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پژوهشگر
Han Wang is a visiting researcher affiliated with Monash University in Melbourne, Australia, pursuing his PhD under Prof. Chunyang Chen, Prof. Burak Turhan, and Prof. Yuan-fang Li. He completed his Bachelor’s degree in Software Engineering with Honours from the Australian National University and began doctoral studies in 2021.
Thomas Langerak is a PhD student and Lecturer at ETH Zurich's Advanced Interactive Technologies lab under Prof. Otmar Hilliges. His academic journey includes a double-degree in Human-Computer Interaction and Design from Aalto University (Finland) and University of Twente (Netherlands), and a B.Sc. in Industrial Design from Eindhoven University of Technology. His research spans Human-Computer Interaction , Reinforcement Learning , and Haptic Systems , with recent work focusing on multi-agent RL for adaptive interfaces and novel electromagnetic actuation for VR/AR. Earlier contributions centered on custom haptic hardware like the Hedgehog pin array and Omni volumetric system. Publication trends reveal an evolution from hardware prototyping (2018-2020) toward intelligent interface optimization (2021-2024), with increasing emphasis on user modeling and adaptive automation. Key venues include ACM UIST, CHI, and IEEE Transactions. Honorable Mention - Best Paper Award at World Haptics Conference 2021 As an academic mentor, he supervised Mengfan Wu's thesis on electromagnetic tracking and Aline Abler's Hedgehog interface development. His service includes UIST organizing roles (Data Co-Chair 2021-2022) and session chairing. Teaching spans HCI, Computational Haptics, and ML fairness courses since 2019. Laboratory work occurs within ETH's Advanced Interactive Technologies group, specializing in computational interaction and electromagnetic systems for immersive environments.
Juan Pablo Galeotti is a Professor at the University of Buenos Aires (UBA) in the Department of Computer Science within the Faculty of Exact and Natural Sciences . He is also a researcher at CONICET and a member of the LaFHIS and LIA-INFINIS laboratories. His research focuses on automatic test generation , program verification , specification inference , and decision procedures like SMT and SAT. Education & Background: While specific degrees are not mentioned, his PhD thesis was titled "Software Verification using Alloy" , advised by Marcelo Fabian Frias . Research Interests: His work spans: Search-based software testing REST API fuzzing and testing Smart contract verification Dynamic and static analysis Testability transformations Loop invariant inference Publications & Trends: Galeotti has published extensively in top-tier venues like ICSE, FSE, ASE, ISSTA, IEEE TSE , and ACM TOSEM . His recent work ( 2020–2025 ) focuses on tools like EvoMaster for REST API testing, EvoSuite for Java unit testing, and TACO for SAT-based verification. Awards & Service: He has served as PC Co-Chair for SBST@ICSE 2017–2018 , PC Member for ICSE, ISSTA, ICST , and reviewer for journals like TOSEM, TSE . He co-organized ISSTA 2016 and ICSE 2017 . Students & Projects: He currently supervises 3 PhD and 4 Master’s students. He has co-directed CONICET and UBA-funded projects on bounded verification and memory analysis. Labs & Collaborations: He leads research at LaFHIS and collaborates with LIA-INFINIS , working on tools like EvoMaster , DynaMate , and TACO .
Sorin Lerner is a Professor and Chair of the Department of Computer Science and Engineering at the University of California, San Diego (UCSD). His research spans programming languages, program verification, security/privacy, and human-computer interaction (HCI). He actively seeks graduate students and postdocs to join his research group. Education: PhD in Computer Science, University of Washington (2006) Research Interests: Sorin’s work focuses on applying programming language techniques to program verification, security, and live programming environments. His projects include the Rango system for retrieval-augmented proving, Projection Boxes for live programming visualization, and Radar for concurrent program analysis. He also explores gamification in education through Proof Games and Code Spells. Awards: Recipient of the PLDI 2003 Best Paper Award ICSE 2025 Distinguished Paper Award for Rango Teaching: Sorin teaches courses on programming languages (CSE 130, CSE 230), compilers (CSE 231), and specialized topics in automated theorem proving (CSE 291). He emphasizes live programming and interactive tools to enhance learning. Lab & Collaborations: Leads the PL@UCSD research group, collaborating with institutions like Microsoft, Google, and The University of Texas at San Antonio. Projects often involve cross-disciplinary efforts in software reliability, formal methods, and educational technology.
