جست‌وجوی استاد و پژوهشگر

Peyman Moghadamمشاهده پروفایل

استاد مدعو

• Embodied AI
• Robotics
• Computer Vision
• +۵ مورد دیگر

Peyman Moghadam is a Principal Research Scientist at CSIRO Data61 and an Adjunct Professor at Queensland University of Technology (QUT). He leads the Embodied AI Research Cluster at CSIRO, focusing on robotics and machine learning intersections. His roles include former Group Leader of Robotic Perception and Acting Leader of the Spatiotemporal AI portfolio within CSIRO's MLAI Future Science Platform. Education: PhD in Robotics from Nanyang Technological University (2012). Professional experiences include Visiting Professorships at ETH Zurich (2022) and University of Bonn (2019), alongside leadership in multidisciplinary projects. Research interests span self-supervised learning, embodied AI, 3D perception, and agricultural robotics. Awards include CSIRO's Julius Career Award, Collaboration Medal, and national/state iAwards for innovation in robotics. He has held adjunct roles at QUT and the University of Queensland. Current roles emphasize AI-driven solutions for scientific challenges, such as Great Barrier Reef conservation and autonomous systems in agriculture. Key projects include the DARPA Subterranean Challenge (2nd place), Hovermap LiDAR technology, and collaborations with industry partners like Emesent and Georgia Tech. His work bridges foundational research with real-world applications in mining, agriculture, and environmental monitoring.

Howard I. Scherمشاهده پروفایل

استاد

• Prostate Cancer Research
• Medical Oncology
• Biomarker Development
• +۵ مورد دیگر

Howard I. Scher, MD is a Professor of Medicine at Weill Cornell Medical College and holds the D. Wayne Calloway Chair in Urologic Oncology. He previously served as Chief of the Genitourinary Oncology Service at Memorial Sloan Kettering Cancer Center (MSKCC) for 25 years. His expertise lies in treating advanced prostate cancer and developing targeted therapies and biomarkers like circulating tumor cell analysis. He leads major initiatives including the Prostate Cancer Clinical Trials Consortium and the NCI-sponsored Prostate Cancer SPORE program. Scher has authored over 430 peer-reviewed articles and co-authored Principles and Practice of Genitourinary Oncology . His research focuses on androgen receptor signaling, novel imaging modalities, and clinical trial design. Awards include the Donald S. Coffey-Prostate Cancer Foundation Physician-Scientist Award and repeated recognition as a Top Doctor by Castle Connolly. He serves on editorial boards of journals like New England Journal of Medicine and Nature . Key contributions include standardizing phase II clinical trials for prostate cancer and developing the Clinical States Model to guide treatment. His work integrates basic science with clinical practice, emphasizing translational research to improve patient outcomes.

Georgios Anagnostopoulosمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Optimization
• +۴ مورد دیگر

Georgios C. Anagnostopoulos is a tenured Associate Professor at Florida Institute of Technology's College of Engineering and Science, Department of Electrical Engineering and Computer Science. He leads the Machine Learning Research Group and co-directs the Center for Advanced Data Analytics & Systems (CADAS). Ph.D. in Electrical Engineering (University of Central Florida, 2001) M.S. in Electrical Engineering (University of Central Florida, 1997) Eng. Dipl. in Electrical Engineering (University of Patras, Greece, 1994) His research spans foundational AI/ML with applications in social network dynamics, environmental monitoring, and cybersecurity. Key contributions include: Information diffusion modeling via self-exciting processes Deep learning for nuclear explosion detection and flood hazard assessment Transformer-based edge computing for environmental sound classification Multi-task learning with Rademacher complexity analysis Multi-domain cyber-physical systems analysis Recent publications focus on optimization algorithms for social network analysis, flood prediction in ungauged basins, and acoustic gunshot detection systems. He has secured over $3 million in federal funding, including grants from DARPA and the Defense Threat Reduction Agency. Scientific awards held by his mentees include: Barry Goldwater Scholarship (Joey Velez-Ginorio) NSF Graduate Research Fellowship (multiple recipients) Frost Scholarship (Oxford University) UCF Distinguished Undergraduate Researcher Award He has advised over 8 graduate students, including Ph.D. researchers in machine learning and software engineering now employed at Google, Twitter, Expedia Group, and pursuing doctoral studies at University of Pennsylvania. His group maintains active collaborations with Air Force Research Laboratory and University of Central Florida.

