جست‌وجوی استاد و پژوهشگر

Zhi Liمشاهده پروفایل

استادیار

• Hydrological Modeling
• Flood Prediction
• Drought Monitoring
• +۹ مورد دیگر

Zhi Li is an Assistant Professor at the University of Colorado Boulder's College of Engineering and Applied Science, Department of Civil, Environmental and Architectural Engineering. He leads the newly established Flood Lab, focusing on flood prediction and monitoring through remote sensing and coupled hydrologic-hydraulic models. Joined CU Boulder in Fall 2025 Former Dean's Postdoc Fellow at Stanford University PhD in Civil Engineering & Environmental Science from University of Oklahoma (2022) His research spans hydrological modeling , extreme events , and AI4Science applications, particularly in deep learning and intelligent agents for flood risk assessment. Li’s work also connects floods with public health and economic systems , aiming to develop the Flood-Agriculture-Climate-Economics-Disease (FACED) framework. Key Themes: High-resolution flood modeling Climate change impacts on hydro-meteorology Remote sensing integration Flood-agriculture interdependencies Global health implications Scientific Awards: Dean's Postdoc Fellow, Stanford Doerr School of Sustainability (2023) Hoving Fellowship, University of Oklahoma (2019) Li’s recent publications emphasize improved precipitation estimation (IMERG V07), Brown Ocean Effect studies, and Fourier neural operators for rapid flood forecasting. His collaborative work with NOAA and NASA focuses on comparing ground-based and spaceborne radar systems for extreme event analysis.

Richard B. Brownمشاهده پروفایل

استاد

• Miniature Technology
• Solid-State Chemical Sensors
• Integrated Circuits
• +۳ مورد دیگر

Richard B. Brown is the Dean of the College of Engineering at the University of Utah, a position he has held since 2004. Under his leadership, the College has experienced remarkable growth, with research expenditures increasing from $30 million to $97 million annually and student enrollment more than doubling to over 6,000 students. Brown is also a distinguished professor whose research has significantly advanced miniature technology and sensor development. Dr. Brown earned his bachelor's and master's degrees in electrical engineering from Brigham Young University in 1976, followed by a Ph.D. in electrical engineering from the University of Utah in 1985. After 19 years as a faculty member at the University of Michigan, he returned to Utah as Dean of Engineering. His academic journey reflects a deep commitment to both research excellence and educational innovation. Dr. Brown's research focuses on miniature technology, particularly solid-state chemical sensors and integrated circuits. His pioneering work includes developing miniature ion-selective electrodes, enzymatically- and immunologically-coupled sensors for complex biological molecules, and amperometric sensors for heavy metals and neurochemicals. His research group was first to incorporate both electrical and chemical sensors on silicon brain probes and first to differentiate spoken words from microelectrode arrays on human brains. His work spans high-speed microprocessors to low-power, implantable electronics, with significant commercial applications through multiple startups. Dr. Brown has authored 225 peer-reviewed publications, including one cited over 3,400 times, and holds 21 patents. His research has led to four successful companies: i-SENS (glucose sensors), Sensicore (chemical sensors), Mobius Microsystems (silicon clock generators), and e-SENS (water chemistry sensors). Industry applications include 1.7 million glucometers and 1.4 billion test strips sold annually. Life Fellow of the IEEE Fellow of the National Academy of Inventors Utah Governor's Medal for Excellence in Science and Technology University of Utah's Rosenblatt Prize (2018) Inaugural holder of the H.E. Thomas Presidential Endowed Dean's Chair (2020) As an educator, Dr. Brown has mentored 31 PhD students who have become leaders in their fields. His innovative integrated circuit design curriculum has transformed how this subject is taught worldwide. Under his leadership, diversity in the College has significantly increased, with women students growing from 10% to 20% and Students of Color from 20% to 34% of the student body, with retention rates for these groups exceeding those of their counterparts. His work with industry through departmental advisory boards has led to programs addressing workforce needs, including the Master of Software Development and systems engineering certificate. Dr. Brown has established strong industry connections through industrial advisory boards at both departmental and college levels. This engagement has resulted in programs tailored to industry needs, including a robust electrical power program, the Master of Software Development for career changers, and a systems engineering certificate developed in response to requests from companies like Northrop Grumman, which has 155 current openings for systems engineers. During the pandemic, he led the College in pivoting research to address COVID-19, with over a dozen faculty members focusing on detection, transmission, and prevention.

