Wojciech Matusik is a Professor of Electrical Engineering and Computer Science at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). He leads the Computational Design and Fabrication Group and is a member of the Computer Graphics Group. His research spans computer graphics, robotics, and AI-driven manufacturing, with a focus on computational design, tactile sensing, and material science. Matusik holds a PhD in Computer Science from MIT (2003), an MS from MIT (2001), and a BS from UC Berkeley (1997). His work includes groundbreaking projects like differentiable cloth simulation (DiffCloth), AI-enhanced molecular design, and tactile sensing gloves. He has received prestigious awards such as the MIT TR35 (2004), DARPA Young Faculty Award (2012), and Ruth and Joel Spira Teaching Award (2014). Matusik teaches courses on computer graphics, machine learning, and computational fabrication at MIT. Key research themes include: Robotics: Robotic assembly, tactile interaction, and soft robotics Graphics: 3D holography, procedural material generation Manufacturing: Additive fabrication, topology optimization His recent articles explore AI-driven molecular synthesis, holographic displays, and tactile-enabled VR systems. Matusik collaborates on open-source tools like the WiReSens tactile platform and Simit language for sparse systems.
James McCann is an Associate Professor at the Carnegie Mellon Robotics Institute, where he leads the Carnegie Mellon Textiles Lab. He has been a faculty member since May 2017 after working at Disney Research Pittsburgh. McCann's academic journey includes a PhD from Carnegie Mellon advised by Nancy Pollard, followed by a postdoc at Adobe Research and a period developing video games. McCann's research focuses on building creative tools that operate in real-time and build user intuition, with particular emphasis on textiles fabrication and machine knitting. His work spans computer-aided fabrication, simulation, graphics, and creative tools development. He has pioneered systems for machine knitting design, including compilers for knitting instructions and tools for automatic conversion of 3D meshes to knitting patterns. His recent publications demonstrate a strong trend toward computational textiles, with significant contributions to knitting semantics, deployable textile structures, and applications of machine knitting in healthcare and robotics. McCann's work bridges computer science, robotics, and textile arts, creating practical systems for once-off manufacturing with industrial knitting machines. McCann actively mentors students, with current PhD candidates working on solid knitting machines, knit calibration, and assistive devices. His teaching portfolio includes courses on Real-Time Graphics, Algorithmic Textiles Design, and Game Programming. He has taught at CMU since 2017, developing innovative courses that blend computer science with physical fabrication. As director of the Textiles Lab, McCann oversees research projects spanning machine knitting, robotic painting, and real-time graphics systems. His lab develops practical tools for creators, emphasizing intuitive interfaces and real-time feedback that lower barriers to advanced fabrication techniques.
Adriana Schulz is an Assistant Professor in the Department of Computer Science & Engineering at the University of Washington's College of Engineering. She leads a research group focused on computational design, computer-aided design (CAD), and digital fabrication. Her work bridges computer science with practical applications in manufacturing, robotics, and sustainable design. Dr. Schulz received her Ph.D. in Computer Science from MIT in 2018 under the supervision of Professor Wojciech Matusik. Prior to her doctoral studies, she earned a Master's degree in Mathematics from IMPA (Instituto Nacional de Matemática Pura e Aplicada) in Rio de Janeiro, where she worked with Professor Luiz Velho, and a Bachelor's degree in Electronics Engineering from UFRJ (Federal University of Rio de Janeiro). Her research interests center around computational tools that enhance design and manufacturing processes. She develops novel algorithms for CAD systems, computational fabrication techniques, and sustainable design approaches. Her work spans multiple domains including robotics, textiles, electronics, and architecture, with a strong emphasis on creating practical tools that designers and engineers can use in real-world applications. She explores how machine learning, particularly neurosymbolic approaches, can improve design workflows and enable new capabilities in computational design systems. Analysis of her recent publications reveals a strong trend toward more intelligent and user-centered design tools. Her research increasingly integrates machine learning with traditional CAD systems to create more intuitive interfaces, supports sustainable design practices with computational tools, and develops novel fabrication techniques that push the boundaries of what's possible with digital manufacturing. She has made significant contributions to zero-waste fashion design, immersion cooling for high-performance computing, and CAD program understanding through novel representation learning techniques. Innovators Under 35 - MIT Technology Review Bolsa Aluno Nota 10 from FAPERJ Engineer 20000 award Dr. Schulz actively mentors several PhD students and postdoctoral researchers, including Haisen Zhao, Ben Jones, Yuxuan Mei, and others, often in collaboration with colleagues across different departments. Her research has attracted significant media attention, with coverage in major outlets including MIT News, BBC, IEEE Spectrum, Wired, and TechCrunch. Her work on Interactive Robogami was noted as the most read article in the International Journal of Robotics Research in its publication year. She leads a vibrant research group at the University of Washington that focuses on computational design systems, with particular emphasis on creating tools that bridge the gap between digital design and physical fabrication. Her team develops novel algorithms for CAD systems, computational fabrication techniques, and sustainable design approaches that have practical applications across multiple industries.
