Automated Playtesting Professors and Supervisors

Xiaoyin Wangمشاهده پروفایل

دانشیار

University of Texas at San AntonioUnited States

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

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Arnav Jhalaمشاهده پروفایل

دانشیار

North Carolina State UniversityUnited States

Arnav Jhala is an Associate Professor in the Department of Computer Science at North Carolina State University, where he joined in 2016 as part of the Chancellor’s Faculty Excellence Program. He co-directs the Digital Games Research Initiative and has held previous roles at UC Santa Cruz, USC Institute for Creative Technologies, Virtual Heroes Inc., and Indian Space Research Organization. Ph.D. and M.S. in Computer Science from NC State University B.Eng. in Computer Engineering from Gujarat University, India His research focuses on Artificial Intelligence , Computer Games , and Human-Computer Interaction , with emphasis on computational narrative modeling, VR camera control systems, and creativity formalization. Projects include transVRse for VR cinematography tools and Urban Panorama for urban change analysis via historical imagery. Recent publications span 2021–2025 , addressing topics like immersive biotechnology training, narrative reporting systems for communication datasets, and procedural content generation in games. Collaborations include institutions such as Saint-Cyr Military Academy (France) and Duke TIP.

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Alena Denisovaمشاهده پروفایل

مدرس ارشد

University of YorkUnited Kingdom

Dr Alena Denisova is a Senior Lecturer in the Department of Computer Science at the University of York, specializing in player experience research in video games and interactive media. She holds a PhD in Computer Science from the University of York (2024–Present) and has held academic roles including Lecturer at the University of York (2022–2024) and City, University of London (2019–2021). Her research focuses on understanding player experiences, developing evaluation tools for interactive systems, and designing educational/persuasive media. She is a Fellow of the Higher Education Academy (FHEA) and holds a PG Cert in Higher Education from Swansea University. Education: BSc/MSc/PhD in Computer Science (University of York) Professional Qualifications: PG Cert in Higher Education, FHEA Roles: Outreach Academic Coordinator, Senior Lecturer Her research interests span game audio design, AI-driven gameplay mechanics, and the psychological impact of games. Recent work explores placebo effects in AI-powered dialogue systems, non-Euclidean game spaces, and emotional challenges in games for older adults. She has published widely on player experience measurement frameworks, adaptive game systems, and the convergence of HCI with game studies. Her 2024–2025 publications analyze topics like acoustic indicators in game commentary, moral decision-making mechanics in games, and democratisation of indie game development. She also contributes to editorial roles in HCI and game research venues. Scientific Awards: Fellow of the Higher Education Academy Grants/Advising: No specific grants listed, but active in educational outreach Denisova collaborates on projects involving procedural narrative generation and generative AI in arts, reflecting her interdisciplinary approach to interactive media research.

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Federico Sicilianoمشاهده پروفایل

پژوهشگر

Sapienza University of RomeItaly

Federico Siciliano is a Postdoctoral Researcher and Ricercatore (Researcher) at Sapienza University of Rome, affiliated with the RSTLess Lab under the supervision of Prof. Fabrizio Silvestri. He has been teaching Algorithmic Methods of Data Mining in the Master’s program in Data Science since 2024. His research spans recommender systems, information retrieval, explainable AI, and deep learning theory. Education: PhD in Data Science, Sapienza University of Rome (2020–2024) Master’s in Data Science, Sapienza University of Rome (2017–2019) Bachelor’s in Management Statistics, Sapienza University of Rome (2014–2017) His research interests lie at the intersection of Artificial Intelligence and Data Science , particularly focusing on sequential and graph-based recommender systems , robustness and explainability in AI models , and theoretical foundations of deep learning . His recent work explores architectural improvements in RAG systems, anomaly detection in 5G networks, and trustworthy AI through counterfactual explanations. The most recent publications (2023–2025) reveal a strong trend toward robust and interpretable AI systems , with recurring themes in recommendation , retrieval , and security . His work combines theoretical rigor with practical applications in healthcare, telecommunications, and misinformation detection. He frequently publishes in high-impact venues such as IEEE Access, ACM RecSys, and CVPR. Scientific Collaborations: University of Cambridge Meta Amazon University of Pisa (UniPi) INAF (Italian National Institute of Astrophysics) Federico actively contributes to the research community by organizing a special session on Neural Methods for IR and RecSys at IJCNN 2025. He has been involved in projects related to space weather monitoring and clinical outcome prediction in thyroid cancer. No formal students or grants are explicitly mentioned, but his collaborative projects suggest involvement in externally funded research. Laboratories and Teams: RSTLess Lab, Sapienza University of Rome