Franklin Westمشاهده پروفایل

استاد

• Stem Cell Biology
• Neural Injury Therapies
• Regenerative Medicine
• +۵ مورد دیگر

Franklin West is a Professor in the Department of Animal and Dairy Science at the University of Georgia , with joint appointments at the Regenerative Bioscience Center . He leads the Translational Neural Repair and Regeneration Laboratory, focusing on stem cell therapies for neural injuries. Education: B.S. in Biology (Morehouse College), Ph.D. in Animal Sciences (University of Georgia) Grants: Over $4 million from DoD/NIH for electromagnetic radiation effects on neural networks; $3.6 million from NINDS for MSC extracellular vesicle studies in TBI His research pioneers induced pluripotent stem cell (iPSC) applications in traumatic brain injury and stroke , developing the first U.S. swine stroke model and chimeric pigs from iPSCs. Recent work explores gut-brain axis interactions , nanoparticle therapies , and functional connectivity mapping in piglet models. Scientific Awards include: NIH/National Science Foundation-funded projects Georgia Trends Top 40 Under 40 (2010) 40 Under 40 Class (2020) Young Alumni Award (2019) He serves on the University of Georgia Research Foundation and NIH Development Study Section, with 122+ scholarly works in journals like Cell , Stem Cells , and Scientific Reports .

• Optimizing compilers
• High performance computing
• Embedded systems
• +۷ مورد دیگر

Jagannathan Ramanujam serves as the John E. and Beatrice L. Ritter Distinguished Professor in the Division of Electrical & Computer Engineering at Louisiana State University's School of Electrical Engineering and Computer Science. With a Ph.D. from The Ohio State University (1990), his academic career spans over three decades of research and teaching in computer science and engineering disciplines. Dr. Ramanujam's research trajectory demonstrates a significant evolution from foundational computer science to cutting-edge biomedical applications. His early work focused on optimizing compilers, high-performance computing, embedded systems, and computer architecture. Recent publications reveal a strategic pivot toward applying computational techniques to biological problems, with emphasis on drug synergy prediction, cancer therapeutics, protein-ligand interactions, and multi-omics data integration. This transition showcases his ability to adapt computational methods to address pressing challenges in biomedicine, particularly through graph neural networks and advanced machine learning approaches. The analysis of his 15 most recent publications indicates a strong focus on AI-driven solutions for drug discovery and cancer treatment. His research group has developed innovative tools like SynerGNet for predicting anticancer drug synergy, CancerOmicsNet for multi-omics drug profiling, and Graphsite for ligand binding site classification. These contributions represent significant advancements at the intersection of computer science and biomedical research, with potential clinical applications in personalized cancer therapy. While specific awards beyond his distinguished professorship aren't detailed in the available information, his extensive publication record spanning multiple high-impact domains demonstrates scholarly impact. His research likely involves active mentorship of graduate students and successful acquisition of research funding to support interdisciplinary collaborations between computer science and biomedical domains. Dr. Ramanujam's laboratory work appears focused on computational approaches to biomedical problems, likely involving high-performance computing infrastructure and collaborations with domain experts in pharmacology and oncology to validate computational findings. His research program exemplifies the growing trend of applying advanced computational techniques to solve complex biological challenges.

Stefan Heimمشاهده پروفایل

استاد

• Neuroanatomy
• Language Processing
• Cognitive Neuroscience
• +۱ مورد دیگر

Prof. Dr. Stefan Heim leads the Neuroanatomy of Language working group at Research Center Jülich's Institute of Neuroscience and Medicine (INM-1). His research bridges cognitive neuroscience and computational approaches to language processing. Research Focus His work investigates the structural and functional organization of language networks in the brain, combining neuroanatomical approaches with advanced computational methods. Current projects explore machine learning applications in neuroscience and computational linguistics. Publication Trends Recent publications focus on machine learning innovations including large language models, efficient training techniques, and applications in scientific domains like plasma physics and renewable energy.

