جست‌وجوی استاد و پژوهشگر

Yayue Panمشاهده پروفایل

استاد

• Additive Manufacturing
• Multi-Material Additive Manufacturing
• Biomedical Additive Manufacturing
• +۴ مورد دیگر

Yayue Pan is a Professor at the Department of Mechanical and Industrial Engineering, University of Illinois Chicago (UIC) , and serves as the Director of NASA MIRO Center for In-Space Manufacturing: Recycling and Regolith Processing (CISM-R2) . Her research focuses on advancing Additive Manufacturing (AM) technologies for applications in biomedical engineering , energy storage , and smart structures . Ph.D., Industrial and Systems Engineering, University of Southern California (2014) M.S., Mechanical Manufacturing and Automation, Zhejiang University, China (2010) B.S., Industrial Engineering, Zhejiang University of Technology, China (2007) Her work addresses technical challenges in AM such as multi-material printing , multi-scale fabrication , and field-assisted processes . Notable projects include: Development of electrostatically-assisted direct ink writing (eDIW) for high-speed, high-resolution printing Continuous projection stereolithography for rapid solid object manufacturing Acoustic field-assisted particle patterning for smart composites Light-curable hydrogels for corneal repair applications Her 15 most recent publications (2022–2025) span topics in: Multi-material AM (conductive polymers, hierarchical composites) Biomedical applications (soft robotics, corneal repair) Energy components (battery electrolytes, supercapacitors) Field-assisted processes (acoustic, electrostatic, magnetic) Scientific Awards : 2024 ASME Chao and Trigger Young Manufacturing Engineer Award 2022 UIC Researcher of the Year Rising Star Award 2020 ASME CIE TC Leadership Award 2019 UIC Outstanding Teaching Award 2017 SME Outstanding Young Manufacturing Engineer Award NSF REU Supplements (2023–2024) Advising : Mentored 24+ graduate/undergraduate researchers, including 17 NASA/GPIP interns. Former advisees hold academic positions at University at Buffalo and University of North Carolina at Charlotte , and industry roles at Apple , GE Healthcare , and ANSYS . Grants : Recipient of a $4.65M NASA grant and multiple NSF awards. Collaborations include Northwestern University, University of Michigan, and NASA centers.

Jennifer L Clarkeمشاهده پروفایل

استاد

• Statistical Methodology
• Bioinformatics/Computational Biology
• Data Mining/Machine Learning
• +۳ مورد دیگر

Jennifer L. Clarke is a Professor in the Department of Statistics at the University of Nebraska–Lincoln and Director of the Quantitative Life Science Initiative. She holds leadership roles in enabling big data integration across the University of Nebraska system through collaborative research programs. Her affiliations include the Institute of Agriculture and Natural Resources (IANR) and the College of Agriculture and Natural Resources. Dr. Clarke's research focuses on statistical methodology for high-dimensional data, computational biology, bioinformatics, and bacterial genomics. Her work bridges statistical innovation with applications in oncology, microbiome analysis, and agricultural phenomics. Key areas include predictive modeling, machine learning, and genomic/metagenomic data integration. Her recent publications span cancer biomarker discovery, plant phenotyping methodologies, and microbial community analysis, reflecting her interdisciplinary approach. Articles emphasize translational applications like therapeutic target identification and precision agriculture. Dr. Clarke leads initiatives fostering collaboration between statisticians and domain scientists, including the Quantitative Life Science Initiative and contributions to the Agricultural Genome-to-Phenome Initiative (AG2PI). Her work advances data-driven solutions for healthcare and food security challenges. Notable projects include developing statistical tools for microbiome studies, analyzing root architecture via 3D imaging, and investigating cranberry-derived compounds' cancer-inhibitory mechanisms. Her methodological contributions include hybrid clustering techniques and predictive model validation frameworks.