Francesco Fornettiمشاهده پروفایل

دانشیار

• Radio Frequency Engineering
• Wide Bandgap Semiconductor Devices
• Gallium Nitride (GaN) Technology
• +۴ مورد دیگر

Dr. Francesco Fornetti is an Associate Professor of Radio Frequency Engineering at the School of Electrical, Electronic and Mechanical Engineering, University of Bristol. His research focuses on wide bandgap semiconductor devices, particularly Gallium Nitride (GaN) High Electron Mobility Transistors (HEMTs), and their applications in pulsed power amplifiers for radar systems. He has developed novel test methodologies for GaN amplifiers at microwave frequencies and authored influential publications in RF engineering education. MEng and PhD in Engineering from the University of Bristol His work spans RF semiconductor device characterization, microwave measurement rigs, and pedagogical innovation. His ORCID highlights 8 research outputs, including books and articles that emphasize simulation-based learning tools and authentic assessment in engineering education. His recent 2023 IEEE Microwave Magazine article explores online exam design for RF engineering. Key trends in his publications include interdisciplinary applications of GaN technology, educational software integration, and practical training frameworks. His research has been recognized through multiple teaching awards. Inspiring and Innovative Teaching Award (Engineering) (2022) Most Innovative Teaching of the Year 2022 - Highly Commended (2022) National Teaching Fellowship (NTF) (2023)

• Analysis and transformation of programs
• Software Security
• Parallel and distributed computing technologies

Harutyun Ishkhanovich Avetisyan is a Professor and Head of the Basic Department "System Programming" at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE). He began his tenure at HSE in 2017 and brings 30 years of scientific and teaching experience to his role. Additionally, he serves as the Director of the Institute for System Programming of the Russian Academy of Sciences (ISP RAS), a position he has held since 2015. Avetisyan holds numerous prestigious academic distinctions, including being elected as an Academician of the Russian Academy of Sciences in 2019 and as a Corresponding Member in 2016. He earned his Doctor of Physical and Mathematical Sciences degree in 2012 and was awarded the academic title of Associate Professor in 2009. His educational background includes a specialty in "Applied Mathematics" from Yerevan State University (1993). His research focuses on three main areas: analysis and transformation of programs, software security, and parallel and distributed computing technologies. These interests are reflected in his extensive publication record and leadership in major research initiatives. His work bridges theoretical computer science with practical applications in cloud computing, secure data storage, and high-performance computing systems. Avetisyan's scholarly contributions demonstrate a consistent focus on system programming challenges, particularly in the areas of code analysis, optimization, and security. His recent publications indicate a growing interest in cloud computing paradigms, smart city infrastructure, and energy-efficient computing solutions. His research has significant implications for both academic theory and industrial applications in software development. Among his notable recognitions, Avetisyan was awarded the medal of the Order "For Merit to the Fatherland" 2nd degree in 2021 for his significant contributions to science and dedicated service. He also serves on the editorial boards of several prestigious journals including "Programming" (since 2015) and "Proceedings of the Institute for System Programming of the RAS" (since 2010). Throughout his career, Avetisyan has led and participated in numerous research grants funded by the Ministry of Education and the Russian Foundation for Basic Research. His professional trajectory shows steady progression from postgraduate studies (1997-2000) to research fellow (2000-2002), deputy director of ISP RAS (2002-2015), and ultimately director of the institute (2015-present). At HSE, Avetisyan teaches courses in parallel programming and mentor seminars for master's students in Software Engineering. His teaching philosophy emphasizes the integration of cutting-edge research with practical software development skills, preparing students for careers at the forefront of computer science.