Stefanie Mueller is the TIBCO Career Development Associate Professor at MIT's Electrical Engineering and Computer Science Department, with joint affiliation in Mechanical Engineering. She leads the HCI Engineering Group at the Computer Science and Artificial Intelligence Laboratory (CSAIL), focusing on advancing fabrication techniques through hardware/software innovations that enable novel object interactions. Develops computational fabrication methods combining photochromic dyes, lenticular lenses, birefringent materials, and optical illusions Co-chaired ACM CHI 2023 and ACM UIST 2020 program committees Recipients of 9 MIT EECS Best Undergraduate Researcher Awards among mentees Her research spans four key directions: Appearance-changing Objects: Photo-Chromeleon (ACM UIST 2019), Lenticular Objects (ACM UIST 2021), and Polagons (ACM CHI 2023) demonstrate reprogrammable surfaces through advanced materials and optical engineering. Tracking Systems: InfraredTags (ACM CHI 2022) and G-ID (ACM CHI 2020) enable passive object tracking via infrared markers and slicing artifacts. Embedded Sensing: MechSense (ACM CHI 2023) and Sprayable User Interfaces (ACM CHI 2020) integrate sensing capabilities into complex geometries. Curved Surface Prototyping: FlexBoard (ACM CHI 2023) and CurveBoard (ACM CHI 2020) develop specialized tools for non-planar electronics. Her recent publications focus on functionality segmentation (UIST 2023), fluorescent markers (UIST 2023), and machine-knitted haptics (UIST 2023). These works combine machine learning, material science, and interactive design principles to push fabrication boundaries. Scientific recognition includes: 2022 MIT Technology Review Innovators Under 35 2020 Microsoft Research Faculty Fellowship 2020 Alfred P. Sloan Research Fellowship 2019 ACM UIST Best Paper Award 2019 NSF CAREER Award 2018 MIT EECS Outstanding Educator Award 2017 Forbes 30 Under 30 in Science Mentoring 9 PhD students and over 20 master's students, her lab has produced 20+ publications at top HCI conferences. She redesigned MIT's 6.810 Engineering Interactive Technologies course during the pandemic, maintaining hands-on learning through home electronics kits and Slack-based collaboration.
Sara Nabil is an Assistant Professor at Queen's University's School of Computing within the Faculty of Arts and Science. She leads the HCI Design Studio and previously held a postdoctoral position at Carleton University's Creative Interactions Lab. Her research focuses on integrating interior design, fashion, and product design with interactive technologies, emphasizing e-textiles, smart materials, and shape-changing interfaces. She holds a PhD from Newcastle University and prior experience as an HCI Lecturer, interior designer, and senior software developer. Education: PhD in Computing, Newcastle University (2019) MSc in Computing BSc in Computing Research interests include designing computational spaces, wearable technology, and e-textile interactions. Her work explores sustainable fabrication methods, user-centered design for smart environments, and bridging traditional crafts with digital technologies. Notable projects include exhibitions like 'Living with Adaptive Architecture' and 'Persuasive Pharmacy Space,' showcasing interactive wearables and spaces. Her recent articles (2023–2025) emphasize e-textile innovations, sustainable design, and human-building interactions. Key themes include smart materials in fashion, modular wearables, and community-driven interaction systems. Awards: None explicitly mentioned. Advising/Grants: No details provided. Labs/Teams: Head of HCI Design Studio and part of iStudio Lab, focusing on interioraction design.
