable achievements include: Receiving the German IT Security Award in 2008 for his "Bingo Voting" system Initiating and directing KASTEL, which evolved from a competence center to a permanent institute at KIT Contributing to influential white papers on AI security and medical applications of AI Providing expert testimony on critical security issues to policymakers As Director of KASTEL — Institute for Information Security and Reliability, Müller-Quade leads a major interdisciplinary research effort that brings together cryptographers, IT security experts, software engineers, lawyers, and network specialists. The institute focuses on "Engineering Secure Systems" for economically and socially relevant fields including energy, mobility, and production. Müller-Quade emphasizes the importance of evaluating security in a comprehensive manner, noting that security engineering should ideally encompass all aspects of a system. His team works closely with existing infrastructures to develop practical security solutions that address real-world challenges.

Horst Lichterمشاهده پروفایل

استاد

• Software Engineering
• Software Architecture
• Test Automation
• +۴ مورد دیگر

Horst Lichter is a Professor at RWTH Aachen University in the Department of Software Construction , focusing on software engineering, architecture, and process improvement. He actively participates in international conferences like ENASE and APSEC , contributing to workshops on quantitative approaches to software quality (QuASoQ) and continuous software engineering. Email: lichter@swc.rwth-aachen.de Office: Room 4104, Building E1, RWTH Aachen Recent Conference Memberships: PC Member for QuASoQ 2024 , APSEC-ERA 2025 , IWCT 2025 His research spans software architecture reconstruction , test automation , enterprise architecture debt , and model-driven engineering . Recent publications address challenges in software modernization, security design patterns for ML systems, and carbon footprint optimization in cloud environments. Key article trends include: 2025 studies on architecture debt prioritization , security pattern recommendation , and ML prototype tooling 2024 work on enterprise architecture debt frameworks , cloud cost optimization , and integration testing 2023-2020 publications on combinatorial testing , architecture evolution , and technical debt analytics Horst Lichter leads the Software Construction Research Group , mentoring students and collaborating on projects like automated test generation, enterprise architecture modeling, and agile process improvement. His team develops tools for metric systems, model libraries, and continuous delivery pipelines.

Ahmed Rezineمشاهده پروفایل

مدرس ارشد

• Computer Science
• Software Verification
• Machine Learning
• +۷ مورد دیگر

Ahmed Rezine is a Senior Lecturer and Associate Professor at the Department of Computer Science (IDA) , specifically within the Software and Systems (SAS) division at Linköping University . His research focuses on software verification , machine learning , and cybersecurity , particularly in the context of deep neural networks and embedded systems . Research Trends: His recent publications, such as VNN: Verification-Friendly Neural Networks (2024) and Trojans in Instruction Sets (2024), highlight his work at the intersection of AI robustness and hardware security . Earlier studies (2023-2017) emphasize formal verification of concurrent systems and GPU architectures , reflecting a consistent focus on parameterized systems and security analysis . Colleagues & Collaborations: Rezine collaborates with researchers in the Software and Systems group, part of the Wallenberg Autonomous Systems Program (WASP) . His work intersects with AI IDA and Embedded Systems (ESLAB) , focusing on autonomous systems and real-time processing .

• Software Engineering
• Artificial Intelligence
• Cyber-Physical Systems
• +۳ مورد دیگر

Mason Brown serves as a Visiting Assistant Professor of Computer Science at Hamilton College, based in Taylor Science Center 3005. His research integrates software engineering and artificial intelligence to advance cyber-physical systems across ground, air, and space domains, with emphasis on practical implementations for real-world applications. Educational Background: Ph.D. in Computer Science from Griffith University M. IT. from Griffith University B. I.T. from Charles Sturt University His doctoral dissertation focused on An Ilities Tool for Minisatellite Software Validation , developed in collaboration with Gilmour Space Technologies. Research expertise spans satellite systems validation, multi-robot coordination, and AI-driven cyber-physical solutions. His postdoctoral work at the University of Technology Sydney involved multi-robot target tracking and path planning under Professor Robert Fitch. Current investigations include aircraft visual inspection via machine learning and natural language interfaces for robotic systems, demonstrating strong interdisciplinary connections between space engineering and robotics. Publication analysis reveals a clear trajectory from foundational satellite software validation (2020-2021) toward advanced human-robot collaboration (2023-2024), with consistent focus on verification methodologies and real-world deployment challenges. Key thematic threads include ilities-based validation frameworks, multi-robot field experimentation, and machine learning applications in aerospace. Teaching includes Computer Science for All and Algorithms and Data Structures , with active supervision of student projects in mechatronics and computer science. He particularly encourages new students to engage in research. Professional activities include appointment to the Australian Computer Science faculty in 2025 and collaborations with laboratories at Griffith University (Professor Paulo de Souza) and University of Technology Sydney (Graeme Best).

Mojtaba Eshghieمشاهده پروفایل

پژوهشگر

• Smart Contracts
• Blockchain Security
• Decentralized Finance (DeFi)
• +۳ مورد دیگر

Mojtaba Eshghie is a doctoral researcher at KTH Royal Institute of Technology, specializing in blockchain security and smart contract analysis. His PhD research focused on mitigating business logic flaws in smart contracts, addressing vulnerabilities that caused $63.8M in losses in 2024. He is affiliated with the Theoretical Computer Science division and supervised 9 master's and 2 bachelor's students in topics ranging from invariant mining to AI-driven contract repair. Education: MSc in Information Technology Engineering (Network Engineering) from University of Tehran (2019) Supervisors: Cyrille Artho (primary), Dilian Gurov (secondary) Roles: Researcher, Teaching Assistant (Software Security, Computer Security courses) His work includes developing tools like HighGuard for cross-chain monitoring, SoliDiffy for AST differencing, and the DISL dataset containing 514,506 Solidity contracts. He has contributed to conferences such as ASE, SANER, and ICST.