Dongwook Yoon is an Associate Professor at the Department of Computer Science , University of British Columbia , and serves as Director of the SOCIUS Lab . He actively contributes to research in Human-Computer Interaction, Human-AI Interaction, and Virtual/Augmented Reality as a member of the Designing for People (DFP) and CAIDA research clusters. Education : PhD in Computer Science from Cornell University (2017), MS (2009) and BS (2007) in Computer Science from Seoul National University Research Focus : Designing socio-technical systems that bridge the gap between technology and human social processes, with innovations in AR/VR, multimodal interaction, and inclusive design Article Trends show his work spans: Temporal and bichronous learning environments AI self-clones and ethical implications Income inequality in virtual platforms Enhanced multimodal collaboration in VR Eyes-reduced interfaces for situational impairments Speculative participatory design for gig economy challenges Scientific Awards include: Google Academic Research Award (2024) Best Paper Award at CHI 2024 High Impact Award in Educational Technology (2024) CHCCS/SCDHM Graphics Interface Early Career Award (2023) Multiple Honorable Mentions at CHI, DIS, and CSCW Students & Collaborators range from active PhD candidates (Anika Sayara, Yuri Kim) to notable alumni (Thitaree Tanprasert, Ashish Chopra) across his SOCIUS Lab projects. His research receives funding from NSERC , KIST , Adobe , Microsoft , and Google grants.
JuHyun Lee is an Associate Professor of Architecture and Computational Design in the School of Built Environment at the Faculty of Arts, Design and Architecture (ADA), University of New South Wales (UNSW) Sydney, where they also hold the prestigious title of Scientia Academic. With a professional background in architecture and construction (1998-2002), they have held academic positions across Australia including a five-year post-doctoral fellowship at the University of Newcastle (2012-2017) and a senior research fellowship at the University of South Australia (2018), following earlier research and teaching roles in South Korea (2003-2011). Lee specializes in architectural design computing, design cognition, and urban complexity, integrating computational methods, cognitive science, and architectural theory to advance architectural intelligence and human-centered design. Their research spans architectural visualization, analysis and design methods, algorithm/protocol design, and data visualization with computational approaches. They have established a strong research program examining the intersection of language, culture, and design cognition, particularly focusing on cross-cultural design communication between Australia and Korea. Lee's recent publications demonstrate a clear trajectory toward increasingly sophisticated integration of computational methods with architectural design theory, particularly in the areas of shape grammar, space syntax, and machine learning applications. Their work shows consistent focus on practical applications of computational design methods to real-world architectural problems, with growing emphasis on cross-cultural collaboration and intelligent design systems. The research portfolio reveals a deepening engagement with AI and machine learning techniques applied to architectural design assessment and generation. Scientia Academic at UNSW Sydney Associate Fellow of the Higher Education Academy (AFHEA, 2020) As an educator, Lee develops cutting-edge courses in computational design and Building Information Modeling (BIM), integrating experiential learning and industry engagement. They have secured over $11 million in research funding, including multiple ARC Discovery Projects and an Australia-Korea Foundation grant. Lee co-directs the Advanced Architectural Analytics Laboratory (A 3 LAB), leading interdisciplinary research on design automation, spatial analysis, and machine learning applications in architecture, while also leading cross-cultural initiatives like the Australia-Korea Architects' Network (AKAN). Lee supervises multiple HDR students working on culturally sustainable urban design, socio-spatial patterns in public housing, and computational layout generation. Their research has significant implications for improving design communication across cultural boundaries and developing more coherent, clear, and accessible built environments through computational design approaches.
Mihye Won is an Associate Professor at Monash University’s Faculty of Education, specializing in innovative science education strategies. Her research integrates dialogic teaching, student-generated diagrams, immersive Virtual Reality (VR), and generative AI to enhance scientific understanding and creativity. She has secured Australian Research Council (ARC) funding for projects like Using Immersive Virtual Reality to Enhance Science Visualisation (2019–2025) and Drawing Science Diagrams to Enhance Scientific Creativity (2018–2025). Her work supports students, teachers, and early-career researchers, aligning with the UN Sustainable Development Goal for Education. PhD, University of Illinois at Urbana-Champaign: Inquiry-based science education via Dewey’s theory of inquiry Her research focuses on: Dialogic teaching to foster student reasoning Student-generated diagrams for conceptual understanding VR for visualizing complex science topics Generative AI in science learning Creative and critical thinking in science education Recent articles span VR applications, AI in physics education, collaborative drawing techniques, and curriculum-aligned creative pedagogy. Awards include the Most Valuable Paper Award 2024 for her work on enzyme-substrate interactions in VR. She serves on the advisory board for Chemistry Education Research and Practice and the editorial board of the International Journal of Science Education .
