جست‌وجوی استاد و پژوهشگر

Eric B. Zhouمشاهده پروفایل

مدرس

• Generative Artificial Intelligence
• Human Creativity in the Age of AI
• Creative Markets
• +۳ مورد دیگر

Eric B. Zhou is a Lecturer in Information Systems and PhD Candidate in Information Systems at Boston University Questrom School of Business (expected 2026), affiliated with the Digital Business Institute and BIT Lab under advisor Professor Dokyun Lee. He is actively on the 2025-26 academic job market after transitioning from Washington University in St. Louis in 2023. His educational background includes: MS in Business Administration, Washington University in St. Louis Olin Business School (2023) MBA, Carnegie Mellon University Tepper School of Business (2021) BSBA, Washington University in St. Louis Olin Business School (2018) Eric's research centers on the co-evolution of human and artificial intelligence, specifically investigating how generative AI augments human creativity rather than displacing it. He examines societal consequences of generative AI and creative market responses through interdisciplinary lenses combining philosophy, psychology, and AI. His methodological toolkit integrates causal inference with deep learning, LLMs, and multimodal analysis to address how AI impacts fundamentally human domains. His publication trajectory reveals a focused exploration of generative AI's creative impact: early work (2024) established baseline productivity and novelty effects in art markets, while his 2025 Science Advances paper identifies evolutionary patterns from concentrated 'mastermind' breakthroughs to distributed 'hivemind' innovation following open-source model releases. Both studies leverage massive art platform datasets to demonstrate AI's dual role in enhancing aggregate creativity while altering individual novelty patterns. Research recognition includes: Marketing Science Institute grant ($5,000) as Co-PI Questrom Outstanding Research Award Falling Walls Science Breakthrough nomination (2024) WISE Best Student Paper Finalist (2022) As an educator, Eric teaches IS223: Introduction to Information Systems with emphasis on practical AI integration. Student testimonials consistently praise his ability to make technical concepts accessible through real-world applications and transparent discussions about AI's workplace implications. His teaching philosophy centers on developing critical AI competency as a professional advantage while addressing ethical considerations. Eric maintains active research collaborations within the BIT Lab and with scholars including Dokyun Lee, Bin Gu, Gordon Burtch, and Daniel Rock, focusing on policy implications for equitable AI-mediated creative markets.

Florian Müllerمشاهده پروفایل

استادیار

• Extended Reality
• Human-Computer Interaction
• Mobile Interaction
• +۴ مورد دیگر

Florian Müller serves as Assistant Professor for Mobile Human-Computer Interaction at Technical University of Darmstadt, leading the Urban Interaction Lab. His research pursues seamless integration of digital information, AI agents, and physical environments into unified Extended Reality (XR), with focus on novel interaction techniques for mobile XR and human-AI collaboration through body-centric, tangible, and haptic interfaces. Müller's primary research spans Extended Reality, Human-Computer Interaction, and Mobile Interaction with specialization in Haptic Interfaces, Tangible Interfaces, and Body-Centric Interaction. He investigates how multimodal sensory feedback enhances user experiences in immersive environments, particularly examining AI-driven adaptation for context-aware XR systems and the social implications of pervasive interactive technologies in urban settings. Recent publications (2024-2025) demonstrate strong interdisciplinary trends across multisensory XR (taste modulation, thermal feedback), social VR/AR applications (privacy, content sharing), and human-AI co-creation systems. Key domains include health (motor control assessment), education, and urban interaction contexts, with consistent emphasis on user experience, safety, and practical implementation challenges. Müller directs the Urban Interaction Lab at TU Darmstadt, which develops and evaluates interactive technologies for public spaces through prototyping novel mobile and XR interfaces. The lab's work emphasizes real-world deployment in urban environments, focusing on social engagement, situational awareness, and seamless interaction between physical and digital layers of city infrastructure.