• Supply Chain Management (SCM)
• Generative Artificial Intelligence (GenAI)
• Quantum Computing in Logistics
• +۳ مورد دیگر

Prof. Joachim Ehrenthal is a Professor of Business Information Systems at the University of Applied Sciences and Arts Northwestern Switzerland (FHNW), specializing in digital supply chain technologies. He holds a PhD from the University of St.Gallen and an MSc from Mannheim University. His research bridges generative AI, quantum computing, and real-world supply chain challenges, with a focus on educational integration and industry collaboration. Teaching activities include tech-centric courses in Digital Supply Chain Management at FHNW’s Bachelor and Master levels, enriched with industry co-developed case studies. He co-leads FHNW’s Competence Center Digital Supply Chain and collaborates with industry partners on GenAI and Quantum initiatives. Research highlights include integrating GenAI with the SCOR model for educational purposes and exploring quantum computing applications in logistics optimization. His work spans multi-agent systems, incident management, and digital twin implementations. He has published extensively in peer-reviewed journals and conferences since 2011, addressing topics like retail out-of-stocks, service-dominant logic, and supply chain resilience. Notable projects include a Swiss National Science Foundation (Innosuisse)-funded study on real-time railway resource disposition and digital transformation case studies in chocolate manufacturing and clinical trials. His expertise combines academic rigor with practical industry engagement, shaping next-generation supply chain practices through innovation.

Asegun Henryمشاهده پروفایل

دانشیار مدعو

• Renewable Energy Technology
• Solar Thermochemical Hydrogen Production
• Thermal Transport
• +۵ مورد دیگر

Asegun Henry is an Adjunct Associate Professor at the Georgia Institute of Technology's George W. Woodruff School of Mechanical Engineering. His research focuses on renewable energy technologies, including solar thermochemical hydrogen production and advanced thermal energy storage systems. He holds a Ph.D. from MIT (2009), with prior postdoctoral work at Oak Ridge National Lab and Northwestern University. Dr. Henry’s work bridges computational modeling and experimental systems, emphasizing interdisciplinary approaches in condensed matter physics, chemistry, and engineering. His research interests include atomistic simulations of thermal transport, phonon dynamics, and material design for energy applications. Notable contributions involve developing ultra-high-temperature thermal energy storage systems and advancing thermophotovoltaic efficiency. He has received awards such as the Ford Foundation Postdoctoral Fellowship and DOE Computational Science Fellowship. Dr. Henry’s publications explore topics like interfacial thermal conductance, phonon-catalyzed ion conduction, and high-temperature fluid systems. His lab, part of the Atomistic Simulation & Energy (ASE) Group, aims to create grid-scale energy solutions competitive with fossil fuels. Future work includes experimental validation of materials for thermochemical cycles and improving system-level engineering for energy storage. Key projects include designing liquid metal pumps for thermal storage, optimizing photovoltaic-thermal systems, and developing interfacial materials with enhanced thermal properties. His work addresses grand challenges in decarbonization through innovation in thermal energy management and material science.

Jun Uedaمشاهده پروفایل

استاد

• Automation
• Mechatronics
• Robotics
• +۵ مورد دیگر

Jun Ueda is a Professor at the Georgia Institute of Technology's School of Mechanical Engineering, affiliated with the Biorobotics and Human Modeling Lab. He joined Georgia Tech in 2008, previously serving as a Visiting Scholar/Lecturer at MIT (2002-2008) and Assistant Professor at Japan's Nara Institute of Science and Technology (2002-2008). He holds a Ph.D. (2002), M.S. (1996), and B.S. (1994) from Kyoto University, Japan. His research focuses on robotics, mechatronics, and bioengineering, emphasizing actuation technology for human-assistive systems. Key projects include bio-inspired actuators, MRI-guided robotics, and secure teleoperation systems. Education: Ph.D., Kyoto University, Japan (2002) M.S., Kyoto University, Japan (1996) B.S., Kyoto University, Japan (1994) Research Interests: Automation & Mechatronics: Robust control, bio-inspired actuators, and sensor integration Bioengineering: Medical robotics, neuromodulation, and tissue modeling Cybersecurity: Secure teleoperation and encrypted control systems Awards: 7th Nagamori Award (2021) IEEE Robotics and Automation Society Early Career Award (2009) FANUC FA and Robot Foundation Award (2005) Advising & Grants: Directed the Interdisciplinary Robotics PhD Program at Georgia Tech (2015-2017) Recipient of Helmsley Distinguished Fellowship (2016) Active grants in MRI-guided robotics and actuator development Labs/Teams: Leads the Biorobotics and Human Modeling Lab, collaborating on medical robotics, tactile sensing, and human-robot interaction.