ONG Soh Khimمشاهده پروفایل

استاد

• Augmented Reality Applications in Manufacturing
• Intelligent Manufacturing Systems
• Sustainable Product Design
• +۴ مورد دیگر

ONG Soh Khim is a Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS) and a member of the NUS Graduate School. She is a Fellow of CIRP (International Academy for Production Engineering), the first Asian and fourth female Fellow globally. Her research focuses on augmented reality (AR) and digital twins in manufacturing, with applications in assistive technology and sustainable design. She has authored/co-edited 6 books, over 300 journal/conference papers, and holds an H-index of 66 (Google Scholar) and 52 (Scopus). She has held leadership roles, including serving as a Nominated Member of the Singapore Parliament (2005–2006) and on multiple NUS governance boards. Her honors include the Singapore Youth Award (2004), M. Eugene Merchant Award (2004), and the 2021 Long Service Medal. She advocates for gender diversity in STEM, leading initiatives like the Girls2Pioneers program. Her current roles include Senior Principal Investigator at NUS Research Institutes in Suzhou and Guangzhou, and Visiting Professorships at Chinese universities.

Nhiem Tranمشاهده پروفایل

مدرس ارشد

• Biomedical Engineering
• Nanotechnology
• Nanomedicine
• +۱۲ مورد دیگر

Dr. Nhiem Tran is a Senior Lecturer in the Department of Applied Chemistry and Environmental Science at RMIT University's School of Science, part of the STEM College. He joined RMIT in 2015 as a Vice Chancellor's Research Fellow after completing his PhD in Physics at Brown University (USA, 2012) and postdoctoral research at Rhode Island Hospital (USA), CSIRO, and the Australian Synchrotron. His research focuses on developing biomaterials for drug delivery, gene therapy, and medical implants, particularly lipid nanoparticles and 3D-printed metallic implants. He leads the Biomaterial Interfaces group, investigating self-assembled lipid nanoparticles for cancer and autoimmune disease treatments. His work has resulted in over 65 high-impact publications and numerous awards, including the RMIT Vice Chancellor's Research Fellowship and the Stein/Bellet Foundation Fellowship. Tran's funding comes from grants such as the ARC Discovery Project, mRNA Victoria, and the CASS Foundation. His research interests span nanomedicine, biomedical engineering, and materials science, with a focus on applications in drug delivery, bacterial infection control, and orthopaedic implants. Education: PhD in Physics (Brown University, 2012) Key Projects: 3D-printed diamond-titanium implants, lipid nanoparticle drug carriers, and antimicrobial coatings. He actively supervises postgraduate research in areas like nanomaterials for drug delivery and biomedical applications.

• Biomaterials
• Tissue Engineering
• Regenerative Medicine
• +۱۲ مورد دیگر

Professor Hala Zreiqat AM is a leading biomedical engineer at The University of Sydney , serving as the Director of the ARC Training Centre for Innovative BioEngineering . A Fellow of all major Australian academies (AAS, ATSE, FAHMS, FRSN), she develops 3D printed bioceramics for bone regeneration while championing diversity through initiatives like the IDEAL Society and BIOTech Futures mentorship program. Her work bridges academia, clinical practice, and industry in musculoskeletal research . Research Focus: Her lab creates synthetic bone scaffolds that mimic natural bone architecture, strength, and porosity, enabling non-rejected bone regeneration via patient-matched implants. Key applications include orthopaedic, dental, and maxillofacial repair , with over $18M in competitive funding and multiple patents. Current projects explore AI-driven scaffold performance prediction and anti-senescence strategies for aging-related bone loss. Scientific Trends: Recent publications highlight 3D printed nanovoxelated ceramics , antisenescence biomaterials , and multifunctional theranostic platforms . Her team integrates machine learning for scaffold design, atom probe tomography for interface analysis, and two-photon imaging for cellular monitoring in 3D environments. 2021-2022 Fulbright Senior Scholar 2018 NSW Premier's Woman of the Year 2019 Eureka Prize for Innovative Use of Technology Fellow of Australian Academy of Science (2021) Over $18M in research funding Teaching & Leadership: She designed core courses like Tissue Engineering and Nanomaterials in Medicine , mentoring 158 students in 2020 alone. As Chair of CAAR (2020-2023), she strengthens Australia-Arab collaborations. Her lab trains early-career researchers , with alumni now in academia and industry.

