جست‌وجوی استاد و پژوهشگر

Xing-Dong Yangمشاهده پروفایل

دانشیار

• Human-Computer Interaction (HCI)
• Wearable Computing
• Interactive Systems Design
• +۵ مورد دیگر

Xing-Dong Yang is an Associate Professor of Computer Science at Simon Fraser University (SFU) and holds an adjunct appointment as Assistant Professor at Dartmouth College. He directs the XDiscovery Lab and focuses on Human-Computer Interaction (HCI), particularly in developing interactive systems for smart everyday objects such as wearables, garments, and appliances. His research emphasizes accessibility for visually impaired users and prototyping tools for non-specialists. He earned his PhD from the University of Alberta, following degrees from the University of Manitoba and University of Alberta. Affiliations: Simon Fraser University (School of Computing Science), Dartmouth College (Adjunct) Education: PhD, Computer Science, University of Alberta MS, Computer Science, University of Alberta BS, Computer Science, University of Manitoba His research explores novel interactive systems, including tactile interfaces for education, assistive technologies for visual impairments, and innovative input methods for wearables. Key projects include MakeBronze (cultural preservation through interactive crafts), AccessibleCircuits (inclusive electronics for blind users), and systems like iWood and MicroFluID that merge materials science with HCI. His work has been recognized with awards such as the Best Paper Award at UIST'19 and multiple Honorable Mentions at CHI and UIST conferences. He advises a dynamic team of PhD and MSc students, emphasizing hands-on prototyping and industry collaborations through internships at companies like Google, Microsoft, and Apple. Yang has secured grants including an NSF CRII grant for device modulation and an NSF CSR Large grant for health-focused earpiece technology. His lab fosters interdisciplinary innovation, bridging computer science with design, engineering, and cultural studies.

Serhat Hosderمشاهده پروفایل

استاد

• Computational aerothermodynamics
• Hypersonic flows and technologies
• Uncertainty quantification
• +۶ مورد دیگر

Dr. Serhat Hosder is the James A. Drallmeier Centennial Professor in the Department of Mechanical and Aerospace Engineering at Missouri S&T. He serves as Director of the Aerospace Simulations Laboratory, focusing on computational aerothermodynamics, hypersonic flow modeling, and uncertainty quantification for planetary entry systems. Professor of Aerospace Engineering (2019–present) Director, Aerospace Simulations Lab Advisor to students receiving NASA Space Technology Research Fellowships and Amelia Earhart Fellowships Research funded by NASA, DoD, and NSF Research Interests: Computational aerothermodynamics, hypersonic flow modeling, uncertainty quantification, multi-fidelity methods, directed energy applications, planetary entry systems, and aerodynamic shape optimization. His work combines numerical methods with robust design principles for high-speed vehicles. Scientific Awards: Missouri S&T Outstanding Faculty for Contributions to Graduate Studies Award (2022) Fellow of the Royal Aeronautical Society (2021) NASA Langley Research Center Henry J. E. Reid Award (2018) Associate Fellow of AIAA (2017) Missouri S&T Faculty Research Awards (2015, 2012) Advising & Grants: His students have secured positions at NASA, Sandia National Labs, and academia. Research funded by DoD Joint Hypersonics Transition Office, NASA (Langley, JPL), Missile Defense Agency, NSF, and industry partners like M4 Engineering, Inc.

Salvatore Livatinoمشاهده پروفایل

دانشیار

• Immersive Systems
• Virtual Reality (VR)
• Augmented Reality (AR)
• +۷ مورد دیگر

Salvatore Livatino is an Associate Professor in Virtual Reality and Robotics at the University of Hertfordshire, UK. He holds a MSc in Computer Science from the University of Pisa (1993) and a PhD in Computer Science and Engineering from Aalborg University, Denmark (2003). His academic journey includes roles as Research Fellow and Associate Professor at Aalborg University, as well as visiting positions at institutions like INRIA Grenoble and the University of Edinburgh. He leads the Communications and Intelligent Systems research group and directs the Virtual Reality and Robotics Laboratory. His research focuses on immersive technologies (VR/AR/XR), stereoscopic 3D visualization, and teleoperation systems for applications in robotics, healthcare, and command-and-control interfaces. He has contributed to over 30 peer-reviewed publications and secured funding for projects such as the Innovate UK-backed 'iDOC: AI Empowered Document Authoring' (2023–2025) and 'Immersion for Care: Using Extended Reality in Healthcare Training' (2025–2027). Teaching expertise includes problem-based learning, 3D visualization, and immersive game design. His work spans interdisciplinary collaborations in robotics, AI, and healthcare, emphasizing practical applications of virtual environments.