Helder Carvalho is an Associate Professor at the University of Minho's School of Engineering, Campus de Azurém, where he also serves as Director of the Department of Textile Engineering and Director of the Master's program in Textile and Accessories Product Design and Innovation. His academic career spans over three decades, with a focus on textile engineering and its intersection with electronics and automation systems. His educational background includes: PhD in Textile Engineering (2004) from University of Minho, School of Engineering MSc in Textile Engineering (1998) from University of Minho, School of Engineering BSc in Electrotechnical and Computer Engineering (1992) from University of Porto, Faculty of Engineering Professor Carvalho's research primarily focuses on smart textiles, textile sensors, and instrumentation systems for industrial sewing machines. His work bridges the gap between traditional textile manufacturing and modern electronics, creating innovative solutions for interactive textiles and wearable technology. He has particular expertise in developing flexible sensors that can be integrated into fabrics for applications ranging from sports performance monitoring to healthcare. His recent publications demonstrate a strong trend toward sports applications of smart textiles, with numerous papers on fencing apparel, karate body protectors, and general athletic performance monitoring. The research spans material science, sensor development, and user experience design, showing a comprehensive approach to creating functional and attractive smart textile products. Professor Carvalho has received recognition through research funding from major institutions: BE@T Bioeconomy Textile and Clothing (current) Greenauto - Green Innovation for the Automotive Industry (current) Factor ST+ (2021-2023) FAMEST (2017-2020) TSSIPRO (2016-2019) He has directed multiple academic programs including the Master's in Textile and Accessories Product Design and Innovation, and coordinated educational initiatives like the CET 'Fashion Commerce' program. His work at the Textile Science and Technology Centre demonstrates a commitment to translating research into practical applications across sports, healthcare, and industrial manufacturing sectors.
Emily Whiting is an Associate Professor of Computer Science at Boston University and Director of the Shape Design & Computation Lab. She also serves as Director of PhD Admissions and Co-Director of the BU Computer Graphics Lab. Her research focuses on computational fabrication, architectural geometry, and computer-aided design, bridging digital geometry processing, engineering mechanics, and rapid prototyping. She holds a PhD from MIT (2012), an SM in Design & Computation from MIT (2006), and a BASc in Engineering Science from the University of Toronto (2004). Previously, she was faculty at Dartmouth and a Marie Curie Postdoctoral Fellow at ETH Zurich. Her research interests include 3D printing optimization, structural design for fabrication, and tools for functionally-valid object creation. Notable projects include work on elastic garments, climbing experience replication, and print-wind instrument design. Her work has been featured on TEDx and PBS NOVA, and she has received awards such as the NSF CAREER Award and Sloan Research Fellowship. Education: PhD (MIT), SM (MIT), BASc (University of Toronto) Labs: Shape Design & Computation Lab, BU Computer Graphics Lab Key Projects: Knitting 4D garments, Environment-Scale Fabrication, Thermal-comfort casts Recent professional activities include program committee roles at SIGGRAPH 2025 and UIST 2024, and serving as Program Co-Chair for Pacific Graphics 2024. She advises a team of PhD and MS students, with alumni now in academia and tech industries.