• Computer Vision
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Habib Ullah is an Associate Professor in Data Science at the Norwegian University of Life Sciences (NMBU), Norway, where he conducts research at the intersection of computer vision and machine learning. He is affiliated with the Institute of Data Science under the Faculty of Science and Technology. He has previously held academic positions at COMSATS University Islamabad, Pakistan, and the University of Ha'il, Saudi Arabia, and served as a postdoctoral researcher at The Arctic University of Norway. Educational Background: PhD in Information and Communication Technology (Computer Vision), University of Trento, Italy (2011–2015) MSc in Electronics and Computer Engineering, Hanyang University, South Korea (2007–2009) BSc in Computer Systems Engineering, NWFP University of Engineering and Technology, Pakistan (2002–2006) Habib Ullah's research is primarily focused on computer vision and machine learning, with applications in aquaculture, agriculture, and human behavior analysis. He investigates underwater fish feeding sounds using audio classification, develops zero-shot learning models for recognizing unseen classes, and applies deep learning to detect stress in salmon via skin dot patterns. He also explores AI-driven controlled environment agriculture, leveraging sensors and automation for optimal crop growth. His work emphasizes practical AI solutions for real-world challenges in environmental and biological domains. The recent publications highlight a strong trend in leveraging deep learning for zero-shot and semi-supervised learning, particularly in computer vision tasks such as sea ice classification, crowd anomaly detection, and agricultural monitoring. His research spans remote sensing, biomedical signal processing, and human activity recognition, demonstrating interdisciplinary versatility. The keywords reflect a focus on robust feature representation, knowledge transfer, and model generalization. Scientific Awards and Funding: Industrial PhD grant 'Advancing Controlled Environment Agriculture AI' from The Research Council of Norway (Project number 354125, 2 million NOK, 2024) Team member (Coordinator-Participant) in the Battery Cell Assembly Twin (BatCAT) project funded by Horizon Europe (7 mEuro, 2023–2027) Development of an AI-Based Image Analysis System for Monitoring Plant Status (Funding: 1.8 mNOK, starting 2025) Habib Ullah actively supervises PhD projects and contributes to academic service through editorial and organizational roles. He has served as an Associate Editor for IEEE Access, Guest Editor for MDPI Remote Sensing, and Editor of the Springer book Machine Learning Techniques and Sensor Applications for Human Emotion, Activity Recognition, and Support (ML-SHEARS) . He has also been a Track Chair and Program Committee Member for several international conferences, reflecting his leadership in the academic community. His research is supported by significant grants and collaborative projects, indicating strong institutional and international engagement. He is involved in multiple research teams and projects, including the BatCAT project on battery manufacturing and AI applications in controlled environment agriculture with RIFT LABS AS. His lab work integrates deep learning, sensor fusion, and data analytics for environmental and biological monitoring systems.

K.W. Hippsمشاهده پروفایل

استاد

• Surface Chemistry
• Nanotechnology
• Materials Science
• +۳ مورد دیگر

Professor K.W. Hipps is a Regents Professor of Chemistry and Materials Science and Engineering at Washington State University (WSU). He holds multiple fellowships, including those from the American Chemical Society, American Physical Society, and American Association for the Advancement of Science. His research focuses on surfaces, interfaces, and nanotechnology, utilizing advanced techniques like Scanning Tunneling Microscopy (STM), Transmission Electron Microscopy (TEM), and spectroscopy. His work explores molecular-scale processes, including surface diffusion, electron transfer, and nanoparticle properties. Education: Ph.D. in Chemical Physics from WSU (1978), followed by a postdoc at the University of Michigan. He has authored over 180 publications and received numerous awards, including the Sahlin Eminent Faculty Award and WSU Distinguished Faculty Award. Research Interests: Surface chemistry, nanotechnology, materials characterization, and molecular dynamics. His lab studies interfaces, thin films, and supramolecular assemblies using STM and spectroscopic methods. Scientific Contributions: His STM images have featured on journal covers, and his work on cobalt and copper phthalocyanines demonstrated chemical selectivity in molecular imaging. Students in his group gain expertise in microscopy, spectroscopy, and materials synthesis.

