Professor Carlo Harvey is a creative technologist at the School of Digital Arts (SODA), Manchester Metropolitan University. His interdisciplinary research merges games , machine learning , virtual production , and cultural heritage reinterpretation . He leads industry collaborations with entities like Jaguar Land Rover and Epic Games, focusing on AI-driven interactive audio, real-time visualization, and accessibility solutions. Award-winning projects : TIGA, Innovate UK, and Epic Games MegaGrant for Accession Industry partnerships : Automotive sector, cultural institutions His research spans human-computer interaction , multisensory virtual environments , and acoustic-visual cross-modal perception . Recent publications address robotic simulations, motion alignment, and haptic feedback systems. Scientific recognition : TIGA Award, Innovate UK Funding, Epic Games MegaGrant Advocacy : Digital inclusion, creative collaboration, social impact of technology
Professor Gabriel Brostow is a faculty member in the Department of Computer Science at University College London (UCL), where he leads research in Computer Vision and Human-Computer Interaction. He also serves as Chief Research Scientist and Senior Director of the R&D Team at Niantic, the company behind Pokémon GO. His work bridges academic research and industry applications, focusing on developing AI systems that enhance human capabilities through what he terms 'Human in the Loop AI'—now commonly referred to as Human-Centered AI. Brostow completed his BS in Electrical Engineering at UT Austin, followed by a PhD with Irfan Essa at Georgia Tech. He then pursued postdoctoral research with Roberto Cipolla's Computer Vision & Robotics Group at Cambridge University as a Marshall Sherfield Fellow, and with Marc Pollefeys in ETH Zurich's CVG Group. His research explores how AI, particularly Computer Vision, can serve as 'super-tools' for professionals across various domains including filmmaking, architecture, robotics, and scientific research. Specific interests include assistive technology for everyday life, authoring systems that maximize user effort, 3D reconstruction, depth estimation, and vision-language models. His work often involves creating systems that are validated through real-world human interaction to ensure practical utility. Analysis of his recent publications reveals a strong focus on practical applications of Computer Vision that directly interact with humans. His research spans 3D scene understanding, depth estimation, sketch-based interfaces, and multimodal AI systems. There's a clear emphasis on creating benchmarks and tools that facilitate human-AI collaboration, with applications in assistive technology, urban planning, filmmaking, and biodiversity monitoring. His work frequently appears at top conferences including CVPR, NeurIPS, ECCV, and CHI. Marshall Sherfield Fellowship Brostow actively mentors PhD students, with current advisees including Ross Murphy, Skanda Koppula, Gizem Unlu, Omiros Pantazis, and Jamie Watson. His alumni include numerous PhD graduates and MSc students who have gone on to successful careers in academia and industry. He emphasizes selecting students based on passion and potential rather than just academic credentials, valuing traits like helpfulness, drive, and hunger to learn. His research is supported through collaborations with major institutions and companies including DeepMind, MIT, and the University of Edinburgh. He leads a research group at UCL that collaborates closely with Niantic's R&D team, creating a unique bridge between academic research and industry application. His team's work frequently involves developing novel Computer Vision techniques that are validated through real-world human interaction, ensuring practical utility alongside technical innovation. The group explores blue-sky research problems with applications ranging from assistive technology to professional tools for filmmakers, architects, and scientists studying diverse environments.
Jiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University. He holds multiple affiliations including membership in Bio-X, Faculty Affiliate status at the Institute for Human-Centered Artificial Intelligence (HAI), and membership in both the Wu Tsai Human Performance Alliance and Wu Tsai Neurosciences Institute. Dr. Wu earned his Ph.D. and S.M. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology before joining Stanford. Dr. Wu's research program focuses on creating AI systems that understand and interact with the physical world through the integration of computer vision, machine learning, robotics, and cognitive science. His work emphasizes physics-based modeling combined with deep learning to develop systems capable of perceiving, reasoning about, and predicting physical interactions. Key research areas include 3D scene understanding, neurosymbolic AI approaches, multimodal perception (combining vision, sound, and language), and embodied intelligence for robotics applications. His lab develops novel frameworks that bridge the gap between neural networks and symbolic reasoning to create more interpretable and robust AI systems. Analysis of Dr. Wu's recent publications reveals a strong trajectory toward integrated multimodal understanding for embodied AI. His work increasingly combines vision, sound, and language processing with physical reasoning to create systems that can interact meaningfully with the physical world. There's a clear progression from foundational computer vision research toward practical robotics applications, with significant emphasis on foundation models for robotics, sim2real transfer techniques, and creating comprehensive datasets for embodied AI research. Dr. Wu's exceptional contributions have been recognized with numerous prestigious awards including the NSF CAREER award (2024), Young Investigator Programs from ONR (2024) and AFOSR (2023), the Okawa research grant (2024), and being named to IEEE Intelligent Systems' 'AI's 10 to Watch' (2024). He has received multiple best paper awards at leading conferences including ICRA (2024), SIGGRAPH Asia (2023), and CoRL (2023). Dr. Wu actively mentors a large cohort of students across multiple levels, serving as primary advisor for doctoral candidates, master's students, and numerous independent researchers. His research is supported by substantial funding from major technology companies including Google, Meta, Amazon, Samsung, and J.P. Morgan, as well as government agencies like NSF, ONR, and AFOSR, reflecting the significance and impact of his work in physical AI and multimodal perception systems. Dr. Wu leads a dynamic research group at Stanford that collaborates extensively with the Wu Tsai Neurosciences Institute and Institute for Human-Centered AI. Current projects include developing neurosymbolic models for computer graphics, creating multisensory datasets like OBJECTFOLDER 2.0 for sim2real transfer in robotics, and building foundation models for embodied intelligence that can understand and manipulate objects with human-like physical intuition.
Dr. Lucian Sulica is the Sean Parker Professor of Laryngology and Director of the Sean Parker Institute for the Voice at Weill Cornell Medical College. He is an attending Otolaryngologist at NewYork-Presbyterian Hospital with a clinical practice exclusively focused on voice disorders. Dr. Sulica served as the 2023 President of the American Laryngological Association and is a Fellow of the American Laryngologic, Rhinologic and Otologic Society (the Triologic Society). His educational background includes: A.B. from Dartmouth College (1989) M.D. from Georgetown University School of Medicine (1993) Residency at Georgetown University Medical Center Fellowship at New York Center for Voice & Swallowing Disorders, St. Luke's-Roosevelt Hospital Center Dr. Sulica's research focuses on evidence-driven principles for treating voice conditions, with particular emphasis on vocal fold injuries from voice use (especially in performers), neurologic voice disorders (including vocal fold paralysis, spasmodic dysphonia, and tremor), and in-office procedures for voice disorders that don't require general anesthesia. His work has addressed critical aspects such as gender differences in vocal fold injury, pathophysiology of laryngeal nerve injury, and diagnostic accuracy in voice disorders. Analysis of Dr. Sulica's recent publications reveals a strong focus on advancing diagnostic techniques through artificial intelligence, improving surgical outcomes for vocal fold lesions, understanding performers' unique voice care needs, and developing evidence-based protocols for vocal fold hemorrhage and other voice disorders. His research increasingly incorporates technology-driven approaches while maintaining a strong clinical focus on patient-centered outcomes. Dr. Sulica has received numerous prestigious awards including: Casselberry Award of the American Laryngological Association (2021) Felix Semon Lectureship in Laryngology, Royal Society of Medicine (2022) American Academy of Otolaryngology – Head & Neck Surgery Honor Award (2008) Consistent recognition as one of "Best Doctors in America" (2005-2024) Designation as one of "America's Top Physicians in Voice Disorders/Laryngology" (since 2006) Inclusion in "New York Magazine Best Doctors" list annually since 2013 As an educator, Dr. Sulica has authored more than 110 journal articles and 40 book chapters, and has edited three books including "Vocal Fold Paralysis," "Classics in Voice and Laryngology," and "Patologia Laringea y Fonocirugia" (in Spanish). He is passionate about teaching and has lectured extensively across the United States, Europe, Latin America, and Australia. His clinical work at the Sean Parker Institute for the Voice represents a comprehensive approach to voice care, incorporating innovative in-office procedures that have helped establish new standards in laryngology.
