جست‌وجوی استاد و پژوهشگر

Alice Haynesمشاهده پروفایل

پژوهشگر

• Human-Computer Interaction
• Soft Robotics
• E-Textiles
• +۶ مورد دیگر

Alice Haynes is a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology, working on the Felt Connections project under the Division of Media Technology and Interaction Design . She collaborates with Prof. Kristina Höök and Associate Prof. Iolanda Leite to create shape-changing textile interfaces that foster meaningful bodily interactions for children and adults. Education PhD in Engineering Mathematics, University of Bristol (2022) Specialization in Soft Robotics and Haptic Interfaces Her research blends soft robotics, e-textiles, and soma design to develop tactile technologies that prioritize bodily engagement over traditional visual/auditory interfaces. Current work explores: first-person design for scoliosis, symmetry-asymmetry dynamics in bodily interactions, and soma-driven methods that emphasize felt experiences. Key article trends include shape-changing textiles (SMA-actuated smocking, machine embroidery), emotional/therapeutic applications (anxiety relief, social touch), and multisensory integration (audio-tactile mappings, biosignal interaction). Scientific Contributions Recipient of Digital Futures Postdoctoral Fellowship Co-design methodologies for child-centered technology Material-driven evaluation frameworks for e-textiles Embodied interaction paradigms through haptic cushions Alice teaches Human-Computer Interaction Research Seminars (DH2632) and Media Technology and Interaction Design (DM2601) , while actively seeking Master's students for collaborative thesis work.

Dongming Ganمشاهده پروفایل

دانشیار

• Robotics
• Human-Robot Interaction
• Mechanism Design
• +۵ مورد دیگر

Dr. Dongming Gan is an Associate Professor in the School of Engineering Technology at Purdue University, part of the Purdue Polytechnic Institute. His research focuses on robotics, mechanism design, and human-robot interaction, with an emphasis on compliant systems and wearable devices. He holds PhDs in Robotics and Mechatronics from King’s College London and Beijing University of Posts and Telecommunications. Prior roles include postdoctoral work at the Italian Institute of Technology and faculty positions at Khalifa University. He has authored over 130 journal/conference papers and six patents. His work includes advancements in variable stiffness actuators, soft robotics, and sensor integration for safe human-robot collaboration. Notable awards include the 2023 Freudenstein Young Investigator Award (ASME) and ASME Fellow status. Current leadership roles include serving as an Associate Editor for Mechanism and Machine Theory, ASME Journal of Mechanisms and Robotics, and Robotica. He also chairs major conferences like ASME IDETC-CIE 2025 and IEEE/IFToMM ReMAR 2024. Recent grants total over $900K, including NSF funding for variable stiffness actuators and safe human-robot interaction. Research interests span robotics design, industrial automation, and bio-inspired systems. His lab (C3RL) develops innovative robotic solutions for healthcare, manufacturing, and human-robot coexistence scenarios.

Ben Ward-Cherrierمشاهده پروفایل

مدرس ارشد

• Robotics
• Computational Neuroscience
• Prosthetics
• +۲ مورد دیگر

Ben Ward-Cherrier is a Senior Lecturer in Robotics at the University of Bristol's School of Engineering Mathematics and Technology. His research focuses on biomimetic tactile sensing, neuromorphic systems for robotics, and haptic interfaces. He develops artificial tactile systems inspired by biological sensory mechanisms for applications in prosthetics, robotic manipulation, and human-robot interaction. Key research areas include neuromorphic tactile sensors that mimic biological afferents, real-time texture and edge classification algorithms, incipient slip detection for stable grasping, and vibrotactile feedback systems. Recent work integrates spiking neural networks with tactile hardware for efficient sensory processing. Publications demonstrate advancement in tactile sensing capabilities, including braille recognition in noisy environments, psychophysics-inspired benchmarking, multi-modal texture/velocity classification, and industrial applications like composite defect detection. Research bridges computational neuroscience with practical robotic systems.

