Jason Smith is a Postdoctoral Scholar at Northwestern University , affiliated with the Interactive Audio Lab . He earned his PhD in Music Technology from the Georgia Institute of Technology . Research Focus Human-AI collaboration in creative domains Interactive music systems AI-driven accessibility solutions Creative autonomy and neural audio generation Recommender systems for music libraries Publication Trends His work spans 2019–2025, emphasizing AI applications in music education, accessibility (especially for blind/visually impaired users), and immersive environments like AI holodecks. Key methodologies include co-design, hybrid recommendation algorithms, and automated creativity assessment. Lab Affiliation He contributes to the Interactive Audio Lab, exploring intersections of sound, code, and AI.
Jon McCormack is a Professor jointly appointed in Monash University's Faculty of Art, Design & Architecture (MADA) and Faculty of Information Technology. He founded and directs SensiLab, a research facility focusing on computational creativity, human-machine interfaces, and generative systems. His work spans electronic media art, evolutionary music, and artificial life. McCormack holds a PhD in Computer Science from Monash University, along with degrees in Computer Science, Applied Mathematics, and Film/Television. Research interests include computational creativity, tangible interfaces, and cybernetic systems. Notable projects include 'Explainable Artificial Creativity' (ARC-funded) and 'Building 4.0 CRC,' addressing architectural innovation through AI. He has been recognized with awards for collaborative projects like the Blundstone Intelligent Footwear for Healthcare. McCormack's recent articles explore AI-driven art, generative systems, and interdisciplinary design. His work bridges artistic practice with technical innovation, emphasizing ethical and creative dimensions of human-AI collaboration. SensiLab serves as a hub for practice-based research in digital media and interactive systems. Education: PhD in Computer Science, Monash University (2004) Bachelor of Science (Honours), Computer Science/Applied Mathematics, Monash University (1987) Graduate Diploma in Film/TV, Swinburne University (1986) Bachelor of Science, Computer Science/Applied Mathematics, Monash University (1985) Key Projects: Lead investigator on 'Explainable Artificial Creativity' (2022–2026) Co-investigator in 'Building 4.0 CRC' (2020–2027), exploring AI-driven architectural design Awards: 2022 Designers Australia Award for Blundstone Footwear 2020 'On the Machine Condition' Prize McCormack's lab, SensiLab, fosters collaborations across disciplines, producing exhibitions, software, and theoretical frameworks for computational creativity. He actively supervises PhD students in practice-based research, emphasizing the intersection of art and technology.
Frank Russo is a Professor in the Department of Psychology at Toronto Metropolitan University, where he holds the NSERC-Sonova Senior Research Chair in Auditory Cognitive Neuroscience. He leads the Science of Music Auditory Research and Technology (SMART) Lab and holds affiliate and adjunct positions at the University Health Network and the University of Toronto, respectively. Research Interests: Dr. Russo's work lies at the intersection of auditory cognitive neuroscience, music psychology, and rehabilitation. His research explores how humans perceive music and speech, particularly under challenging conditions such as hearing loss or non-native accents. He investigates the cognitive and neural mechanisms of listening effort, emotional speech processing, and the social and therapeutic benefits of music, especially through community choirs and digital interventions. Publication Trends: His recent publications emphasize objective measurement of listening effort using functional near-infrared spectroscopy (fNIRS), music-based interventions for Parkinson’s disease and dementia, vocal and emotional responses to singing, and multisensory integration in beat perception. The work is highly translational, bridging basic cognitive neuroscience with clinical and community applications. Scientific Awards and Honors: NSERC-Sonova Senior Research Chair in Auditory Cognitive Neuroscience Fellow of the Canadian Psychological Association Fellow of Massey College Fellow of the Canadian Society for Brain, Behavior and Cognitive Science Past President of the Canadian Acoustical Association Advising and Grants: Dr. Russo actively mentors students and researchers, as evidenced by his co-authorship with numerous junior colleagues. He has secured major funding through NSERC and industry partnerships, enabling the development of impactful technologies such as hearing aid algorithms, sensory substitution systems, and digital therapeutics. His SingWell project fosters collaboration across academic, clinical, and community sectors. Labs and Teams: He directs the SMART Lab at Toronto Metropolitan University, a hub for interdisciplinary research on music, hearing, and cognition. The lab collaborates extensively with KITE Research Institute, Rehabilitation Sciences at the University of Toronto, and various community organizations focused on aging, hearing loss, and neurodegenerative conditions.
