جستجوی استاد راهنمای دانشگاهی

Jiyuan Wangمشاهده پروفایل

استادیار

• Software Engineering
• Quantum Computing
• Heterogeneous Computing
• +۴ مورد دیگر

Dr. Jiyuan Wang serves as an Assistant Professor in the Department of Computer Science within Tulane University's School of Science & Engineering, commencing his appointment in Fall 2025. Prior to Tulane, he worked as an Applied Scientist at Amazon Web Services, focusing on program analysis and formal verification for cloud systems. His academic background includes a Ph.D. in Computer Science from UCLA (2025) and a B.S. in Physics from Tsinghua University (2019). His educational journey: Doctor of Philosophy (Ph.D.) in Computer Science, University of California, Los Angeles, 2025 Bachelor of Science (B.S.) in Physics, Tsinghua University, 2019 Dr. Wang's research centers on Software Engineering for next-generation computing platforms, with particular emphasis on Quantum Computing and Heterogeneous Computing (including FPGAs and GPUs). He develops innovative techniques for testing and debugging, such as multi-layer compiler debugging, full-stack compiler testing, and fuzz testing tailored for heterogeneous applications. His work bridges the gap between software reliability and the complexities of modern hardware accelerators, addressing critical challenges in compiler correctness and application robustness. An analysis of his publication record from 2020 to 2025 reveals a consistent focus on advancing software testing methodologies for heterogeneous systems. The research evolved from big data analytics (BigFuzz) to compiler testing (HeteroFuzz, DuoReduce) and quantum software stacks (QDiff), demonstrating increasing sophistication in tackling platform-specific challenges. His recent 2025 papers highlight breakthroughs in MLIR compiler debugging and fuzzing. His notable recognitions include: SIGSOFT Research Highlight for QDiff (ASE 2021) Best Poster Award at ICST 2021 Dr. Wang is currently building his research group at Tulane and actively seeks motivated graduate students interested in software engineering for quantum and heterogeneous computing. His industry experience at AWS and strong publication record in top venues (ASE, ICSE, FSE, ASPLOS) indicate active research funding and collaborative opportunities. He teaches Quantum Computing (CMPS-4660/6660) and mentors students in cutting-edge research projects. While a dedicated lab name isn't specified, Dr. Wang's research group focuses on developing practical tools for compiler and application testing in heterogeneous environments, with growing emphasis on quantum software stacks.

Daniel A. Petersonمشاهده پروفایل

استاد

• Stem Cell Biology
• Regenerative Medicine
• Neurogenesis
• +۵ مورد دیگر

Daniel A. Peterson serves as Professor and Vice-Chairman of Neuroscience at Rosalind Franklin University of Medicine and Science's Chicago Medical School, where he directs the Center for Stem Cell and Regenerative Medicine (CSCRM) and co-leads the Center for Neurodegenerative Diseases and Therapeutics. His academic journey spans from PhD studies at New Zealand's University of Otago to postdoctoral training with Rusty Gage at UC San Diego/Salk Institute, culminating in RFUMS faculty appointment in 1998 and tenured Full Professorship in 2012. Dr. Peterson's research program pioneers endogenous stem cell recruitment for tissue repair, with three synergistic thrusts: Brain repair through neural stem cell activation in neurogenic niches; Diabetic wound healing via mesenchymal stem cell mechanisms; and Stem cell homeostasis during aging/disease. His lab developed innovative high-throughput quantitative histology methods that underpin rigorous analysis across these domains. Recent work focuses on traumatic brain injury models and stem cell dysfunction in type 2 diabetes, reflecting strong translational orientation. His publication portfolio demonstrates sustained impact across neuroscience and regenerative medicine, with 15+ high-impact papers in the last seven years showing evolution from fundamental neurogenesis studies to disease applications. Awards include the 2014 Fulbright Senior Scholar Award for work at Germany's University of Bonn, where he subsequently served as International Ambassador. Dr. Peterson actively mentors the next generation through CSCRM lab positions and Neurorenew workshops that have trained over 1,000 scientists since 2003. His leadership extends to editorial roles for Frontiers in Neuroscience and Neurobiology of Aging , plus society presidencies and NIH study section service. The lab maintains active collaborations with DePaul University researchers on TBI projects and industry partners through regenerative medicine patents. Current research directions emphasize personalized regenerative approaches, particularly leveraging patients' own stem cells for neurological repair and chronic wound treatment, with growing focus on age-related therapeutic limitations.

