جست‌وجوی استاد و پژوهشگر

Brittany Johnson-Matthewsمشاهده پروفایل

استادیار

• Empirical Software Engineering
• Human Computer Interaction
• Machine Learning
• +۳ مورد دیگر

Brittany Johnson-Matthews is an Assistant Professor in the Department of Computer Science at George Mason University, where she directs the INSPIRED Lab (INterdisciplinary Software Practice Improvement REsearch and Development). Her work bridges software engineering, human-computer interaction, and machine learning to address sociotechnical challenges in software development. Her educational background includes: Ph.D. in Computer Science from North Carolina State University (2017) B.A. in Computer Science from the College of Charleston (2011) Dr. Johnson-Matthews' research centers on sociotechnical problems in software development, with emphasis on developer productivity, tool support, work environments, ethics, and software for social good. She employs interdisciplinary approaches to study how developers interact with tools and environments, particularly in the context of emerging technologies like AI. Her work often involves empirical studies and tool development to promote fairness, inclusivity, and well-being in software engineering. Analysis of her recent publications (2023-2026) reveals a consistent focus on the human aspects of software engineering. Key themes include the impact of AI-assisted tools on developer well-being, fairness in machine learning toolkits, and ethical considerations in software development. Her research frequently involves building and evaluating tools (e.g., for detecting harmful terminology or causal testing) and conducting empirical studies across open source and industrial settings. She leads the INSPIRED Lab, which fosters interdisciplinary collaboration to improve software practices through research in human-centered computing, empirical software engineering, and ethical AI.

Martin J. Hayesمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Wireless Communications
• +۵ مورد دیگر

Professor Martin J. Hayes serves in the Department of Electronic and Computer Engineering at the University of Limerick's Faculty of Science and Engineering. His institutional affiliation includes campus location ERB2-021 and contact details: email Martin.J.Hayes@ul.ie and phone +353 (0)61 202577. His research concentrates on Artificial Intelligence and Computer Vision applications within Smart Manufacturing and Autonomous Vehicles . Key specialties include deep learning for defect detection, visual question answering systems, and real-time failure monitoring in industrial environments. He also investigates interoperable IoT security frameworks and private 5G network implementations for Industry 4.0. Analysis of recent publications (2023-2025) reveals dominant themes in AI-driven manufacturing solutions and autonomous driving technologies. His work consistently addresses data-constrained training environments and real-time performance requirements, with growing emphasis on human-machine interaction patterns and subjective evaluation frameworks for vision systems. Scientific Awards: No scientific awards were documented in available sources Advising and Grants: While specific student advisement records and grant details were not provided, Professor Hayes' extensive publication output across manufacturing automation, autonomous systems, and wireless communications indicates active leadership in multiple research initiatives. His involvement in the REEdI (Rethinking Engineering Education in Ireland) project demonstrates commitment to educational innovation alongside technical research.

Catalina Gabriela MIHALCEAمشاهده پروفایل

پژوهشگر

• Gas Sensing
• Photocatalysis
• Nanomaterials
• +۳ مورد دیگر

Catalina Gabriela MIHALCEA serves as an Assistant Researcher at the Laboratory of Atomic Structures and Defects in Advanced Materials (LASDAM) within the National Institute of Materials Physics. Her work focuses on advanced nanomaterials for gas sensing and photocatalytic applications, with particular expertise in metal oxide semiconductors including TiO 2 , SnO 2 , NiO, and WO 3 . Her research interests span gas sensing mechanisms (particularly for CO 2 , methane, acetone, and hydrogen), defect engineering in nanomaterials , and photocatalytic performance optimization . Key methodologies include hydrothermal synthesis, co-precipitation, and advanced characterization techniques such as EPR spectroscopy, TEM, and XRD. She investigates how morpho-structural properties, synthesis parameters, and environmental conditions (humidity, temperature) affect material performance. Analysis of her 15 most recent publications reveals a strong emphasis on in-field condition testing using computer-controlled Gas Mixing Systems, with significant contributions to understanding charge carrier trapping in phase-transforming TiO 2 , electrode geometry effects in SnO 2 sensors, and humidity-resistant sensing platforms. Her work demonstrates consistent innovation in sensor design and fundamental material behavior under operational conditions. She actively collaborates with researchers across multiple institutions, evidenced by co-authorship on publications spanning materials synthesis, characterization, and application testing. Her technical contributions include developing synthesis protocols for black TiO 2 with enhanced visible-light photocatalysis and optimizing WO 3 sensors for low-concentration acetone detection in high-humidity environments.