Tatsuhiro Ueno serves as Professor at Waseda University's Faculty of Law and School of Law, specializing in Intellectual Property Law, Copyright Law, and Information Law. He currently holds leadership positions as Director of the Institute of Comparative Law (since 2024) and President of SARLIB (Society for Administration of Remuneration for Public Transmission by Libraries or Similar Facilities). With extensive international experience including visiting scholar positions at Ludwig Maximilian University of Munich and the Max Planck Institute for Intellectual Property and Competition Law, Professor Ueno has established himself as a leading authority in copyright law reform and international intellectual property matters. Professor Ueno earned his Master of Law from Kyoto University following undergraduate and graduate studies there. His academic career includes teaching positions at Rikkyo University College of Law and Politics and Seijo University Faculty of Law before joining Waseda University in 2013, where he now contributes to shaping Japan's legal education landscape. His research focuses on the critical intersection of intellectual property law with emerging technologies, particularly artificial intelligence systems and digital platforms. Professor Ueno has pioneered work on text and data mining exceptions, copyright limitations in digital environments, and creator-oriented copyright frameworks. His scholarship bridges theoretical analysis with practical policy development, influencing both domestic legislation and international copyright discourse. His recent publications demonstrate a concentrated focus on AI and copyright law, with numerous articles examining the legal challenges posed by generative AI systems, text and data mining exceptions, and the evolving landscape of copyright protection in the digital era. Professor Ueno's work consistently addresses the balance between protecting creators' rights and ensuring public access to knowledge. KDDI Foundation Book Publishing Grant (January 2025) for "Creator-Oriented Copyright System" Professor Ueno actively participates in numerous government committees shaping Japan's copyright law, including serving as Chairman of the Law and Computers Society and as a longstanding member of the Copyright Subcommittee of the Council for Cultural Affairs. His research is supported by multiple grants from the Japan Society for the Promotion of Science, including ongoing projects examining human portraits and voices in the AI age (2025-2029) and AI and intellectual property rights systems (2024-2029). He regularly presents at international forums including WIPO Summer Schools, ATRIP conferences, and copyright forums worldwide, establishing his reputation as a key thought leader in global copyright policy development.
Dr. Robert Lieck is an Assistant Professor in the Department of Computer Science at Durham University. His research focuses on interdisciplinary applications of machine learning (ML) and artificial intelligence (AI), emphasizing interpretability, robustness, and ethical considerations. He explores computational models in music cognition, communication dynamics, and medical image analysis, aiming to bridge theory and practical tools for domain experts. Before Durham, he was a postdoctoral researcher at EPFL's Digital and Cognitive Musicology Lab (2018–2021) and earned his PhD from the Learning and Intelligent Systems Lab in Stuttgart/Berlin (2012–2017). His work combines probabilistic modelling, neuro-symbolic systems, and reinforcement learning to address challenges in music analysis, autonomous decision-making, and medical robotics. Key research themes include: Music structure and perception modelling Symbol emergence in multi-agent communication Ethical AI and autonomous systems governance Medical imaging applications (CT/MRI analysis) Recent projects involve developing patient-agnostic diabetes management systems using deep reinforcement learning and surgical workflow anticipation through graph learning algorithms. He actively contributes to conferences such as NeurIPS, ISMIR, and AAAI, with publications spanning music informatics, robotics, and biomedical engineering. Current supervision includes four postgraduate students focusing on AI applications in healthcare, music technology, and autonomous systems. His work bridges technical innovation with societal impact, addressing challenges in policy, legislation, and interdisciplinary collaboration.
