جست‌وجوی استاد و پژوهشگر

Chengnian Sunمشاهده پروفایل

دانشیار

• Software Engineering
• Software Reliability
• Software Security
• +۵ مورد دیگر

Chengnian Sun is an Associate Professor at the University of Waterloo's David R. Cheriton School of Computer Science. He holds a Ph.D. from the National University of Singapore (2013). His research focuses on software engineering, emphasizing software reliability, security, and developer productivity. His work spans compiler testing, program analysis, cybersecurity, and programming language tools. Key research trends include leveraging large language models (LLMs) for compiler testing and program reduction, probabilistic debugging techniques, and enhancing software security against ransomware and fuzzing attacks. His contributions address challenges in program simplification, fault localization, and vulnerability detection. Notable projects include frameworks like Perses (syntax-guided program reduction), T-Rec (language-agnostic program reduction), and tools like AddressWatcher for memory leak detection. His work bridges theoretical advancements with practical software engineering solutions. Chengnian advises on compiler reliability, cybersecurity, and developer productivity. His research has led to collaborations with industry on testing tools and security frameworks. He maintains an active lab focused on advancing software systems through rigorous analysis and innovation.

Michal Kalkowskiمشاهده پروفایل

دانشیار

• Non-destructive testing
• Material characterisation
• Ultrasonic imaging
• +۶ مورد دیگر

Michal Kalkowski is an Associate Professor at the University of Southampton's Institute of Sound and Vibration Research (ISVR). His research focuses on structural wave and vibration analysis for non-destructive testing, material characterization, and infrastructure monitoring. He develops advanced modeling tools and signal processing techniques for applications in nuclear energy, aerospace, and water industries. Current projects include weld inspection through ultrasound-based 'weld map tomography' and leak detection in buried pipes using distributed acoustic sensing. He is Editor of the Journal of Sound and Vibration and Co-chair of the UK Acoustics Network UKAN+. Education: MEng in Control Engineering & Robotics (AGH University, Krakow), PhD in Structural Wave Applications (ISVR, 2010). Postdoctoral work included EPSRC projects on active vibration control and underground structure interrogation. Served as H2020 ADVISE project researcher at Imperial College London before returning to Southampton in 2021 as Lecturer in Dynamics. Teaching responsibilities include coordinating the Mechanics, Machines & Vibration module (joint with Harbin Engineering University), and teaching Statics/Dynamics (FEEG1002) and Fundamentals of Vibration (ISVR6141). Actively supervises four PhD students in engineering disciplines. Research highlights include: Developing numerical models for wave propagation in complex materials Pioneering weld map tomography for grain orientation analysis Advancing distributed acoustic sensing for infrastructure monitoring AI integration for coarse-grained metal characterization Current active projects: Horizon Europe iWeld intelligent Weld inspection and EPSRC Core Equipment grants.

Manish Motwaniمشاهده پروفایل

استادیار

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

Manish Motwani is an Assistant Professor at the School of Electrical Engineering and Computer Science, Oregon State University. His research focuses on automating software engineering practices to improve software quality, particularly in high-performance computing (HPC), REST APIs, and natural language-driven program repair. He leads the Advanced Software Engineering Research (ANSWER) lab, which is part of the Software Engineering and Human-Computer Interaction group. Education: Ph.D. in Computer Science (University of Massachusetts Amherst), Postdoctoral Fellow (Georgia Institute of Technology) Motwani's research bridges empirical analysis of software repositories with automated techniques for testing, debugging, and program repair. Key projects include: Automated Testing for HPC Applications OpenAPI Specification Generation via Static Analysis High-Quality Patch Validation Using Bug Reports JaRFLy Framework for Patch Evaluation Swami Tool for Natural Language Test Oracles RAFL and Blues Fault Localization Techniques His work addresses critical challenges such as patch overfitting, HPC bug detection, and semantic search for real-world defects. He has published in top venues like ICSE, TSE, and EMSE, and holds two U.S. patents for automated requirements and regulatory compliance tools. At Oregon State, Motwani actively mentors and seeks motivated PhD students interested in software testing, debugging, and program repair for HPC and AI/ML applications. He previously contributed to requirements engineering at Tata Research Development and Design Centre in India.