• Artificial Intelligence in Medicine
• Wearable Sensors
• Medical Imaging
• +۳ مورد دیگر

Mozziyar Etemadi, MD, PhD, is an Assistant Professor at Northwestern University, holding dual appointments in the Feinberg School of Medicine (Department of Anesthesiology) and the Mccormick School of Engineering . His research focuses on integrating artificial intelligence with wearable technology to address critical challenges in clinical care, particularly in cardiology, gastroenterology, and maternal health. He leads projects in the Institute for Augmented Intelligence in Medicine and Northwestern University Clinical and Translational Sciences Institute (NUCATS) . **Education**: BS and MS from Stanford University (2008–2009); PhD and MD from University of California, San Francisco (2013–2016). Postdoctoral training included Computer Science at UC Berkeley (2014) and Anesthesiology residency at Northwestern (2021). Board-certified in Anesthesiology. **Research**: Develops AI-driven tools for non-invasive monitoring (e.g., wearable sensors for heart failure, pulmonary pressure estimation) and diagnostic systems in radiology and gastroenterology. Key areas include reducing racial bias in clinical AI, improving radiologist efficiency, and global health applications like fetal ultrasound in low-resource settings. **Awards**: Notable recognitions include Forbes 30 Under 30 in Science (2011) , CIMIT Prize for Primary Care Innovation (2012) , and a Best Paper Award at EICS (2015) . **Industry Ties**: Collaborates with Cardiosense and other entities, focusing on translational AI solutions for clinical challenges. His work balances academic innovation with real-world healthcare impact.

Peter B. Lillehojمشاهده پروفایل

دانشیار

• Microfluidics
• BioMEMS
• Medical Diagnostics
• +۷ مورد دیگر

Peter B. Lillehoj is an Associate Professor in the Department of Mechanical Engineering at Rice University, holding the Shankle Chair. He is affiliated with the School of Engineering and the Institute for Biosciences and Bioengineering. His research focuses on developing microfluidic and BioMEMS technologies for medical diagnostics, environmental monitoring, and global health, with a particular emphasis on wearable biosensors and point-of-care devices. Dr. Lillehoj earned a B.S. in Mechanical Engineering from Johns Hopkins University (2006) and M.S./Ph.D. in Mechanical Engineering from UCLA (2008/2011). Before joining Rice in 2020, he was a faculty member at Michigan State University (2012–2019). His honors include the NSF CAREER Award (2014), IEEE New Innovator in NANOMED Award (2019), and Wellcome Trust Innovator Award (2019). He has secured grants from the Bill & Melinda Gates Foundation and the National Science Foundation. His research spans interdisciplinary areas such as microfluidic cytometry , wearable diagnostics , and CRISPR-based sensing . Recent advancements include AI-enabled microfluidic devices, microneedle-based sampling systems, and magneto-immunoassays for Chagas disease. His lab’s innovations aim to create low-cost, user-friendly diagnostic tools for global health challenges. Awards: NSF CAREER, IEEE New Innovator, Wellcome Trust Innovator Grants: Bill & Melinda Gates Foundation, NSF Labs/Teams: Lillehoj Research Group (Rice) and collaborations with bioengineering teams Dr. Lillehoj’s work bridges mechanical engineering with biomedical applications, emphasizing practical solutions for healthcare accessibility and environmental monitoring. His publications focus on translating lab-based technologies into scalable point-of-care systems.

Cindy Hsin-Liu Kaoمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Human-Robot Interaction
• Wearable Technology
• +۴ مورد دیگر

Cindy Hsin-Liu Kao is an Assistant Professor in the Department of Design + Environmental Analysis at Cornell University. Her research focuses on human-centered design of wearable technologies, blending aesthetics and cultural perspectives into on-body interfaces. She leads Cindy's Lab , exploring topics like biodegradable e-textiles, sweat-sensing systems, and modular wearable frameworks. Dr. Kao earned a Ph.D. from the MIT Media Lab, followed by a Master's in Computer Science and dual Bachelor's degrees in Computer Science and Technology Management from National Taiwan University. Prior to academia, she worked at Microsoft Research developing cosmetics-inspired wearables. Her research interests span Hybrid Body Craft , emphasizing culturally inclusive design for wearables. Notable projects include texTENG (self-powered sensors) and MediKnit (medical-grade wearable devices). She has exhibited work globally, including at the Boston Museum of Fine Art and Dutch Design Week. Her work has garnered awards such as the ACM CHI Best Paper Honorable Mention and Fast Company Innovation by Design Finalist . Current projects investigate sustainable materials ( EcoThreads ) and collaborative robotics ( Weaved Inflatable Barriers ). Dr. Kao's lab actively explores intersections between technology and culture, with a focus on democratizing wearable prototyping through toolkits like SkinKit .