• Statistics
• High-Dimensional Data Analysis
• Statistical Genetics
• +۷ مورد دیگر

Aaron J Molstad is an Assistant Professor in the Department of Statistics at the University of Minnesota – Twin Cities, within the College of Science and Engineering. His research lies at the intersection of statistical methodology and genomic data science, with a focus on developing rigorous and scalable methods for modern high-dimensional datasets. His research interests include high-dimensional statistics, covariance and precision matrix estimation, regression modeling with structured responses, variable selection, and integrative analysis of omics data. He develops methods tailored for compositional data, multivariate responses, and ancestry-specific genetic association studies, contributing to both theoretical statistics and public health applications. The recent publications and funded projects highlight a strong trend in developing objective, reliable, and heterogeneous-aware statistical frameworks for genomics and biomedicine. His work emphasizes methodological innovation with direct applicability to complex biological data, particularly in diverse populations and multi-omics integration. Awarded grants from the National Science Foundation and the National Institutes of Health demonstrate recognition of his research’s significance and impact. These include projects on inference from omics data, new regression models for categorical responses, and integrative genomics in African American populations. Objective and reliable methods for inference from modern omics data (NSF, 2024–2027) Collaborative Research: New Regression Models for Multiple Categorical Responses (NSF, 2024–2025) Integrative Genomics into Genetic Association Studies of Blood Pressure and Stroke in African Americans (NIH/Fred Hutchinson, 2023–2024) Dr. Molstad advises and collaborates on major genomic studies involving protein expression, blood pressure, stroke, and ancestry-specific effects. While specific PhD students are not listed, his role as Principal Investigator on multiple grants indicates mentorship of graduate researchers and postdoctoral scholars. He is also active in the broader statistical community, with publications in top-tier journals such as Biometrika , Biometrics , and Genome Biology .

Fangneng Zhanمشاهده پروفایل

پژوهشگر ارشد

• Computer Science
• Artificial Intelligence
• Neural Rendering
• +۷ مورد دیگر

Currently a Research Fellow at Harvard University & MIT , Fangneng Zhan specializes in Neural Rendering and Generative AI . His research focuses on developing evolutive rendering frameworks, 3D-aware generative models, and multimodal synthesis techniques. Previously, he was a postdoctoral researcher at the Max Planck Institute for Informatics under Prof. Christian Theobalt. He earned his Ph.D. in Computer Science & Engineering from Nanyang Technological University, Singapore and a Bachelor's in Communication Engineering from the University of Electronic Science and Technology of China . His work spans 3D reconstruction, robotics applications , and lighting estimation , with significant contributions to SIGGRAPH , NeurIPS , and CVPR conferences. Recent research highlights include evolutive gauge transformations for neural fields, generalizable 3D style transfer via Gaussian splatting, and multimodal synthesis frameworks leveraging pre-trained models like CLIP and Stable Diffusion. He has co-authored Top50 Popular Paper in TPAMI 2023 and organized workshops at CVPR 2024 on generative models. Scientific Awards: Top50 Popular Paper, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2023 Collaborative Network: Mentored students at institutions like Harvard, NTU, and ETH Zurich. His projects include datasets for lighting estimation and real-time scene text detection systems.

• Computer Vision
• Robotics
• Human-Computer Interaction
• +۴ مورد دیگر

Włodzimierz Kasprzak is a Professor at the Institute of Control and Computation Engineering, Faculty of Electronics and Information Technology, Warsaw University of Technology. His research focuses on computer vision, robotics, human-computer interaction, and machine learning. He has contributed to advancements in human action classification, skeleton-based feature analysis, and multimodal interface design. Research Highlights: Development of lightweight classification models for human actions in video using skeleton-based features. Advances in multi-stream fusion techniques for image and video analysis. Design of embodied agent systems for cybersecurity event visualization and control. Awards and Recognition: 2024: Individual First Class Rector's Award for Scientific Achievements (2022-2023) 2021: Medal of the Commission of National Education 2011: Golden Cross of Merit His work integrates theoretical contributions with practical applications in robotics, surveillance systems, and human-centered technologies.