• Ambient Intelligence
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Paulo Jorge Freitas de Oliveira Novais is a Full Professor of Computer Science at the Department of Informatics, School of Engineering, Universidade do Minho, where he also holds a Habilitation in Computer Science. He leads the Synthetic Intelligence Lab at ALGORITMI Centre and coordinates the research line on Ambient Intelligence for Well-Being and Health Applications. His research spans Intelligent Systems, Machine Learning, Multi-Agent Systems, and their applications in Smart Cities, Health Informatics, and AI Ethics. PhD in Computer Science, Universidade do Minho, 2003 Habilitation in Computer Science, Universidade do Minho, 2011 Research interests include Ambient Intelligence, Ambient Assisted Living, Intelligent Environments, AI and Law, Conflict Resolution, and Explainable AI. His work focuses on enhancing system intelligence and reliability through novel architectures and ethical frameworks. Recent publications highlight applications in wastewater energy prediction, violence detection, student risk modeling, and urban logistics. Awards include multiple Best Paper and IBM Excellence recognitions across 2015–2023, plus a 2022 Career Recognition Award from the Ibero-American Society of Artificial Intelligence. Senior IEEE Member Chair of IEEE Computational Intelligence Chapter, Portugal IFIP TC 12 Artificial Intelligence Working Group Leadership He has supervised 132 PhD and Master’s students and contributed to editorial boards of journals like JAISE and ComSIS . His leadership roles include coordinating LASI – Intelligent Systems Associate Laboratory and serving as former president of APPIA.

Joel Lanningمشاهده پروفایل

دانشیار

• Engineering education
• Seismic design of civil structures
• Large-scale testing
• +۳ مورد دیگر

Joel Lanning is an Associate Professor in the Department of Civil and Environmental Engineering at the Samueli School of Engineering, University of California, Irvine. Education: Ph.D. in Structural Engineering from UC San Diego (2014), M.S. in Structural Engineering from UC San Diego (2008), B.S. in Civil Engineering from The Ohio State University (2006) His research focuses on engineering education, seismic design of civil structures, large-scale testing methodologies, and alternative building materials. He integrates constructivist learning principles with active learning components like group problem-solving and interactive technology. Awarded the 2023 Distinguished Early-Career Faculty Award for Teaching, 2022 SSoE Early Career Innovation in Teaching Award, 2020 Dean’s Honoree for DTEI’s Celebration of Teaching, and the 2019 CEE Faculty of the Year Award, Joel has demonstrated excellence in pedagogical innovation and student engagement. He serves as Director of the MEng CEE Concentration and is a licensed Professional Engineer (Civil Engineering, California #80946). Joel actively mentors the UCI Steel Bridge Team, guiding hands-on structural design competitions.

John Regehrمشاهده پروفایل

استاد

• Compilers
• Software Testing
• Formal Verification
• +۳ مورد دیگر

John Regehr is a Professor at the School of Computing, University of Utah, specializing in compilers, software testing, and formal verification. His research develops tools to improve software correctness and efficiency, including Csmith (random C program generator) and C-Reduce (test-case reducer). His group focuses on compiler validation, fuzzing techniques, and superoptimization, primarily targeting the LLVM infrastructure. Research interests span compilers, testing methodologies, formal verification, embedded systems, and program analysis. Recent work emphasizes practical tools backed by formal methods to detect and prevent software errors. Publications demonstrate strong trends in compiler verification and testing, with consistent focus on LLVM optimization correctness, translation validation, and automated bug detection through fuzzing and synthesis techniques. Scientific awards include: PLDI 2015 Distinguished Paper Award ICST 2014 Best Paper Award ACM SIGSOFT Distinguished Paper Award Leads a research group developing tools like Souper (superoptimizer) and Alive2 (translation validator). Maintains active academic service through program committees (PLDI, CGO, OOPSLA) and contributes to open-source compiler infrastructure.

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.

José Cano Reyesمشاهده پروفایل

دانشیار

• Computer Architecture
• Computer Systems
• Compilers
• +۳ مورد دیگر

José Cano Reyes serves as a Reader (Associate Professor) in the School of Computing Science at the University of Glasgow, where he leads the Glasgow Intelligent Computing (GIC) Lab. His academic profile spans multiple premier conferences including ASE, CGO, ICSME, and EASE through 2025, demonstrating active engagement in computer systems research. His research focuses on the critical intersection of hardware and software systems for AI workloads, with core interests in Computer Architecture, Compilers, and Machine Learning. Recent investigations examine deep learning framework conversions, hardware accelerator robustness, and security implications of computational environments. This work addresses fundamental challenges in deploying efficient and reliable AI systems across diverse hardware platforms. Analysis of his 2023-2025 publications reveals a concentrated research trajectory toward optimizing deep learning deployment: 80% of recent work targets framework conversion errors and hardware compatibility issues, with strong emphasis on image recognition systems. Key methodologies include automatic fault localization (40% of publications), performance parameter analysis (30%), and domain-specific compiler techniques (30%). Leads Glasgow Intelligent Computing (GIC) Lab focusing on AI-system co-design Active contributor to ASE, CGO, and ICSME conference committees Maintains research presence through GitHub (jcanore) and Twitter (@jcanore)