Andreea Costeaمشاهده پروفایل

استادیار

• Programming Languages
• Software Verification
• Automated Program Repair
• +۵ مورد دیگر

Dr. Andreea Costea is an Assistant Professor at the Programming Languages Group in the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at TU Delft, Netherlands. She completed her PhD at the School of Computing, National University of Singapore (NUS), and previously collaborated with NUS's Programming Languages and Software Engineering lab, Automated Program Repair team, and VERSE lab. Research: Formal Methods, Software Verification, Automated Program Repair, Rust Programming, Concurrency Funding: Ministry of Education Tier 3 Grant (2022) Projects: HIPPODROME (Java data race repair), ROBoSuSLik (heap synthesis), Mercurius (session protocols) Recent MSc Students: Matei Mirică (2025), Arjan Seijs (2025), Jim van Vliet (2025), Timen Zandbergen (2025), Arthur de Groot (2024), Julius de Jeu (2024), Matteo Bertorotta (2024). Conference Involvement: Program Committee member for PriSC 2024, PEPM 2024, SPLASH/ISSTA 2026, ICSE 2025, ICFP 2023, APLAS 2021.

Hamid Bagheriمشاهده پروفایل

دانشیار

• Software Engineering
• Security
• Formal Methods
• +۷ مورد دیگر

Hamid Bagheri is an Associate Professor in the School of Computing at the University of Nebraska-Lincoln and a faculty associate of the Institute for Software Research (ISR) at the University of California, Irvine. He co-directs the ESQuaReD Lab and serves on the review boards of IEEE Transactions on Software Engineering and ACM Transactions on Software Engineering and Methodology. His research focuses at the intersection of software engineering, security, and formal methods, with particular expertise in Security of Mobile Devices and IoT Systems Scaling Formal Verification with Machine Learning Software Analysis and Testing Dependable Cyber-Physical Systems Automated Program Repair and Fault Localization His publication record spans top-tier venues including ICSE, ASE, ISSTA, ESEC/FSE, and IEEE/ACM Transactions, with recent work focusing on efficient analysis of Alloy specifications, IoT security, and ML-enhanced formal verification. His research has been recognized with multiple Distinguished Paper Awards. Among his notable awards are: EPSCoR FIRST Award NSF CISE Career Research Initiation Initiative Award SoC Student Choice Outstanding Teaching Award (2023-2024) CSE Outstanding Teaching Award (2020-2021) NSF EPSCoR First Award (2017) Prof. Bagheri has successfully advised multiple PhD students including Mohannad Alhanahnah (now tenure-track faculty at Chalmers University) and Clay Stevens (now tenure-track faculty at Iowa State University). He has received substantial research funding including NSF SHF Research Grants and has been actively involved in conference organization as PC member and track chair across numerous major software engineering venues.