David E. Breen is a Professor in the Department of Computer Science within the College of Computing & Informatics (CCI) at Drexel University. He leads the Geometric Biomedical Computing Group and is affiliated with the Metadata Research Center and the Center for Biological Discovery from Big Data. His research spans interdisciplinary domains including biomedical image informatics, geometric modeling, textile modeling, and bio-inspired self-organization algorithms. Education: PhD, Computer and Systems Engineering, Rensselaer Polytechnic Institute MS, Computer and Systems Engineering, Rensselaer Polytechnic Institute BA, Physics, Colgate University His research interests focus on computational methods for biomedical applications, including shape and image analysis for cancer diagnosis, 3D reconstruction of biological tissues, and video analysis of animal behavior. He also investigates geometric modeling techniques for textiles and self-organizing systems. His work integrates computer science with biology, medicine, and engineering to solve complex problems in biomedical computing. The recent publications highlight a strong trend in computational modeling of textiles, biomedical image informatics, and AI-driven data analysis. Key themes include geometric modeling of knitted fabrics, deep learning for medical image classification, agent-based modeling of cancer metastasis, and metadata generation for biological image collections. His work bridges fundamental geometric algorithms with practical applications in healthcare and digital archives. Scientific Awards: No specific awards mentioned in the provided text. Breen has advised numerous students and collaborators across multiple domains, particularly in biomedical computing and textile modeling. His research has been supported through affiliations with major centers and collaborations with institutions such as Johns Hopkins University and the Max Planck Institute. He has been involved in projects related to NSF Center for Visual & Decision Informatics and has contributed to over 100 technical publications. He leads the Geometric Biomedical Computing Group , which conducts research at the intersection of biology, medicine, engineering, and computer science. The group develops algorithms and software for geometry-related computing problems in biomedical applications. Collaborations include the Drexel Integrated Laboratory for Cellular Tissue Engineering, Dr. Dan Marenda's Lab, and Dr. Aleister Saunder's Lab in Drexel's Biology Department.
Dr. Bai Ziqian is an Assistant Professor in the School of Automation and Intelligent Manufacturing at Southern University of Science and Technology (SUSTech) in Shenzhen, China. Recognized as a Pujiang Scholar and Shenzhen Pengcheng Peacock Talent, she has established herself as a leading researcher at the intersection of wearable technology, textile engineering, and human-computer interaction. Her work bridges technical innovation with practical design applications, focusing on user-centered solutions that enhance human experience through technology integration. Dr. Bai's educational background includes: PhD in Smart Wearable Product Design (2011-2015), Hong Kong Polytechnic University MA in Fashion and Textile Design (2005-2006), Hong Kong Polytechnic University BA in Fashion Design and Engineering (2001-2005), South China Agricultural University Her research spans wearable technology, tangible interactive interfaces, IoTs, ergonomics, functional garments, wearables for healthcare, material innovation, smart home applications, and user-centered design. Dr. Bai has pioneered work in smart wearable fabrics and sensing mechanisms based on flexible materials, with a particular focus on human-computer interaction theory and practice. She has established a research team that has mastered key technologies in smart fabrics, interactive textiles, physiological signal monitoring, and human-computer interaction systems. Her approach consistently emphasizes user-centered design principles, ensuring that technological innovations serve practical human needs while maintaining aesthetic appeal. Dr. Bai's publication record demonstrates a clear evolution from foundational work in photonic textiles toward increasingly sophisticated wearable healthcare and human-computer interaction systems. Her recent publications focus on advanced sensor technologies, energy harvesting for wearables, and sophisticated data analysis for human motion and physiological monitoring. The interdisciplinary nature of her work is evident in publications spanning materials science, biomedical engineering, textile technology, and design methodology, with papers appearing in high-impact journals including Advanced Functional Materials (IF: 19.5), ACS Sensors (IF: 8.9), and Computers in Industry (IF: 10). Dr. Bai has received numerous prestigious awards that highlight both the technical and artistic dimensions of her work: 2024 German Red Dot Design Award for Best Design 2013 Neo-Neon, permanent collection at China Silk Museum (State grade 1 museum) 2019 Finalist, ThermoBlanket, TechStyle for Social Good International Competition 2017 1st Prize Teaching Award, Donghua University 2017 China National Textile and Apparel Council Teaching Award Multiple Service Learning Awards from Hong Kong Polytechnic University She has successfully secured research funding from prestigious sources including the National Natural Science Foundation of China and Guangdong Province's General Project. Her projects include a collaborative effort with the Guangdong Provincial Department of Education and Li Ning Company on a 'flexible wearable lower limb functional electrical stimulation system.' Dr. Bai has extensive teaching experience across multiple institutions and has guided student teams to success in national competitions. She currently leads the Human-Computer Interaction Design Laboratory (HCID) at SUSTech, which focuses on advanced design, engineering, and technology research at the intersection of disciplines, training the next generation of interdisciplinary designers and engineers.