Chang Louمشاهده پروفایل

استادیار

• Distributed Systems
• Cloud Computing
• Runtime Assurance
• +۴ مورد دیگر

Chang Lou is an Assistant Professor in the Department of Computer Science at the University of Virginia, part of the School of Engineering and Applied Science. His research focuses on enhancing cloud system reliability through runtime assurance, distributed systems, and formal verification techniques. He holds a Ph.D. from Johns Hopkins University (2023) and a B.S. from Shanghai Jiao Tong University (2016), with a gap year at IPADS under Prof. Haibo Chen. Education: Ph.D., Computer Science, Johns Hopkins University, 2023 (Advisor: Prof. Peng Huang) B.S., Computer Science, Shanghai Jiao Tong University, 2016 Research Interests: Dr. Lou’s work addresses complex failures in distributed systems, including runtime failure detection, formal verification for ML models, and anomaly mitigation in cloud infrastructure. His lab develops tools like OKLib and RESIN , deployed in production environments such as Microsoft Azure. Recent efforts include NSF-funded research on low-effort runtime assurance for cloud systems. Awards: Recipient of the NSF CAREER Award (2024), NSDI’20 Best Paper Award, and the ACM SIGOPS Dissertation Honorable Mention (2023). Teaching: Teaches CS4740: Cloud Computing and CS6501: Cloud System Reliability at UVA. Courses emphasize distributed systems principles, reliability techniques, and practical project-based learning. Service: Serves on program committees for NSDI’26, SOSP’25, EuroSys’25, and others. Co-organizes workshops on Formal Methods in Networked Systems (SIGCOMM 2024).

Thomas E. Ahleringمشاهده پروفایل

استاد

• Urologic Oncology
• Robotic Surgery
• Prostate Cancer
• +۷ مورد دیگر

Dr. Thomas E. Ahlering is a Professor and Vice Chairman in the Department of Urology at the University of California, Irvine (UCI) School of Medicine. He is a leading expert in urologic oncology, specializing in robotic radical prostatectomy for prostate cancer, with over 2,500 surgeries performed. He previously served as Chief of Urologic Oncology at City of Hope and Chief of Urology at UC Irvine. His clinical and research work has earned him recognition as one of America’s Best Doctors since 1994 and as a Top 2% Medical Scientist globally. Dr. Ahlering's research interests center on urologic oncology , particularly robotic surgery , functional recovery after prostatectomy , and patient-reported outcomes . He has pioneered techniques in nerve-sparing and urinary anastomosis to improve continence and potency. His work has significantly contributed to the adoption and refinement of da Vinci robotic systems in urologic surgery. His scholarly output includes over 400 publications, with recent work focusing on surgical innovation, international training, patient selection, and long-term oncological outcomes. The articles reflect a strong emphasis on improving surgical precision, minimizing complications, and enhancing quality of life. Themes include technological evolution, global dissemination of robotic techniques, and patient-centered care. Scientific recognition includes: Lifetime Achievement Award in Robotic Surgery (North American Robotic Urology Symposium) Outstanding Faculty Achievement – Lauds and Laurels (UCI Alumni Association) Mentor of the Year (UCI Institute of Clinical and Translational Science) Top 2% of Medical Scientists in the World (Stanford Study) Consistently listed in America’s Best Doctors since 1994 Dr. Ahlering has mentored numerous trainees and residents, contributing significantly to education in urologic oncology. His lab and surgical team, often referred to as "The A-Team," operate at MiVIP Surgical Center and are known for their high coordination, patient-centered approach, and expertise in robotic prostatectomy. He continues to lead innovation in urinary diversion techniques such as the Indiana pouch and ileal neobladder.

Chengnian Sunمشاهده پروفایل

دانشیار

• Software Engineering
• Programming Languages
• Compiler Testing
• +۴ مورد دیگر

Chengnian Sun is an Associate Professor at the Cheriton School of Computer Science , University of Waterloo, Canada. His research focuses on software engineering and programming languages with an emphasis on software reliability and programming productivity. Education : Ph.D. in Computer Science from National University of Singapore (2013) His work spans compiler testing (EMI, Dfusor, Kitten), program reduction (Perses, Vulcan, PPR), Android testing, and DNN testing. He has received multiple grants including Google Research Scholar Program (2025) and NSERC Discovery Grants (2024-2029). His recent publications focus on LLM-based compiler testing, weighted delta debugging, and ransomware resilience. Scientific Awards : Most Influential Paper Award at SANER (2022) NUS Research Scholarship (2008-2012) ACM SIGSOFT Distinguished Paper Award at ASE (2012) IBM Cup Campus Innovation Contest First Prize (2005) He advises Ph.D. and MMath students in software engineering, compiler testing, and program analysis, including several who have contributed to top-tier conferences like ICSE, ISSTA, and ASPLOS. His service includes program committee roles in ICSE, OOPSLA, and ISSTA.