Chris Speed is a Professor of Design for Regenerative Futures at RMIT University, Australia, and Director of Regenerative Futures. Previously, he held academic roles at the University of Edinburgh, including leading the Institute for Design Informatics and co-designing the Edinburgh Futures Institute. His research focuses on design-driven solutions for social, environmental, and economic challenges, leveraging data and emerging technologies. Key areas include blockchain applications, sustainable design, and regenerative systems. Affiliations: RMIT University (Current), University of Edinburgh (2012–2024) Grants: £7.4m Creative Informatics (UK), £5m DECaDE (Digital Economy) Publications: Over 50 peer-reviewed articles on design informatics, regenerative futures, and blockchain ethics. Research interests span Design Informatics, Human-Computer Interaction, and Sustainable Design. He has supervised 23 PhD/MPhil students and pioneered projects like OxChain (blockchain for charitable giving) and Creative Informatics (data-driven creative industries). Awards: Fellow of the Royal Society of Edinburgh (2020), Chancellor’s Award for Research (University of Edinburgh, 2020). Collaborations include BBC, Oxfam, and the Digital Catapult. His work emphasizes co-creation with communities to address systemic challenges, such as climate action and cultural value measurement.
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.
Richard Zemel is a Professor in the Department of Computer Science at the University of Toronto, where he has been since 2000. He holds an Industrial Research Chair in Machine Learning and co-founded the Vector Institute for Artificial Intelligence. His research focuses on machine learning, including unsupervised learning, deep learning, and ethical AI, with contributions to probabilistic models, fairness, and representation learning. Zemel has developed influential systems like the Toronto Paper Matching System and holds awards such as the NVIDIA Pioneers of AI Award and multiple NSERC grants. Education: B.Sc. in History & Science from Harvard University (1984), Ph.D. in Computer Science from the University of Toronto (1993). Postdoctoral work at the Salk Institute and Carnegie Mellon University. Research Interests: Machine Learning (unsupervised/deep learning), probabilistic models, fairness in algorithms, computer vision, natural language processing. He emphasizes ethical AI and practical applications like recommendation systems and causal inference. Awards & Affiliations: Fellow of CIFAR, member of the Neural Information Processing Society (NIPS) Executive Board, and advisor to the Creative Destruction Lab. His work is funded by NSERC, CIFAR, Google, Microsoft, and DARPA. Grants & Labs: Active in grants supporting machine learning research, including projects on fairness and invariant learning. Collaborates with industry partners and leads teams at the University of Toronto and Vector Institute.
Sebastian Pokutta is a Professor at Technische Universität Berlin, Vice President at the Zuse Institute Berlin (ZIB), and Chair of the Cluster of Excellence MATH+ and MODAL. His research lies at the intersection of Artificial Intelligence, Optimization, and Machine Learning, with applications in sustainability, quantum computing, and mathematical discovery. Research Interests: Development of novel optimization algorithms, particularly Frank-Wolfe and Conditional Gradient methods. Integration of machine learning with decision-making and combinatorial optimization. AI for Science (AI4Science), including applications in quantum mechanics and ecology. AI and creativity, human-AI co-creativity, and social science modeling using multi-agent LLMs. His recent publications (2025) demonstrate a strong focus on scalable optimization, interpretability, and algorithmic foundations. The work spans theoretical advances in convergence analysis, practical implementations in Julia (FrankWolfe.jl), and real-world deployments in biomass estimation and quantum certification. Scientific Awards: Gödel Prize (2023) STOC Test of Time Award (2022) Science Prize of the Association for Pediatric Orthopedics (2025) Google Research Awards (2021, 2020) NSF CAREER Award (2015) He advises a vibrant research group, with former students and postdocs securing faculty positions at institutions like Inria, Carlos III University, and James Madison University. His group has received funding from Google, DFG, and Math+, and he leads major collaborative efforts such as the Thematic Einstein Semester on Mathematical Optimization for Machine Learning. Labs and Teams: Interactive Optimization and Learning Lab at TU Berlin and ZIB. Leadership in MODAL and MATH+ research clusters, fostering interdisciplinary collaboration in mathematical optimization and AI.