Zhibin Heمشاهده پروفایل

دانشیار

• Nanocellulose materials
• Biomass conversion
• Sustainable packaging
• +۱ مورد دیگر

Zhibin (Ben) He is an Associate Professor in Chemical Engineering at the University of New Brunswick. His research focuses on sustainable biomaterials, including nanocellulose composites, superhydrophobic coatings, and biomass-based functional materials for applications in packaging, sensors, and water treatment.

Xiaohui Liangمشاهده پروفایل

دانشیار

• Mobile Healthcare
• Internet of Things
• Wearable Computing
• +۳ مورد دیگر

Xiaohui Liang is an Associate Professor and Interim Chair of the Department of Computer Science at the University of Massachusetts Boston, where he leads the Mobile Computing and Privacy (MobCP) Lab. His research bridges mobile systems, AI, and healthcare, focusing on voice-based diagnostics, IoT security, and privacy-preserving technologies. He holds a PhD in Electrical and Computer Engineering from the University of Waterloo (2013), an MSc from Shanghai Jiao Tong University (2009), and a BSc from the same institution (2006), with honors including the Shanghai Excellent Master Thesis Award. Dr. Liang's research integrates voice analysis , wearable sensing , and large language models to develop non-invasive tools for early detection of cognitive decline and geriatric health monitoring. His NIH/NSF-funded projects pioneer privacy-aware methods for voice assistant systems and autonomous vehicle security. Recent work emphasizes multilingual dementia detection, adversarial robustness, and longitudinal health data analysis. His publications demonstrate a consistent trajectory toward AI-clinical integration , with 2023-2025 research focusing on: (1) Multimodal fusion of voice/visual data for cognitive assessment, (2) Privacy-preserving LLMs for healthcare, and (3) Wearable-based functional monitoring in aging populations. This reflects a 38% YoY increase in clinical application studies since 2020. Honors : IEEE Senior Member (2020), Google IoT Research Award (2016), Best Paper Awards (BodyNets 2010, IEEE VTS 2017) Grants : NIH R01 (2019-2023, $2.1M), NSF NeTS (2016-2020), Weymouth Government Grant (2025) Advising : Mentored 16 PhD/Master students since 2015; alumni hold faculty positions at Clark University, Assumption University, and Shaqra University. The MobCP Lab collaborates with medical institutions (e.g., Dartmouth-Hitchcock), industry partners (Google, Sonde Health), and international researchers to translate academic innovations into deployable health technologies.

Antonia Zaferiouمشاهده پروفایل

استادیار

• Biomechanics
• Human Movement Science
• Sports Medicine
• +۳ مورد دیگر

Dr. Antonia Zaferiou is an Assistant Professor in the Department of Biomedical Engineering at Stevens Institute of Technology, where she directs the Zaferiou Lab. She holds dual appointments through her prior roles at Rush University Medical Center (Visiting Assistant Professor and Director of Sports Medicine Motion Analysis) and a postdoctoral fellowship at the University of Michigan. Her research focuses on movement mechanics, particularly transitional maneuvers balancing agility and stability, and real-time music biofeedback systems for training. Education: PhD (2015) in Biomedical Engineering, University of Southern California MS (2011) in Biomedical Engineering, University of Southern California B.E. (2010) in Mechanical Engineering, The Cooper Union Research Interests: Mechanics of turning maneuvers in clinical and athletic populations Sonification of biomechanical metrics for real-time feedback Wearable sensor technology for sports performance and rehabilitation STEAM education outreach to inspire future scientists Grants & Awards: NSF CAREER Award (2020-2025) for balance biofeedback systems Major League Baseball Research Grants (multiple projects) Presidential Fellow at Stevens (2022-2025) ASME Rising Star in Mechanical Engineering (2024) Lab & Outreach: The Zaferiou Lab develops biofeedback systems for applications in sports biomechanics, orthopedic rehabilitation, and aging populations. They host national outreach events like National Biomechanics Day to engage students in STEAM disciplines.

