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Yali LingView profile

Assistant Professor

California State University, Long BeachUnited States

Dr. Yali Ling serves as an Assistant Professor in the Fashion Merchandising and Design program within the Department of Family and Consumer Sciences at California State University, Long Beach's College of Health and Human Services. Her research bridges traditional textile engineering with cutting-edge sustainable material innovation. Education: Ph.D. in Textile Technology Management, North Carolina State University (2021-2024) M.S. in Fashion Design and Engineering, Wuhan Textile University (2018-2021) B.S. in Fashion Design, Wuhan Textile University (2014-2018) Research Focus: Dr. Ling's work pioneers sustainable textile production through hemp/cotton blends and recycled materials, while advancing digital fashion technologies via 3D body scanning applications. Her expertise spans yarn engineering for performance textiles and functional apparel design addressing ergonomic challenges in diverse populations. This dual focus creates synergies between eco-conscious manufacturing and precision garment engineering. Publication Trends: Her 15 most recent publications (2019-2025) reveal three converging trajectories: (1) Sustainable material innovation (hemp textiles, eco-spinning), (2) Triboelectric wearable technology development, and (3) Anthropometric-driven apparel design. These strands collectively address industry demands for environmentally responsible production while enhancing human-technology interfaces in textile applications. Scientific Recognition: 2024 Best Poster Presentation at Textile Research Open House (NCSU) 2022 VF Graduate Student Impact Award ($5,000) 2021 Wuhan Textile University Special Graduate Scholarship ($1,500) 2020 Chinese Ministry of Education National Scholarship ($3,000) 2020 CNTAC "Maker China" Innovation Excellence Award 2019 China Natural Dialectics Research Association Symposium Prize Professional Engagement: Dr. Ling maintains active industry partnerships through her sustainable textile research while mentoring undergraduate students in the Fashion Merchandising and Design program. Her current work focuses on scaling hemp-based textile production and developing AI-integrated pattern generation systems. Research Infrastructure: While specific laboratory facilities aren't detailed in available materials, her publications indicate collaborations with Wilson College of Textiles' advanced manufacturing facilities and access to 3D body scanning technologies for anthropometric research.

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Emily WhitingView profile

Associate Professor

Boston UniversityUnited States

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.

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David E. BreenView profile

Professor

Drexel UniversityUnited States

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.

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Justin HarveyView profile

Lecturer

University of Technology SydneyAustralia

Justin Harvey is a Lecturer at the University of Technology Sydney (UTS) within the Faculty of Design, Architecture and Building, specializing in Media Arts and Production. He is an active member of the Creative Practice Research Group and serves on the Faculty Board and Faculty Research Committee. Harvey holds a PhD in Media Art & Design from the University of New South Wales and a Bachelor of Arts in Communication (Media Arts & Production) with First Class Honors from UTS. Harvey's research interests focus on creative uses of generative Artificial Intelligence, experimental approaches to media art making, and creative practice led research. His artistic practice spans moving image, installation, and virtual reality experiences, with a particular fascination for human-machine interaction and the creative potentials of digital technologies. He explores glitch aesthetics, digital video feedback, and imagery generated using diffusion models, often collaborating with AI systems in unexpected ways. Harvey has exhibited his work internationally at venues including VIVID Sydney, ISEA (International Symposium on Electronic Art) in Vancouver, Hong Kong, and South Korea. His 2023 collaboration with generative AI, Unprompted Studies 1-3 , was a finalist in the Fisher's Ghost Art Award. In 2024, he was selected as a Scholar in the Sydney Powerhouse Museum's Research Scholars Program for the "Knit Forward" project, which reimagines historical garments using generative AI and seamless knitwear technology. His research on creative applications of GenAI directly informs his teaching in Experimental Media and Creative Project Development. Harvey has extensive studio-based teaching experience since 2010, covering subjects such as Situated Media Installation Studio, Drama Production, and Experimental Media. Fisher's Ghost Art Award (2023 finalist) Powerhouse Museum Scholars Program funding (2024) UTS ECR Capability Development Initiative funding (2024) FASS ECR Funding (2024) Harvey supervises PhD and Masters of Research students in creative practice research and has mentored hundreds of students through capstone projects in drama, documentary, animation, and media arts installation. His current research projects include collaborations with Dr. Doris Li on reimagining historical garments using AI, and exploring the intersection of Surrealist techniques with generative AI in works like Oneironaut , exhibited at VIVID Sydney 2025.