Andrew Campana is an Assistant Professor of Asian Studies at Cornell University's College of Arts and Sciences, specializing in modern and contemporary Japanese literature and media. His research explores the possibilities and limitations of expression during media transitions, with particular focus on poetry, digital media, and disability studies. His academic journey includes a Ph.D. in East Asian Languages and Civilizations from Harvard University and an Honors B.A. in East Asian Studies from the University of Toronto. Campana's first book, Expanding Verse: Japanese Poetry at the Edge of Media , published by the University of California Press in 2024 as an open access work, examines Japanese poetic practice from the 1920s to the present as poets engaged with evolving media technologies including film, tape recording, television, and the internet. As a researcher, Campana's work bridges literary studies, media studies, game studies, and disability studies, with current projects exploring how poetry became a key site of digital experimentation in Japan. His research methodology combines traditional literary analysis with hands-on creative practice, informed by his experiences at MIT's Trope Tank laboratory. His scholarly interests span Japanese media history, disability representation in literature and gaming, digital poetics, and gender studies. His research has received significant media attention, including features in the Cornell Chronicle ('Poets in Japan Experiment at the Edge of Media' and 'Japanese Poets Open New Ways of Thinking About Media'), The Statesman, and interviews on NPR's Academic Minute and the Curiosity Daily podcast discussing his work on gaming and accessibility. As an educator, Campana teaches courses including 'Introduction to Japan,' 'Japanese Poetry,' and 'The Glitch: Errors, Disability, and the Edges of Digital Media' (ASIAN 4703/6703), guiding students through interdisciplinary explorations of Japanese literature, media, and digital culture. His teaching reflects his commitment to understanding media transitions through both theoretical and practical lenses.
Hirokatsu Kataoka serves as Chief Senior Researcher at the National Institute of Advanced Industrial Science and Technology (AIST) in Japan, with multiple academic affiliations including Academic Visitor at the Visual Geometry Group (VGG) at University of Oxford, Visiting Associate Professor at Keio University, and Adjunct Associate Professor at Tokyo Denki University. He is Principal Investigator of both cvpaper.challenge and LIMIT.Lab, and serves as Research Advisor for SB Intuitions. Dr. Kataoka earned his Ph.D. in Engineering from Keio University (April 2011 - March 2014), where he received the Fujiwara Prize in 2014 as valedictorian equivalent. His research primarily focuses on innovative pre-training methodologies that eliminate dependency on natural image datasets, with his Formula-Driven Supervised Learning (FDSL) framework being particularly influential in the field. Kataoka's research interests center around representation learning with limited data resources, including zero-shot, unsupervised, and synthetic learning approaches. His work explores how visual/multimodal models can be effectively trained with minimal real-world data, addressing critical ethical concerns related to large-scale datasets. He has pioneered methods using fractal geometry, mathematical formulas, and procedural generation to create effective pre-training frameworks that rival traditional ImageNet-based approaches. His publication record shows a clear trajectory toward solving the challenges of learning with limited resources, with recent work expanding FDSL to audio processing, microfossil analysis, and visible-to-infrared translation. His papers consistently address the core challenge of building robust visual recognition systems without relying on massive annotated datasets, with increasing focus on practical applications across diverse domains. Scientific Awards & Recognition ACCV 2020 Best Paper Honorable Mention Award for 'Pre-training without Natural Images' AIST Best Paper Award (2019, 2022) BMVC 2023 Best Industry Paper Finalist Featured in MIT Technology Review His 3D ResNets paper ranks among the top 0.5% most-cited CVPR papers over a five-year period Dr. Kataoka actively advises numerous researchers across multiple institutions, with his research team comprising Ph.D. and Master's students from various universities. He has served as Area Chair for CVPR 2024 and 2025, will serve as IEEE TPAMI Associate Editor beginning in 2025, and organizes the LIMIT Workshop series at major computer vision conferences. His LIMIT.Lab, established in June 2025, serves as a collaboration hub focused on building multimodal AI models under constrained resources including compute, data, and labels.