Professor Fevzi Belli specializes in Software Reliability Engineering at Izmir Institute of Technology's Computer Engineering Department. Educated at Technical University of Berlin (PhD 1978), his career includes industrial positions at Siemens AG and academic appointments in Germany before joining IYTE. Research focuses on: Model-based testing of software/hardware systems Formal verification using cause-effect graphs and decision tables GUI and firewall testing methodologies Mutation testing frameworks Honored as Knight Commander of Spain's Order of Isabel la Catolica, he has chaired IEEE conferences and authored over 100 publications. Current projects explore VHDL program verification and reusable component reliability.
Jerry Zeyu Gao is a Professor at San Jose State University's College of Engineering, Department of Computer Engineering. He has affiliations with institutions like University of Auckland, University of Melbourne, and Xi'an Jiaotong University, reflecting a global research network. PhD in Computer Science and Engineering from University of Texas at Arlington (1995) Research focus: Software testing, AI, machine learning, and smart systems His research spans AI testing , mobile application quality assurance , and big data analytics for smart cities. Recent work includes autonomous vehicle testing , drone-based security systems , and encryption technologies . Publications highlight GUI testing , environmental data modeling , and reinforcement learning applications. Key trends include machine learning in test automation , smart city infrastructure , and data-driven environmental solutions . He has served as General Chair for IEEE CISOSE conferences and contributed to AI quality standards. His work involves collaborations with researchers across institutions, focusing on security , data quality , and urban sustainability . Notable projects: smart OCR testing , EV charging infrastructure analysis , and automated graffiti detection .
Walter S. Lasecki is an Associate Professor at the University of Michigan's School of Information, where he leads research at the intersection of Human-Computer Interaction, Crowdsourcing, and Artificial Intelligence. His work focuses on creating systems that integrate human and machine intelligence to solve complex problems in real-time. Dr. Lasecki's research interests center on human-AI collaboration, particularly in developing crowd-powered systems that enhance accessibility, improve programming education, and create more effective human-computer interfaces. His work explores how to effectively integrate human intelligence with AI systems, focusing on real-time applications where speed and accuracy are critical. His research has significant implications for accessibility technologies, educational tools, and conversational AI systems. He has pioneered approaches to real-time captioning, crowd-powered interfaces, and human-in-the-loop machine learning systems that adapt to user needs. Analysis of his recent publications reveals a strong focus on multi-agent conversational AI, human-in-the-loop systems for pose estimation and object recognition, and innovative approaches to programming education through live streaming. His research consistently explores the intersection of human computation and artificial intelligence, with particular attention to how crowd workers can complement and enhance AI capabilities. His work demonstrates a trajectory from foundational crowd-powered systems to more sophisticated integrations of human and machine intelligence in complex tasks. Dr. Lasecki has collaborated extensively with researchers across multiple institutions, particularly with Jeffrey P. Bigham (earlier in his career) and more recently with colleagues at the University of Michigan including Juho Kim. His research has been supported by substantial grants that have enabled the development of systems like Scribe for real-time captioning and Codeon for on-demand programming assistance. He has mentored numerous graduate students who have gone on to contribute to the fields of HCI and AI. His laboratory focuses on developing practical applications of crowd-AI hybrid systems, with particular emphasis on creating tools that can be deployed in real-world settings. Current projects explore how to make conversational AI more robust through multi-agent approaches, improve programming education at scale, and create more accessible interfaces for diverse user populations.
Joseph P Vybihal is a Professor at McGill University's School of Computer Science, serving as a Masters Non-Thesis Advisor and Discipline Officer for the Department of Science. His research focuses on intelligent software systems, multi-agent robotics, and the societal impact of social media. He leads the Prometheus Lab, exploring autonomous robotic systems and social media algorithm analysis. Active in professional organizations, he serves as Secretary on the CSCA Executive Board and founded vSolutions, a software development firm. Education: Ph.D. in Computer Science (inferred from roles) Research interests include AI-driven robotics navigation, swarm coordination, and mitigating social media siloing effects. Current projects involve hospital delivery robots using computer vision, swarm robotics communication APIs, and developing healthy social media user interfaces. Students collaborate on robot assembly, black-box algorithm analysis, and GUI design. Teaching includes courses like COMP 208, COMP 310/ECSE 427 Operating Systems, and COMP 599 Multi Agent Robotics. Advised student projects include an 8-bit Turing Complete CPU and social media impact analysis tools. Labs: Prometheus Lab (multi-agent robotics & social media impact studies). Industry ties via vSolutions provide practical software engineering experience in Windows/Linux/Android ecosystems.