Julia W.P. Hsuمشاهده پروفایل

استاد

• Materials Science
• Nanotechnology
• Photovoltaics
• +۷ مورد دیگر

Dr. Julia W.P. Hsu is a Professor and Texas Instruments Distinguished Chair in Nanoelectronics at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. She holds leadership roles, including Director of the MaSTeR facility and former Associate Head of the Materials Science and Engineering Department. Previously, she served at Sandia National Laboratories (2003–2010), Bell Laboratories (1999–2003), and the University of Virginia (1993–2001). Education: PhD in Physics (Stanford, 1991), MS in Physics (Stanford, 1987), BSE in Chemical Engineering (Princeton, 1985). Research: Focuses on nanomaterials, photovoltaics, interfacial phenomena, and semiconductor nanostructures. Key areas include solution-synthesized materials, low-temperature processing, and device physics. Her work bridges experimental techniques like scanning probe microscopy and industry-relevant applications in energy materials. Notable achievements include pioneering studies on organic-inorganic hybrid systems and contributions to nanofabrication. Awards and Honors: MRS Fellow (2011) APS Fellow (2001) AAAS Fellow (2007) Simons Foundation Pivot Fellow (2023) Advising and Leadership: Supervised over 15 PhD and MS students. Directed the Light Institute of Texas and UT Dallas’ MaSTeR facility, emphasizing interdisciplinary research and industry collaboration. Labs/Teams: Leads the MaSTeR facility for material characterization and collaborates with the Light Institute for optoelectronics research.

• Neuroscience
• Neurobiology
• Cerebellar Plasticity
• +۷ مورد دیگر

Dr. Ting-Feng Lin is an Assistant Professor at the Cell Biology, Neurobiology and Biophysics department within the Faculty of Science at Utrecht University, Netherlands. His research focuses on understanding the mechanisms of learning and memory formation in the cerebellum, particularly how synaptic and intrinsic plasticity mechanisms coordinate to regulate neuronal signaling and behavior. He employs advanced microscopy, optogenetic, and chemogenetic techniques in transparent zebrafish models to study these processes in vivo, with implications for neurodevelopmental disorders like autism spectrum disorder (ASD) and schizophrenia. 2025: Assistant Professor, Utrecht University 2019-2025: Postdoctoral Researcher, University of Chicago 2015-2019: PhD in Neuroscience, Neuroscience Center Zurich (ZNZ) 2010-2014: MS in Physiology, National Taiwan University 2006-2010: BS in Sports Medicine, China Medical University His work investigates how sensory experiences shape cerebellar processing during development, focusing on climbing fiber pathways and their role in sensory prediction errors. His group also studies the interaction between synaptic, intrinsic, and structural plasticity mechanisms in neural circuits, using zebrafish models with genetic modifications (e.g., Grid2 knockout) to model human neurological conditions. Dr. Lin has received scientific recognition including the SfN Trainee Professional Development Award for his work on Purkinje cell plasticity and the JNS Meeting Award for research on parallel fiber ramping activity and LTD. His publications span topics from cerebellar plasticity to voltage-gated K+ channel dynamics, reflecting his interdisciplinary approach to neurobiology.