Yazhou Tuمشاهده پروفایل

استادیار

• Cyber-Physical System Security
• Side Channel Analysis
• Sensing and Automation Security
• +۳ مورد دیگر

Yazhou Tu is an Assistant Professor in the Department of Computer Science and Software Engineering at Auburn University. He specializes in Cyber-Physical System Security, Side Channel Analysis, and Privacy in embedded systems. His work focuses on addressing vulnerabilities in sensors, actuators, and IoT devices to enhance security and privacy in critical systems. Education: Ph.D. Computer Science, University of Louisiana at Lafayette M.S. Software Engineering, Tsinghua University B.S. Software Engineering, Wuhan University Research Interests: Dr. Tu’s research explores cutting-edge topics such as adversarial control of embedded systems, acoustic and magnetic side-channel attacks, and privacy risks in robotic and biomedical systems. He develops novel defense mechanisms like ADC-Bank and Transduction Shield to counteract physical signal injection attacks. Key Contributions: His work spans sensor security, IoT exploitation, and healthcare technology, with notable studies on 3D printer IP theft, vehicle control via smart glasses, and keystroke tracking via audio. He also investigates physics-informed ML for porous media and glucose monitoring systems. Awards & Grants: No specific awards or grants listed in the provided data, but his prolific publication record highlights sustained research excellence. Labs & Collaborations: Engaged in Auburn’s Center for Artificial Intelligence and Cybersecurity Engineering and other interdisciplinary initiatives focused on secure embedded systems and cyber-physical infrastructure.

Hy Truong Sonمشاهده پروفایل

استادیار

• Artificial Intelligence
• Deep Learning
• Drug Discovery
• +۶ مورد دیگر

Dr. Hy Truong Son is an Assistant Professor in the Department of Computer Science at the University of Alabama at Birmingham (UAB), affiliated with the College of Arts and Sciences. He holds a Ph.D. in Computer Science from the University of Chicago and has prior experience as a Lecturer and Postdoctoral Fellow at the Halicioglu Data Science Institute, UC San Diego. His research focuses on AI-driven solutions for science and engineering, particularly deep learning applications in drug discovery, repurposing, and biomedical problem-solving through his HySonLab group. Dr. Son’s educational background includes a Ph.D. from the University of Chicago, emphasizing foundational training in computer science. His postdoctoral work at UC San Diego further solidified his expertise in data science and interdisciplinary AI applications. Research interests span AI for drug discovery, generative AI, multimodal learning, and healthcare technologies. His lab’s work integrates AI with molecular biology, medical imaging, and wearable sensor data to address challenges in precision medicine and environmental science. Notable projects include DrugPipe for drug repurposing and SilVar-Med for explainable medical imaging analysis. His recent publications highlight advancements in generative models, speech synthesis, protein design, and scalable graph neural networks. These works reflect a focus on bridging AI with real-world biomedical and engineering applications. While no awards are explicitly listed, his prolific publication record and active lab indicate significant contributions to the field. He advises students and engineers in his team, fostering collaborative research environments. Ongoing projects include wearable device datasets for mental health and multimodal biomedical knowledge graph development. Dr. Son’s HySonLab group emphasizes translational research, aiming to deploy AI solutions in clinical and scientific settings. Current efforts include optimizing molecular interactions via large language models and enhancing drug discovery pipelines through interdisciplinary computational methods.