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Caroline CrockettView profile

Assistant Professor

University of VirginiaUnited States

Caroline Crockett is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Virginia, part of the School of Engineering and Applied Science. She holds a Ph.D. in Electrical Engineering from the University of Michigan and a B.S. from the University of Virginia. Her academic role emphasizes teaching and engineering education research. B.S., Electrical Engineering, University of Virginia, 2015 Ph.D., Electrical Engineering, University of Michigan, 2022 Her research interests are centered on engineering education, particularly how students develop conceptual understanding in core electrical engineering topics and learn to troubleshoot. She also has a background in machine learning and image reconstruction, though her current work focuses on pedagogy. She actively engages undergraduate students in research projects related to education and is a member of IEEE and ASEE. Her recent publications reflect a strong trend toward engineering education research, especially in signals and systems comprehension and affective student responses to active learning. Earlier work includes advanced image reconstruction techniques using bilevel optimization, showing a transition from technical signal processing to educational research. Caroline Crockett does not supervise graduate students or maintain a research lab, but she mentors undergraduates interested in engineering education. She has taught several key courses including Fundamentals of ECE 2, Fundamentals of ECE 3, and an Introduction to Machine Learning. She is committed to undergraduate instruction and curriculum development. She is involved in the broader academic community through her memberships in IEEE and ASEE, contributing to educational research and dissemination through conferences and publications. Outside of her academic duties, she enjoys knitting, reading, crafts, and spending time with her family and rescue dog Oreo. She is also a licensed amateur radio operator.

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Bai ZiqianView profile

Assistant Professor

Southern University of Science and Technology (SUSTech)China

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.

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Sevil YazıcıView profile

Associate Professor

Istanbul Technical UniversityTurkey

Sevil Yazıcı is an Associate Professor at the Department of Architecture , Istanbul Technical University , with a focus on computational design, material efficiency, and structural performance in architecture. She previously served as a Doctor Lecturer at Ozyegin University (2013–2020). Educational background: PhD in Building Sciences (2009–2013), Istanbul Technical University Degree in Architecture from Architectural Association School of Architecture (2004–2006) Research interests span computational design, bio-inspired material organization, and sustainable construction. Her recent work explores VR-driven spatial performance analysis, demolition waste reuse, and microstructure-informed shell topologies. Selected trends in publications include: Integrating environmental/structural data in early design Material-efficient generative models Biomimetic computational analysis AI-assisted architectural creativity Scientific awards highlight her achievements: 2024 Best Article Award (Frontiers of Architectural Research) 2018 Gold Medal (Istanbul International Invention Fair) 2016 UK Graduate Professional Achievement Award 2014 ITU Most Successful Doctoral Thesis Award Advising includes theses on reversible structures, sustainable façades, AI-driven design, and material-efficient fabrication. She served on the Executive Board of the Informatics in Architectural Design Graduate Program (2021–present) and was Deputy Head of Department (2022).

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Sepideh GhodratView profile

Assistant Professor

Delft University of TechnologyNetherlands

Dr. Sepideh Ghodrat is an Assistant Professor of Shape Morphing Design at TU Delft's Faculty of Industrial Design Engineering. She bridges materials science and design, focusing on stimuli-responsive materials for dynamic, interactive products. Her research emphasizes 4D printing, smart materials, and sustainable applications. Research Projects include 4D Printing Magnetically Activated Shape Morphing Objects and SereniSleeve (wearables for anxiety modulation). Courses taught: Materials and Manufacturing (2023-2024). Research Interests : Shape Morphing Design (SMD) Stimuli-Responsive Materials (e.g., shape memory alloys, polymers) 4D Printing and Magnetic Soft Materials Applications in healthcare, automotive, and sustainability Key Contributions : Developed modular self-folding hinges (Mimosa Kit). Explored haptic wearables for visually impaired users. Advocates for adaptive, environment-responsive products. Labs/Teams : Involved in multiple interdisciplinary research teams at TU Delft, focusing on smart materials and sustainable design engineering.