Michael Lampsonمشاهده پروفایل

استاد

• Cell and Developmental Biology
• Evolution
• Cell biology of meiotic drive
• +۷ مورد دیگر

Michael Lampson is Professor of Biology at the University of Pennsylvania's School of Arts and Sciences, with secondary appointments in the Department of Cell and Developmental Biology. He serves as faculty in the Cell and Molecular Biology (CAMB) and Biochemistry and Molecular Biophysics (BMB) Graduate Groups, and is affiliated with the American Society for Cell Biology (ASCB). Ph.D., Cornell University, Weill Medical College, 2002 AB, Harvard College, 1994 Dr. Lampson's research program focuses on fundamental mechanisms of chromosome biology, with particular emphasis on cell division, centromere inheritance, and meiotic drive. His lab investigates how selfish genetic elements can violate Mendel's First Law through meiotic drive, the stability of centromere chromatin through the germline, and the role of repetitive satellite DNA in chromosome segregation. Using innovative approaches including mouse model systems, optogenetic tools, and biochemical techniques, his work bridges cell biology, genetics, and evolutionary biology to address questions with implications for reproductive biology, cancer, and genetic inheritance. Analysis of Dr. Lampson's recent publications reveals a strong focus on the intersection of centromere biology, meiotic drive, and chromosome segregation mechanisms. His work increasingly incorporates computational approaches alongside experimental systems to study evolutionary aspects of centromere function. The research demonstrates consistent innovation in methodology, particularly in developing optogenetic tools for precise manipulation of cellular processes. Key themes include the role of satellite DNA variation, mechanisms of non-Mendelian inheritance, and the stability of chromatin structures through cell division and development. Searle Scholar Award American Association for the Advancement of Science (AAAS) fellow Dr. Lampson's research is supported by multiple NIH grants including from NIGMS, NHGRI, NICHD, and NCI, as well as University of Pennsylvania funding sources including the University Research Foundation, Abramson Cancer Center, and several specialized research centers. He collaborates extensively with researchers across disciplines, including Ben Black (Biochemistry), Dennis Discher (Chemical Engineering), Dave Chenoweth (Chemistry), and Roger Greenberg (Cancer Biology), reflecting the interdisciplinary nature of his work. His lab has trained numerous graduate students and postdocs who have gone on to successful careers in academia and industry. The Lampson Lab maintains state-of-the-art facilities for cell biological, genetic, and biochemical research, with specialized equipment for live-cell imaging, optogenetic manipulation, and mouse genetics. The lab fosters a collaborative environment that bridges molecular, cellular, and evolutionary perspectives on chromosome biology.

Achim Mengesمشاهده پروفایل

استاد پژوهشی

• Computational Design
• Robotic Construction
• Biomimetic Architecture
• +۵ مورد دیگر

Achim Menges is a Research Professor and Max Planck Fellow at the University of Stuttgart, where he directs the Institute for Computational Design and Construction (ICD). His work bridges architecture, engineering, and computational design, with a focus on developing innovative construction methods and materials. Menges leads the Cluster of Excellence IntCDC: Integrative Computational Design and Construction for Architecture, a major research initiative funded by the German Research Foundation. Menges' research centers on computational design, robotic construction, and biomimetic architecture, with particular emphasis on timber construction, adaptive building systems, and digital fabrication. His work integrates principles from bionics to create responsive, sustainable building systems that adapt to environmental conditions. Notable projects include the BUGA Wood Pavilion (2019), Urbach Tower, BUGA Fibre Pavilion, and the livMatS Biomimetic Shell, all demonstrating his commitment to material innovation and sustainable construction practices. His recent publications reveal a consistent focus on advancing timber construction techniques, developing bio-inspired responsive systems, and implementing robotic fabrication processes. The research shows a clear trajectory toward more sustainable, resource-efficient building methods that integrate digital design with physical construction processes. Menges' work increasingly addresses multi-story timber systems and circular construction principles. Bauwende Prize der Universität Stuttgart 2025 Menges leads numerous research initiatives through the Cluster of Excellence IntCDC, securing significant funding for projects exploring computational design and robotic construction. His work involves extensive collaboration with industry partners and interdisciplinary research teams. Menges directs the ICD research laboratory, which focuses on developing novel computational design methods, robotic fabrication processes, and innovative material systems for architecture. The institute maintains strong partnerships with industry leaders in construction technology and materials science, facilitating the translation of research into practical applications.