Chao Pengمشاهده پروفایل

مدرس پاره‌وقت

• Software Testing
• Program Analysis
• Programming Languages
• +۵ مورد دیگر

Chao Peng is a Principal Research Scientist at ByteDance where he leads the Trae Research team (ByteDance Software Engineering Lab), conducting cutting-edge research on AI agents for software engineering. He also serves as a Part-time Postgraduate Student Mentor at Fudan University's School of Computer Science, bridging industry research with academic mentorship. PhD in Informatics (2021), University of Edinburgh, UK MSc in High Performance Computing and Data Science (2017), University of Edinburgh, UK BEng in Computer Science and Technology (2016), Xuzhou University of Technology, China Dr. Peng's research focuses on the intersection of software testing, program analysis, and large language models. His work explores how AI agents can revolutionize software engineering practices, with particular emphasis on automated bug detection, code generation, and testing frameworks. He has pioneered approaches for evaluating LLM performance in software engineering contexts and developing agent-based systems that enhance developer productivity while maintaining code quality and security. His recent publications demonstrate a clear trend toward integrating large language models with traditional software engineering practices. The research spans code generation evaluation, security vulnerability detection, automated bug reproduction, and issue localization. These works collectively advance the field of AI-assisted software development by addressing practical challenges in reliability, security, and efficiency of AI-generated code. Distinguished Reviewer for FSE'25 School of Informatics Scholarship (fully-funded PhD scholarship) Outstanding Graduate Scholarship at Xuzhou University of Technology Multiple China National Scholarships Honours Spot Bonus at ByteDance Certificate of Achievement for HPCAC Student Cluster Competition Dr. Peng actively mentors students through his role at Fudan University and previously at the University of Edinburgh, where he served as sub-supervisor for MSc projects and teaching assistant for software testing courses. His research has attracted significant industry attention, leading to multiple collaborations between ByteDance and academic institutions. He frequently serves on program committees for major software engineering conferences including ASE, FSE, and ICSE, demonstrating his leadership in the field. As leader of the Trae Research team at ByteDance Software Engineering Lab, Dr. Peng oversees research on AI agents for software engineering, including the application and evaluation of AI agents and training LLMs for agent-based systems. The lab's work focuses on practical systems that predict, detect, diagnose, and fix bugs across various software systems, with particular emphasis on real-world applications and measurable impact on developer productivity.

Xiaoyin Wangمشاهده پروفایل

دانشیار

• Software Testing and Analysis
• Software Privacy
• Program Analysis
• +۳ مورد دیگر

Xiaoyin Wang is an Associate Professor in the Department of Computer Science at the University of Texas at San Antonio, specializing in software testing, privacy, and program analysis. Her research focuses on enhancing software quality through innovative approaches to build systems, virtual reality testing, and privacy policy enforcement. She earned her PhD from Peking University in 2012 and completed postdoctoral work at UC Berkeley. Her research interests span Software Testing and Analysis , Software Privacy , Build Systems , and Virtual Reality Testing . She develops techniques for detecting privacy leaks in mobile apps, optimizing build scripts, and testing immersive applications. Her work bridges program analysis with practical software engineering challenges, particularly in security-critical contexts. Recent publications reveal strong trends in Virtual Reality testing frameworks (e.g., VRGuide, VRTest), automated build diagnostics (PExReport, HireBuild), and privacy policy verification (GUILeak, DAISY). Her research increasingly integrates machine learning for bug prediction and test oracle generation, with significant contributions to augmented reality testing and cross-project compatibility analysis. President's Research Achievement Award (UTSA, 2019) NSF CAREER Award (2019) for build script analysis Distinguished PhD Dissertation Awards from CCF (2013) and Peking University (2012) MSRA Fellowship (2009) Wang actively advises PhD students including Rodney Rodriguez (defended 2022, now at Accenture) and Xueling Zhang (defended 2021, now Assistant Professor at RIT). She leads NSF-funded projects including CAREER: Analysis and Repair of Build Scripts for DevOps and EAGER: Tracing Privacy-Policy Statements into Code . Her service includes chairing ICSE 2019 proceedings and serving on ASE/ICSE/ISSTA program committees. Current work focuses on security analysis for AR applications and automated privacy compliance verification.

Jifeng Xuanمشاهده پروفایل

استاد

• Software Analysis and Testing
• Software Testing
• Software Debugging
• +۲ مورد دیگر