Megan Hofmann is an Assistant Professor holding dual roles at Northeastern University's Khoury College of Computer Sciences and the Department of Mechanical and Industrial Engineering (College of Engineering). She earned her PhD in Human-Computer Interaction from Carnegie Mellon University in 2022. Her research focuses on accessibility and digital fabrication, particularly in healthcare contexts, including automated machine knitting and medical making. She leads the Accessible Creative Technologies (ACT) Lab, which develops tools like Maptimizer (custom tactile maps), OPTIMISM (collaborative optimization frameworks), and KnitGIST (generative knitting design). Her work addresses challenges in assistive technology fabrication, such as creating accessible medical devices and optimizing rapid prototyping in healthcare. Recent projects include NSF-funded research on interactive smart textiles and studies on distributed manufacturing during the COVID-19 pandemic. Hofmann’s contributions span interdisciplinary domains, blending computer science, mechanical engineering, and healthcare innovation. Grants & Awards: Recipient of a $550,000 NSF grant for smart textile tools (2024). Labs: ACT Lab focuses on inclusive digital fabrication systems.
Katia Bertoldi is the William and Ami Kuan Danoff Professor of Applied Mechanics at Harvard University's John A. Paulson School of Engineering and Applied Sciences . She leads the Bertoldi Group: Solid Mechanics , focusing on mechanical metamaterials, multistable systems, and soft robotics. Her work integrates applied mathematics, materials science, and nonlinear dynamics to design architected materials with programmable properties. Research interests include: Mechanical metamaterials with tunable properties Multistable structures for energy absorption and reprogrammability Soft robotics leveraging origami/kirigami principles Machine learning-driven design of complex materials Recent work emphasizes reprogrammable systems (e.g., magnetic and thermal actuation) and textile-based metamaterials for wearable applications. Her team collaborates across disciplines, addressing challenges in biomedical devices, robotics, and sustainable manufacturing. Key contributions include: Developing metafluids with programmable shell instabilities Designing inflatable origami actuators for meter-scale reconfigurable structures Creating knitted fabrics with tunable mechanical responses Her lab explores energy-efficient actuators, adaptive fluid networks, and AI-driven material discovery, aiming to bridge theory and real-world applications.
Lee Su-hyeon is an Assistant Professor at the Department of Clothing and Textiles in Seoul National University's College of Human Ecology . Previously, she served at Jeonbuk National University (2021-2023) and conducted postdoctoral research at the Korea Institute of Industrial Technology (2018-2021). Her work focuses on smart textiles , superhydrophobic materials , and conductive fabrics for wearable technology. Ph.D. (2018), Seoul National University M.Sc. (2012), Seoul National University B.Sc. (2009), Ewha Womans University Research interests include: Surface chemistry of textiles Water-repellent fabric structures Conductive yarn blending Metal-organic framework coatings E-textile manufacturing automation Thermo-electric clothing systems Her 15 most recent publications (2018-2023) demonstrate expertise in superhydrophobic polyester films , smart sports bras , MIL-100(Fe) cotton coatings , and carbon nanotube composites . Key trends show integration of conductive materials with environmental sustainability approaches. Scientific recognition includes: 2022 FTEX Best Reviewer Award 2021 Korea Fashion Business Association New Researcher Award Multiple Korean Society of Clothing and Textiles presentation awards (2013-2018) Lectures on undergraduate courses: Basic chemistry of clothing materials , Clothing material composition , Cleaning principles . Graduate courses: New clothing materials , Textile physics , Smart fabric evaluation .