Shin Hongمشاهده پروفایل

دانشیار

• Software Testing
• Automated Debugging
• Program Analyses
• +۶ مورد دیگر

Shin Hong is an Associate Professor at the School of Computer Science, Chungbuk National University (CBNU) in South Korea. He leads the SDEV lab (소프트웨어 개발검증 연구실) and maintains active roles in major software engineering conferences including ASE 2025 (Local Arrangement Co-Chair), ICST 2026 (General Co-Chair), and SSBSE 2025 (General Chair). His research focuses on Software Testing, Automated Debugging, and Program Analyses , with specific expertise in test case generation, debugging automation, and static/dynamic/neural program analysis techniques. Dr. Hong's work bridges theoretical advances with practical applications, as evidenced by his industrial case study with SAP HANA. Analysis of his recent publications reveals strong trends in fuzzing techniques (ZigZagFuzz, BUGOSS), regression bug benchmarking, mutation analysis, and GUI test case repair. His research demonstrates increasing sophistication in combining traditional software engineering approaches with machine learning methods for test optimization and fault diagnosis. Research Focus Areas: Advanced test generation techniques Automated debugging and fault localization Machine learning applications in software testing Empirical evaluation of testing techniques Dr. Hong actively contributes to the academic community through program committee service at top conferences and mentorship of graduate students at CBNU. His leadership roles in major conferences reflect his standing in the software engineering research community.

Max Hortمشاهده پروفایل

پژوهشگر

• Machine Learning for Software Engineering
• Defect Detection
• Software Fairness
• +۲ مورد دیگر

Max Hort is a researcher at Simula Research Laboratory in Norway specializing in Machine Learning for Software Engineering, Defect Detection, and Software Fairness. He has established himself as an active contributor to the software engineering research community through numerous publications and program committee roles at major conferences. His research focuses on: Machine Learning for Software Engineering Defect Detection Software Fairness Program Repair Log Parsing Hort's recent work demonstrates a strong emphasis on applying large language models to software engineering challenges, particularly in program repair and defect detection. His publications reveal a methodical approach to evaluating AI techniques in software engineering contexts, with special attention to reliability concerns like non-determinism in language models. He has also made significant contributions to the understanding of software fairness and bias mitigation. Through his active participation in program committees for ASE, ICSE, ESEC/FSE, and SANER conferences, Hort has earned recognition as a knowledgeable contributor to the field. His work bridges theoretical machine learning advancements with practical software engineering challenges, addressing critical issues in modern software development as AI-assisted programming becomes increasingly prevalent.

Georgina Cosmaمشاهده پروفایل

استاد

• Artificial Intelligence
• Data Science
• Natural Language Processing
• +۵ مورد دیگر

Professor Georgina Cosma is a Professor of AI and Data Science in the Department of Computer Science at Loughborough University, serving as Programme Director for the MSc in Data Science programme while teaching Natural Language Processing and Data Analytics & Visualisation courses. She earned her PhD in Computer Science (Intelligent Information Retrieval) from the University of Warwick in 2008, developing novel approaches for detecting similarities in natural language text and source-code files. Her research spans Artificial Intelligence, Data Science, and Natural Language Processing with specialization in Neural Information Retrieval, Ethical AI, and Continual Lifelong Learning. She develops responsible AI solutions for healthcare predictive modeling and personalized predictions, engineering defect detection systems, and digital library search engines, emphasizing explainable AI and temporal information modeling for multi-modal data including biomedical and sensor inputs. Dr Cosma leads a research team of PhD students and associates on funded healthcare AI projects, actively seeking academic and industry collaborations. She welcomes PhD candidates interested in neural information retrieval and AI applications, providing supervision for thesis development and research direction.