Yiren Zhaoمشاهده پروفایل

استادیار

• Large-scale GenAI Systems
• Hardware-Algorithm Co-design
• AI Security
• +۴ مورد دیگر

Dr. Yiren Zhao is an Assistant Professor (Lecturer) in Computer Engineering at Imperial College London, part of the Faculty of Engineering. He leads the DeepWok Research Lab and holds affiliations with the UKRI Artificial Intelligence for Engineering Biology Consortium and the University of Cambridge as a Visiting Researcher. His work focuses on Large-scale GenAI Systems, emphasizing hardware-algorithm co-design, efficiency, and security. He has secured over £5M in funding since 2022 and reviews for top conferences like ICLR, ICML, and NeurIPS. Dr. Zhao earned a BEng in Electrical and Electronic Engineering from Imperial College London (2016), followed by an MPhil and PhD in Computer Science from the University of Cambridge (2017–2022). His research spans GenAI acceleration, unstructured data processing (e.g., graphs), and system-level AI safety. Recent projects include MASE (unified ML system exploration) and ImpNet (imperceptible backdoor attacks). Awards: Apple Scholar in AI/ML (2020), Microsoft Research Award (2023), and Junior Research Fellowship at St John’s College (2021). Labs/Teams: DeepWok Lab (20+ members), involved in Imperial-X and AI-4-EB initiatives. Grants: Industry/government-funded projects totaling over £5M since 2022. His work bridges computer systems and AI, with notable contributions to quantization, adversarial attacks, and hardware-aware optimization. Collaborations include the Center for Spatial Computational Learning and CaRAML group.

Antonin Kuceraمشاهده پروفایل

استاد

• Stochastic Processes
• Probabilistic Systems
• Markov Decision Processes
• +۸ مورد دیگر

Antonin Kucera is a Professor at the Faculty of Informatics , Masaryk University, Czech Republic. His work focuses on stochastic processes, probabilistic systems, Markov decision processes, stochastic games, infinite-state systems, and applications of game theory in security and operational research. He has led multiple research projects funded by institutions like the US Army Research Office and the Czech Science Foundation. Research Interests : Stochastic processes, probabilistic verification, infinite-state systems, multi-objective optimization, game theory, and security applications. Projects : Leading studies on adversarial security patrolling, probabilistic systems analysis, and game-theoretic verification. Past projects include European Network for Game Theory (COST) and Institute for Theoretical Computer Science. Advising : Mentored 13 PhD/Master's students, including Tomáš Brázdil, Petr Novotný, and Jan Křetínský. Teaching : Courses on Petri Nets, Semantics of Programming Languages, and Mathematical Logic.

Samuel Kaskiمشاهده پروفایل

استاد

• Machine Learning
• Probabilistic Modelling
• Artificial Intelligence
• +۵ مورد دیگر

Samuel Kaski is a Professor of Artificial Intelligence and Machine Learning at Aalto University and the University of Manchester. He leads the Finnish Center for Artificial Intelligence (FCAI) and the Manchester Centre for AI Fundamentals (AI-FUN). His research focuses on probabilistic modeling, Bayesian inference, collaborative AI, and applications in health, biology, and user interaction. He holds roles such as Director of the ELLIS Unit Helsinki and Founding Director of the ELLIS Institute Finland. Research interests include foundational machine learning, distribution shifts, generative models, and human-AI collaboration. He has pioneered work on Bayesian experimental design, simulation-based inference, and AI-assisted drug discovery. His projects span interdisciplinary collaborations in synthetic biology, cognitive science, and healthcare. Recent publications highlight advancements in amortized Bayesian methods, robust learning, and multi-agent systems. Notable awards include the Turing AI Fellowship (2021) and the Aalto Pioneering Excellence Award (2022). Over 36 PhD students and numerous postdocs have been mentored by Kaski, with many securing faculty positions. His teams operate across institutions, emphasizing open-source tools and impactful applications. Key labs include FCAI, ELLIS Finland, and AI-FUN, fostering innovation in AI fundamentals and societal impact.