Qing Caoمشاهده پروفایل

دانشیار

• Nanomaterials
• Electronic Devices
• Optoelectronic Devices
• +۵ مورد دیگر

Qing Cao is an Associate Professor of Materials Science and Engineering at the University of Illinois at Urbana-Champaign, with courtesy appointments in Chemistry and Electrical Engineering. He leads the Cao Research Group within the Grainger College of Engineering and serves as Deputy Editor of Science Advances. Dr. Cao received his B.S. in Chemistry from Nanjing University in 2004 and his Ph.D. in Materials Chemistry from the University of Illinois at Urbana-Champaign in 2009. After working for 9 years as a research scientist at IBM Thomas J. Watson Research Center, he returned to UIUC in 2018 as a faculty member. His research focuses on developing functional nanomaterials for unconventional electronic systems, high-performance logic devices, and low-cost energy harvesting. The Cao Research Group specifically works on: nanoelectronic devices based on novel nanomaterials; next-generation memory devices for neuromorphic and in-memory computing; monolithic 3D integration for high performance electronics; high-performance printable electronic materials; and bioelectronics for healthcare applications. His work bridges materials science, chemistry, electrical engineering, and device physics. Analysis of Dr. Cao's recent publications reveals a strong focus on electrochemical memory devices for neuromorphic computing, with significant work on carbon nanotube-based electronics and novel nanomaterials. His 2023 Nature Electronics paper on CMOS-compatible electrochemical synaptic transistors demonstrates his leadership in developing hardware solutions for deep learning acceleration. His research trajectory shows a progression from fundamental carbon nanotube device physics to more applied systems for computing and sensing applications. IBM Pat Goldberg Memorial Best Paper Award (2017) IBM Master Inventor Award (2016) MIT Technology Review TR35 (2016) Forbes '30 Under 30' (2012) and 'Most Influential All-Star Alumni' (2016) Atlantic Council Millennium Fellow (2017) US Frontiers of Engineering by National Academy of Engineering (2016, 2019) 17 IBM Invention Achievement Awards (2011-2018) Dr. Cao has secured significant research funding including NSF grants 1950182 and 2139185. His research group actively recruits graduate students and postdoctoral researchers to work on cutting-edge materials and device projects. His work has resulted in over thirty research papers and fifty patents and patent applications. He teaches graduate courses including MSE 403 (Synthesis of Materials), MSE 460 (Electronic Materials I), and MSE 488 (Optical Materials). The Cao Research Group operates within the University of Illinois' world-class facilities including the Frederick Seitz Materials Research Laboratory and Holonyak Micro and Nanotechnology Laboratory. His research has received support from NSF, DoD, DOE, and industry partners including TSMC. The group's recent $2 million project focuses on developing technology to help mobile devices learn and adapt to their surroundings.

Pim de Vinkمشاهده پروفایل

پژوهشگر

• Supramolecular Chemistry
• Chemical Biology
• Protein-Protein Interactions
• +۳ مورد دیگر

Pim de Vink is a doctoral researcher at Eindhoven University of Technology , affiliated with the Biomedical Engineering department and Chemical Biology group. Supervised by dr. L.-G. Milroy and prof. L. Brunsveld , his work bridges supramolecular chemistry and chemical biology , focusing on host/guest chemistry for protein complex modulation. Education: B.Sc. in Chemistry (2014) from University of Amsterdam M.Sc. in Biomedical Engineering (2016) from TU/e Internship at Max Planck Institute for Molecular Physiology (2016) on gold-catalyzed synthesis Research Themes: His research develops switchable cucurbituril-based systems for light-controlled enzyme activation and artificial signaling networks. Key areas include protein-protein interaction stabilization , thermodynamic modeling , and allosteric nuclear receptor modulation . Publication Trends: Across JACS , Chemical Science , and RSC Chemical Biology , his work from 2017–2023 emphasizes supramolecular tools for biochemical applications. Notable contributions include 100-fold affinity enhancement of 14-3-3 ligands and UV-responsive cucurbituril release mechanisms . Grants: Funded by Netherlands Organization for Scientific Research (NWO) through Gravity program 024.001.035 and VICI grant 016.150.366.

