جستجوی استاد راهنمای دانشگاهی

Danielle Griegoمشاهده پروفایل

مدرس

• Building Integrated Solar Photovoltaics
• Building Energy Efficiency
• Participant-Driven Behavior Change via Mobile Apps
• +۳ مورد دیگر

Dr. Danielle Griego is a Lecturer at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering and Executive Director of Design++, an interdisciplinary initiative fostering collaboration across 6 departments and over 20 professors. She holds a Ph.D. from ETH Zurich (2020), focusing on building-integrated solar photovoltaics and energy efficiency through participant-driven mobile apps. Her work bridges architecture, engineering, and sustainability, with prior roles including leading Singapore’s EcoCampus program at NTU. Her research emphasizes energy-efficient building design, community solar policy, and smart urban technologies. Education: Ph.D. in Architecture and Building Systems (ETH Zurich, 2020) M.Sc. Civil Engineering (University of Colorado Boulder, 20XX) B.Sc. Architectural Engineering (University of Colorado Boulder, 20XX) Her research interests include sustainable urban energy systems, behavioral change via technology, and the integration of renewable energy into built environments. She leads Design++ to advance interdisciplinary projects with industry partners, addressing real-world challenges in energy efficiency and smart cities. Grants & Advising: No formal advisee list provided, but actively involved in supervising Design++ initiatives and teaching courses related to building energy systems and sustainable design. Labs/Teams: Design++ at ETH Zurich serves as a central hub for cross-disciplinary research and education in design innovation and sustainability.

Kevin Buchinمشاهده پروفایل

استاد

• algorithm engineering
• computational geometry
• spatial networks
• +۲ مورد دیگر

Kevin Buchin is a Professor at the Department of Computer Science, Faculty of Computer Science at Technical University of Dortmund, where he leads Chair 11: Algorithm Engineering. His work focuses on bridging theoretical and experimental algorithm development, particularly in computational geometry and spatial data analysis. Professor Buchin's research spans several key areas in algorithm engineering, with particular expertise in computational geometry, spatial networks, algorithms for GIS (Geographic Information Systems), and motion planning algorithms. His work combines theoretical foundations with practical applications, developing algorithms that address real-world challenges in spatial data processing and analysis. He has made significant contributions to trajectory analysis, geometric spanners, Fréchet distance computations, and map construction algorithms. His research often involves interdisciplinary collaborations that connect computer science with geographic applications and movement data analysis. An analysis of Professor Buchin's recent publications reveals a strong focus on trajectory analysis and spatial network algorithms. His work consistently addresses fundamental problems in computational geometry while developing practical solutions for real-world applications. Key trends include advancements in Fréchet distance computations, trajectory clustering techniques, geometric spanner constructions, and map-matching algorithms. His research demonstrates a balanced approach between theoretical algorithm development and practical implementation, often resulting in benchmark suites and publicly available code to support reproducibility and further research. Professor Buchin actively supervises student research projects and theses. For Bachelor's theses, he requires successful completion of "Effiziente Algorithmen (EA)" and DAP2 courses, while Master's thesis students should have completed "Algorithmen und Datenstrukturen (AuD)" and ideally specialized courses and seminars in algorithms/algorithm engineering. His group offers final projects in algorithm engineering, geometric algorithms, geometric graphs, networks, GIS algorithms, and motion planning. He has supervised numerous Master's theses, with examples of completed projects available on his group's website. The Algorithm Engineering research group led by Professor Buchin includes Mart Hagedoorn (MSc), Antonia Kalb (MSc), Dr. Guangping Li, Aleksandr Popov (external, MSc), Dr. Carolin Rehs, and student assistants Jan Erik Swiadek and Torben Scheele. The group develops tools like the "Ruler of the Plane" game that illustrates geometric problems and algorithms, which is also available online. They maintain repositories containing game sources, art, and documentation for extending the games, including the "dots & polygons" game and new levels for the art gallery game. The group also produces educational videos illustrating research results, particularly in trajectory analysis, and offers a Coursera course on geometric algorithms.