Rabih Younesمشاهده پروفایل

دانشیار

• wearable computing
• artificial intelligence
• machine learning
• +۶ مورد دیگر

Rabih Younes is an Associate Professor of the Practice in the Department of Electrical and Computer Engineering at Duke University's Pratt School of Engineering. He also serves as the Associate Director of Undergraduate Studies and is a Faculty Network Member of the Duke Institute for Brain Sciences. Additionally, he is the Duke FRC Program Director for team 8429, Valence Robotics, and Head of the Duke KEEN Leadership Team. Dr. Younes received his PhD in Computer Engineering from Virginia Tech in 2018, following his MSE in Computer Engineering from the Lebanese American University in 2013 and his BE in Computer Engineering from the same university in 2011. He speaks nine languages (fluent in three) and holds various certificates including Engineering Education and Future Professoriate, Cisco Networking Academy certifications (CCNP, CCNA, ITE Instructor Trainer), National Instruments CLAD, and USPA A-Licensed Skydiver. His research spans wearable computing, ubiquitous/pervasive computing, activity recognition, context awareness, machine learning, engineering education, and Middle Eastern politics. Dr. Younes has published extensively on topics ranging from wearable health monitoring systems to innovative approaches in engineering education. His recent work demonstrates a growing integration of machine learning techniques with wearable sensor data for health applications, activity recognition, and educational assessment tools. Dr. Younes' scholarly output shows a consistent trajectory from fundamental wearable computing research toward practical applications in health monitoring and educational technology. His publications reveal an increasing focus on real-world implementation challenges, data augmentation techniques, and educational assessment tools that bridge engineering theory with practical classroom applications. Tau Beta Pi honor society member Eta Kappa Nu honor society member Phi Kappa Phi honor society member Golden Key honor society member KEEN Annual Support grant (2024-2026) Dr. Younes actively mentors students through various programs including EGR 393: Research Projects in Engineering and ECE 899: Special Readings in Electrical Engineering. He has received grant support through the KEEN Annual Support program for 2024-2026, focusing on innovative engineering education approaches. His teaching philosophy emphasizes student development beyond academics, incorporating life skills and critical thinking. As Director of Valence Robotics (team 8429), Dr. Younes leads high school robotics initiatives that have earned state championship qualifications. His lab work focuses on wearable computing systems with applications in health monitoring (including pet emotional health tracking), activity recognition, and educational technology tools. He utilizes agile project management frameworks like Scrum in his courses and implements tools to enhance student learning retention.

Manolya Kavakli-Thorneمشاهده پروفایل

دانشیار

• Virtual Reality
• Human-Computer Interaction
• Augmented Reality
• +۴ مورد دیگر

Dr. Manolya Kavakli-Thorne serves as Associate Professor and Honorary Professor at Macquarie University's School of Computing, specializing in advanced human-computer interaction systems. Her research bridges virtual reality, augmented reality, and gaming technologies with practical applications across diverse domains including healthcare, film production, and transportation safety. Her primary research interests focus on: Virtual reality systems design and implementation Human-computer interaction paradigms Augmented reality applications in real-world contexts Computer game mechanics and serious gaming Gesture recognition systems for 3D modeling Generative adversarial networks for image synthesis Analysis of her recent publications reveals a strong trajectory toward practical implementations of immersive technologies. Her work demonstrates increasing focus on real-world applications of virtual production systems in filmmaking, gamification for behavioral change, and medical applications of VR/AR technologies. The interdisciplinary nature of her research connects computer science with psychology, engineering, and creative industries. Dr. Kavakli-Thorne has secured significant research funding through 15 projects including the Centre for Elite Performance Expertise and Training (CEPET), Virtual-Reality intervention platforms for Cerebral Palsy patients, and Mobile Augmented Reality Systems (MARS) Design. Her collaborative approach is evident in projects spanning lifeguard performance enhancement and virtual reality dome systems development. Her laboratory work centers around immersive simulation environments, virtual production studios, and mobile augmented reality systems. Current research directions include refining generative AI applications in medical imaging, developing more intuitive multi-modal interfaces for 3D modeling, and expanding the use of serious games for safety-critical training scenarios.