Konstantinos A. Tsintotasمشاهده پروفایل

استادیار

• Artificial Intelligence
• Robotics
• Computer Vision
• +۹ مورد دیگر

Konstantinos A. Tsintotas is an Assistant Professor at the Department of Information and Electronic Engineering, International Hellenic University. His research focuses on artificial intelligence, robotics, computer vision, and their applications in smart cities, healthcare, and manufacturing. He is actively involved in advancing AI-driven systems for critical infrastructure management, robotic vision, and embedded device technologies. His work spans theoretical advancements and practical implementations, including projects like SLAM algorithms for autonomous navigation, deep learning models for medical diagnosis, and IoT-integrated smart supply chains. Tsintotas also explores ethical implications of AI in human action recognition and contributes to neuromorphic computing through spiking neural networks. Key technical contributions include ReJSHand (real-time hand pose estimation), fall detection systems for embedded devices, and visual place recognition frameworks. His interdisciplinary approach bridges computer science, electrical engineering, and biomedical applications, reflecting a strong commitment to innovation at the hardware-software interface. Notable trends in his publications emphasize AI ethics, multimodal perception for robotics, and low-power embedded solutions. Ongoing work includes advancing digital twin technologies for supply chains and refining bio-inspired neural architectures for robotics applications.

• Structural Dynamics
• Structural Health Monitoring
• Renewable Energy
• +۵ مورد دیگر

Dr. Vikram Pakrashi is an Associate Professor in Mechanical Engineering and Director of the Dynamical Systems and Risk Laboratory (DSRL) at University College Dublin. He specializes in structural dynamics, structural health monitoring (SHM), vibration control, and renewable energy systems. His work bridges industry and academia, focusing on infrastructure resilience and emerging technologies. Education: BEng (1st Class Hons) from Jadavpur University; PhD from Trinity College Dublin. Research interests include dynamical systems, risk analysis, and smart structures. He leads interdisciplinary projects funded by industry and agencies like SEAI and the EU. Recent research trends emphasize renewable energy infrastructure (e.g., offshore wind, wave energy devices) and innovative SHM techniques using machine learning and sensor networks. His articles highlight advancements in wave measurement, defect detection algorithms, and structural fragility analysis. Awards: Engineering Laboratory of the Year 2018 (Irish Laboratory Awards). Grants: Includes projects like SISdATA (Atlantic aquaculture systems) and FlOWDyn (dynamic cable analysis for floating offshore wind). Lab Leadership: Directs DSRL, fostering industry collaboration and applied research.

Michael W. Godfreyمشاهده پروفایل

استاد

• Software Engineering
• Program Comprehension
• Mining Software Repositories
• +۵ مورد دیگر

Affiliations & Roles Michael W. Godfrey is a Professor in the David R. Cheriton School of Computer Science at the University of Waterloo . He holds the David R. Cheriton Faculty Fellowship and has served as an associate director of Cornell's M.Eng. program. His roles include: General Chair for ICPC 2025 (IEEE Program Comprehension) Member of steering committees for ICSME, MSR, SCAM, and SWAN Course coordinator for CS138/CS246 and instructor for advanced topics courses Research Focuses on software evolution , program comprehension , and mining software repositories . His work addresses challenges in code clone analysis, developer productivity, and empirical software engineering. Notable contributions include: Advocating for intentional cloning as valid design practice Pioneering studies on code review quality and anomaly detection Developing tools like JavaDUCK (educational project) and mel (model extraction) Awards & Recognition Recipient of: Best Paper Awards at WCRE 2006, 2011, 2013 Most Influential Paper Award at SANER 2016 Outstanding Reviewer Awards (ICSME 2019/2020) Service & Outreach Active in: Program committee roles for ICSE, ICSM, MSR, and 30+ conferences University service: Undergraduate Recruitment Committee (2016–present) Industry collaborations with CWI (Amsterdam), Sun Microsystems, and automotive software teams

Zuhal Erمشاهده پروفایل

دانشیار

• Solar Energy Engineering
• Photovoltaic Systems
• Solar Radiation
• +۳ مورد دیگر