Xiaoyin Wangمشاهده پروفایل

دانشیار

• Natural Language Processing
• Program Analysis
• Software Engineering
• +۶ مورد دیگر

Xiaoyin Wang is an Associate Professor in the Department of Computer Science at the University of Texas at San Antonio, with affiliations to the College of AI, Cyber and Computing. She previously held a PostDoc position at UC Berkeley's Department of Electrical Engineering and Computer Science. Ph.D. in Computer Science, Peking University (2012) B.Eng. in Computer Science, Harbin Institute of Technology Her research focuses on Natural Language Processing , Program Analysis , Software Engineering , and Software Security . Key sub-areas include: Software migration and compatibility Build system automation Testing and debugging methodologies Privacy policy enforcement in mobile apps Deep learning for software analysis Augmented/Virtual Reality testing Recent publications (2022-2024) emphasize automated oracle prediction for AR/VR testing, data-sensitive analysis, and DevOps toolchain optimization. Trends include: Adaptation of program analysis to immersive environments Privacy-preserving software engineering Empirical studies on testing frameworks Academic accolades include: NSF CAREER Award (2019) President's Research Achievement Award (UTSA, 2019) Multiple best paper awards at ICSE, TOSEM She has advised 7 graduate students, including: Current: Rodney Rodriguez, Xueling Zhang, Sunzhou Huang Graduated: Xue Qin (Villanova), Foyzul Hassan (UM-Dearborn), Shaikh Mostafa (Amazon/Microsoft) Laboratory work involves tools like: TranStrL: Software internationalization Hima: API mapping for framework evolution NetworkProfiler: Android app fingerprinting DOVAR: AR/VR visualization for education Uniloc: CI failure diagnosis

Jyotsna Sharmaمشاهده پروفایل

دانشیار

• Fiber Optic Sensing
• Enhanced Oil Recovery
• Machine Learning
• +۳ مورد دیگر

Dr. Jyotsna Sharma is an Associate Professor in the Craft & Hawkins Department of Petroleum Engineering at Louisiana State University (LSU), serving concurrently as Program Director at the U.S. Department of Energy's Advanced Research Projects Agency-Energy (ARPA-E). She holds an adjunct appointment in LSU's Department of Electrical Engineering. Her research focuses on fiber optic sensing technologies, machine learning applications in energy systems, enhanced oil recovery, and sensor development. Sharma earned her Ph.D. in Petroleum Engineering from the University of Calgary (2012) and a B.Tech. in Electrical Engineering from IIT Delhi (2006). Her professional experience spans industry roles at Chevron (2012-2018), including reservoir engineering and heavy oil projects, as well as academic appointments at LSU since 2019. Key research areas include distributed acoustic sensing (DAS), satellite gravimetry for hydrocarbon mapping, and quantum-enhanced sensors. Collaborations involve NASA, Oak Ridge National Lab, and major energy companies. Awards include the NSF I-Corps program (2024), LSU Alumni Association Rising Faculty Award (2023), and multiple industry-sponsored grants. Her work has been featured in high-impact journals and conferences, addressing challenges in well integrity, offshore drilling safety, and energy transition technologies. Sharma’s lab integrates machine learning with experimental facilities like the LSU PERTT Lab, advancing real-time monitoring solutions for energy systems. She leads initiatives in leak detection, gas migration analysis, and smart sensor networks, emphasizing interdisciplinary innovation.

• Control Systems
• Water Resource Management
• Data-Driven Methods
• +۳ مورد دیگر

Luis Romero Ben is a Researcher at the Department of Automatic Control, Universitat Politècnica de Catalunya (UPC). His work focuses on advanced monitoring and control systems for water distribution networks, emphasizing real-time leak detection, data-driven methodologies, and sensor network optimization. He is affiliated with the IRI (Institut de Robòtica i Informàtica Industrial) research institute. Key projects include: FUSAGUA (CSIC Project): Real-time sensor fusion for water leak monitoring (2025–). RUBIES (European Project): Pollution-based control of urban drainage systems (2021–). Research interests revolve around: Hydraulic modeling and state estimation (e.g., Unscented Kalman Filters). Graph-based and machine learning techniques for anomaly detection. Optimal sensor placement using genetic algorithms and clustering. Comparative analysis of model-based vs. data-driven approaches. Publications highlight contributions in leak localization algorithms, network resilience strategies, and interdisciplinary methods bridging physics-based models with modern data science.