Michal Piovarciمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Computational Fabrication
• Haptic Reproduction
• +۳ مورد دیگر

Michal Piovarci is a Researcher (Postdoc) at ETH Zurich's Computational Design Lab led by Bernd Bickel. He holds a Ph.D. from USI Lugano (2020) under Piotr Didyk, receiving the Eurographics PhD Award for his thesis on Perception-Aware Computational Fabrication. His research focuses on computer graphics, computational fabrication, and haptic/appearance reproduction, emphasizing perception-driven solutions. Education: Ph.D., USI Lugano (2020) Previous postdoc at ISTA's Visual Computing Group Research interests include 3D Printing Innovations Haptic Feedback Systems Material Perception Modeling Directional Surface Design Professional Activities: Area chair at ACM Symposium on Computational Fabrication (2024), program committee roles at SIGGRAPH, SAP, and Eurographics. Organized Computational Fabrication Seminars (2021-2022). Grants: SNSF Project Funding (CHF 1M, 2025-2029) and FWF Lise Meitner Grant (2022-2023). Teaching: Taught Scientific Machine Learning for Design (ETH Zurich, 2024) Computational Fabrication (TU Wien, 2022)

• Electric Power Conversion
• Electromagnetic Devices
• Wireless Power Transfer
• +۲ مورد دیگر

Chi-Kwan Lee is a Professor at the University of Technology Sydney (UTS), School of Electrical and Data Engineering since 2024. Previously, he held roles including Associate Professor (2018-2023) and Assistant Professor (2012-2017) at the University of Hong Kong. He earned his B.Eng. and Ph.D. in Electronic Engineering from City University of Hong Kong (1999 and 2004). His research focuses on electric power conversion, electromagnetic devices, wireless power transfer, renewable energy, and smart grid technologies. He was a Visiting Researcher at Imperial College London (2010-2020). Research Highlights: Prof. Lee has pioneered advancements in wireless power transfer for medical devices (e.g., capsule endoscopy) and electric vehicles, with breakthroughs in efficiency optimization and misalignment mitigation. His work on hybrid stepper motor systems and magnetoresistive sensors addresses challenges in contactless actuation and high-voltage current sensing. Awards & Contributions: A Senior Member of IEEE and recipient of the 2015 IEEE Power Electronics Society Transactions First Prize Paper Award. He serves on IEEE PELS committees and editorial boards of key journals like IEEE Transactions on Power Electronics. Grants & Labs: Active in funded research projects related to wireless charging systems, smart grids, and renewable energy integration. His work spans academic collaborations, industry partnerships, and international conferences.

• Robotics
• Human-Robot Interaction (HRI)
• Artificial Intelligence
• +۳ مورد دیگر

Marc Hanheide is a Professor of Intelligent Robotics and Interactive Systems at the University of Lincoln 's School of Computer Science. With a career spanning EU projects like VAMPIRE, COGNIRON, CogX, and STRANDS, his work focuses on long-term robotic behavior, human-robot spatial interaction, and cognitive system architectures. He has secured over 12 major grants from organizations including EPSRC, BBSRC, and the European Commission. Key Research Areas : Autonomous robotics, HRI, AI, cognitive systems, agricultural robotics Current Projects : STRANDS (long-term behavior), AgriFoRwArdS (robotics training), NCNR (nuclear robotics) Major Contributions : Human-aware navigation modules, topology optimization for robot fleets, causal analysis frameworks Scientific Awards: While no specific awards are listed, his numerous EPSRC grants and leadership in multi-institutional projects highlight his impact. He has over 172 publications and collaborates with institutions like CoR-Lab and CITEC.