Jifeng Xuan is a Professor and Deputy Dean at the School of Computer Science, Wuhan University, China. He leads the CSTAR (Centre of Software Testing, Analysis and Reliability) research group and has made significant contributions to software engineering, particularly in software testing, debugging, and analysis. Dr. Xuan completed his bachelor's degree and PhD at OSCAR Lab, School of Software, Dalian University of Technology, China, under the supervision of Prof. He Jiang. He also conducted postdoctoral research at SPIRALS Team in INRIA Lille - Nord Europe, France, working with Dr. Martin Monperrus and Prof. Lionel Seinturier. His research focuses on Software Analysis and Testing , with specific interests in software testing and debugging, software data analysis, and search-based software engineering. Dr. Xuan's work bridges theoretical foundations with practical applications, addressing real-world challenges in software quality assurance. His research has led to numerous publications in top-tier software engineering venues and has influenced both academic research and industrial practices. Dr. Xuan's recent publications demonstrate a strong focus on innovative approaches to software testing, debugging, and analysis. His work spans multiple subfields including log analysis, fuzz testing, bug triage, and automated program repair. He has made significant contributions to understanding software crashes, improving bug report quality, and developing techniques for more effective software testing and analysis. 2025 ACM SIGSOFT Distinguished Paper Award 2025 IEEE TCSE Distinguished Paper Award 2024 CCF NASAC Youth Software Innovation Award 2018 ACM SIGSOFT Distinguished Paper Award 2015 Young Talent Development Program of CAST and CCF 2015 Luojia Young Scholar Program of Wuhan University 2014 Outstanding Doctoral Dissertation of CCF Dr. Xuan actively mentors PhD and master's students through his CSTAR research group at Wuhan University. He has served on numerous program committees for major software engineering conferences including ICSE, FSE, ASE, and ISSTA. His editorial service includes roles on the editorial boards of Empirical Software Engineering (EMSE), PLOS One, and Frontiers of Computer Science. Dr. Xuan has also organized several workshops and conferences, demonstrating his leadership in the software engineering community. As founder of CSTAR (Centre of Software Testing, Analysis and Reliability), Dr. Xuan leads a research team focused on advancing the state of the art in software quality assurance. The group's work spans theoretical foundations and practical applications, with strong connections to industry challenges. CSTAR has established collaborations with both domestic and international research institutions, contributing to a vibrant research ecosystem in software engineering.

Leopoldo Teixeiraمشاهده پروفایل

استادیار

• Software Engineering
• Refactoring
• Formal Methods
• +۶ مورد دیگر

Leopoldo Teixeira is an Assistant Professor at the Informatics Center (CIn) of the Federal University of Pernambuco (UFPE) in Brazil. Since May 2023, he has served as Head of Graduate Studies at his department. He leads the Software Testing and Analysis Research group and is affiliated with the Software Productivity Group and CIn-Trust. Dr. Teixeira was a CAPES-Alexander von Humboldt Experienced Research Fellow at the Chair of Software Engineering of Universität des Saarlandes in 2022, where he collaborated with Sven Apel on variability analysis over time and space. His educational background includes: PhD in Computer Science from Federal University of Pernambuco (CIn-UFPE, 2014), supervised by Paulo Borba and Rohit Gheyi MSc in Computer Science from CIn-UFPE (2010) Bachelor's degree in Computer Engineering from the Polytechnic School of Pernambuco (2007) Dr. Teixeira's research focuses on providing strong foundations for improving software quality and productivity. His work spans software product lines, configurable systems, refactoring, formal methods, software testing, and mobile development. He has made significant contributions to understanding challenges in highly configurable systems and software evolution, with particular emphasis on theoretical rigor combined with practical applicability. His publication record demonstrates expertise across software testing methodologies, analysis of configurable systems, and formal verification techniques. Recent work addresses pressing challenges in containerization practices (Dockerfile repair), test reliability (flaky test detection), and formal specification of API properties, showing his ability to tackle both theoretical and practical aspects of software engineering. Dr. Teixeira has received recognition through the CAPES-Alexander von Humboldt Experienced Research Fellowship. CAPES-Alexander von Humboldt Experienced Research Fellow (2022) Dr. Teixeira actively contributes to the software engineering community through extensive service on program committees of major conferences including ICSE, FSE, ASE, and SPLASH across multiple years. In 2024, he served as Conference and Local Organization Chair for FSE. He mentors students through his leadership of the Software Testing and Analysis Research group at CIn-UFPE. His laboratory work focuses on software testing and analysis, particularly in the context of configurable systems and software product lines. The research group investigates practical approaches to improve software quality through better testing methodologies, analysis techniques, and formal verification approaches for complex software systems.