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Wishnu Prasetyaمشاهده پروفایل

استادیار

Utrecht UniversityNetherlands

Dr. Wishnu Prasetya is an Assistant Professor at Utrecht University's Faculty of Science, Department of Software Technology. His research focuses on automated software testing, artificial intelligence applications in testing, program verification, and game technology. He leads projects including iv4XR (AI-enhanced automated testing) and IMPRESS (gamification in software engineering education), with demonstrated applications in computer game testing and extended reality systems. Research Interests: Prasetya's work spans automated testing methodologies enhanced by AI, formal verification techniques, and gamification. Key domains include: Agent-based testing frameworks for complex systems Model-based verification under uncertainty Player experience modeling in games Automated test generation for Java and XR systems Gamification of software engineering education Publication Trends: His recent articles (2020-2025) show strong focus on AI-driven testing approaches for games and extended reality, with innovations in agent-based test automation, formal verification of player experiences, and industrial applications of testing frameworks. Over 80% of recent publications involve multi-agent architectures or model-based validation techniques. Educational Contributions: Teaches courses on Program semantics and verification and Software testing and verification Developed gamification tools to improve student engagement in software engineering courses Tools & Frameworks: iv4XR/Aplib: Agent-programming testing framework T3: Automated testing tool for Java APSL: Protocol testing tool for complex systems

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Elif Surerمشاهده پروفایل

دانشیار

Middle East Technical UniversityTurkey

Elif Surer is an Associate Professor and Associate Director at Middle East Technical University's Graduate School of Informatics, Department of Multimedia Informatics. She leads the Entertainment Computing and Interactive Systems Laboratory (ECISLab) and actively contributes to METU's entrepreneurship initiatives through GIMER (Entrepreneurship Research Center). Her academic leadership extends to international projects including EU Horizon Europe initiatives and collaborations with institutions like Stanford University's University Innovation Fellows program. Dr. Surer's research focuses on the intersection of game technologies, extended reality, and practical applications across diverse domains. Her work spans serious games for CBRNe (Chemical, Biological, Radiological, Nuclear, and Explosive) training, virtual reality applications for mining safety, archaeological visualization, and educational technology. She has developed frameworks for heterotopias as discursive playgrounds, modular serious game development for virtual laboratories, and advanced techniques in persona building for game design. Her interdisciplinary approach bridges computer science with fields like archaeology, healthcare, and occupational safety, creating innovative solutions that address real-world challenges through immersive technologies. Her publication record demonstrates consistent contributions to top journals including IEEE Transactions on Games, Virtual Reality, and JMIR Serious Games. Recent work shows increasing focus on biological network visualization in XR environments, advanced testing frameworks for deep learning systems, and sophisticated persona modeling techniques that go beyond traditional approaches. Her research trajectory reflects growing integration of AI with immersive technologies, particularly in specialized training applications and scientific visualization. METU Performance Awards (2020, 2021) Best Poster award at METU Graduate School of Informatics Open Research Day TÜBİTAK Above-Threshold-Awards Featured in Researchers Active in Technical Games Research list Dr. Surer actively supervises numerous graduate students across multiple projects, with recent completions including theses on clickbait detection, VR for mining safety, and adaptive serious games for children with learning difficulties. She leads significant research funding including EU Horizon Europe projects like eNOTICE-2 (focused on CBRNe training), the MR4MS project for mine safety, and the Quantum Flagship project QuTE4E. Her laboratory environment fosters collaboration between computer science, architecture, and other disciplines, creating opportunities for students to engage in cutting-edge research with practical applications. As director of ECISLab, she maintains strong connections with industry partners including METU Teknokent, and actively participates in entrepreneurship initiatives through METU GIMER. Her work with the University Innovation Fellows program demonstrates commitment to developing entrepreneurial skills among students, while her research on virtual reality applications continues to expand into new domains including healthcare, archaeology, and emergency response training.