Professor Gary Edmond is a law professor at the University of New South Wales School of Law, directing the Program in Expertise, Evidence and Law. Holding a BA(Hons) from the University of Wollongong, LLB(Hons) from the University of Sydney, and PhD from the University of Cambridge, he bridges legal scholarship with forensic science expertise through extensive research grants and international collaborations. Education: BA(Hons), LLB(Hons), PhD Institutions: University of New South Wales, Australian Academy of Forensic Sciences His research focuses on the intersection of law and forensic science, examining expert evidence reliability, forensic reporting practices, and the adversarial legal system's limitations. With over $1.4 million in research funding since 2007, he leads interdisciplinary projects involving policing agencies and forensic institutions across Australia and international partners. Recent publications analyze judicial handling of expert evidence, cognitive biases in courtroom identification, and forensic science reform. His work has shaped evidence law understanding through the 6th edition of 'Australian Evidence: A principled approach to the common law and the uniform acts' and advisory roles in high-profile inquiries like the Goudge Inquiry. Awards: Fellow of the Royal Society of New South Wales As Chair of the Evidence-based forensics initiative and member of Standards Australia’s forensic science committee, he continues to influence policy while teaching core legal subjects including Courts, Procedure, Evidence and Proof, and Introducing Law and Justice.
Cara M. Nunez is an Assistant Professor in Mechanical and Aerospace Engineering at Cornell Engineering. Her research focuses on haptic interfaces, sensory perception, and human-robot interaction. Research Areas: Development of wearable haptic devices for sensory feedback Human perception of tactile stimuli under cognitive load Multimodal interaction combining haptic, audio, and visual cues Medical applications of haptic guidance systems Key publications explore smartphone-based sensory assessment, affective mediated touch, and haptic guidance for medical procedures. Her work appears in robotics and human-computer interaction venues.
Christian Wolff is a University Professor and Chair of Media Informatics at the Institute for Information and Media, Language and Culture at the University of Regensburg. Since April 2022, he has served as the founding Dean of the Faculty of Computer Science and Data Science, while maintaining secondary membership in the Faculty of Languages, Literature and Cultural Studies (SLK). His academic career spans over three decades with significant contributions to multiple disciplines at the intersection of computer science and humanities. Wolff's research interests center around multimedia and multimodal information systems, electronic publishing, and text technology, particularly text mining. His work bridges computer science with digital humanities, legal informatics, and social media analysis. Recent publications demonstrate a strong focus on large language models, sentiment analysis applications across various domains, legal technology innovations, and virtual reality research for cognitive studies. His interdisciplinary approach has produced significant contributions in both technical and humanities domains. His recent publication trends reveal a strategic shift toward applied AI research, particularly in legal technology (LegalTech), social media analysis, and sentiment analysis using large language models. The publications show increasing collaboration across disciplines, connecting computer science with law, political science, literature, and psychology. His work on the digital basis document for legal proceedings represents a major practical application of his research in the German justice system. East Bavarian Cultural Prize Doctoral Award of the University of Regensburg Wolff has led numerous interdisciplinary research projects connecting computer science with humanities and legal studies. His leadership extends to institutional roles including Dean of Research, Vice Dean, and Dean of Faculty positions. He has been instrumental in establishing the new Faculty of Computer Science and Data Science at the University of Regensburg, demonstrating significant impact on institutional development and research infrastructure. Wolff directs research initiatives focused on text technology, digital humanities, and legal informatics. His work with the INDIGO - Internet and Digitization Eastern Bavaria initiative and the TRIO project demonstrates commitment to regional technology transfer and innovation. The interdisciplinary nature of his research groups connects computer scientists with legal scholars, linguists, and social scientists to address complex digital transformation challenges.