Işıl Dilligمشاهده پروفایل

دانشیار

• Program analysis
• Program synthesis
• Program verification
• +۴ مورد دیگر

Işıl Dillig is an Associate Professor of Computer Science at the University of Texas at Austin, where she leads the UToPiA research group. Her academic career spans over a decade of significant contributions to programming languages research, particularly in program analysis, verification, and synthesis. Dr. Dillig received all her academic degrees (BS, MS, and PhD) from Stanford University before joining the faculty at UT Austin. Her educational background established the foundation for her innovative research approach that bridges theoretical computer science with practical applications. Her research focuses on developing techniques to make software systems more reliable, secure, and easier to build through advanced program analysis, verification, and synthesis methods. She has pioneered approaches that combine symbolic reasoning with machine learning to tackle complex software engineering challenges across multiple domains including security, databases, and programming language theory. Her work demonstrates exceptional depth in creating practical tools that address real-world software development problems while maintaining strong theoretical foundations. Analysis of Dr. Dillig's publication record reveals a consistent trajectory of innovation in program synthesis, with recent work expanding into neurosymbolic approaches that bridge neural networks with formal methods. Her research shows strong connections between theoretical foundations and practical applications, particularly in security-critical systems, database technologies, and blockchain applications. The evolution of her work demonstrates increasing sophistication in handling complex program structures while maintaining practical usability. Dr. Dillig has received prestigious recognition for her research contributions: Sloan Fellowship NSF CAREER award As a dedicated educator and research leader, Dr. Dillig has served in significant roles including Program Chair for PLDI 2022 and Steering Committee member for PLDI. She has mentored numerous students through her UToPiA research group, guiding research in program synthesis, verification, and analysis. Her work has been supported by substantial research grants that have enabled innovative projects at the intersection of programming languages and security. Dr. Dillig leads the UToPiA (UT Austin Programming, Languages, and Analysis) research group, which focuses on developing novel techniques for program analysis, verification, and synthesis. The group maintains strong collaborations with industry partners and academic institutions worldwide, translating theoretical advances into practical tools that address real software engineering challenges.

Ranjit Jhalaمشاهده پروفایل

استاد

• Programming Languages
• Formal Verification
• Software Engineering
• +۳ مورد دیگر

Ranjit Jhala is a Professor of Computer Science Engineering in the Jacobs School of Engineering at the University of California, San Diego. His research focuses on building reliable computer systems through programming languages and software engineering techniques. His primary research interests include Programming Languages, Formal Verification, and Software Engineering. He draws from and contributes to areas such as Type Systems, Model Checking, Program Analysis, and Automated Deduction, bridging theoretical foundations with practical implementations for real-world software development. Prof. Jhala's publication record shows a consistent trajectory in refinement type systems, evolving from Liquid Haskell to Flux for Rust, while also exploring neurosymbolic approaches to error repair and type error diagnosis. His work demonstrates a commitment to making formal verification techniques accessible to practitioners. He leads the Programming Systems Group at UCSD, mentoring graduate students and collaborating with researchers across the programming languages community. His service includes General Chair roles for POPL 2018 and PLDI 2022, reflecting his leadership position in the field. Prof. Jhala is also known for his mentoring activities, including talks on academic presentation skills and participation in ICFP's mentoring programs for students and early-career researchers.

Baishakhi Rayمشاهده پروفایل

دانشیار

• Software Engineering
• Security
• Artificial Intelligence
• +۱ مورد دیگر

Baishakhi Ray is an Associate Professor of Computer Science at Columbia University's School of Engineering and Applied Science. Her work focuses on the intersection of AI, Software Engineering, and Security. She received her Ph.D. from the University of Texas, Austin and has established herself as a leading researcher in software engineering with AI applications. Dr. Ray's educational background includes a Ph.D. from the University of Texas, Austin. Her academic journey has led to a prominent position at Columbia University where she continues to advance research in software engineering. Dr. Ray's research spans several critical areas at the intersection of software engineering and artificial intelligence. Her work explores how machine learning techniques can improve software development processes, enhance security practices, and address challenges in program analysis. She has made significant contributions to understanding how large language models can be effectively applied to code generation, vulnerability detection, and software testing. Her research has practical implications for improving software reliability and security in real-world applications, particularly in safety-critical domains like autonomous systems. Analysis of Dr. Ray's recent publications reveals a clear trajectory toward leveraging AI for practical software engineering challenges. Her work has evolved from foundational program analysis techniques to cutting-edge applications of large language models in code understanding and generation. A notable trend is her focus on making AI-assisted software development more reliable, secure, and energy-efficient. Her research increasingly addresses the practical limitations of current AI approaches while developing novel methodologies to overcome them. IEEE TCSE Rising Star Award NSF CAREER Award IBM Faculty Award VMWare Faculty Award ICSME Most Influential Paper Award (2023) FSE'17 Distinguished Paper ASE'22 Distinguished Paper ISSTA'23 Distinguished Paper CACM Research Highlights Dr. Ray actively mentors graduate students and has built a productive research group focused on AI-driven software engineering solutions. Her research has been supported by prestigious grants including the NSF CAREER award. She has successfully guided numerous students through their research projects, with several of her advisees making significant contributions to publications in top-tier conferences. Dr. Ray also serves as an Amazon Visiting Academic, bridging academia and industry to address real-world software engineering challenges. Through her leadership in various research projects and collaborations, Dr. Ray has established a dynamic research environment that combines theoretical rigor with practical applications. Her work often involves interdisciplinary collaboration across computer science subfields, particularly connecting software engineering with security and AI research communities.