Noeska Smit is a Professor in Medical Visualization at the Department of Informatics, University of Bergen , where she has held a tenure-track position funded by the Trond Mohn Foundation since 2017. She is also a senior researcher and member of the leadership team at the Mohn Medical Imaging and Visualization (MMIV) Centre . Her research focuses on novel interactive visualization techniques for exploring and communicating multimodal medical imaging data , particularly in multi-parametric MR acquisitions . She leads projects in gynecologic cancer imaging , Multiple Sclerosis neuroimaging , and human anatomy education through collaborations with institutions like UGent (Belgium) and HVL. 2019: Dirk Bartz Prize for Visual Computing in Medicine 2016: PhD at Delft University of Technology , Netherlands 2012: MSc in Computer Science (Computer Graphics & Visualization) , Delft University Recent publications highlight her work in MRI radiomics , narrative visualization , open-source anatomy platforms , and interactive clustering tools for tumor analysis. Her methods are applied in oncological pelvic surgery planning , neurological disease monitoring , and 3D learning environments . She supervises PhD candidates Eric Mörth and Sherin Sugathan , and has contributed to open-source medical visualization tools like RegistrationShop and Online Anatomical Human (OAH) . Her work bridges clinical practice and computer science through collaborations with radiologists, surgeons, and ML researchers.
Meghan Huber is an Adjunct Assistant Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst and director of the Human Robot Systems Laboratory. She holds a B.S. in Biomedical Engineering from Rutgers University (2009), an M.S. in Biomedical Engineering from the University of Texas at Dallas (2011), and a Ph.D. in Bioengineering from Northeastern University (2016). Her postdoctoral research was conducted at MIT's Department of Mechanical Engineering (2016-2020), and she was a Visiting Junior Scientist at the Max Planck Institute for Intelligent Systems (2014). Her research focuses on Robotics, Computer Vision, and Human-Computer Interactions, with emphasis on gait adaptation, robotic exoskeletons, and biomechanical systems. Recent work explores adjustable compliance footwear, surface stiffness effects on gait, and human-robot harmony challenges. Her contributions bridge robotics, biomechanics, and rehabilitation engineering, aiming to improve motor adaptation and assistive technologies. Key themes in her publications include exoskeleton design, gait rehabilitation strategies, and adaptive control systems. Her lab develops novel devices like the AdjuSST treadmill and explores how variable impedance environments influence human movement. Meghan’s interdisciplinary approach integrates robotics, materials science, and clinical applications to advance wearable technologies. Her research also addresses challenges in human-robot collaboration, including trust dynamics and ethical considerations. Beyond academia, she enjoys knitting, biking, and spending time with her miniature dachshund, Yoshi.
Marcus Oliver Weber is a Professor at the Department of Textile and Clothing Technology at Niederrhein University of Applied Sciences. He also serves as Head of the Department of Textile Management at Technische Universität Berlin (TUB). His work spans textile engineering, knitting innovation, and sustainable material science. Academic Rank: Professor Primary Role: Niederrhein University of Applied Sciences Secondary Role: Head of Department of Textile Management at TUB Research Interests focus on advanced knitting technologies , smart textiles , and sustainable fiber applications . Key areas include biodegradable textile solutions, conductive yarns for sensor applications, and technical textiles for protective, medical, and automotive sectors. Recent Publications highlight innovations in PLA-based biodegradable packaging , ultrasonic welding of nanofibers , and thermodynamic properties of spacer fabrics . His work emphasizes sustainable practices, material testing, and smart textile integration. Scientific Awards & Activities include UNIDO Technical Advisor Bundesgerichtshof (BGH) Technical Advisor ISO Standardization Committee for Knitting Machines Patents cover novel yarn feeding systems and textile machine designs. Teaching responsibilities include courses in Textile and Clothing Technology , Design Engineering , and Textile Product Management .