• Human Activity Understanding
• Computer Vision
• Sensor Fusion
• +۶ مورد دیگر

Rahul Chaudhari is a Senior Researcher at the Chair of Media Technology, Technical University of Munich (TUM), where he has been working since August 2019. He is affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI) and contributes to research in human-computer interaction, particularly in human activity understanding. Dr. Chaudhari earned his doctoral degree (Summa cum Laude) in Communications and Signal Processing from TUM in 2015, following a Master's degree in Communications Engineering from TUM in 2009 and a Bachelor's degree in Electronics and Telecommunications from the University of Pune, India. His academic journey reflects a strong foundation in communications engineering and signal processing that has evolved into interdisciplinary research spanning haptics, computer vision, and artificial intelligence. His research focuses on Human Activity Understanding using Computer Vision, Sensor Fusion, and AI techniques. His current work centers on understanding Human-Object Interactions using camera data (RGB and Depth) recorded in indoor environments, with potential integration of wearable sensors or environmental sensors. His work has significant applications in improving human well-being, comfort, and convenience through intelligent environments and ambient assisted living systems. Dr. Chaudhari's publication record shows a clear evolution from foundational work in haptic communications to cutting-edge research in human-object interaction and 3D pose estimation. His recent publications demonstrate expertise across multiple domains including computer vision for activity recognition, synthetic data generation for training models, and neurosymbolic approaches to human-AI collaboration. This interdisciplinary approach reflects the increasingly connected nature of modern AI research. Best student paper award for Yujun Wang (2025) LMT Spin-off Wins Third Place at euRobotics Technology Transfer Award 2025 LMT featured in Süddeutsche Zeitung (2025) Diego Fernandez Prado selected as finalist for IEEE CASE Best Paper Award (2024) Dr. Chaudhari actively supervises student research, including Master's theses on advanced topics such as 'Simulation and Optimization for 6G Network Planning using Digital Twins.' His supervision work involves guiding students through complex technical challenges in simulation software evaluation, digital twin implementation, and network optimization. He also serves on thesis committees and provides mentorship to students working on related research topics. His research group operates within the broader context of TUM's initiatives in robotics and machine intelligence, contributing to projects like the Centre for Tactile Internet with Human-in-the-Loop (CeTI) and 5G Testbed Bayern. The group maintains a strong focus on both theoretical foundations and practical implementations, with research that bridges the gap between academic innovation and real-world applications in intelligent environments.

Simon Nestlerمشاهده پروفایل

استاد

• Human-Computer Interaction
• User Experience Design
• Interactive Systems
• +۹ مورد دیگر

Prof. Dr. Simon Nestler is a Professor for Human-Computer Interaction at Technische Hochschule Ingolstadt (THI) since 2019, previously at Hochschule Hamm-Lippstadt (HSHL) (2011-2019). He holds a Diploma in Computer Science and a Ph.D. in Human-Computer Interaction from Technische Universität München (TUM) and International Graduate School of Science and Engineering (IGSSE) , supervised by Prof. Gudrun Klinker . Educated: TUM (Diploma), IGSSE (Ph.D.) Affiliations: THI (2019-present), HSHL (2011-2019), Intraworlds (User Experience Engineer) Research Interests focus on applying HCI principles to safety-critical systems , particularly in emergency scenarios . He designs interfaces for car drivers , disaster response teams , and crisis management , addressing challenges like mental workload , collaborative problem-solving , and RFID patient tracking . His work includes developing virtual reality crisis simulations and mobile disaster apps . Teaching includes courses like Masterpraktikum GAMES and FAR Oberseminar . He also offers digital accessibility training , UX workshops , and keynotes on digitalization through his Prof. Nestler Akademie , which has trained 5000+ learners and delivered 100+ corporate trainings .

• Human-AI Interaction
• Artificial Intelligence
• Human Factors Engineering
• +۳ مورد دیگر