Csaba Zoltán KERTÉSZ is a Lecturer at the Department of Electronic and Computers, Faculty of Electrical Engineering and Computer Science, Technical University of Brașov. His research focuses on embedded systems, microcontroller applications, graphical user interfaces, digital signal processing, and real-time operating systems. He has contributed to IoT/M2M communication, wireless sensor networks, and SDR platforms. He has also explored the use of GitHub in collaborative learning and automotive industry-supported curriculum design. Key research interests include: Embedded GUI development frameworks IoT gateway systems using SDR Real-time monitoring and control systems HbbTV architecture performance analysis His recent work (2021-2024) emphasizes: AI-driven programming assessment tools SIMD extension optimization Wireless sensor networks for water distribution Reconfigurable IoT infrastructure Publications span over 15 years, showing sustained contributions in embedded systems, telecommunications, and educational technology. No specific awards mentioned. Labs/Teams: Actively involved in the University's embedded systems and IoT research groups.
دانشیار
Niraj Dayama is an Associate Professor in the Department of Information Technology at Arcada University of Applied Sciences, affiliated with the School of Engineering, Culture and Wellbeing. He holds a Doctor of Philosophy. His research focuses on optimization techniques, quantum computing applications, user interface design, and algorithm development for interactive systems. Dr. Dayama's work bridges computational methods with human-centric design challenges. Educational Background: Doctor of Philosophy (PhD), details of academic programs not explicitly stated in provided texts. Affiliations include Arcada UAS with a primary role in Information Technology education and research. Research Interests: Dr. Dayama explores optimization in diverse domains such as quantum computing ecosystems, user interface layout generation, and scheduling problems. His contributions span algorithm design for grid-based layouts, real-time adaptive interfaces, and combinatorial solutions for UI/UX challenges. Recent work emphasizes leveraging quantum computing for problem decomposition and full-stack quantum software development. Publications reflect a shift toward quantum computing and optimization since 2020, complemented by longstanding engagement with layout design and scheduling algorithms. Notable trends include cross-disciplinary approaches merging computational methods with human interaction principles. No scientific awards or grants are explicitly mentioned in the provided texts. Advising roles or student supervision details are not listed.
Adam Porter Atif Memon is a Professor at the Department of Computer Science, University of Maryland, and Executive Director of the Fraunhofer Center for Experimental Software Engineering (CESE). His primary affiliation is with the College of Computer, Mathematical, and Natural Sciences. He holds a Ph.D. from the University of California, Irvine (1991). His research focuses on software engineering, software testing, and mobile application development, particularly in model-based testing and empirical software analysis. Education: Ph.D., University of California at Irvine, 1991 Research interests include software assurance, automated performance tuning, and the development of frameworks like GUITAR for GUI testing. He is a co-creator of a Coursera MOOC on Android development, reaching over 500,000 students globally. He has received awards such as the NSF CAREER Award (1995) and the Board of Visitors Creative Educator Award (2015). Key contributions include leadership roles at Fraunhofer CESE and collaborations with institutions like Carnegie Mellon’s Software Engineering Institute. His work emphasizes bridging academic research with industrial applications, particularly in smart ecosystems and software systems. Labs and teams include the Event Driven Software Lab (EDSL) and leadership at Fraunhofer CESE, fostering collaborations between UMD and industry partners. He advises multiple Ph.D. students and has been instrumental in advancing teaching methodologies through flipped classrooms and multimedia integration.