George Britovsekمشاهده پروفایل

استاد

• Catalysis
• Sustainable Carbon Management
• Transition Metal Complexes
• +۳ مورد دیگر

Professor George Britovsek (FRSC) is a leading figure in catalysis and sustainable carbon management at Imperial College London . As Director of the MRes in Catalysis & Engineering and Head of Teaching in Inorganic Chemistry, he bridges academic leadership with cutting-edge research. His work focuses on transition metal complexes for converting ethylene , alkanes , biomass , and CO₂ into valuable chemicals and fuels through industrial collaborations. Education : M.Sc. (Technical University of Aachen, 1990), Ph.D. (Aachen, 1993) under Prof. W. Keim Postdoctoral Training : University of Tasmania (1994-1996), Imperial College London (1996-2000) His research interests span: Selective oxidation of alkanes using bio-inspired iron complexes Alkene conversions to functional polymers via novel catalysts CO₂ valorization into polymers and cyclic carbonates Biomass-derived feedstocks for chemical synthesis Recent catalysis trends highlight his work on: Designing Fe-N/C catalysts for epoxidation Developing PN3P pincer ligands for H₂ activation Creating degradable polyethylene via iron-catalyzed chain growth Modeling alternating α-olefin distributions in chromium systems Awards : Fellow of the Royal Society of Chemistry (FRSC) Students & Collaborators actively engage in: Photocatalytic polymer degradation Electrocatalytic CO₂ conversion Functionalized polymeric materials 3D-printed catalytic scaffolds His Britovsek Research Group operates at the Molecular Sciences Research Hub, White City Campus, advancing both homogeneous and heterogeneous catalysis through experimental and computational approaches.

Chuang Ganمشاهده پروفایل

استادیار

• Artificial Intelligence
• Robotics
• Computer Vision
• +۷ مورد دیگر

Chuang Gan is an Assistant Professor at the University of Massachusetts Amherst, affiliated with the College of Information and Computer Sciences and the Department of Computer Science. His work focuses on advancing artificial intelligence, robotics, computer vision, and embodied agents through interdisciplinary research combining neural networks, physical simulations, and multimodal learning. Research interests include generative models, reinforcement learning, vision-language integration, and scalable autonomous systems. He explores topics like world modeling for robots, adaptive policy learning, and physics-driven AI. His projects often involve creating systems that learn from visual, auditory, and tactile inputs to perform complex tasks such as object manipulation, navigation, and decision-making in dynamic environments. Recent research trends emphasize embodied AI systems capable of long-horizon planning, compositional reasoning, and efficient learning from limited data. His work bridges theory and practice, with applications in robotics, simulation platforms, and multimodal generation. Key contributions include frameworks for 3D scene understanding, adaptive world models, and novel training paradigms for large language models. His research has been applied to robotics platforms like RoboDreamer and UBSoft, focusing on unbounded soft environments. Collaborations involve designing benchmarks for physical scene understanding (e.g., Physion++), and creating tools like DiffTactile for tactile simulation. His work often integrates principles from differential geometry, PDE dynamics, and game theory. Chuang Gan’s research group develops open-source tools and benchmarks, such as the SoftZoo robot co-design platform and the SOK-Bench situated reasoning benchmark. His team emphasizes scalable alignment methods beyond human supervision and explores ethical AI through principles like symmetry-enhanced training.