Veronique Hosteمشاهده پروفایل

استاد

• Computational Linguistics
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Veronique Hoste is a Full Professor of Computational Linguistics at Ghent University's Faculty of Arts and Philosophy , where she serves as Department Head of the Department of Translation, Interpreting and Communication and Director of the LT3 Language and Translation Technology Team . Her work bridges machine learning with natural language processing, focusing on semantics, discourse modeling, and practical applications in emotion detection, irony recognition, and customer service dialogue analysis. PhD in Computational Linguistics from University of Antwerp (2005) 2023-2024: Francqui Chair at Université Libre de Bruxelles 2024: Elected to Royal Flemish Academy of Belgium (KVAB) Research Interests: Specializes in machine learning approaches to coreference resolution, sentiment analysis, and multimodal emotion detection. Leads projects like FlandersAI (empathy in conversational agents), METRICS (emotion trajectories in service dialogues), and SENTiVENT (financial event extraction). Develops high-quality datasets (e.g., EmotioNL , ENCORE ) for broader NLP community use. Recent Publications span Dutch social media irony detection, Classical Chinese poetry sentiment analysis, and multimodal emotion datasets. Collaborates on interdisciplinary initiatives like NewsDNA (news recommendation) and SentEMO (commercial sentiment analysis). Scientific Awards Francqui Chair (2023-2024) KVAB Membership (2024) Outreach includes co-founding AlfaSent (LT3 spin-off for customer feedback analysis) and authoring the first Dutch-language NLP book Taaltechnologie Ontrafeld (2024). Coordinates AI education initiatives like the AI at School project.

Jack Collinsمشاهده پروفایل

پژوهشگر

• Robot Simulation
• Sim-to-Real Methods
• Robotics Foundation Models
• +۷ مورد دیگر

Jack Collins is a Researcher and AI Research Scientist at Collaborative Robotics, focusing on robotics foundation models for collaborative robots. Previously, he served as a Postdoctoral Researcher at the University of Oxford's Applied Artificial Intelligence Lab and completed his PhD at Queensland University of Technology (QUT) in collaboration with CSIRO. His research emphasizes sim-to-real methods, robot simulation, and bridging the 'Reality Gap.' He holds a Bachelor of Engineering (Mechatronics) with First Class Honours from QUT. Education: PhD in Robotics (2018-2022), QUT/CSIRO BEng (Mechatronics) (Honours) (2014-2017), QUT Research Interests: Robot simulation and sim-to-real transfer Bimanual/mobile robotic manipulation Generative models and world modeling Task planning for long-horizon tasks Evolutionary robotics and component design Publications: Over 15 peer-reviewed articles focusing on simulation realism, robotic manipulation benchmarks, and generative modeling techniques. Key work includes the COMBO-Grasp framework and TWIST distillation method for sim-to-real transfer. Lab Affiliations: QUT Centre for Robotics (QCR), Oxford Robotics Institute's Applied AI Lab.

• Artificial Intelligence
• Electrical Engineering
• Robotics
• +۳ مورد دیگر

Professor Christopher McCool is a faculty member at Queensland University of Technology (QUT), specializing in Artificial Intelligence and Electrical Engineering. He holds a PhD from QUT and has contributed extensively to robotics and automation in agriculture, focusing on applications such as precision agriculture, weed management systems, and robotic vision for fruit detection. His work integrates computer vision, mechatronics, and environmental sustainability. Education: PhD in Electrical Engineering, Queensland University of Technology Research Interests: Development of agricultural robotics for crop monitoring and harvesting Computer vision techniques for environmental and agricultural analysis Autonomous systems for obstacle detection and navigation Unsupervised learning methods in robotic weed management Key Contributions: Co-edited special issues on agricultural robotics in the Journal of Field Robotics Advanced fruit detection and ripeness estimation through robotic vision systems Designed mechatronic systems for precision weed management Grants and Collaborations: Active in interdisciplinary projects involving robotics and environmental science Partnerships with industry for agricultural automation solutions

• Artificial Intelligence
• Reinforcement Learning
• Machine Learning
• +۳ مورد دیگر

Stuart Russell is a Professor at the University of California, Berkeley , affiliated with the Department of Electrical Engineering and Computer Sciences in the College of Engineering. His research spans Artificial Intelligence , Reinforcement Learning , and AI Ethics , focusing on safety, alignment, and theoretical foundations. Research Interests : Provably beneficial AI systems Human-compatible AI Reinforcement learning theory Language model interpretability AI safety and control mechanisms Recent Work Trends : 2025-2024: Safety frameworks (off-switch games, reversal curse analysis) 2024: Reward learning with partial observability, program synthesis via diffusion 2023: Societal risk taxonomy, human feedback coordination Collaborations include leading researchers like Anca D. Dragan (UC Berkeley), Yoshua Bengio (Mila), and Michael I. Jordan (UC Berkeley), with publications in venues such as NeurIPS , ICLR , and ICML .