• Artificial Intelligence
• Explainable AI (XAI)
• Green AI
• +۱۲ مورد دیگر

Dr Andrew Starkey is a Reader in the School of Engineering at the University of Aberdeen, where he also completed his PhD in 2001. He holds an Honours degree in Applied Mathematics from the University of St Andrews. He is actively involved in research and currently accepting PhD students in Engineering. His work bridges academia and industry, with a focus on AI applications in engineering, bioinformatics, and geosciences. University: University of Aberdeen School: School of Engineering Academic Rank: Reader Email: a.starkey@abdn.ac.uk Phone: +44 (0)1224 272801 Dr Starkey's research centers on Explainable AI (XAI) , Green AI , and Autonomous AI , with applications in robotics, econometrics, bioinformatics, seismic data analysis, and virtual reality. He has developed novel methods for feature selection, autonomous learning, and knowledge abstraction from agent-environment interactions. His work emphasizes low computational cost and transparency in AI systems. The most recent publications reflect a strong trend in applying AI to complex real-world problems, including digital rock technology, robotic grasping, real-time event detection, and medical data analysis. His interdisciplinary research combines machine learning with domain-specific knowledge in engineering and life sciences, often resulting in practical, industry-ready solutions. Millennium Product Award John Logie Baird Award for Innovation Enterprise Fellowship from Royal Society of Edinburgh and Scottish Enterprise Dr Starkey has supervised multiple research projects and secured funding from major bodies including EPSRC, BBSRC, and industry partners. His past work on the GRANIT project led to the development of AI-based condition monitoring for ground anchorages, resulting in commercialization through BlueFlow Ltd. He has collaborated with researchers across disciplines, including Dr Alasdair MacKenzie (bioinformatics), Dr Anne Schwab (seismic analysis), and Dr David Hazlerigg (genomics). He leads research in AI-driven engineering solutions and is the CEO of BlueFlow Ltd, a spinout company commercializing AI technologies developed at the University of Aberdeen. His lab focuses on developing autonomous, explainable, and environmentally sustainable AI systems for real-world deployment.

• Digital Circuits and Systems
• Energy-Efficient Circuits and Systems
• Embedded Systems
• +۷ مورد دیگر

Massimo Poncino is a Full Professor at the Department of Control and Computer Science (DAUIN) within the Faculty of Engineering at Politecnico di Torino. He serves as Scientific Advisor for the STMicroelectronics partnership and coordinates basic engineering subjects. A Senior Member of IEEE since 2012 and Fellow since 2012, he has served on editorial boards for IEEE Transactions on Computer-Aided Design, IEEE Design & Test of Computers, and ACM Transactions on Design Automation. Education: Laurea in Electronic Engineering (1989) and PhD in Computer and Systems Engineering (1993) from Politecnico di Torino Academic Career: Visiting Scientist University of Colorado (1993-1994), Researcher at Politecnico di Torino (1995-2001), Associate Professor at University of Verona (2001-2004), Full Professor at Politecnico di Torino (2006-present) His research focuses on energy-efficient digital systems , including design automation of SoCs, hardware-aware AI, battery management, cyber-physical systems, and embedded systems. Recent publications highlight advancements in digital twins for batteries , low-power neural network deployment , and IoT privacy . Scientific Awards: Recognition of Service Award - ACM (2013) Certificate of Appreciation - IEEE Circuits and Systems Society (2006, 2008, 2009) IEEE Fellow (2012-) Research Involvement: EU H2020, VI/VII Framework Programs evaluator Scientific Director for projects: Approxim@ction, EMBAI, DISLO-MAN, DAMASCO Member of EDA research group Teaching: Course director for Energy Management for IoT (2019-2025) Lecturer for Computer Science courses (2003-2025)

Daniel Hernández de la Iglesiaمشاهده پروفایل

پژوهشگر

• Internet of Things (IoT)
• Multi-Agent Systems
• Artificial Intelligence
• +۳ مورد دیگر

Daniel Hernández de la Iglesia is a researcher at the University of Salamanca , affiliated with the School of Informatics and the Department of Computer Science and Artificial Intelligence . He completed his PhD at the University of Salamanca in 2018 with the thesis titled "Embedding smart software agents in resource constrained internet of things devices." Research Focus: Specializes in integrating Multi-Agent Systems and IoT for sustainable applications, including electric vehicle optimization, battery reuse, and smart urban solutions. Academic Contributions: Published extensively on AI-driven energy management, smart mobility, and ethical implications of technology. Key Trends in Publications (2022-2025): His work spans IoT , Artificial Intelligence , and Sustainable Mobility , with a focus on electric vehicle battery health, strategic management in digitalization, and ethical considerations in technology. Collaboration: Supervised by Dr. Gabriel Villarrubia González and Dr. Juan Francisco de Paz Santana , his research bridges academic rigor with real-world applications in smart systems and renewable energy.