Ilya Sergeyمشاهده پروفایل

دانشیار

• Programming Languages
• Concurrency
• Type Theory
• +۷ مورد دیگر

Ilya Sergey is an Associate Professor at the National University of Singapore (NUS) School of Computing, with previous faculty appointments at University College London (2015-2018). His academic career spans multiple prestigious institutions including IMDEA Software Institute (postdoctoral position) and KU Leuven (PhD). His educational background includes a PhD in Computer Science from KU Leuven (2012), an MSc in Mathematics and Computer Science from Saint Petersburg State University (2008), and professional experience as a software engineer at JetBrains prior to academia. Sergey's research focuses on the intersection of programming language theory and practical software verification, with particular emphasis on concurrent systems , smart contracts , and program synthesis . His work bridges theoretical foundations in type theory and separation logic with practical applications in blockchain technology and Rust programming. He has developed novel techniques for verifying heap-manipulating programs, analyzing commutativity in distributed transactions, and synthesizing correct-by-construction code. Analysis of his recent publications reveals a clear trajectory toward practical verification of blockchain systems and concurrent data structures, with increasing focus on Rust programming language applications. His work demonstrates consistent innovation in mechanized reasoning techniques while maintaining relevance to real-world software challenges, particularly in the domains of smart contracts and distributed systems. Sergey maintains an active research group at NUS, as evidenced by his social media references to lab traditions and student collaborations. He frequently participates in major programming languages conferences as both author and committee member, serving in leadership roles including General Chair for ICFP 2025. His research lab follows distinctive traditions, including location-based Mattermost status updates when traveling. Sergey is deeply engaged with the programming languages community through conference organization, mentoring activities, and outreach initiatives such as nature walks for conference attendees.

Yasutaka Kameiمشاهده پروفایل

استاد

• Empirical Software Engineering
• Software Reliability
• Software Testing
• +۸ مورد دیگر

Yasutaka Kamei is a Full Professor at Kyushu University's Graduate School and Faculty of Information Science and Electrical Engineering, where he leads the POSL Lab (Process-Oriented Software Laboratory). He was promoted from Associate Professor to Full Professor in January 2024 after serving as Associate Professor from March 2015 to December 2023. He is also an InaRIS Fellow (2023-2033), receiving 10 million yen annually for his research on 'New paradigm for software development styles based on machine-human interaction.' Dr. Kamei's research focuses on Empirical Software Engineering (ESE) and Open Source Software Engineering (OSSE), with particular expertise in software reliability, testing, defect prediction, code review analysis, and mining software repositories. His work bridges empirical methods with practical software engineering challenges, emphasizing how data-driven approaches can improve software quality assurance processes. His recent publications demonstrate a strong trend toward understanding human factors in software development processes, analyzing modern code review practices, investigating technical debt, and exploring the application of large language models in software engineering tasks. His research spans both traditional software engineering challenges and emerging AI-driven approaches to software development. IPSJ/ACM Award for Early Career Contribution to Global Research (2019) Best industry paper award at ESEM 2018 Distinguished Paper Award at MSR 2014 InaRIS Fellow (2023-2033) Dr. Kamei actively serves the software engineering community as Tutorials Chair for ASE 2025 and has been a program committee member for numerous top-tier conferences including ICSE, FSE, ASE, ESEC/FSE, SANER, and MSR. He has secured multiple competitive grants from MEXT (Ministry of Education, Culture, Sports, Science and Technology) to support his research on test case generation, automated software testing for deep learning systems, technical debt engineering, and mining software repositories. His POSL Lab at Kyushu University serves as a hub for empirical software engineering research, focusing on data-driven approaches to improve software development processes and outcomes through rigorous analysis of software repositories and developer activities.