Mingfei Sunمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Deep Reinforcement Learning
• +۴ مورد دیگر

Mingfei Sun is a Lecturer (Assistant Professor) in the Department of Computer Science at the University of Manchester, UK. His research focuses on artificial intelligence, particularly machine learning techniques including deep reinforcement learning and generative models, with applications in robotics, multi-agent systems, and video games. He holds a PhD in Computer Science & Engineering from the Hong Kong University of Science and Technology (HKUST), where he received the Top Research Postgraduate Award, and a B.S. in Electronic Engineering & Information Science from the University of Science and Technology of China (USTC). Dr. Sun's work spans theoretical advancements and practical applications, including contributions to the SMACV2 benchmark for multi-agent reinforcement learning and the development of the LoKO optimizer for large models. He has secured significant funding, such as the EPSRC Doctoral Landscape Award and the TICM Collaborative R&D program on reinforcement learning for automated system calibration. His research has been recognized through awards like the AAMAS Best Paper Award (2023) and the AAAI-20 Studentship (2020). He has held research positions at Microsoft Research Cambridge, the University of Oxford, and Tencent AI Lab. His academic service includes roles as a Senior Program Committee member for AAMAS 2024 and a reviewer for top conferences like ICML, NeurIPS, and AAAI. His GitHub repository demonstrates contributions to projects like DeepMimic_mujoco, focusing on reinforcement learning for humanoid control using Mujoco simulations.

Dimitris Tzionasمشاهده پروفایل

استادیار

• Computer Vision
• Computer Graphics
• Machine Learning
• +۲ مورد دیگر

Dr. Dimitris Tzionas is an Assistant Professor at the University of Amsterdam leading research at the intersection of Computer Vision, Computer Graphics, and Machine Learning. His work focuses on modeling human appearance, motion, and interactions within physical environments. His research explores: 3D reconstruction of humans and objects from images/video Modeling whole-body interactions with scenes Developing novel representations for articulated motion Creating realistic digital avatars for AR/VR applications Recent publications demonstrate consistent focus on human-object interaction modeling, 3D reconstruction under challenging conditions, and the development of novel datasets. Work frequently appears in top-tier venues like CVPR, ICCV, and ECCV. Awards & Recognition: Outstanding Reviewer - CVPR 2021 Outstanding Reviewer - CVPR 2023 Best Paper Finalist - CVPR 2022 Current PhD students include George Paschalidis and Dimitrije Antic. Research is supported by grants including BMBF funding for 'Machine Learning for Interacting Human Avatars'. The lab maintains collaborations with MPI-IS Tübingen and develops novel capture systems for human motion analysis.

Moira Scerriمشاهده پروفایل

مدرس ارشد

• Supply Chain Management
• Digital Therapeutics
• Remote Monitoring Technologies
• +۵ مورد دیگر

Dr. Moira Scerri is a Senior Lecturer in Strategic Supply Chain Management at the University of Technology Sydney (UTS) Business School. Her research focuses on technology adoption in healthcare, service value networks, and productivity measurement in service industries. She holds a PhD and Master’s in Management from UTS, with over 30 years of industry experience spanning travel, IT, and education sectors. Education: PhD in Management, UTS (2015) Master of Business Operations and Supply Chain Management, UTS (2010) Her research explores innovations like digital therapeutics, remote monitoring, and 3D printing in healthcare. She teaches courses in supply chain technology, service productivity analytics, and quality management. Current funded projects include studies on additive manufacturing in medical devices and diabetes care evaluation. Her work aligns with UN Sustainable Development Goals related to health, education, and inequality reduction. Supervision includes projects on logistics outsourcing, telehealth capabilities, and pharmacy service sustainability.