Dongming Xu is an Associate Professor in Business Information Systems at the University of Queensland Business School. She holds a PhD from the City University of Hong Kong in Information Systems and has established herself as a prominent researcher in the field of information systems with over 100 publications in top-tier journals and conference proceedings. Her educational background includes a PhD from City University of Hong Kong in Information Systems, though specific details about earlier degrees are not provided in the available text. Dr. Xu's research focuses on the confluence of information technology use and innovation, with particular emphasis on IT entrepreneurship, social media applications in business contexts, and business intelligence systems. Her work explores how information systems influence society and business performance, with applications spanning disaster management, eFinance, eHealth, and knowledge management. She combines theoretical model building with laboratory and field experiments, often developing prototype systems to validate her research. Her publication record demonstrates consistent high-quality output across multiple domains of information systems research, with recent work emphasizing digital disruption, platform ecosystems, social media in disasters, healthcare technology, and micro-learning applications. Her research shows a clear trajectory from foundational work on intelligent agents and decision support systems toward contemporary topics in digital transformation and platform-based innovation. Associate Editor, Information & Management Associate Editor, Journal of Electronic Commerce Research Associate Editor, Australasian Journal of Information Systems Dr. Xu has supervised numerous PhD students to completion, with research topics spanning digital disruption, IT startup development, social media in disasters, conceptual modeling, and environmental management. She has received multiple research grants, including current funding for 'Empowering Australia's Visual Arts via Creative Blockchain Opportunities' (2023-2026) and past projects on 'Smart micro learning with open education resources' (2018-2022). Her research has been supported by various agencies including the Hong Kong Government Research Grant Council, The National Natural Science Foundation of China, The University of Queensland, and City University of Hong Kong. She leads research in several key areas including IT entrepreneurship, business intelligence systems, and social media applications across multiple domains. Her work often involves developing innovative systems such as web-service-agent-based family wealth management systems, decision support systems for securities exception management, and knowledge management systems for disaster management.
Yan Huang is an Associate Professor of Business Technologies at the Tepper School of Business, Carnegie Mellon University. She holds a Ph.D. in Information Systems and Management from Carnegie Mellon University (2013) and a B.Sc. (with honors) in Information Systems and Management from Tsinghua University, Beijing, China (2009). Prior to joining Carnegie Mellon University, she served as an Assistant Professor of Technology and Operations at the University of Michigan–Ann Arbor, Ross School of Business (2013-2018). Her educational background includes: B.Sc. (with honors) in Information Systems and Management, Tsinghua University, Beijing, China (2009) Ph.D. in Information Systems and Management, Carnegie Mellon University, Pittsburgh, United States (2013) Dr. Huang's research examines the economic and social impacts of technologies and identifies effective designs and policies for technology-enabled markets and platforms. She employs economic theories, structural modeling, statistical modeling, machine learning methods, and an understanding of the underlying technologies in her research. Her recent work focuses on the economics of artificial intelligence (AI) and machine learning (ML), with particular attention to algorithmic fairness, transparency, and collusion. She is among the first to bring economic and social perspectives to research on fair ML. Additionally, she studies digital platforms and online markets, examining how firms can leverage data-driven strategies to optimize pricing, personalization, and user engagement. Her recent publications demonstrate a strong focus on the intersection of AI/ML with economic principles, particularly in areas like algorithmic bias, pricing strategies, and platform regulation. A significant portion of her work examines how machine learning algorithms impact financial lending decisions, housing markets, and content creation platforms. Her research methodology frequently combines structural econometric modeling with empirical analysis of real-world data, providing both theoretical insights and practical implications for platform design and policy. Dr. Huang has received several prestigious awards for her scholarly contributions: AIS Senior Scholar Best Publication of 2023 Award for "Algorithmic Transparency with Strategic Users" Runner Up, Best Paper Published in Information Systems Research for 2021 for "Crowds, Lending, Machine, and Bias" INFORMS Information Systems Society Sandy Slaughter Early Career Award Finalist, Best Student Paper Award, CIST 2021 for "Human-Algorithmic Bias: Source, Evolution, and Impact" Pounds Fellowship As an active member of the academic community, Dr. Huang serves on various committees at CMU including the MSBA Curriculum Review Committee and the Tepper School Strategic Plan Task Force. She has also held editorial positions for Management Science, Information Systems Research, and the International Conference on Information Systems. Her teaching portfolio includes courses on Human and Algorithmic Bias, Modern Data Management, and PhD-level instruction at the Tepper School.