Junho Park is an Assistant Professor at the University of Calgary, holding cross-appointment across three academic units: Schulich School of Engineering (Biomedical Engineering), Cumming School of Medicine (Community Health Sciences), and Faculty of Arts (Psychology). He also serves as Faculty Researcher at W21C Research and Innovation Centre, Member at O'Brien Institute for Public Health, and Child Health and Wellness Researcher at Alberta Children's Hospital Research Institute. PhD in Industrial and Systems Engineering (Texas A&M University) MSc in Industrial Engineering (Seoul National University) BSc in Computer and Industrial Engineering with Psychology minor (Yonsei University) His research focuses on Human-AI Interaction, Human Factors Engineering, and Ergonomics, with specific applications in biosignal processing for prosthetics, workload assessment in assistive technologies, and cognitive support systems for aging populations. Current projects include augmented reality biofeedback systems and autonomous vehicle interfaces for individuals with cognitive impairments. Recent publications demonstrate expertise in applying machine learning to biomedical engineering challenges and human factors assessments. The HERO Lab actively seeks postdoctoral researchers and graduate students in areas spanning human-AI interaction, ergonomics, and computational modeling. Scientific Awards Student Member with Honours, Human Factors and Ergonomics Society (2023) IEEE International Conference on Human-Machine Systems Travel Grant (2022) Institute for Applied Creativity Student Fellowship, TAMU (2022) Korean-American Scholarship Foundation (2021) HFES Best Student Paper Award (2021)

Ella Peltonenمشاهده پروفایل

استادیار

• Ubiquitous Computing
• Large-scale Data Analysis
• Applied Machine Learning
• +۵ مورد دیگر

Ella Peltonen is an Assistant Professor at the M3S research unit, University of Oulu, Finland. She joined the Ubicomp Oulu research centre and 6Genesis research programme in November 2018. Prior to this position, she was a postdoctoral researcher at the Insight Centre for Data Analytics in Cork, Ireland. She completed her PhD in the Nodes group at the University of Helsinki, Finland, working on the Carat project of collaborative energy diagnostics for mobile devices. Her educational background includes: PhD in Computer Science, University of Helsinki, Finland (Carat project on collaborative energy diagnostics) Ella Peltonen's research focuses on ubiquitous computing, large-scale data analysis, and applied machine learning. Her work particularly emphasizes everyday sensing and mobile and wearable devices. She aims to apply machine learning algorithms to large, complex data in real-time systems, with a focus on distributed machine learning and data analysis of smart devices. Her research spans various applications including energy consumption monitoring of mobile devices, wearable technology for measuring physiological signals, and exploring future sensing technologies. Peltonen has expressed interest in how future devices might sense human states, become smarter, and provide greater benefits, potentially through innovations like augmented reality glasses or subcutaneous chips. Analysis of her recent publications shows a strong focus on edge computing, vehicular networks, and sustainable computing systems. Her work bridges the gap between theoretical machine learning approaches and practical applications in transportation, healthcare, and environmental monitoring. Many of her papers address challenges in distributed systems, real-time data processing, and privacy-preserving techniques for edge intelligence. Her notable scientific awards include: Nominated to the list of 10 Rising Stars in Networking and Communications by N2 Women 2017 Selected as one of 50 Finnish Researchers by the Finnish Union of University Researchers and Teachers Nokia Scholarship 2015 and 2016 Jorma Ollila Grant 2018 Young Teacher of the Year 2012 Young Researcher of the Year 2015 Peltonen is actively involved in teaching and mentoring, with a teaching philosophy focused on supporting students' independent learning rather than lecturing from above. She enjoys guiding small groups where she can discuss topics together with students and get to know them personally. As a researcher, she describes herself as precise, detail-oriented, and committed to verifying the correctness of her work carefully. She values the combination of mathematical work with experimental work and creativity in technology, noting that research tasks are diverse and can apply different types of methodology. She is part of international research collaborations with several major universities worldwide, as required by Finnish Academy funding. Peltonen is also an advocate for diversity in technology fields, noting that technology is used by all kinds of people from various backgrounds, yet the producers of technology lack diversity. She has highlighted the importance of encouraging more women to pursue technology careers from an early age.

• Visual Communication Design
• Artificial Intelligence and Design
• Computational Creativity
• +۳ مورد دیگر