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Youngmoo KimView profile

Professor

Drexel UniversityUnited States

Youngmoo Kim is Professor of Electrical and Computer Engineering at Drexel University, where he directs the Expressive and Creative Interactive Technologies (ExCITe) Center. His leadership extends to the Music & Entertainment Technology Laboratory (MET-lab), focusing on machine listening, robotics for expressive interaction, and STEM education through music technology. Education: PhD, Media Arts & Sciences, MIT (2003) MS, Electrical Engineering, Stanford University MA, Music, Stanford University BS, Engineering, Swarthmore College BA, Music, Swarthmore College Research Focus: Kim's interdisciplinary work bridges audio signal processing, machine learning for music information retrieval, human-robot interaction, and acoustic synthesis. His lab develops novel interfaces including brain-controlled robotics, augmented instruments, and AI-driven music systems, while championing K-12 STEAM education through technological innovation. Publication Trends: Recent articles demonstrate strong convergence of deep learning with music technology, particularly in neural audio synthesis, instrument recognition, and robotic control systems. Emerging themes include differentiable physical modeling of instruments, neuroadaptive interfaces using fNIRS/tDCS, and computational approaches to creative collaboration. Awards & Honors: 2021 College of Engineering Inclusive Excellence Award 2013 Apple Distinguished Educator 2012 Lindback Foundation Distinguished Teaching Award 2012 Philadelphia Geek Awards Scientist of the Year 2007 NSF CAREER Award Leadership & Funding: Kim has secured research support from the National Science Foundation and Knight Foundation. His ExCITe Center serves as an interdisciplinary hub for creative technology development, while MET-lab advances audio-machine intelligence through collaborations across engineering, computer science, and performing arts.

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Sri Niwas SinghView profile

Professor

Indian Institute of Technology Kanpur (IITK)India

Sri Niwas Singh serves as Chair Professor in the Department of Electrical Engineering at the Indian Institute of Technology, Kanpur, where he has established himself as a leading expert in power systems engineering with significant research contributions spanning multiple critical areas. His educational qualifications include: PhD in Electrical Engineering from IIT Kanpur (1995) M.Tech in Electrical Engineering from IIT Kanpur (1989) B.Tech in Electrical Engineering from KNIT Sultanpur (1987) Professor Singh's research program focuses on Power System Restructuring, FACTS Technology, Optimal Power Dispatch and Security Analysis, Power System Dynamics, Operation and Control, Distribution System Planning and Demand Side Management, and Application of Genetic Algorithms and Artificial Neural Networks in Power Systems. His work bridges theoretical concepts with practical applications, particularly in smart grid technologies and renewable energy integration. His publication record reveals a consistent research trajectory addressing evolving power system challenges, with increasing emphasis on renewable energy integration and computational intelligence techniques. The progression from traditional power system analysis toward smart grid technologies and AI applications demonstrates his ability to adapt research focus to emerging industry needs. His significant professional recognitions include: 2013 IEEE Educational Activities Board Meritorious Achievement Award in Continuing Education Three PhD theses supervised by him receiving the POSOCO Power System Award (2012) Humboldt Research Fellowship (awarded 2005 and 2007) INAE Young Engineer Award (2000) C.B.I.P. Young Engineer Award (1996) Professor Singh has mentored numerous graduate students, with three of his PhD students receiving the prestigious POSOCO Power System Award in 2012. His research has attracted substantial funding and collaboration opportunities, supporting advanced work in power systems analysis and control. His laboratory focuses on power system simulation, renewable energy integration studies, and smart grid technology development, with a research team comprising PhD scholars and industry collaborators working on cutting-edge power engineering problems.