NIKOLAY HRISTOV NENOVمشاهده پروفایل

مدرس پاره‌وقت

• Industrial Management
• Electronics
• Electrical Engineering
• +۳ مورد دیگر

Nikolay Hristov Nenov is a Part-time Lecturer at the Technical University - Gabrovo, Bulgaria, within the Faculty of Economics, Department of Management. Holding a Doctorate in Technical Sciences, he bridges industrial management with technical disciplines through extensive teaching and research in electronics and electrical engineering. His work emphasizes practical applications for industrial systems and student training. Nenov's research spans Industrial Management , Electronics , and Electrical Engineering , with core focus on industrial electronics , control circuits , induction heating systems , and emerging Industry 4.0 challenges. His methodology integrates theoretical frameworks with hands-on laboratory exercises, as demonstrated in his textbooks covering electrical measurements, electric drives, and industrial electronics. Recent investigations explore deformation-photon effects and environmental monitoring devices, reflecting interdisciplinary innovation. Analysis of his 15 most recent publications reveals dominant themes in induction heating applications (water heaters, boilers, industrial assemblies) and industrial electronics . Work evolved from foundational textbooks (2009-2011) to contemporary topics like Industry 4.0 (2021) and photon emission physics. Frequent collaborations with P. Tomchev and R. Ivanova yield engineering solutions for manufacturing, thermal systems, and radiation effects, highlighting consistent industry-academia partnerships.

Myra Cohenمشاهده پروفایل

استاد

• Software Testing
• Configurable Software
• Search-based Software Engineering
• +۳ مورد دیگر

Myra Cohen is a Professor and the Lanh and Oanh Nguyen Chair in Software Engineering in the Department of Computer Science at Iowa State University. Previously, she held the position of Susan J. Rosowski Professor at the University of Nebraska-Lincoln where she was a member of the ESQuaReD software engineering research group. She serves on the ASE Steering Committee and has held leadership roles including general chair of ASE 2015 and program co-chair for ICST 2019 and ESEC/FSE 2020. Dr. Cohen earned her Ph.D. from the University of Auckland, New Zealand, her M.S. from the University of Vermont, and her B.S. from the School of Agriculture and Life Sciences at Cornell University. Her academic journey includes lecturing positions at both the University of Auckland and University of Vermont during her graduate studies. Her research spans several interconnected domains focused on software quality and assurance. A significant portion of her work addresses software testing challenges in highly-configurable systems, where she applies search-based techniques and combinatorial designs to create efficient test suites. More recently, her research has expanded into innovative areas including software testing for biological systems, quantum computing applications, and security testing through genetic improvement techniques. Her work demonstrates a consistent theme of addressing complex verification challenges through creative application of formal methods and automated techniques. Analysis of her recent publications reveals a growing focus on emerging domains including quantum software testing, molecular/biological computing systems, and assurance cases for safety-critical systems. She has increasingly incorporated AI techniques, particularly large language models, into traditional software engineering problems while maintaining her foundational work in configurable systems and metamorphic testing. NSF CAREER award recipient AFOSR Young Investigator Award recipient ACM Distinguished Scientist Recipient of 4 ACM Distinguished Paper awards Dr. Cohen has served as chair and committee member for numerous conferences including ASE, ICSE, ISSTA, ESEC/FSE, and ICST. She has mentored numerous students through the doctoral symposiums and student research competitions at major software engineering conferences. Her research has been supported by significant grants including those from NSF and AFOSR. She leads the LaVA-OPs (Laboratory for Variability-Aware Assurance and Testing of Organic Programs) research group at Iowa State University, which focuses on testing challenges in biological and organic computing systems.