Tyler Simko is an Assistant Professor of Political Science at the University of Michigan, specializing in US state and local politics, political geography, and computational social science. His research focuses on understanding and addressing inequality in American public policy through innovative methodological approaches. Education: Ph.D. in Government, Harvard University (2024) A.B. in Politics, Princeton University Simko's research examines state and local politics in the United States with particular focus on political geography and subnational policymaking. His active research agendas include legislative redistricting ("gerrymandering"), local public meetings, school segregation, affordable housing, and data privacy. Methodologically, he develops new techniques in computational social science and machine learning to evaluate subnational inequality and how it can be reduced. His work regularly involves partnerships with federal, state, and local officials to improve the design of public policy. His recent publications demonstrate a strong focus on applying computational methods to address real-world policy challenges, particularly in school desegregation, redistricting, and local government transparency. His research often leverages large-scale data collection efforts, such as LocalView (the largest database of local government meetings in the US), to analyze patterns of political behavior and policy outcomes across different jurisdictions. Awards and Recognition: APSA 2024-25 Best Paper in Education Politics and Policy Award APSA 2024-25 Best Paper in Urban and Local Politics, Honorable Mention MPSA 2024 Robert H. Durr Award for "the best paper applying quantitative methods to a substantive problem" Derek C. Bok Award for Excellence in Graduate Student Teaching of Undergraduates (2023) Simko teaches graduate and undergraduate courses in American Politics and Political Methodology at the University of Michigan. His teaching experience spans multiple institutions, including Harvard University and Princeton University. He has designed innovative courses on US Local Policymaking, data science, and computational social science. As a Data Scientist at the Office of Evaluation Sciences, he partners with federal, state, and local officials to improve program design and reduce administrative burdens. He is a co-PI of the Algorithm-Assisted Redistricting Methodology (ALARM) Project and co-creator of LocalView, the largest audio, video, and text database of local government meetings in the United States. These projects represent significant contributions to the field of computational social science and provide valuable resources for researchers studying local governance and policy-making.
Mayank Goel serves as an Assistant Professor in the Software and Societal Systems Department (S3D) at Carnegie Mellon University's School of Computer Science. His research bridges computer science and societal impact through practical sensing systems that leverage existing environmental devices for health monitoring and human-computer interaction without requiring hardware modifications. Dr. Goel specializes in mobile computing, signal processing, and machine learning to develop unobtrusive health technologies applicable to real-world scenarios. His core research areas include passive activity recognition for chronic disease management (particularly multiple sclerosis), privacy-preserving acoustic sensing, smartwatch-based clinical interventions for post-operative care, and equitable healthcare systems for global development contexts. He emphasizes end-to-end solutions through close collaboration with medical professionals and designers to ensure immediate deployability outside laboratory environments. Analysis of his 2024-2025 publications reveals a strong interdisciplinary focus spanning computer science, biomedical engineering, and clinical practice. Key trends include longitudinal digital phenotyping for neurological conditions, on-device privacy preservation in activity recognition, and multimodal procedural assistance systems. His work consistently addresses real-world challenges in sensor placement flexibility, user adoption barriers, and equitable access to medical technologies. No scientific awards were mentioned in the available documentation. Information regarding student advising, research grants, or laboratory affiliations was not specified in the provided materials, though his publication record indicates active collaboration with medical professionals and bio-engineers for clinical validation of health technologies.