Sivaranjani Seetharamanمشاهده پروفایل

استادیار

• Control Systems
• Machine Learning
• Energy Systems
• +۳ مورد دیگر

Dr. Sivaranjani Seetharaman is an Assistant Professor at Purdue University's Edwardson School of Industrial Engineering. She holds a PhD from the University of Notre Dame, completed postdoctoral research at Texas A&M University, and earned her M.S. from the Indian Institute of Science. Her research integrates control theory and machine learning for distributed decision-making in large-scale cyber-physical-human systems, with applications in transportation networks, power grids, and interdependent infrastructures. Her work focuses on developing efficient algorithms for real-time control, safety guarantees in learning systems, and optimization of networked systems. Analysis of her publications reveals strong emphasis on energy systems and safe learning-based control, with consistent applications to smart grids and electrified transportation. Her research demonstrates progressive integration of machine learning techniques with traditional control theory to address complex infrastructure challenges.

José L. Ponsمشاهده پروفایل

پژوهشگر

• Wearable Robotics
• Neuroprosthetics
• Gait Rehabilitation
• +۵ مورد دیگر

About José L. Pons Dr. José L. Pons is a world-renowned scientist and researcher in the field of neurorehabilitation and neural engineering. He leads the Neurorehabilitation and Neural Engineering Laboratory at Shirley Ryan AbilityLab, part of Northwestern University. His work focuses on developing advanced methods to measure and restore lower-limb function in patients with spinal cord injury, stroke, Parkinson's disease, and other movement disorders. He has authored over 150 peer-reviewed articles and pioneered innovations in wearable robotics, neuroprosthetics, and movement sensor technologies. Education & Training Bachelor of Science in Mechanical Engineering, University of Navarra PhD in Physics, Complutense University of Madrid Research Interests Dr. Pons' research spans wearable robotics , neuroprosthetics , and gait rehabilitation . He has developed robotic devices for children with cerebral palsy, advanced prosthetics for amputees, and technologies to study balance and tremors in Parkinson's patients. His recent work emphasizes closed-loop sensory stimulation for tremor management and neuromechanical modeling for exoskeleton control. Awards & Recognition Fellow of the American Institute of Medical and Biological Engineering (AIMBE, 2021) Leadership roles in global research networks, including CSIC (Spain's National Research Council) Labs & Teams He directs the Neurorehabilitation and Neural Engineering Lab at Shirley Ryan AbilityLab, collaborating with clinical and engineering teams to translate research into clinical tools. His lab is part of the Legs + Walking Lab initiative, advancing technologies like multi-channel electrodes and adaptive exoskeletons .

Zackory Ericksonمشاهده پروفایل

استادیار

• Human-Robot Interaction
• Rehabilitation and Health Care Robotics
• Robot Learning
• +۱۳ مورد دیگر

Zackory Erickson is an Assistant Professor at Carnegie Mellon University's Robotics Institute, leading the Robotic Caregiving and Human Interaction (RCHI) Lab. His work focuses on healthcare robotics, particularly empowering older adults and people with disabilities through assistive technologies. Research Interests: At the intersection of physically assistive robotics , robot learning , physics simulation , and haptic perception , Erickson develops methods for robotic caregivers to intelligently interact with humans. Key areas include physical human-robot interaction , deep learning , rehabilitation robotics , and deformable object manipulation . Notable trends in his recent publications include large language model integration for assistive robotics, electromyography control systems, and sim-to-real frameworks for human mesh recovery. His work emphasizes safe, adaptive human-robot collaboration in healthcare settings. Scientific Awards: Best Paper Nomination at HRI 2025 Best Paper Award at HRI 2024 He advises both PhD and Masters students in projects ranging from robotic feeding systems to wearable interfaces for mobility assistance . Teaching responsibilities include graduate courses on Mechanics of Manipulation and Human-Robot Interaction .