Zuhal Er serves as a Docent (Associate Professor) in the Department of Basic Sciences at Istanbul Technical University, Istanbul, Turkey. With an active research profile spanning from 2005 to 2024, she has established herself as a leading researcher in solar energy engineering and renewable energy systems through 23 research outputs and two major funded projects. Research Interests: Dr. Er's work centers on solar radiation engineering (100% fingerprint match), photovoltaic systems including CdTe/CZTS/CZTSe solar cells (61-100% relevance), and solar collector optimization. Her research extends to computational materials science for energy applications, neutron shielding materials, and hybrid wind-solar systems for practical implementations like water pumping. She integrates engineering principles with materials science to solve real-world renewable energy challenges. Publications and Research Trends: Analysis of her 23 publications reveals a strategic evolution from fundamental solar calculations (2005-2010) toward advanced materials engineering (2015-2024). Recent work (2021-2024) demonstrates strong focus on computational modeling of doped semiconductors, optimization of chalcogenide solar cells, and development of radiation shielding materials, with increasing interdisciplinary collaboration evidenced by international co-authorships. Scientific Awards: THE RUNNERUP FOR THE BEST PAPER (2004) Advising and Grants: Dr. Er has supervised 5 students as indicated by institutional records. She successfully led two significant projects: Güneş radyasyonu tahmini ve PV panellerin bozulma modlarının bir uygulama çalışması (Solar Radiation Forecasting and PV Panel Failure Modes, 2019-2022) and Solar Enerjili Sistemler için Simülasyon ve Hesaplama (Simulation and Calculation for Solar Energy Systems, 2015-2018), demonstrating sustained research leadership in applied renewable energy. Labs and Teams: Her research is conducted within Istanbul Technical University's Department of Basic Sciences infrastructure, with extensive collaborative networks visible in co-authorships spanning computational materials science, photovoltaic engineering, and radiation physics teams across multiple international institutions.

Chetan Aroraمشاهده پروفایل

مدرس ارشد

• Applied Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۵ مورد دیگر

Dr. Chetan Arora is a Senior Lecturer in Software Engineering at Monash University's Faculty of IT, specializing in applied Artificial Intelligence (AI), including Machine Learning (ML) and Natural Language Processing (NLP). He serves as Director of Education (SSC) at the Faculty of IT and leads research in requirements engineering, software trustworthiness, and satellite communication (SatCom). His work contributes to UN SDGs related to education and innovation. Education : PhD in Computer Science, University of Luxembourg (2016) Masters in Software Engineering, Technische Universität Kaiserslautern (Germany) Bachelor's in Computer Science, Thapar University (India) Research Interests : Focus on AI-driven requirements engineering, generative AI applications in software development, and human-centric cybersecurity. Recent work explores ethical AI, persona-based design, and IoT integration in critical systems. Recent Research Trends : Over 65 publications since 2013, with 2025 highlighting generative AI's role in requirements engineering, ethical AI practices, and persona-driven design. 2024 research emphasizes optimization algorithms for EV networks and LLM-driven modeling. Awards : Best PhD Thesis Award (University of Luxembourg, 2016) ACM SIGSOFT Distinguished Paper Award (2022) Multiple Best Paper Awards at IEEE/ACM Conferences Grants & Collaboration : Secured >$1.1M in grants as Lead CI. Active in projects like RAISE: Responsible AI Software Engineering and GenAI-Powered ICT Education . Collaborates with industry partners like Episoft Pty Ltd and Swordfish Computing. Labs/Teams : Leads initiatives in the Department of Software Systems & Cybersecurity Impact Labs, focusing on AI ethics and human-centric software systems. Member of the International Requirements Engineering Board (IREB).

Andreas Baumgartnerمشاهده پروفایل

پژوهشگر

• Quantum Electronics
• Nanoelectronics
• Semiconductor Physics
• +۷ مورد دیگر

Andreas Baumgartner is a leading researcher in quantum electronics and nanoelectronics at the University of Basel. He currently serves as a Group Leader and Head of the SNI PhD School, with prior roles as Senior Scientist (since 2014) and Postdoctoral Fellow. His work focuses on quantum transport, superconductivity, spintronics, and topological materials, leveraging advanced nanofabrication and cryogenic techniques. Key projects include Cooper pair splitting, Majorana bound states, and quantum dot-based qubits. Education: PhD in Physics (ETH Zurich, 2005), Diploma in Interdisciplinary Science (ETH Zurich, 2000). Awards include EPSRC and Swiss National Science Foundation support. His lab develops ultra-clean carbon nanotube and semiconductor nanowire devices, with contributions to quantum computing hardware and graphene spintronics. Research emphasizes experimental probes of quantum phenomena: high-resolution electrical measurements, cryogenics down to 10 mK, and strain engineering. Recent advancements include long-distance qubit coupling, twisted trilayer graphene superlattices, and photon-mediated qubit interactions. Collaborative efforts with institutions like Kavli Institute and CERN highlight his interdisciplinary impact.