Ezgi ŞEN serves as Assistant Professor in Visual Communication Design at Uskudar University since 2022, specializing in artificial intelligence applications within creative disciplines. Her research bridges computational systems and artistic practice, focusing on illustration, character design, and digital creativity. Her academic foundation includes: Licence in Visual Communication Design, Gazi University (2015) Master's in Visual Communication Design, Ondokuz Mayis University (2018) Doctorate in Graphic Design, Anadolu University (2022) ŞEN investigates how AI technologies transform creative workflows, examining human-AI collaboration models in illustration and animation. Her work analyzes generative systems like DALL-E and GPT-3 for data visualization, while addressing ethical implications of algorithmic creativity. Current projects explore AI's impact on design pedagogy and character development pipelines, emphasizing augmentation rather than replacement of human artistry. Her publication timeline reveals accelerating AI integration in design: beginning with foundational applications (2020), advancing to technical implementation studies (2021-2022), and culminating in educational paradigm analyses (2023). This progression demonstrates increasing sophistication in both technical execution and theoretical framing of AI's role in visual arts. Recognition includes: Multiple Achievement Awards (2018-2021) Repeated Display honors (2020-2021) International exhibition at Poland's Centrum Spotkania (2022) Certificate and Exhibition awards (2022-2023) Academic service encompasses student counseling for 41-50 undergraduates, Erasmus coordination since 2023, and membership on Education, Graduation, and Events Commissions. Her teaching integrates emerging AI tools into design curricula while maintaining core artistic principles. Though institutional labs aren't specified, her collaborative conference presentations indicate active engagement with international design-AI research communities through symposia and academic networks.

Mochen Yangمشاهده پروفایل

دانشیار

• Algorithmic Decision-Making
• Machine Learning
• Federated Learning
• +۴ مورد دیگر

Mochen Yang is an Associate Professor in the Department of Information and Decision Sciences at the Carlson School of Management, University of Minnesota. His research bridges algorithmic decision-making with practical organizational challenges. Education: Ph.D. (2018) and B.A. (2013) from Tsinghua University. His research focuses on algorithmic decision-making from both "make" and "use" perspectives. From the "make" angle, he designs robust algorithms for information-intensive environments, while the "use" perspective examines how algorithmic decisions affect fairness, privacy, and user trust. Key areas include federated learning, causal inference, and human-AI collaboration. Recent work explores federated learning partnership dynamics, classifier calibration, and algorithmic governance in short-video platforms. He also investigates user engagement on social media and error impacts in human-AI reliance. Current affiliations include the University of Minnesota, where he contributes to academic and research initiatives in information systems.

Jivko Sinapovمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Developmental Robotics
• Human-Robot Interaction
• +۴ مورد دیگر

Jivko Sinapov is an Associate Professor with dual appointments in the Department of Computer Science and Department of Mechanical Engineering at Tufts University's School of Engineering. He also serves as a CEEO Fellow at the Center for Engineering Education Outreach. His research focuses on enabling physical robots to operate and learn in human-inhabited environments through developmental approaches. Education: PhD in Computer Science and Human-Computer Interaction, Iowa State University (2013) BSc in Computer Science and Mathematics, University of Rochester (2005) Professor Sinapov's research centers on Artificial Intelligence, Developmental Robotics, Computational Perception, and Human-Robot Interaction . His work addresses fundamental questions about implementing intelligence in physical robots, with emphasis on enabling extended operation in human environments. His laboratory develops methods for behavioral object exploration, multi-modal perception, and knowledge transfer between robots, with applications ranging from educational robotics to space exploration. Current research directions include neurosymbolic approaches for handling novelty in open worlds, multimodal object property learning, and augmented reality interfaces for improved human-robot collaboration. Scientific Awards and Recognition: Winner of the Verizon 100K 5G EdTech Challenge (Spring 2019) for AR-based robotics education NSF CAREER Award: "Learning and Sharing Transferable Grounded Object Knowledge for Collaborative Robots" (2023) CEEO Fellow at the Center for Engineering Education Outreach Professor Sinapov actively mentors graduate students in the Multimodal Learning, Interaction, and Perception (MLIP) Lab, currently advising five PhD students across Computer Science and Mechanical Engineering departments. His research has been supported by significant grants including his NSF CAREER award. He has co-organized prominent symposia including the AAAI Spring Symposium on "Interactive Multi-Sensory Perception for Embodied Agents" (2017) and the AAAI Fall Symposium on "AI for Human-Robot Interaction" (2019). He directs the Multimodal Learning, Interaction, and Perception (MLIP) Lab , which develops cognitive robotics systems capable of learning through environmental interaction. The lab's research spans robot learning, computational perception, and human-robot interaction, with applications in education, space technology, and collaborative robotics systems operating in complex human environments.