Dr. Lin Wang is a Lecturer in Applied Data Science and Signal Processing at Queen Mary University of London (QMUL), affiliated with the School of Electronic Engineering and Computer Science. He leads the Machine Listening Lab and is a member of the Centre for Multimodal AI, Centre for Intelligent Sensing (CIS), and Institute of Coding (IoC). His research focuses on audio-visual signal processing, robotic perception, and machine learning, with applications in healthcare, drone-based sensing, and human activity recognition. Dr. Wang holds a PhD from Dalian University of Technology and has held postdoctoral positions at QMUL, the University of Sussex, and the Alexander von Humboldt Foundation in Germany. Education and Roles: PhD in Signal Processing, Dalian University of Technology (2010) Postdoc at Queen Mary University of London (2014–2017) Postdoc at University of Sussex (2017–2018) Alexander von Humboldt Fellow at University of Oldenburg (2011–2013) Fellow of the Higher Education Academy (UK) Research Interests: Audio-visual signal processing for drones and wearable devices Machine listening and robotic perception Machine learning for healthcare and environmental monitoring Human activity recognition using multimodal sensors Awards and Grants: Early Career Champion on AI&Data, UK Acoustics Network Outstanding Article Award, Frontiers in Computer Science (2022) EPSRC grant: Bioacoustic Monitoring Using Drones (£46,821, 2022–2023) Innovate UK grant: Music Source Separation (£48,144, 2024–2025) Teaching and Students: Dr. Wang teaches Applied Statistics , Website Design and Authoring , and Machine Learning for Visual Data Analysis . He supervises PhD students including Ashish Alex (speech separation), Michael Clayton (drone audition), and Dmitrii Mukhutdinov (audio-visual processing). Labs and Teams: He co-leads the Machine Listening Lab and is part of the Centre for Multimodal AI, focusing on interdisciplinary projects in robotics, acoustics, and AI.
Olga Vechtomova is a Professor at the University of Waterloo, affiliated with the Information Systems research group and specializing in Search Engines and Natural Language Processing. Her work bridges computational creativity, multimodal systems, and AI-driven text generation. She leads projects like LyricJam , a real-time lyric generation system for live music, and explores applications in dynamic story generation, hate speech detection, and low-resource summarization. Her research emphasizes ethical AI, creative technologies, and leveraging large language models for diverse tasks. Research interests include natural language processing, machine learning, and multimodal interaction. Recent work focuses on artistic inspiration modeling, stylized text generation, and improving NLP efficiency through semi-supervised learning and distillation techniques. Her contributions span over 60 papers since 2000, with a strong emphasis on foundational NLP challenges and real-world applications. She collaborates on systems like Promptmix for model distillation and LyricJam sonic for music-audio lyric generation.
Susanne M. Jaeggi is a Professor of Psychology at Northeastern University, with additional affiliations in the Bouve College of Health Sciences and the College of Arts, Media, and Design. Her research focuses on cognitive training, executive functions, and individual differences in cognition across the lifespan. She holds PhDs in Cognitive Psychology and Neuroscience from the University of Bern (Switzerland), and completed postdoctoral work in Cognitive Neuroscience at the University of Michigan. Her work has been funded by NIH, NSF, IES, ONR, and the Advanced Education Research and Development Fund (AERDF). She leads the Working Memory & Plasticity Lab , which develops interventions to improve working memory and executive functions, and co-leads the Brain Game Center for Mental Fitness and Well-Being , creating evidence-based brain fitness tools. Jaeggi’s research emphasizes understanding mechanisms of cognitive improvement through training, including neuroplasticity and individual variability. Key areas include cognitive aging interventions, gamification, sensory-cognitive interactions, and the impact of socioeconomic factors on academic achievement. Her work integrates behavioral experiments, neuroimaging, and digital health technologies to address real-world challenges in education and healthcare. Recent studies explore music/art-based interventions, brain stimulation (e.g., tDCS), and scalable cognitive assessments. Collaborations span disciplines, with publications addressing topics like neural correlates of training, motivational features in interventions, and cross-modal perception. Her labs emphasize translating findings into public-facing tools, such as freely accessible brain fitness apps. Current projects include optimizing interventions for ADHD populations and leveraging digital platforms for global mental fitness.
Fattane Zarrinkalam is an Assistant Professor in the School of Engineering at the University of Guelph. She holds a PhD from Ferdowsi University of Mashhad, Iran, and completed a Postdoctoral Research Fellowship at Ryerson University (2018–2020). Her research focuses on social media mining, semantic technologies, and user modeling, with applications in healthcare, legal tech, and e-commerce. She is a Vector Institute Postgraduate Affiliate and serves on editorial boards for journals like Information Processing & Management and IEEE Transactions on Network Science and Engineering . Her work emphasizes actionable insights from social data, including sarcasm detection, user interest prediction, and fairness in social media analytics. Zarrinkalam has contributed to over 30 peer-reviewed publications and holds multiple patents in data analysis and social media sentiment modeling. Education: PhD, Ferdowsi University of Mashhad, Iran Postdoctoral Fellowship, Ryerson University Research Scientist, Thomson Reuters Labs Research Interests: Semantic interpretation of social content User modeling via temporal analysis Social good applications (e.g., mental health, telecommunication) Fairness in social media mining Recent Work Trends: Her articles span network representation learning, dynamic user interest prediction, and interdisciplinary applications. Notable themes include neural networks for sarcasm detection, heterogeneous graph embeddings, and leveraging Twitter data for psychological insights. Awards & Service: Co-chair, International Workshop on Mining Actionable Insights from Social Networks (MAISoN) Editorial board roles for top journals Labs & Teams: Involved in interdisciplinary collaborations at the Vector Institute and partnerships with industry on legal tech and social analytics projects.