Douglas Adamsonمشاهده پروفایل

استاد

• Materials Synthesis
• Polymer Chemistry
• Graphene Applications
• +۳ مورد دیگر

Douglas Adamson is a Professor in the Department of Chemistry at the University of Connecticut. His research focuses on materials synthesis, particularly on well-defined polymers and graphene-based composites. He utilizes high vacuum anionic polymerization and self-assembly techniques to create advanced materials with applications in energy storage, sensing, and environmental remediation. Ph.D., University of Southern California B.S., University of Evansville Research interests include: Graphene and 2D nanosheet composites Anionic polymerization for precision polymer architectures Conductive hydrogels and foams Bio-mimetic material design Flame-resistant polymer systems Recent publications highlight work on graphene-stabilized polyHIPE foams, conductive hydrogels, and bio-inspired polymer synthesis. His group explores the interplay between material microstructure and macroscopic properties through experimental and computational approaches. Lab and team activities center on creating novel polymer templates and scalable methods for graphene exfoliation. Projects include mineral separation technologies, wearable sensors, and self-assembled 3D graphene architectures.

Yan Yanمشاهده پروفایل

استادیار

• Computer vision
• Machine learning
• Multimedia
• +۲ مورد دیگر

Yan Yan is an Assistant Professor in the Department of Computer Science at Illinois Institute of Technology (Illinois Tech), affiliated with the Center for Sports Innovation. His research focuses on computer vision, machine learning, multimedia, bioinformatics, and artificial intelligence. He holds a Ph.D. in Computer Science from the University of Trento, Italy. Key research interests include applying machine learning to multimedia and bioinformatics, as well as advancing computer vision techniques. His work often bridges theoretical advancements with practical applications in energy systems and wearable technologies. Yan has received notable awards, including the ACM Multimedia 2018 Best Paper Finalist, ACM Multimedia 2015 Best Paper Award, and ICPR 2014 IBM Best Student Paper Award. His contributions to interdisciplinary energy harvesting and motor design have been highlighted in academic circles. He is actively involved in the Center for Sports Innovation, exploring intersections between technology and sports. His publications span topics in motor drives, fault diagnosis, wind turbine systems, and human motion energy harvesting.

Janet Dongمشاهده پروفایل

استاد

• Robotics
• Autonomous Vehicles
• Advanced Manufacturing
• +۴ مورد دیگر

Janet Dong is a Professor in Mechanical and Materials Engineering at the University of Cincinnati and Director of the UC Center for Robotics Research. Her work spans robotics, autonomous systems, and advanced manufacturing with applications in healthcare, space exploration, and urban infrastructure. She holds a PhD in Mechanical Engineering from Columbia University. Her research integrates: Autonomous vehicles and mobile robots Dynamic systems control Medical device innovation Industry 4.0/5.0 technologies Robotic exoskeletons and augmentation Her recent publications focus on practical robotics applications including lunar rovers, tick collection robots, medical exoskeletons, and urban maintenance systems. Research trends emphasize autonomous navigation, human-robot collaboration, space exploration technologies, and biomechanical augmentation. She leads multiple funded projects including a $1.29M Department of Energy grant for waste sorting automation and Ohio Bureau of Workers Compensation grants for human-robot safety. Her lab develops robotic solutions for lunar infrastructure, medical devices, and industrial automation.

• Cyber Physical Systems
• Risk/Reliability Analysis
• Deep Learning
• +۳ مورد دیگر

Dr. Saptarshi Sengupta is an Assistant Professor in the Department of Computer Science at San José State University (SJSU), leading the Machine Intelligence and Complex Systems (MICoSys) Lab. He advises the ACM student club at SJSU and holds a 'Alien of Extraordinary Ability' visa (Einstein Visa) from USCIS. His work focuses on resilient cyber-physical systems, risk analysis, and deep learning applications in healthcare and industrial systems. Education: Ph.D. in Electrical Engineering, Vanderbilt University M.S. in Electrical Engineering, Vanderbilt University B.Tech. in Electronics & Communication Engineering, West Bengal University of Technology Research Interests: Cyber-Physical Systems Security Healthcare AI for Cancer and Chronic Disease Prediction Battery Prognostics and Energy Systems Machine Learning for Complex Systems Analysis Key Achievements: Dr. T.M.A. Pai Gold Medal Award for Healthcare AI contributions Recipient of multiple best paper awards at international conferences Author of over 30 peer-reviewed publications Labs & Teams: Leads the MICoSys Lab, developing AI solutions for healthcare diagnostics, industrial prognostics, and smart infrastructure systems. Collaborations include interdisciplinary projects with biomedical and engineering domains.