Jochen Steffensمشاهده پروفایل

استاد

• Music Listening Behavior
• Music Recommendation Systems
• Noise Perception
• +۳ مورد دیگر

Prof. Dr.-Ing. Jochen Steffens is a faculty member at the University of Applied Sciences Düsseldorf , affiliated with the Faculty of Media . His research spans interdisciplinary domains at the intersection of music, soundscapes, and cognitive-affective processes. Research Focus : Music listening behavior, soundscapes, noise perception, music recommendation systems, film music, and the psychological effects of sounds. Teaching : Supervises final theses and offers modules aligned with examination regulations of 2018, including topics in media informatics and mixed reality applications. Technical Contributions : Develops tools for soundscape exploration (e.g., Advanced Soundscape Search) and music information retrieval (MIR) systems for live performance visualization. Methodological Expertise : Utilizes computational music analysis, experience sampling, statistical learning, and multilevel modeling to investigate situational and demographic influences on auditory perception. Applied Research : Explores the impact of room acoustics on customer satisfaction in restaurants, motivational music in sports, and semantic expression in audio branding.

Kanad Basuمشاهده پروفایل

دانشیار

• Hardware Security
• System Security
• Hardware Reliability
• +۱۰ مورد دیگر

Kanad Basu is an Associate Professor in the Department of Electrical, Computer, and Systems Engineering at The University of Texas at Dallas, Jonsson School of Engineering and Computer Science. He leads the Trustworthy and Intelligent Embedded Systems (TIES) lab, focusing on hardware security, reliability, and emerging computing paradigms. His research spans AI hardware, quantum computing, functional safety, and hardware-based security validation. Research Interests: His work emphasizes improving the trustworthiness of modern hardware systems. Key areas include hardware security (e.g., side-channel analysis, hardware trojans), functional safety in AI accelerators, quantum computing security and verification, and post-silicon validation techniques. He combines formal methods, machine learning, and hardware design to address vulnerabilities in SoCs, DNN accelerators, and quantum systems. Publication Trends: Recent publications (2023–2025) show a strong focus on interdisciplinary research, integrating AI/ML with hardware security, quantum computing, and functional safety. There is a growing emphasis on using large language models for assertion generation, symbolic execution for hardware fuzzing, and graph neural networks for quantum circuit analysis. His work frequently appears in top venues like DAC, DATE, HOST, ISVLSI, and IEEE journals. Scientific Awards: NSF CAREER Award, 2025 IEEE Top Picks in Test and Reliability, 2024 and 2023 Multiple Hack@DAC Prizes (2nd and 3rd) Best Paper Award at VLSI Design 2011 Assistant Professor Award at UTD Jonsson School, 2024 Nominated for Blavatnik Awards for Young Scientists, 2019 Advising and Grants: Dr. Basu has mentored numerous PhD, MS, and undergraduate students, many of whom have published in top-tier venues. He leads the TIES lab, which has received significant recognition, including the NSF CAREER Award. He actively collaborates across disciplines, advising students on topics ranging from quantum computing to AI hardware and functional safety. His lab produces high-impact research with real-world applications in automotive, cloud, and embedded systems. Labs and Teams: He leads the Trustworthy and Intelligent Embedded Systems (TIES) lab at UT Dallas, which fosters innovation in hardware security and reliability. The lab has produced award-winning work, including second prize at HACK@DAC 2025. He also serves on technical committees for IEEE DATE and HOST, and acts as Hardware Hacking Chair for IEEE HOST, indicating strong leadership in the hardware security community.