• Machine Learning
• Computer Vision
• Autonomous Driving
• +۴ مورد دیگر

Ross Greer is an Assistant Professor in the Department of Computer Science & Engineering at the University of California Merced. He leads the Mi³ Lab, focusing on machine intelligence, human-agent interaction, and safe autonomous systems. Education : B.S. and B.A. in EECS, Engineering Physics, and Music from UC Berkeley (2015), M.S. in Electrical & Computer Engineering from UC San Diego (2018), Ph.D. in Electrical & Computer Engineering at UC San Diego (2021) under Mohan Trivedi and Shlomo Dubnov. His research explores computational intelligence for open-world adaptability, robustness to rare events, and safety in chaotic environments. Key applications include autonomous driving, driver state analysis, trajectory prediction, and AI-assisted musical creativity. Recent publications emphasize vision-language models, active learning for 3D object detection, and safety metrics. Awards include the 2024 Interdisciplinary Research Award, Henry Booker Award for Ethical Engineering, and multiple best poster/grand prizes. Scientific Awards : 2024 Interdisciplinary Research Award 2024 Henry Booker Award for Exemplary Ethical Engineering Postdoctoral Networking Fellowship (Germany's Academic Exchange Service) Grand Prize (AWS Automotive Day competition at IEEE Intelligent Vehicles Symposium, 2023) Best Poster Awards (2021/2023 Jacobs Research Expo) He also co-authored the textbook Deep and Shallow: Machine Learning in Music and Audio (Chapman & Hall, 2023) and serves as a music director for UCSD's Symphonic Student Association and UC Merced's marching band.

Klaus Muellerمشاهده پروفایل

استاد

• Visualization
• Visual Analytics
• Data Science
• +۱۲ مورد دیگر

Klaus Mueller is a Professor in the Department of Computer Science at Stony Brook University, where he also serves as Interim Chair of the Department of Technology and Society. He holds adjunct faculty positions in the Biomedical Engineering Department and Radiology Department, and is a Senior Scientist at the Computational Science Initiative at Brookhaven National Laboratory. His research spans visualization, visual analytics, explainable AI, computational fairness, and medical imaging, with significant contributions to volume rendering, GPU computing, and virtual reality. Dr. Mueller received his educational credentials from prestigious institutions: PhD in Computer and Information Science, The Ohio State University, 1998 MS in Computer and Information Science, The Ohio State University, 1996 MS in Biomedical Engineering, The Ohio State University, 1990 BS in Electrical Engineering, Polytechnic University of Ulm, Germany, 1987 Professor Mueller's research focuses on making complex data accessible and understandable through innovative visualization techniques. His work in visual analytics empowers users to explore high-dimensional data spaces, while his contributions to explainable AI help bridge the gap between complex machine learning models and human understanding. In medical imaging, he has pioneered GPU-accelerated reconstruction techniques that significantly improve CT imaging while reducing radiation exposure. His recent work explores the intersection of large language models with visualization, creating tools that enhance data understanding through natural language interaction. His extensive publication record shows a consistent focus on visualization techniques, with recent work increasingly incorporating AI and machine learning components. The trend shows a progression from foundational visualization techniques to more complex applications involving explainable AI, fairness in algorithms, and medical imaging applications. His work often bridges theoretical advances with practical implementations, particularly through GPU acceleration. Dr. Mueller's scientific achievements have been recognized with numerous prestigious awards: US National Science Foundation CAREER award (2001) SUNY Chancellor Award for Excellence in Scholarship and Creative Activity (2011) Inducted into the National Academy of Inventors (2018) Golden Core Award, IEEE Computer Society (2016, 2022) Meritorious Service Certificate, IEEE Computer Society (2016) IEEE Fellow (2024) Best Paper Award, IEEE Visual Data Science Symposium (2019) His research has been generously supported by major funding agencies including the National Science Foundation (NSF), National Institutes of Health (NIH), Department of Energy (DOE), and Department of Homeland Security (DHS), as well as private industry partners. As Editor-in-Chief of IEEE Transactions on Visualization and Computer Graphics (2019-2022), he has shaped the direction of visualization research globally. He has advised numerous PhD students whose work has advanced the field of visual analytics and medical imaging. Dr. Mueller directs the Visual Analytics and Imaging (VAI) Lab at Stony Brook, which focuses on developing innovative visualization techniques for complex data analysis. The lab has been instrumental in creating tools for medical imaging, security applications, and data science. His team has developed frameworks for smoke and fire simulation, visual analytics for healthcare, and GPU-accelerated medical imaging algorithms. The lab fosters interdisciplinary collaboration between computer scientists, medical researchers, and domain experts to solve real-world problems through visualization.