Ryo Ikeshiro is an Assistant Professor at the School of Creative Media, City University of Hong Kong, and co-director of the spatial audio art/research unit SoundLab. His work bridges sound art, computational creativity, and cultural studies through immersive installations, algorithmic audio-visual systems, and sonification techniques. PhD in Creative Practice (Goldsmiths, University of London) MPhil in Music (University of Cambridge) BMus (King's College London) Ikeshiro's research interrogates the materiality of sound through: Multichannel Ambisonics and directional audio Neural network-driven temporal dislocation Sonification of climate data and historical soundscapes Machine learning for artistic interpretation Interplay of identity and technology East Asian ideophonic traditions His 2010-2024 publications and installations reveal cross-disciplinary engagement with: Fractal mathematics in audiovisual art Algorithmic composition systems Interactive installation technologies Sonic cartography Historical memory in sound Collaborative research frameworks SoundLab, which he co-directs, develops spatial audio research at the intersection of: Technical innovation Cultural representation Experimental pedagogy Public engagement International artistic exchange Practice-based research
Lennie Moore serves as a faculty member in the Technology and Applied Composition (TAC) program at the San Francisco Conservatory of Music (SFCM), where he teaches Applied Lessons, Tools, Techniques and Analysis, and Orchestration for the Media Composer. With decades of experience as a composer, arranger, and orchestrator for video games, commercials, film, and television, Moore brings real-world industry expertise to his academic role. His teaching extends beyond SFCM, having developed and taught courses in Composing for Video Games at USC and UCLA Extension. Moore's research interests focus on the complex puzzle of video game scoring, emphasizing the deconstructionist approach required for interactive media. His work explores how to break down compositions into vertical layers and horizontal procedural components that can be implemented into music playback systems in real-time based on player choices. He specializes in open-world environments where music must smoothly transition through different game areas. His passion for building computers and video games outside of traditional music informs his innovative approach to media composition. His recent work includes the 2024 release of Outcast: A New Beginning , a sequel to his groundbreaking 1999 score for the original Outcast game, which was one of the first live orchestra and choir scores in gaming history. This new project involved approximately two hours and fifteen minutes of music with complex interactive elements, recorded during the pandemic with remote sessions. Best Soundtrack Album, G.A.N.G. Awards, 2011 Best Interactive Score, G.A.N.G. Awards, 2011 Best Audio — Other, G.A.N.G. Awards, 2008 Moore actively mentors students in the TAC program, with notable alumni including Kyle Randall (winner of the American Prize in composition), Shengyuan Li (Top 10 Finalist in the Berlin International Film Scoring Competition 2023), and Shawne Workman (now SFCM TAC faculty). His 2023 album Mentors pays tribute to his influences including Weather Report, Steps Ahead, Arif Mardin, Michael Gibbs, Don Grolnick, David Mash, Nick & Andy, Ken Kraintz, and Toshiko Akiyoshi. Moore emphasizes to students that 'Failure is an option' and encourages them to consider 'Who am I as an artist?' early in their development.
Prof. Dr.-Ing. André Jakob is a faculty member at Berlin University of Technology , affiliated with the Department VII - Electrical Engineering - Mechatronics - Optometry. His academic role spans teaching and research in digital signal processing, audio technology, and acoustics. Digital Signal Processing Audio Technology Acoustics Active Noise Control His research focuses on active noise control , simulation of moving sound sources , and audio signal processing , with applications in robotics, building acoustics, and medical devices. Publications include advancements in anti-noise window systems , sound source localization , and acoustic measurement techniques . His recent work explores real-time auralization for educational robotics and nonlinear acoustic modeling with neural networks. The 15 most recent articles demonstrate a consistent focus on acoustic simulation , active control systems , and sound propagation modeling , with conference contributions at DAGA, NAG-DAGA, and international acoustics events. Topics range from dental drill noise reduction to active sound design in musical instruments , reflecting interdisciplinary applications. He supervises numerous Master's and Bachelor's theses in areas like real-time signal processing, deep learning for sound recognition, and virtual acoustics. His lab at TU Berlin explores multi-loudspeaker systems , acoustic beamforming , and active noise cancellation for both industrial and consumer applications.
Josh Reiss is a Professor of Audio Engineering at Queen Mary University of London (QMUL), part of the School of Electronic Engineering and Computer Science . He holds additional roles including President-Elect and Fellow of the Audio Engineering Society (AES), and Visiting Professor at Birmingham City University. His research focuses on audio signal processing, procedural audio, and intelligent music production. He earned degrees including BSc in Physics, BSc in Mathematics, and a PhD. Research & Awards : Reiss has published over 200 papers, authored books like Intelligent Music Production , and received awards such as the AES Board of Governors Award (2009, 2010) and Best JAES Paper 2016. His work spans sound synthesis, dynamic range compression, and live audio systems. Teaching & Industry : Teaches modules like Artificial Intelligence and Sound Design. Co-founded startups LandR (AI mixing), Tonz, and Nemisindo. Leads the Centre for Digital Music at QMUL, advancing research in audio technology. Labs & Teams : Active in the Centre for Digital Music, collaborating on projects like the Open Multitrack Testbed and semantic audio evaluation tools.