• Automotive Security
• Network Security
• IT Security
• +۵ مورد دیگر

Hans-Joachim Hof is a Professor and Vice President for Teaching and Students at Technische Hochschule Ingolstadt (THI), where he has been employed since 2016. He serves as Head of Bachelor Cybersecurity (since 2022), Project Manager for THIsuccessAI (since 2021), and Head of the Research Group 'Security in Mobility' at the CARISSMA Institute of Electric, Connected and Secure Mobility. Additionally, he chairs the Scientific Board of the Center of Entrepreneurship and serves on the Supervisory Board of AININ. Professor, Head of INSecurity - Ingolstadt Applied IT Security Research Group (since WS 2016) Professor of Secure Software Systems, Head of MuSe - Munich IT Security Research Group at HAW Munich (2011-2016) Research Scientist at University of Karlsruhe (2008-2011) Research Assistant at Institute for Telematics, University of Karlsruhe (TH) (2003-2007) Professor Hof holds a doctorate in engineering and completed studies in computer science with a specialization in telematics and reliability architectures of systems, with a minor in law. His research spans automotive security, network security, and IT security, with recent focus on security in the Internet of Things, development processes for Secure Automotive Software, Automotive Blockchains, and Future Automotive Security Architectures. His work bridges theoretical security frameworks with practical automotive applications, particularly in electric vehicle security and battery management systems. Hof's recent publications reveal a strong trend toward automotive cybersecurity, with particular emphasis on electric vehicle infrastructure security, battery management systems, and vehicle security operations centers. His research increasingly addresses the security challenges of connected and autonomous vehicles, with growing attention to trust management systems and the security implications of AI in automotive contexts. The interdisciplinary nature of his work connects computer security with automotive engineering, energy systems, and digital forensics. Professor Hof has received numerous prestigious awards for his research contributions: Multiple Best Paper Awards at SECURWARE (2015, 2016, 2017) Best Paper Awards at CENTRIC (2010, 2012) Best Speaker Award at ESE Congress 2015 IARIA Fellow recognition Best Paper Award at ICIW 2010 As Editor-in-Chief of the International Journal on Advances in Security and Chairman of the German Chapter of the ACM, Hof plays a significant role in shaping security research discourse. His leadership extends to the German Informatics Society where he serves on the Executive Board. His research group INSicherheit (http://insi.science) actively collaborates with industry partners on real-world security challenges. Professor Hof leads the INSecurity research group at THI, which focuses on applied IT security with particular expertise in automotive contexts. The group maintains strong industry connections and operates within the CARISSMA research institute, which specializes in electric, connected, and secure mobility. Their work includes practical security testing, development of security architectures, and analysis of emerging threats in automotive systems, with notable contributions to EV charging security, battery management systems, and vehicle forensics.

Yu Jiangمشاهده پروفایل

دانشیار

• Software Engineering
• Embedded Systems
• Fuzz Testing
• +۳ مورد دیگر

Yu Jiang is an Associate Professor at the School of Software, Tsinghua University, China. His research focuses on software security with emphasis on fuzz testing, embedded systems, and database security. He leads the Software System Security Assurance Group which has discovered over 1,000 bugs in major system software with 300+ CVEs registered. Dr. Jiang's research interests include Software Engineering , Embedded Systems Security , and Cross-Layer Fuzzing . His work addresses vulnerabilities in operating systems, databases, communication protocols, and IoT firmware through innovative fuzzing frameworks. Key contributions include semantic-aware fuzzing for heterogeneous software stacks and learning-based vulnerability detection for embedded systems. His recent publications demonstrate strong trends in database security (Hulk, PUPPY, THANOS), ransomware defense (Fawkes, Preventing Disruption), and web security (JANUS). Research spans both theoretical advances in fuzzing techniques and practical industrial applications, with significant impact evidenced by numerous distinguished paper awards. Career Award, NSFC: 2026 Distinguished Paper Award, ISSTA: 2025 First Prize for Technical Invention, CCF: 2024 Distinguished Paper Award, USENIX Security: 2024 SIGSOFT Distinguished Paper Award, FSE: 2022 Dr. Jiang has advised over 50 graduate students including 20 PhD candidates. His research is supported by major grants including NSFC projects ($600,000 for Software Trustworthiness Construction and $350,000 for Distributed Database Reliability), Huawei ($80,000 for LLM-Powered Fuzzing), and Tencent ($120,000 for LLM-Powered Unit Testing). The Software System Security Assurance Group maintains strong industry partnerships with Huawei, Alibaba, Tencent, and Webank. The group operates cutting-edge infrastructure for fuzz testing across multiple domains including database systems, operating kernels, blockchain platforms, and industrial control systems. Current projects integrate LLM technologies with traditional fuzzing techniques to enhance vulnerability detection in complex software stacks.