Oya Aşan Yükselمشاهده پروفایل

دانشیار

• Ceramic Art
• Ceramic Design
• Alternative Printing Techniques
• +۵ مورد دیگر

Prof. Oya Aşan Yüksel serves as Associate Professor in the Department of Ceramics at Kutahya Dumlupinar University's Faculty of Fine Arts, where she also holds key administrative roles including Faculty Erasmus Coordinator and Quality Board Member. With over 20 years of academic experience spanning Dokuz Eylul University and her current institution, she maintains active industry collaboration as Business Consultant for Heriş Ceramics and Tourism Industry Inc. Her educational background includes: Bachelor's Degree in Ceramic Department, Anadolu University (2000-2005) Master's Degree in Ceramic (Thesis), Dokuz Eylul University (2006-2011) Proficiency in Arts, Ceramic and Glass Design, Dokuz Eylul University (2011-2014) Research centers on ceramic innovation through three interconnected pillars: alternative printing techniques (including digital transfer methods), climate crisis responses in artistic practice, and historical analysis of Kütahya ceramics traditions. Her work bridges material science with cultural studies, examining boron waste utilization in glazes and AI integration in ceramic design while maintaining deep engagement with Ottoman ceramic heritage. Recent publications reveal increasing international collaboration and interdisciplinary scope, with 2025 work exploring Anatolian-Troyan ceramic connections and 2024 studies on AI's creative dimensions. The output shows strong thematic continuity in material innovation while expanding into climate-responsive design and cross-cultural analysis. Scientific recognition includes: Dual 2021 Zirve Başarı Ödülleri 2017 Bilim Teşvik Ödülü and Latvia Art Center Zvartava award Multiple competition wins including Selçuk Sözen Ödülü (2014) Dumlupınar University Industrial Design First Prize (2014) Uşak University Karo Competition awards (2011, 2014) She actively supervises graduate research through thesis management courses while leading TÜBİTAK 4004 Future Climate Project and university-industry collaborations. Current grants focus on sustainable ceramic production and climate-art intersections, with international partnerships facilitated through her Erasmus coordination role. Her teaching portfolio spans 30+ courses from foundational 'Ceramic Art History' to advanced 'Alternative Printing Techniques', demonstrating vertically integrated pedagogical approach. Though no formal research lab is specified, her project leadership in boron waste glaze production and climate-responsive design creates practical research environments within university ceramics studios, enhanced by industry partnerships providing real-world application contexts.

Chris Donahueمشاهده پروفایل

استادیار

• Generative AI
• Music and Creativity
• Machine Learning for Sequential Data
• +۴ مورد دیگر

Chris Donahue is an Assistant Professor in the Computer Science Department at Carnegie Mellon University and a part-time Research Scientist at Google DeepMind's Magenta team . He leads the Generative Creativity Lab (G-CLef) , focusing on unlocking human creative potential through generative AI for music, programming, gaming, and natural language. Education : PhD at UCSD (advised by Miller Puckette and Julian McAuley), postdoc at Stanford CS (advised by Percy Liang). Research Interests : Controllable generative modeling for sequential data, interactive AI systems for non-musicians, and real-world applications of machine learning in creative domains. Scientific Awards : Best Paper Award (top 1% of submissions) at CHI 2025 Best Paper Award (top 1) at NAACL Student Research Workshop 2025 Advisees : PhD students Wayne Chi, Irmak Bukey, Yewon Kim, Nathan Pruyne, and Satvik Dixit, along with incoming and alumni mentees. Labs & Teams : Leads the Generative Creativity Lab (G-CLef) at CMU and collaborates with Google DeepMind's Magenta team on real-time music generation projects like MusicFX DJ Mode and Piano Genie.