Aaron Steinfeldمشاهده پروفایل

استاد پژوهش

• Human-Robot Interaction
• Advanced Transportation Systems
• Assistive Robotics
• +۴ مورد دیگر

Aaron Steinfeld is a Research Professor at Carnegie Mellon University 's Robotics Institute with a courtesy appointment in the Human-Computer Interaction Institute . His work bridges human-robot interaction and advanced transportation , focusing on inclusive design for users with disabilities. PhD in Industrial and Operations Engineering (1999) and MSE/BSE in the same field (1994/1993) from University of Michigan Postdoctoral work in Transportation Human Factors at UC Berkeley's California PATH program (2000) Research spans four key areas: Assistive Robotics : Developing inclusive technologies for visually impaired and disabled users Transportation Innovation : Redesigning transit systems through crowdsourcing and citizen science Human-Robot Group Dynamics : Studying social navigation and multi-robot coordination Trust & Communication : Creating frameworks for robot self-assessment and user trust alignment Recent publications emphasize social navigation benchmarks , pedestrian behavior modeling , and adaptive transit interfaces . Current projects include accessible delivery robots (NIDILRR 90IFDV0042) and FHWA-funded work on autonomous vehicle accessibility. Scientific Recognition NSF AI Institute (AI-CARING) co-PI ONR MURI grant recipient DARPA and multiple NSF grant collaborations Best Paper awards at CHI 2019 and IROS 2020 Advising both PhD and Master's students in human-robot interaction, his lab maintains partnerships with Georgia Tech, UMass Lowell, and Disney Research. He co-edited the book Accessible Public Transportation .

• Machine Learning
• Deep Learning
• Computer Vision
• +۸ مورد دیگر

Dr. Amir Atapour-Abarghouei is an Assistant Professor in the Department of Computer Science at Durham University, UK, and a Fellow of the Wolfson Research Institute for Health and Wellbeing. He leads the VIViD (Vision, Imaging and Visualisation in Durham) research group. Previously, he held roles at Newcastle University and Shahid Bahonar University of Kerman (Iran). His research focuses on machine learning, deep learning, computer vision, 3D scene understanding, and natural language processing. Notable contributions include the GANomaly anomaly detection framework, now part of Intel's AI products. Education : Ph.D., Computer Science, Durham University (UK) M.Sc., Computer Science, Universiti Teknologi Malaysia (Malaysia) B.Sc., Computer Engineering, Shahid Bahonar University of Kerman (Iran) Research Interests : His work spans machine learning, deep learning, image processing, 3D scene analysis, and robotics. Key areas include depth estimation, domain adaptation, semantic segmentation, and causal-based models for action quality assessment. Recent projects involve datasets like DurTOMD and Dur360BEV for autonomous systems and image inpainting techniques (e.g., HINT, SEM-Net). Advising & Grants : He supervises over 15 postgraduate students and has contributed to grants focused on AI-driven systems in healthcare, robotics, and computer vision. His team's work on GANomaly and neural architecture search (NAS) has been widely cited and applied in industry. Labs/Teams : Leads the VIViD Research Group and collaborates on interdisciplinary projects involving healthcare imaging, autonomous vehicles, and ethical AI. Active in organizing workshops at CVPR, IEEE BigData, and the BMVA Summer School.

• Radiation Therapy
• Medical Physics
• Dosimetry
• +۳ مورد دیگر

Dean Cutajar is a Lecturer in the School of Physics at the University of Wollongong since 2021. His research focuses on advanced radiation therapy techniques, medical dosimetry, and quality assurance in brachytherapy and MRI-Linac systems. He has contributed to the development of high-resolution dosimetry tools like MagicPlates and MOSkin sensors, enhancing precision in cancer treatment. His work spans HDR and LDR brachytherapy, real-time dosimetry validation, and adaptive radiotherapy strategies for prostate and cervical cancers. Key projects include optimizing source tracking in HDR treatments and improving dosimetric accuracy in complex geometries like MR-Linacs. He has supervised numerous PhD and Master’s students in radiation oncology and medical physics. Research Highlights: Fiber-optic dosimeters, Geant4 benchmarking, in-vivo dosimetry, and MRI-Linac integration. Grants: Led projects funded by NHMRC, AINSE, and the University of Wollongong, totaling over $5M in research support. Dean collaborates internationally on advancing radiation therapy technologies, emphasizing clinical translation and evidence-based treatment planning.