Professor Kylie Peppler is a dual Professor of Informatics and Education at the University of California, Irvine, leading the Creativity Labs and the Connected Learning Lab. Her research focuses on leveraging hands-on creativity—such as e-textiles, robotics, and traditional fiber crafts—to enhance STEM education, particularly for marginalized populations. She emphasizes the role of materiality in fostering systems thinking and equity in learning environments. Education: PhD in Education (UCLA), Postdoctoral training at UC Irvine, and prior roles at Indiana University. Her academic journey bridges psychology, art, and technology. Research Interests: Maker culture, computational thinking, STEAM integration, workforce development, and the impact of arts in education. She explores how tools like e-textiles and looms democratize access to STEM while addressing gender disparities. Key Projects: NSF-funded work on computational construction kits, Re-Crafting STEM initiatives, and Future of Work research using AR/VR for manufacturing training. Collaborations include Boeing, Inner-City Arts, and NYSCI. Awards: NSF Early CAREER Award, Mira Tech Educator of the Year, and Indiana Governor's Award. Her work is supported by NSF, Wallace Foundation, and industry partners. Grants & Labs: Over $10M in grants; directs labs advancing connected learning and equity through technology. Recent studies include virtual reality welding simulators and culturally sustaining arts practices. Labs/Teams: Creativity Labs (designing maker tools), Connected Learning Lab (digital equity), and partnerships with museums and industry to scale inclusive learning.
Steven Devleminck is an Associate Professor in the Department of Computer Science at KU Leuven's Faculty of Engineering Technology, concurrently serving as coordinator of the School of Arts (Associated Faculty) in Brussels. His dual appointment bridges engineering and arts through the Human-Computer Interaction (HCI) group at Group T Leuven Campus and Unit Art & Technology in Brussels, with active membership in DigiSoc – KU Leuven Digital Society Institute. His research centers on human-centered computing and speculative design methodologies , with core expertise in tangible interaction for emotion regulation and multispecies futures. Key themes include biofuturing as co-creative response to climate crises, squeeze-based interfaces for workplace stress, and artistic AI collaborations. His work uniquely integrates computer science with choreography, film studies, and anthropology through projects like “Youth TikTok production as public pedagogy” and “Imagining the Post-Anthropocene in BioFutures Living Lab”. Analysis of recent publications reveals three dominant trajectories: (1) Advancement of squeeze interaction techniques for affective computing, (2) Development of biofuturing frameworks for multispecies speculation, and (3) Critical examinations of AI's role in artistic mediumship. Cross-cutting themes include post-anthropocentric design, climate-responsive technologies, and decolonial approaches to digital pedagogy. Devleminck actively mentors doctoral candidates including Ula Sickle (choreographic exhibitions) and J. Verbesselt (cinema studies), while leading major funded projects such as: Living Corpora (2025-2029): Pioneering human-AI collaboration in digital humanities as Co-promotor Experiential Futuring (2022-2026): Co-creative methodology for social media outage response as Co-promotor Deradicalizing the City (2021-2025): Urban intervention research as Promotor He serves on the Computer Science Department Council and Doctoral Committee for the Associated Faculty of Arts. His laboratory ecosystem spans the HCI Group T Leuven Campus for technical development, Brussels-based Unit Art & Technology for artistic integration, and BioFutures Living Lab for participatory multispecies experimentation. This tripartite structure enables transdisciplinary work connecting squeeze sensor engineering with climate futures speculation and museum interface design.
Maria K. E. Lahman is a Professor in the Department of Applied Statistics and Research Methods within the College of Education and Behavioral Sciences at the University of Northern Colorado. She holds a Ph.D. in Child Development from Virginia Polytechnic Institute and State University (2001) and serves as Co-Chair of the Institutional Research Board at UNC. Her academic work bridges qualitative methodology with ethical research practices and creative representation. Dr. Lahman's research focuses on culturally responsive qualitative research, research ethics, early childhood education, and the aesthetic representation of research through poetry and other creative forms. Her scholarship addresses creating ethical solutions for culturally complex methodological situations, diversity issues, young children, mothering experiences, and qualitative writing representation. As a Mennonite, she integrates social justice and peacebuilding into her pedagogy and scholarship. Her recent publications show a clear trajectory toward innovative research representation, with a particular emphasis on research poetry and culturally responsive methodologies. The 15 most recent articles reveal a consistent focus on ethical research practices, creative representation forms, and culturally responsive approaches to qualitative inquiry, with increasing attention to poetry as a legitimate research method and representation form. Outstanding Advisor Award, College of Education and Behavioral Sciences, UNC (2008-2009) Outstanding Scholar Award, College of Education and Behavioral Sciences, UNC (2007-2008) Service Provider Award, University of Northern CO (2006-2007) Outstanding Teacher Award, College of Education, UNC (2002-2003) Dr. Lahman has advised numerous graduate students in qualitative methodology and has been recognized for her exceptional mentorship. Her research program has generated multiple textbooks including Ethics in Social Science Research: Becoming Culturally Responsive (2017) and Writing and Representing Qualitative Research (2021), which have become influential resources in the field. She maintains an active research agenda focused on advancing ethical research with diverse groups and developing innovative methods for representing qualitative findings. Her work centers around creating spaces for culturally responsive research practices, with particular attention to vulnerable populations and ethical dilemmas in fieldwork. Dr. Lahman's scholarship challenges traditional research boundaries through her exploration of research poetry and other aesthetic forms of representation that maintain academic rigor while embracing creative expression.