Moez Louatiمشاهده پروفایل

دانشیار مدعو

• Fluid Mechanics of Waves
• Pipeline Hydraulics
• Water Loss Management
• +۵ مورد دیگر

Moez Louati is an Adjunct Associate Professor in the Department of Civil and Environmental Engineering at The Hong Kong University of Science and Technology (HKUST). His expertise spans fluid mechanics of waves, pipeline hydraulics, and smart water infrastructure. He holds a PhD from HKUST, supported by scholarships and the SENG PhD Fellowship Award. His research focuses on pipeline defect detection, hydraulic transients, and smart urban water systems, with notable contributions including the discovery of Bragg resonance connections in pressurized pipes. He has led projects funded by RGC, ITF, and international collaborations, and co-founded Hyele Limited, a startup developing pipeline condition assessment technologies. Education: B.Eng. (Electro-Mechanical Engineering) and MPhil (Renewable Energy) from Tunisia’s National School of Engineering of Sfax (ENIS). Professional credentials include HKIE chartered engineer status and roles as Chair of IAHR’s Africa Division and Assistant Editor of the Journal of Hydraulic Research. Research Interests: Fluid mechanics of waves, computational fluid dynamics (CFD), machine learning for infrastructure optimization, and sustainable water management. Key projects include Smart Urban Water Supply Systems and high-frequency wave-based defect detection methods. Awards: Geneva Innovations Expo 2023/24 awards, Straub Award nomination, and HKUST’s Tech-Ship startup funding. Active in international organizations and advisory roles for Hong Kong’s WSD and DSD. Labs & Facilities: Designed three water lab facilities at HKUST and collaborated globally on projects like the FREJLEV Facility’s air-water stratified flow studies. Holds five patents in pipeline diagnostics and HPC applications.

Chaoxiong Yeمشاهده پروفایل

پژوهشگر ارشد

• Cognitive Neuroscience
• Visual Memory
• Working Memory
• +۳ مورد دیگر

Dr. Chaoxiong Ye is an Academy Research Fellow (PI) at the Department of Psychology, University of Jyväskylä. He holds two PhDs: one in Cognitive Science (2015–2018) and another in Psychology (2018–2020). He holds four docentships (Associate Professor titles) at Finnish universities in Cognitive Neuroscience and Cognitive Psychology. As a PI, he has secured over €1.5M in funding and supervises nine doctoral students. He serves on editorial boards of BMC Psychology and PLOS ONE , and fosters international collaborations with leading institutions globally. Education: PhD in Cognitive Science, University of Jyväskylä (2015–2018) PhD in Psychology, University of Jyväskylä (2018–2020) Master’s in Applied Psychology, MinNan Normal University (2012–2015) Research Interests: Focuses on cognitive and neural mechanisms of visual memory, working memory, and emotional face processing. Current projects include studying memorability’s impact on long-term memory and developing diagnostic strategies for memory disorders. Principal Investigator: Cognitive and Neural Mechanisms for Memorable Visual Stimuli (€0.93M, 2023–2027) Previous project: Two-Phase Resource Allocation Model of Visual Working Memory (2020–2023) Publications: Over 110 publications in top journals, emphasizing working memory mechanisms, emotional interference, and neural basis of depression. Notable contributions include studies on retro-cue effects, dimension-based attention, and face distractor impacts. Awards & Grants: Secured €1.5M+ in grants from the Research Council of Finland. Recognized for editorial work and international collaborations. Labs & Teams: Leads Ye’s Lab at the University of Jyväskylä, fostering research on cognitive processes and neural mechanisms.

• Calcium Signaling
• Cardiac Physiology
• Excitation-Contraction Coupling
• +۶ مورد دیگر