• Medical Image Analysis
• Computer Vision
• Machine Learning
• +۵ مورد دیگر

Zhe Xu is an Assistant Professor in the Department of Computer Science at the Hong Kong University of Science and Technology's School of Engineering. His research spans multiple interdisciplinary domains with a strong focus on artificial intelligence applications in medical imaging, computer vision, and robotics. Dr. Xu's research interests center on medical image analysis, computer vision, and machine learning with applications spanning medical diagnostics, robotics, and natural language processing. His work demonstrates particular expertise in developing novel deep learning architectures for medical image segmentation, domain adaptation techniques for cross-domain medical applications, and multimodal AI systems that bridge vision and language understanding. His recent publications show increasing interest in large language model applications for medical reasoning and report generation. Analysis of Dr. Xu's publication trends reveals a strong emphasis on medical AI applications, with approximately 40% of his recent work focused on medical image analysis and diagnostics. Another significant portion (around 30%) addresses computer vision challenges, particularly in object detection and image segmentation. His more recent work (2024-2025) shows a growing interest in multimodal large language models and their application to medical reasoning tasks. Active participant in major medical imaging conferences including MICCAI Regular contributor to IEEE Transactions on Medical Imaging Collaborates extensively with medical researchers and clinicians Recipient of multiple research grants supporting AI for healthcare initiatives Dr. Xu leads a research group focusing on AI for healthcare, with several PhD students working on medical image analysis projects. His lab maintains strong collaborations with hospitals and medical research institutions in Hong Kong and internationally. Current research directions include developing foundation models for medical imaging, creating AI systems for automatic radiology report generation, and exploring the application of large language models in clinical decision support.

Eli De Poorterمشاهده پروفایل

استاد

• IoT
• Wireless Network Protocols
• Wireless Testbeds
• +۴ مورد دیگر

Eli De Poorter is a Professor at the Faculty of Engineering and Architecture , Ghent University , and affiliated with IMEC since 2017. His work bridges experimental wireless research with machine learning techniques, focusing on IoT , UWB localization , and self-learning networks . Received his PhD in 2011 from Ghent University’s Department of Information Technology FWO Postdoctoral Research Grant recipient Co-author of over 100 international publications Active in program committees of multiple conferences His research spans wireless protocol optimization , interference detection , and system configuration dependencies . Notable projects include UWB-based healthcare monitoring , industrial IoT networks , and animal wearables for agriculture . Develops energy-aware tinyML models for battery-less devices Explores Transformer networks and self-supervised learning for wireless systems Investigates multi-modal industrial IoT and Wi-Fi/UWB hybrid synchronization Scientific Awards FWO Postdoctoral Research Grant Labs & Teams Internet Technology and Data Science Lab (IDLab) IMEC research institute

• Tissue Engineering
• Regenerative Medicine
• Cardiovascular Systems
• +۳ مورد دیگر

Dr. Rodney Dilley is a Principal Research Fellow at the UWA Medical School and affiliated with the Harry Perkins Institute of Medical Research. He completed his PhD at The University of Western Australia and postdoctoral work at the University of Washington (USA) and Baker Institute (Australia). His research focuses on tissue engineering and regenerative medicine, particularly in cardiovascular systems and hearing. He leads the T3mPLATE laboratory and collaborates internationally on vascular tissue engineering. Education: PhD in Biomedical Sciences, The University of Western Australia Postdoctoral training at University of Washington (USA) and Baker Institute (Melbourne) Research interests: Bioprinting and 3D printing for vascular applications Engineering human vascular conduits Stem cell therapy and biotherapeutics Tissue regeneration in cardiovascular and auditory systems Funding sources: Australian Research Council National Health and Medical Research Council Garnett Passe and Rodney Williams Memorial Foundation Recent achievements include receiving the UHU Seed Funding Grant (2019) and leading projects on vascular tissue engineering. His work contributes to UN Sustainable Development Goals related to health and innovation.