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Yuhiro IwamotoView profile

Associate Professor

Nagoya Institute of Technology (NIT)Japan

Yuhiro Iwamoto serves as Associate Professor at Nagoya Institute of Technology within the Department of Electrical and Mechanical Engineering, with additional affiliation to the Graduate School of Engineering's Mechanical Engineering Program and the Center for Innovative Young Researchers. His academic foundation includes: Bachelor of Engineering from Doshisha University (2008) Master's degree from Doshisha University (2010) Doctor of Engineering from Doshisha University (2013) Dr. Iwamoto's research centers on fluid engineering phenomena with emphasis on magnetic responsive fluids. His work explores thermomagnetic pumping mechanisms, phase-change behavior in water-based magnetic fluids, and innovative applications of permanent magnet elastomers for energy harvesting and tactile sensing. This research bridges fundamental fluid dynamics with practical implementations in thermal management systems, robotic sensing, and sustainable energy technologies, demonstrating significant contributions to manufacturing technology and mechanical engineering disciplines. Analysis of his recent publications reveals a cohesive trajectory in functional fluid systems, particularly focusing on temperature-sensitive magnetic fluids for self-driving thermal transport and elastomer-based transduction mechanisms. His work consistently integrates material science, electromagnetic principles, and fluid mechanics to develop novel solutions for heat transfer enhancement, energy conversion, and soft robotics applications. His research excellence has been recognized through prestigious awards: Japanese Society of Mechanical Engineers Encouragement Award (2020) for research on thermal conductivity control using silver nanowire magnetic nanofluids Best Presentation Award at the 9th Asia-Pacific Symposium on Applied Electromagnetics and Mechanics (2018) Dr. Iwamoto actively contributes to academic governance as committee member for the Institute of Electrical Engineers of Japan's Special Committee on Electromagnetic Responsive Fluids (2019-2022) and the Japan AEM Society Editorial Committee (2017-2022). His industrial property portfolio includes multiple patents related to magnetic elastomers and thermal transfer systems, reflecting strong industry-academia collaboration. He maintains active membership in eight professional societies including The Japan Society of Applied Electromagnetics and Mechanics and The Japanese Society for Multiphase Flow.

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Michael HummelView profile

Associate Professor

Aalto UniversityFinland

Michael Hummel is Associate Professor at Aalto University's School of Chemical Engineering, Department of Bioproducts and Biosystems. His research focuses on sustainable biopolymer chemistry, cellulose processing, and development of renewable materials from natural resources. Hummel leads research on advanced cellulose fiber technologies including the Ioncell process for eco-friendly textile production. His recent work includes developing dope-dyed Lyocell fibers, recycling post-consumer textiles into new materials, creating multifunctional cellulose textiles, and pioneering medical textiles for wound care applications. Research spans fundamental chemistry of biomass conversion to applied material development, with emphasis on circular economy principles. Hummel's publications demonstrate advancements in sustainable materials science, particularly in cellulose chemistry, fiber engineering, lignin valorization, and green chemistry applications for textiles and advanced materials.

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Megan HofmannView profile

Assistant Professor

Northeastern UniversityUnited States

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.

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Katia BertoldiView profile

Professor

Harvard UniversityUnited States

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.

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Stephen KobourovView profile

Professor

Technical University of MunichGermany

Prof. Stephen Kobourov is a Professor in the TUM School of Computation, Information and Technology at Technische Universität München (TUM). Previously, he held positions at the University of Arizona from 2000 to 2024, progressing from Assistant Professor to Full Professor, and served as Deputy Director of the Data Science Institute. His expertise lies in algorithm design, computational geometry, and graph visualization, with over 250 publications and significant funding from NSF, ONR, and USDA grants. Education: BS in Computer Science and Mathematics from Dartmouth College (1995), PhD in Computer Science from Johns Hopkins University (2000). Research focuses on efficient algorithms for graph drawing, visualization techniques for networks, and geometric algorithms. Notable contributions include work on stress metrics in graph layouts, hypergraph representations, and non-Euclidean visualization frameworks. He has co-chaired committees for ALENEX, IEEE PacificVis, and GD, and serves as an editor for JGAA, CGTA, and IEEE TVCG. Awards include the Fulbright Distinguished Chair (2015–2016), Humboldt Research Fellowship (2011–2014), and NSF Career Award (2006–2011). His recent work explores multi-layer network visualization, AI-driven graph analysis (e.g., MLLMs perception), and graph embeddings in non-Euclidean spaces. Advising and grants: Extensive grants from NSF and other agencies support his research. He has advised numerous students and collaborates internationally, contributing to labs like the Data Science Institute and initiatives such as the Institutional Knowledge Map (KMAP). Visualization projects include MetroSets (metro map-style set visualization), Wooly Graphs (knitting pattern frameworks), and tools for interactive network analysis. His work bridges theoretical algorithms with practical applications in science and technology.

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