Mariya Toneva is a tenure-track faculty member at the Max Planck Institute for Software Systems , conducting groundbreaking research at the intersection of Machine Learning , Natural Language Processing , and Neuroscience . She leads the Bridging AI and Neuroscience (BrAIN) group , focusing on computational models that align AI systems with human brain processes. Her work aims to enhance both AI capabilities and neuroscience understanding through this cross-disciplinary approach. Actively recruiting postdocs, PhDs, and research interns in areas like code/text representation, brain-AI alignment, and neuroimaging data analysis Collaborator on NIH-funded projects using fMRI and neuropixel data Research Themes : Her group explores neural mechanisms of language processing, event segmentation in narratives, memory reactivation via music, and effective human-AI collaboration frameworks. Key methods include LLM analysis, cross-modal similarity metrics, and naturalistic task-based fMRI studies. Key Publications (2024-2025): Brain-tuned speech models (INTERSPEECH 2025) Cognitive event boundaries in LLMs (Behavioral Research Methods 2025) Music-induced memory reactivation (biorxiv 2024) LLM-brain alignment reasons (EMNLP 2024) Advising : Mentors PhD candidates Omer Moussa (speech processing), Camila Kolling (representational similarity), and Gabriele Merlin (LLM alignment). Collaborates with institutions like MIT, NYU, and ETH Zurich.
Berit Greinke is an Assistant Professor of Wearable Computing at the Berlin University of the Arts (UdK) and the Einstein Center Digital Future (ECDF) since 2018, previously serving as a researcher at UdK's Design Research Lab and DFKI (2016-2018). Her academic foundation includes a PhD from Queen Mary University of London (2017), an MA from Central St Martins (2009), and a Diploma from Weissensee Academy of Art Berlin (2007). Her educational trajectory: PhD in Media and Arts Technology, Queen Mary University of London (2017) MA in Design for Textile Futures, Central St Martins College of Art and Design (2009) Diploma in Textile and Surface Design, Berlin Weissensee School of Art (2007) Greinke's research pioneers the convergence of craft, textile design, and digital technology, with core expertise in electronic textiles and smart materials. She investigates metamaterial-based 'metatextiles' for electromagnetic applications and explores transdisciplinary collaboration between designers and scientists, particularly regarding 'negative data' in creative and scientific workflows. Her current UdK work focuses on four interconnected domains: performing materials for expressive textile/fashion design; multi-modal sensing converting visual processes into haptic/audible experiences; micro-to-macro material design spanning nanostructures to final products; and transdisciplinary processes for technology-art-science collaboration. Analysis of her 2020-2025 publications reveals dominant trends in sustainable textile electronics, with emphasis on knitted/folded sensor structures, origami-inspired capacitive shape estimation, and social sustainability in e-textile communities. Her work uniquely bridges fundamental material science (e.g., textile metamaterials) with artistic applications (e.g., interactive orchestra garments) and industrial production challenges. Berit Greinke supervises PhD students including Giorgia Petri. Her junior professorship is co-financed by SAP under a public-private partnership model, supporting projects like WEAR (Wearable technologists engage with artists for responsible innovation) and STELEC (Sustainable Textile Electronics), which emphasize ethical co-design and industry-academia collaboration. She leads research within UdK's Institute for Product and Process Design and collaborates with the Design Research Lab (formerly part of Connected Textiles group), focusing on sustainable industrial production of electronic clothing and transdisciplinary innovation frameworks.