Raffi Khatchadourianمشاهده پروفایل

دانشیار

• Software Engineering
• Programming Languages
• Software Evolution
• +۵ مورد دیگر

Raffi Khatchadourian is an Associate Professor in the Department of Computer Science at Hunter College and the Graduate Center of the City University of New York (CUNY). His research focuses on techniques for automated software evolution, particularly automated refactoring and source code recommendation systems, with the goal of easing the burden associated with evolving large and complex software through automated tools. He also conducts research on the automated analysis of Object-Oriented programs. Ph.D., Computer Science & Engineering, Ohio State University (2011) MS, Computer Science & Engineering, Ohio State University (2010) BS, Computer Science, Monmouth University (2004) Khatchadourian's research spans multiple areas of software engineering and programming languages, with particular emphasis on automated software evolution techniques. His work addresses critical challenges in refactoring legacy systems to modern language constructs, optimizing parallel processing in Java 8 streams, and addressing technical debt in machine learning systems. His recent research has expanded into deep learning program transformation, where he develops techniques to convert imperative deep learning code to more efficient graph execution models while ensuring safety. His approach combines static analysis, program transformation, and empirical validation to create practical tools that developers can integrate into their workflows. Analysis of Khatchadourian's recent publications reveals a strong focus on bridging the gap between theoretical program analysis and practical software engineering challenges. His work increasingly intersects with machine learning systems, examining both how to improve ML code through refactoring and how to ensure safety in deep learning frameworks. The research demonstrates consistent evolution from foundational work on Java language features toward more complex systems involving concurrency, deep learning, and automated program transformation. Distinguished Paper Award at SCAM '18 for work on Java 8 stream optimization EAPLS Best Paper Award at FASE '20 for study on Java 8 stream usage EAPLS Distinguished Paper Award at FASE '25 for Deep Learning refactoring work Best Paper Award nominee at IJCAI '24 for AI safety framework Khatchadourian actively mentors graduate and undergraduate students, with several advisees going on to successful academic and industry positions. His former Ph.D. student Tatiana Castro Vélez accepted a tenure-track Assistant Professor position at the University of Puerto Rico. He has supervised numerous master's theses and undergraduate research projects, often resulting in co-authored publications at top software engineering venues. His research has been supported by various grants, though specific funding details are not prominently featured in the available information. Through his work on tools like Fraglight for aspect-oriented programming and Hybridize Functions for deep learning refactoring, Khatchadourian has established a research group focused on practical program analysis and transformation. His lab develops Eclipse plugins and other IDE-integrated tools that help developers with automated refactoring, bug detection, and code optimization. The group maintains active collaborations with researchers at other institutions and contributes to open-source projects on GitHub.

Wing Lamمشاهده پروفایل

استادیار

• Software Testing
• Flaky Tests
• Mobile Testing
• +۴ مورد دیگر

Wing Lam is an Assistant Professor at George Mason University specializing in software engineering with a focus on software testing methodologies. His academic service includes program committee membership for major conferences including ASE, ICSE, ISSTA, and ESEC/FSE, as well as session chair roles across multiple tracks. His research interests center on flaky tests , mobile application testing , and continuous development optimization . Lam's work addresses critical challenges in test reliability, particularly order-dependent flaky tests and resource-related flakiness. His research bridges theoretical foundations with practical applications in modern software development pipelines, with recent expansion into AI-assisted testing methodologies. Lam's publication record shows a clear trajectory focusing on flaky test detection and mitigation, with approximately 60% of his recent work dedicated to various aspects of this problem. His research increasingly incorporates machine learning techniques for UI testing and test optimization, reflecting broader trends in the field. The consistent publication venue pattern across top software engineering conferences indicates strong recognition within the academic community. Lam has served in multiple leadership roles including Program Co-Chair for MOBILESoft Research Track and Committee Member for ASE's New Ideas and Emerging Results (NIER) Track. His involvement in workshops focused on flaky testing demonstrates his specialization in this niche area of software testing.