• Materials engineering
• Mechanical engineering
• Machine learning
• +۱۲ مورد دیگر

Professor Nick Birbilis serves as the Executive Dean of the Faculty of Science Engineering and Built Environment at Deakin University. With a distinguished career spanning materials science, corrosion engineering, and machine learning applications, he leads one of Australia's most innovative academic faculties. His research has significantly impacted the fields of materials engineering, particularly in corrosion science, alloy development, and advanced manufacturing techniques. Professor Birbilis's educational background includes a Doctor of Philosophy, Graduate Certificate of Higher Education, and Bachelor of Engineering (with Honours) in Materials Engineering, all from Monash University. His research interests span materials engineering, mechanical engineering, machine learning, metals and alloy materials, electrochemistry, and glass technology. His recent publications demonstrate a strong focus on the intersection of traditional materials science with cutting-edge computational approaches. The research trends show increasing integration of machine learning techniques for alloy design and property prediction, alongside continued fundamental work on corrosion mechanisms in advanced materials including multi-principal element alloys, magnesium alloys, and additively manufactured components. Fellow, ASM International (2022) Fellow, Engineers Australia (2021) Fellow, International Society of Electrochemistry (2020) H.H. Uhlig Award, The Electrochemical Society (2020) Batterham Medal, Academy of Technological Sciences and Engineering (2017) Lee Hsun Award, Chinese Academy of Science (2015) Professor Birbilis currently supervises multiple doctoral students working on cutting-edge projects including sustainable engineering models, 3D printed glass behavior, corrosion-resistant coatings, and biomolecular extraction techniques. His research is supported by significant grants from the Australian Research Council, Department of Education, Office of Naval Research USA, and industry partners including Advanced Alloy Holdings, InfraBuild, and Bluescope Steel. These projects focus on hydrogen economy applications, corrosion-resistant alloys, advanced protective coatings, and steel innovation.

• Artificial Intelligence
• Smart Manufacturing
• Fault Diagnosis
• +۶ مورد دیگر

Dr. M M Manjurul Islam is a Research Associate in Artificial Intelligence for Smart Manufacturing at Ulster University's School of Computing, Engineering and Intelligent Systems. His research focuses on applying advanced AI techniques to solve critical challenges in manufacturing systems, with particular expertise in fault diagnosis, predictive maintenance, and semiconductor production optimization. His research interests span Artificial Intelligence , Smart Manufacturing , Fault Diagnosis , Machine Learning , Deep Learning , Predictive Maintenance , and Semiconductor Manufacturing . He has made significant contributions to the application of convolutional neural networks, support vector machines, and generative adversarial networks in industrial settings, particularly for bearing fault diagnosis and wafer defect classification. Dr. Islam's recent publications (2023-2025) demonstrate a strong focus on practical AI applications in manufacturing, with multiple chapters in the Springer Series in Advanced Manufacturing. His work shows an evolving trajectory from traditional machine learning approaches to more sophisticated deep learning and explainable AI techniques, with increasing emphasis on semiconductor manufacturing challenges and trustworthy AI systems. His research contributes to UN Sustainable Development Goals, particularly in industrial innovation and infrastructure. He is an active member of professional organizations including IEEE and Advance HE, serving as Chair for both networks. According to Scopus data, Dr. Islam has accumulated 1,706 citations with an h-index of 16, reflecting the impact of his research in the field. His publication record shows consistent productivity, with research outputs spanning from 2015 to anticipated publications in 2025.

Andrés Bruhnمشاهده پروفایل

استاد

• Computer Vision
• Optical Flow
• Scene Flow
• +۵ مورد دیگر

Andrés Bruhn is a Professor for Intelligent Systems and Dean of Computer Science Studies at the University of Stuttgart, where he leads research in the Institute for Visualization and Interactive Systems (VIS). His academic career spans over a decade with significant contributions to computer vision, particularly in optical flow, scene flow, and motion estimation. As Dean of Studies, he oversees academic programs while maintaining an active research agenda focused on cutting-edge computer vision problems. Bruhn's research interests center around computer vision with emphasis on optical flow estimation, scene flow, motion analysis, and adversarial machine learning. His work bridges theoretical foundations with practical applications, developing algorithms that address real-world challenges in motion estimation, image processing, and visual understanding. His research group has pioneered approaches that combine variational methods with deep learning, creating robust systems for motion analysis that can withstand adversarial attacks and challenging environmental conditions. The publication record demonstrates a strong focus on advancing the state-of-the-art in motion estimation, with recent work exploring adversarial attacks on optical flow systems, high-resolution datasets for benchmarking, and multi-frame fusion techniques. His research shows consistent innovation, moving from traditional variational methods to modern deep learning approaches while maintaining mathematical rigor. The work spans both theoretical contributions and practical implementations with real-world applicability. Bruhn has mentored numerous researchers who appear as first authors on publications, including Jenny Schmalfuss, Lukas Mehl, and Azin Jahedi, indicating his commitment to developing the next generation of computer vision researchers. His leadership role as Dean of Studies demonstrates institutional recognition of his expertise and administrative capabilities.