Maria Camila Ceballos Betancourt is an Assistant Professor (Teaching & Research) in Beef Cattle Welfare at the Faculty of Veterinary Medicine , University of Calgary . She holds a Ph.D. and M.Sc. in Animal Welfare and Behaviour from São Paulo State University (UNESP) , Brazil, and a B.Sc. in Animal Science from National University of Colombia . Her research focuses on animal welfare , human-animal interactions , and cattle temperament , with an emphasis on livestock handling practices and sustainable production systems . Education: B.Sc. in Animal Science, National University of Colombia (2010) M.Sc. in Animal Welfare and Behaviour, UNESP (2014) Ph.D. in Animal Welfare and Behaviour, UNESP (2017) She teaches VETM322: Animal Welfare and Behaviour annually since 2020. Her research integrates animal behavior , physiological and reproductive performance measures , and applied handling interventions . Recent publications address grimace scales for pain assessment , human-animal dynamics in livestock systems , and technological innovations for piglet monitoring , reflecting her interdisciplinary approach between agricultural science , veterinary medicine , and behavioral neuroscience . Her work spans continents, including internships at the Animal Welfare Science Centre (University of Melbourne, Australia) and postdoctoral research at the University of Pennsylvania (USA). While no formal awards are listed, her research has been highlighted in media outlets like Canadian Cattlemen’s The Beef Magazine and CBC Calgary .
Dr. Sam Ferguson is a Senior Lecturer at the School of Computer Science, University of Technology Sydney (UTS), with a multidisciplinary background in music performance, cognitive science, and psycho-acoustics. His research explores the intersection of sound, music, and human experience through creative coding, machine learning, and interactive systems. Key Research Areas: Sound and Music Computing, Human-Computer Interaction, Creative Coding, Cognitive Science, Installation Art, and Acoustics. Current Projects: ARC Linkage project on creative coding and multiplicitous media; industry collaborations on IoT-based audiovisual systems. Recent Publications: Focus on spatial audio complexity, gestural interaction with networked sound, music emotion recognition frameworks, and robotic performance through genre-based cultural platforms. Leadership Roles: Director of Teaching & Learning Engagement; former Deputy Head of School (Teaching and Learning); active in ACM Creativity and Cognition Steering Committee. Teaching: Courses like Digital Media Studio , Prototyping Physical Interaction , and Data Processing using R within UTS's interdisciplinary Software Development Studio.
Hugh Churchill is a Professor in the Department of Physics at the University of Arkansas, College of Arts & Sciences. His research focuses on quantum materials and devices, particularly condensed matter physics with applications in 2D systems and quantum transport. Education: PhD in Physics from Harvard University, BA in Physics and BM in Music Performance from Oberlin College Recent research trends include studies on 2D materials like transition metal dichalcogenides and black phosphorus, investigating quantum transport phenomena, supercurrent tuning, strain engineering for exciton control, and applications of machine learning in quantum material discovery. His work also explores THz emission mechanisms and quantum noise mitigation strategies. Arkansas Research Alliance Fellow Presidential Early Career Award for Scientists and Engineers NSF CAREER Award ORAU Powe Junior Faculty Award AFOSR Young Investigator Connor Faculty Fellowship Hugh teaches graduate and undergraduate courses in quantum mechanics, modern physics, and 2D materials, including PHYS 5413 Quantum Mechanics I and PHYS 6713 Condensed Matter Physics II.
Theodora Varvarigou is a Professor in the Department of Electrical and Computer Engineering at the National Technical University of Athens (NTUA). She holds a B.Eng. from NTUA and M.Eng. and Ph.D. degrees from Stanford University. Her career includes research at AT&T Bell Labs and roles at the Technical University of Crete. From 2008-2012, she served as director of NTUA's 'Technoeconomic Systems' postgraduate program. Her research focuses on Cloud Computing, Multimedia Content Processing, Social Networking Technologies, and emerging areas like blockchain, edge computing, and cybersecurity. She has published over 200 papers and led numerous European research projects, emphasizing scalable systems, data management, and smart infrastructure applications. Her work spans technical innovations such as intrusion detection systems, edge resource optimization, and blockchain-based solutions for IoT, healthcare, and smart cities. Recent publications highlight advancements in AI-driven resource allocation, privacy-preserving blockchain designs, and predictive analytics for edge computing environments. Professor Varvarigou has contributed to interdisciplinary initiatives, including cohort data harmonization in biomedical research and social media analytics for urban planning. Her teaching includes courses on digital systems, network programming, and fault-tolerant systems.