Claire O'Brien is a Senior Lecturer in Computer Animation at Teesside University, affiliated with the Department of Digital Arts and Animation within the School of Computing, Engineering & Digital Technologies. She serves as Course Leader for the MA Animation program and coordinates Animex Screen, the international student film festival linked to the annual Animex event. Her academic journey includes roles at Northumbria University and South Tyneside College before returning to Teesside in 2022. Education: Bachelor of Fine Art (Painting and Printmaking), University of East London, 1997 Post-Graduate Diploma in Arts Management, Northumbria University, 2000 Master of Computer Animation, Teesside University, 2005 Postgraduate Certificate in Teaching and Learning in Higher Education (PgCTLHE), Teesside University, 2024 Fellow of Advance Higher Education (FHEA), awarded November 2024 Claire's research focuses on Animation Studies , Immersive Technologies (AR/VR/MR) for education, healthcare, and industrial training, Full-dome 360 filmmaking , and pedagogical innovation in digital arts. Her recent work explores how animated visualizations in film convey complex information through interfaces like HUDs and holograms, and how animation functions in public and cultural spaces such as cruise ships and heritage exhibitions. Her recent publications from 2023–2024 demonstrate a consistent engagement with animation as a tool for communication, cultural storytelling, and technological critique. Themes include representational vehicles, folklore in digital art, and the integration of generative AI in creative processes, particularly in health awareness contexts like menopause support. Scientific Awards and Recognitions: Fellow of Advance Higher Education (FHEA), 2024 Postgraduate Certificate in Teaching and Learning in Higher Education, Teesside University, 2024 Claire leads the MenopauseXR project funded by Innovate UK (2024–2025), which investigates the use of Generative AI and Extended Reality to support menopause awareness and education. She has no listed formal students, but her role as course leader and lecturer implies significant student mentorship. Her enterprise activity includes participation in the XR Stories XR Accelerator in 2024, focusing on commercializing mobile augmented reality research. Claire is actively involved in Animex , a major animation and games festival, where she coordinates Animex Screen. She also collaborates with cultural institutions such as the National Trust , having contributed animation and prints to the exhibition "Washington: Fact, Fiction and Folklore." Her work bridges academia, creative practice, and public engagement.
Stéphane Doncieux is a University Professor in Computer Science at Sorbonne University, where he is affiliated with the Institute of Intelligent Systems and Robotics (ISIR), a joint research laboratory with CNRS. Since January 2024, he has served as Director of ISIR, following a term as Deputy Director from 2019 to 2023. He leads the ASIMOV research team and is based at the Pierre and Marie Curie Campus in Paris. His primary research interests lie in cognitive and developmental robotics, with a strong focus on open-ended learning, evolutionary algorithms, and adaptive systems. He investigates how robots can autonomously learn diverse skills through mechanisms such as novelty search, quality-diversity optimization, and intrinsic motivation. His work bridges theoretical foundations in artificial life and practical applications in robotic manipulation, perception, and control. The recent publications highlight a consistent trend in advancing robotic learning under sparse rewards and in open-ended environments. Key themes include quality-diversity optimization for grasping, state representation learning, sim-to-real transfer, and the development of behavioral repertoires. These works are published in high-impact journals such as IEEE Transactions on Robotics, Evolutionary Computation, and Frontiers in Robotics and AI. Coordinator, DREAM FET H2020 project (2015–2018) Principal Investigator, ANR projects on Creative Adaptation by Evolution, Learning Movement Skills, and Grasping with Multimodal Feedback Involved in European initiatives including VeriDREAM and HumanE-AI-Net He has supervised numerous PhD and Master’s students, including Leni Le Goff, Giuseppe Paolo, Alban Laflaquière, and Achkan Salehi, often in collaboration with leading researchers like Olivier Sigaud and Jean-Baptiste Mouret. He teaches computer science and robotics at both undergraduate and graduate levels at Sorbonne University. Doncieux has been instrumental in shaping research directions in evolutionary and developmental robotics, notably through his leadership in the IEEE Task Force on Evo-Devo-Robotics and his editorial contributions. His lab, ASIMOV, fosters interdisciplinary research integrating computer science, neuroscience, and engineering to create more autonomous and intelligent robotic systems.
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.