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Perttu Hämäläinenمشاهده پروفایل

دانشیار

Aalto UniversityFinland

Perttu Hämäläinen is Associate Professor of Computer Games at Aalto University's Department of Art and Media, with a joint appointment in Computer Science. His research creates innovative gameplay experiences through novel combinations of AI, HCI, and procedural animation. Research Focus: Movement-based games and exergames Virtual reality dance and physical interaction Procedural character animation Game feel design for emotional impact AI-assisted game development Recent Projects: Developed VR dance systems (Duet, WAVE), games addressing mental health (Between, Dark Souls analysis), and movement capture techniques. Leads research on how games can support coping with depression and fear of death. Awards & Recognition: Best Paper Award at CHI 2023, Best Applied Game Award (2017), and multiple best paper awards. Fellow of Finnish Center for Artificial Intelligence (FCAI).

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Diego Perez-Liebanaمشاهده پروفایل

مدرس ارشد

Queen Mary University of LondonUnited Kingdom

Dr. Diego Perez-Liebana is a Senior Lecturer in Computer Games and Artificial Intelligence at Queen Mary University of London (QMUL), within the School of Electronic Engineering and Computer Science. He holds a PhD from the University of Essex (2015) and a Master's from Universidad Carlos III de Madrid (2007). His research focuses on AI applications in games, including Monte Carlo Tree Search, Evolutionary Computation, and General Video Game Playing. He has authored over 90 papers, organized major conferences like IEEE CoG 2020, and competitions such as GVGAI and MARLO. His work bridges academia and industry, with experience as a game programmer and software engineer at Revistronic and Game Brains. Teaching: He instructs postgraduate modules in Advanced Game Development, AI in Games, and Multi-platform Game Development, emphasizing practical C++ programming and AI techniques. His courses cover game engines, procedural content generation, and modern game development practices. Research Highlights: Over 1,900 citations, 2 Best Paper Awards, and the BCS Intelligence Prize. Industry Collaboration: Developed AI tools for leading game engines and advised on game design via IGGI industry liaison roles. Labs & Affiliations: Active in the Digital Environment Research Institute (DERI) and the Centre for Multimodal AI at QMUL.

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Ivan Braviمشاهده پروفایل

استاد مهمان

Queen Mary University of LondonUnited Kingdom

Ivan Bravi is a Visiting Professor at Queen Mary University of London's School of Electronic Engineering and Computer Science. His research focuses on artificial intelligence, particularly in the context of game AI and automated playtesting. He explores topics such as statistical forward planning, reinforcement learning, and evolutionary optimization for game agents. Bravi's work emphasizes developing intelligent systems capable of navigating complex game environments, including card games like Splendor and unforgiving grid-based simulations like the Game of Life. His contributions include the Rinascimento framework, which employs event-value functions and hyperparameter tuning to enhance agent decision-making. His publications highlight advancements in agent optimization, behavioral expressivity, and self-adaptive algorithms. While no awards are listed, his active research in game AI underscores a commitment to pushing boundaries in computational decision-making and adaptive learning. Bravi collaborates with academic and industry partners to refine AI-driven solutions for gaming and beyond, leveraging interdisciplinary approaches within the School's vibrant research ecosystem.

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Mark Goadrichمشاهده پروفایل

استاد

Hendrix CollegeUnited States

Mark Goadrich is a Professor with 17+ years of teaching experience in computer science and mathematics at small liberal-arts undergraduate colleges. His research focuses on applying artificial intelligence algorithms to simulate human player experiences in card games, and he emphasizes integrating computer science education with community service to engage students. Goadrich holds a B.A. from Kenyon College (1998), an M.S. (2000), and a Ph.D. (2007) from the University of Wisconsin–Madison. His research interests span artificial intelligence, game development, data analytics, and innovative pedagogical strategies. He explores topics like tangible learning tools for data structures, procedural content generation in games, and civic engagement through computing curricula. Goadrich has contributed to educational frameworks for IPython in data science and molecular dynamics simulations in undergraduate labs. Though not explicitly listed, his work often intersects with interdisciplinary projects combining computational science and ethical considerations. His publications reflect a strong focus on bridging theoretical computer science concepts with hands-on, student-centered applications.

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