Sergio Feo-Arenis is a Researcher at the Department of Informatics, University of Freiburg, affiliated with the Software & Systems Theory (SWT) group. His research focuses on Embedded Systems Verification, Real-Time Systems, and Formal Methods, with expertise in Program Verification and Static Analysis. He contributes to the Salomo project and has published extensively in areas like timed automata and network protocols. Teaching responsibilities include courses such as Program Verification, Cyber-Physical Systems, and Software Engineering, spanning undergraduate and graduate levels. He has advised numerous student projects and theses, emphasizing practical applications of theoretical concepts. Research highlights include formal verification of data aggregation protocols, GPU-accelerated model checking, and semantic layer development for aerospace systems. His work bridges theoretical computer science with industrial applications, ensuring compliance with safety-critical standards. Key projects include Salomo, exploring parametric analysis models, and contributions to interdisciplinary system design. Consultation hours require appointment scheduling via email.
پژوهشگر ارشد
Dr. Abigail Koay is an Honorary Research Fellow at the University of Queensland's School of Electrical Engineering and Computer Science. Her research focuses on cybersecurity, machine learning applications in industrial systems, and healthcare technology. She has contributed to projects such as real-time cyber-attack detection using weakly supervised learning, supported by UQ Cyber Seed Funding (2021–2022). Her work spans multiple disciplines including: Cybersecurity for Industrial Control Systems (ICS) IoT network anomaly detection using fog-assisted frameworks Machine learning for medical imaging (e.g., glaucoma detection) AI-driven cybersecurity strategies for smart grids Recent publications highlight advancements in: Irregular time series analysis using GNNs Positive-unlabeled learning with random forests Domain generalization in retinal image analysis Dr. Koay has authored/co-authored 15+ peer-reviewed articles across journals like Frontiers of Computer Science , IEEE Access , and conferences including NeurIPS and ISGT Asia. She collaborates with industry partners on projects like Plan2Defend for smart grid security and SDGen for synthetic cybersecurity dataset generation. Her research integrates theoretical machine learning with practical cybersecurity challenges, emphasizing real-world applicability in critical infrastructure and healthcare systems.
استادیار
Yue Jiang is an incoming Assistant Professor at the University of Utah (Fall 2025) and is completing their PhD at Aalto University and the Finnish Center for Artificial Intelligence (FCAI). Their research focuses on computational user interface understanding, eye tracking, and adaptive GUI layouts. They have held roles such as Accessibility Chair for CHI2023/2024 and have organized workshops on computational UI methodologies. Education : PhD in Intelligent Systems (Aalto University & FCAI, Finland) Visiting PhD Student (CMU's BIG Lab, 2024) Master's in Computer Graphics (UMD, USA) Bachelor's in Computer Science & Mathematics (U of Toronto, Canada) Research Interests : Developing human-centered technologies for adaptive UIs, eye tracking analysis, and AI-driven HCI. Key projects include Graph4GUI, EyeFormer, and computational methods for GUI layout optimization. Awards : Meta PhD Fellowship (2023-2025) Google Europe Students with Disabilities Scholarship (2022) CHI2022 Best Paper Honorable Mention Heidelberg Laureate Forum Young Researcher (2024) Service : PC Member for VL/HCC2025, CHI2026 Associate Chair for CHI2025/2026 Organized three Computational UI Workshops at CHI Labs & Collaborations : Collaborates with Prof. Jeffrey Bigham (CMU), Prof. Wolfgang Stuerzlinger (SFU), and Prof. Christof Lutteroth (U of Bath). Former internships at Apple AIML Lab and Adobe Research.
Tanja Vos is a Full Professor at the Faculty of Science , Department of Computer Science , specializing in Software Testing , Automated Testing , and Behavior-Driven Development (BDD) . Her work extends to Gamification in Education and Artificial Intelligence (AI) in Learning Systems . Research Program: Towards High-quality and Intelligent Systems (THIS) Active in Graphical User Interface (GUI) Analysis and Test Automation Research Interests : Vos focuses on advancing software testing methodologies through AI-driven solutions , particularly in 3D game testing , chatbot applications , and gamified educational platforms . Her work bridges theoretical research with industrial implementation . Recent Article Trends : Her publications emphasize automated testing frameworks (e.g., iv4XR ), GUI regression analysis , and AI chatbots for personalized learning . Subfields include evolutionary algorithms , dynamic interface testing , and gamification mechanics . Supervision & Collaboration : Vos leads projects like TESTOMAT and AI Study Coach , collaborating with institutions such as Universidad Politecnica de Valencia .