• Magnetoresistive Sensors
• Non-Destructive Testing
• Neural Networks
• +۵ مورد دیگر

Diogo Caetano is an Invited Assistant Professor at the Department of Electrical and Computer Engineering, Higher Technical Institute (University of Lisbon). His research focuses on advanced sensor systems, magnetoresistive technologies, and biomedical applications. Key areas include integrated circuits for magnetic sensors, non-destructive testing methodologies, neural networks for defect detection, and miniature diagnostic tools. He is affiliated with INESC MN, a prominent research unit in applied engineering. His work spans interdisciplinary projects such as magnetic flow cytometry for bacteria detection, eddy-current based industrial inspection systems, and low-power biomedical sensor interfaces. Recent contributions include innovations in sigma-delta modulators for organ-on-chip systems and high-resolution nondestructive test probes using magnetoresistive arrays. Caetano has co-authored over 30 technical publications and holds patents in sensor interface design and signal processing. His research emphasizes practical applications in healthcare, industrial automation, and structural monitoring, leveraging both hardware innovation and machine learning techniques.

Christian Benzمشاهده پروفایل

پژوهشگر

• Computer Vision
• Structural Health Monitoring
• Deep Learning
• +۴ مورد دیگر

Christian Benz is a Researcher at the Computer Science Department, Faculty of Media, Bauhaus-University Weimar since 2019. He holds an M.Sc. and B.Sc. in Computer Science from TU Darmstadt, with specialization in machine learning applied to image data. His research focuses on structural health monitoring, crack detection, and 3D reconstruction using computer vision techniques. He concurrently works part-time as a Computer Vision Scientist at ZEISS since 2023. Research interests include crack segmentation , multi-view learning , point cloud processing , and deep learning for infrastructure inspection . Notable projects include the AISTEC initiative for evaluating aging infrastructure using digital technologies. His work bridges computer vision with civil engineering applications, particularly in bridge and building safety assessment. Publications emphasize interdisciplinary approaches to structural defect detection, leveraging CNNs, attention mechanisms, and novel benchmarks like OmniCrack30k. His methods address challenges in concrete surface analysis, UAV-based imaging, and semantic segmentation during bridge inspections. Professional activities include lab coordination in the 3D-RealityCapture-ScanLab and participation in the Bauhaus Path Planning Challenge. His research contributes to advancing automated inspection tools for civil infrastructure safety.

Radu MARINESCUمشاهده پروفایل

استاد

• Software Engineering
• Software Quality Assurance
• Software Metrics
• +۳ مورد دیگر

Radu Marinescu is a Professor of Software Engineering at the Politehnica University of Timisoara, affiliated with the Department of Computer Science and Engineering. He leads the LOOSE Research Group and is a senior researcher at the e-Austria Institute. His primary roles include teaching graduate courses like Foundations of Software Engineering and Research Topics in Software Engineering. Marinescu's research focuses on software quality assurance, metrics, and maintenance, emphasizing object-oriented systems. He co-founded Intooitus, a spin-off company that develops quality assessment tools like inFusion and inCode. Marinescu holds a Dr. Habil. Eng. and a joint PhD ('magna cum laude') from Politehnica University of Timisoara and University of Karlsruhe. He has authored over 30 international publications and co-authored the best-selling book Object-Oriented Metrics in Practice (Springer). His awards include the IBM John W. Backus Award (2009) and an IBM Eclipse Innovation Award (2006). Marinescu has served as General Chair for ICSM 2010 and on numerous conference program committees. His research projects include developing tools like iPlasma for software analysis and inCode for real-time design flaw detection. Marinescu has advised four PhD students and participated in consultancy projects for companies like Nokia, Alcatel-Lucent, and Siemens VDO Automotive. He actively contributes to the software engineering community through editorial roles, conference organization, and evaluations for EU research programs.