Rafael Mejia-Alvarez is a Professor at Midwestern University , where he holds appointments in the Chicago College of Optometry , College of Graduate Studies - Illinois , Chicago College of Osteopathic Medicine , and College of Dental Medicine-Illinois . His academic career spans multiple disciplines, including Physiology , Biomedical Sciences , and Cardiovascular Research . Ph.D. from Baylor College of Medicine/CINVESTAV, USA (1990) M.D. from Universidad Nacional Autonoma de Mexico, USA (1982) His research focuses on Calcium Signaling in excitable cells, particularly the mechanisms of Ca²⁺ release via Ryanodine Receptors (RyRs) and Inositol 1,4,5-Trisphosphate Receptors (IP3Rs) . He investigates their roles in cardiac excitation-contraction coupling , arrhythmogenic intracellular channelopathies , and the antiarrhythmic effects of scorpion venom peptides . Techniques include immunocytochemistry , electrophysiology , and pulsed local-field fluorescence microscopy to study intact beating hearts. Recent publications (2023–2005) highlight his work on Ca²⁺ signaling dynamics in cardiac cells, genetic mutations in IP3Rs linked to arrhythmias, and innovations in imaging methodologies . His multidisciplinary approach bridges molecular physiology, pharmacology, and translational medicine. Teaching Interests: Courses include Neuromuscular & Cardiovascular Physiology , Obesity & Cardiovascular Diseases , Cardiac Arrhythmias & Channelopathies , and Precision Medicine in Cardiovascular Systems across multiple academic schools. Grants: Recipient of a 2023 MWU Intramural Grant for research on IP3R2-mediated Ca²⁺ Signaling in Ventricular Myocytes .

Ramin Moghaddassمشاهده پروفایل

دانشیار

• Predictive Analytics
• Machine Learning
• Industrial Engineering
• +۴ مورد دیگر

Ramin Moghaddass is an Associate Professor in the Department of Industrial Engineering at the University of Miami's College of Engineering. He serves as Director of both the Industrial Research and Assessment Center and the Building Training, Research, and Assessment Center. His work bridges machine learning with industrial engineering to solve complex system monitoring and maintenance challenges. University of Miami, College of Engineering Director, Industrial Research and Assessment Center Director, Building Training, Research, and Assessment Center His research focuses on: Deep state-space modeling for dynamic systems Graph neural networks for smart grid and network anomaly detection Thermal-RGB sensor fusion for manufacturing plant efficiency Image processing for vegetation risk analysis in power networks Bayesian filtering techniques with stochastic neural networks Recent publications highlight trends in sensor-driven system modeling (2025), thermal-RGB fusion for HVAC optimization (2025), anomaly detection in smart grids (2025), and adaptive inspection protocols for large-scale networks (2024). His work combines recurrent neural networks with dynamic Bayesian layers for predictive analytics while exploring graph topology integration. Contact: rxm991@miami.edu | (305) 284-9505

Katharina Kohlsمشاهده پروفایل

استاد

• System Security
• Mobile Network Security
• Privacy and Anonymity
• +۳ مورد دیگر

Prof. Dr. Katharina Kohls serves as a Professor at Ruhr University Bochum specializing in system security, with research spanning mobile network vulnerabilities (4G/5G), privacy/anonymity systems, and internet censorship detection. Her work addresses critical security flaws in cellular infrastructure and anonymity networks through empirical attack simulations and defensive techniques. Her primary research domains include: Mobile Network Security : Investigating protocol vulnerabilities in 4G/5G including fake base stations, bidding-down attacks, and voice call eavesdropping (ReVoLTE/IMP4GT) Privacy & Anonymity : Analyzing traffic on Tor, location leaks in messaging apps, and information leakage in mobile VPNs Internet Measurement : Leading censorship monitoring initiatives like Censored Planet for longitudinal internet freedom analysis Analysis of her 2019-2024 publications reveals escalating focus on 5G security challenges and machine learning applications for intrusion detection, with consistent contributions to identifying practical attack vectors against real-world communication systems. Her methodology combines large-scale simulations with field measurements to expose systemic vulnerabilities. No scientific awards or student advising information was documented in the provided materials. Her contact details (room MC 4.137, tel +49 (0)234 32-27814) confirm active faculty status without indication of specialized labs or research teams in the source data.

Mahmoud Alfadelمشاهده پروفایل

استادیار

• Software Engineering
• Mining Software Repositories
• Empirical Software Engineering
• +۳ مورد دیگر

Mahmoud Alfadel is an Assistant Professor at the University of Calgary, Canada, actively contributing to software engineering research through program committee roles at ASE, ICSE, and ESEC/FSE conferences from 2021-2025. His research centers on Software Ecosystems, Release Engineering, and Empirical Software Engineering, with specific focus on build systems, continuous integration pipelines, dependency management, and software quality metrics in open-source environments. Methodologically, he employs large-scale empirical studies of real-world development practices. Analysis of his 2021-2025 publications reveals consistent investigation into build technology evolution (particularly Bazel), dependency-induced waste in NPM, and testing practices like fuzzing adoption. His work bridges theoretical software engineering concepts with practical industry challenges, often through case studies of major open-source projects like Kubernetes.