جستجوی استاد راهنمای دانشگاهی

Brendan Englot is the Anson Wood Burchard Endowed Professor and Director of the Stevens Institute for Artificial Intelligence (SIAI) at Stevens Institute of Technology. He holds a Ph.D., S.M., and S.B. in Mechanical Engineering from MIT. His research focuses on perception, navigation, and decision-making algorithms for mobile robots in complex environments, particularly underwater and autonomous systems. He has held roles such as Professor (2024–present), Associate Professor (2020–2024), and Assistant Professor (2014–2020) at Stevens, and previously worked at the United Technologies Research Center and Yale University. Education: Ph.D., Mechanical Engineering, MIT, 2012 S.M., Mechanical Engineering, MIT, 2009 S.B., Mechanical Engineering, MIT, 2007 Research Interests: Englot’s work emphasizes robust autonomy for unmanned vehicles in degraded conditions, leveraging AI to enhance situational awareness and decision-making under uncertainty. Key areas include navigation algorithms for underwater, aerial, and ground vehicles, sensor fusion, and multi-agent systems. Awards: AMiner’s Top 100 Robotics Scholars (2023, 2024) Provost’s Award for Research Excellence (2021) NSF CAREER Award (2017) ONR Young Investigator Award (2020) Grants & Advising: Englot has secured over $5M in grants as PI, including projects on underwater exploration, reinforcement learning for navigation, and robotic inspection systems. He mentors students in robotics, autonomy, and AI applications. Labs & Teams: Leads the SIAI and collaborates on projects involving autonomous vehicles, SLAM systems, and marine robotics through Stevens’ interdisciplinary initiatives.

• Robotics
• Autonomous Systems
• Artificial Intelligence
• +۳ مورد دیگر

Di Zhu is an Assistant Professor of Geographic Information Science at the University of Minnesota's Department of Geography, Environment and Society. He directs the Geospatial Data Intelligence (GeoDI) Lab, focusing on GeoAI and social sensing to analyze human-environment interactions in urban systems, public health, and socioeconomic dynamics. His educational background includes a PhD in Cartology and GIScience from Peking University, complemented by a BSc in GIS and a BA in Economics from the same institution. Key research interests include spatial regression models, human mobility patterns, and GeoAI applications. He has collaborated on projects funded by NIH, NSF, and other agencies, exploring topics like spatiotemporal data imputation, urban flow analysis, and pandemic spatial dynamics. His work bridges traditional GIScience with modern machine learning techniques, emphasizing actionable insights from big geospatial data. Teaching focuses on advanced GIS, numerical spatial analysis, and urban sensing. He actively mentors students through the University of Minnesota's Master of GIS program and serves on academic boards including CPGIS. Current projects include analyzing Twin Cities mobility networks and developing intelligent spatial prediction frameworks.

• Geographic Information Science
• Geospatial Artificial Intelligence (GeoAI)
• Spatial Networks
• +۶ مورد دیگر

Anders Brandt is an Associate Professor (Docent) in Geospatial Information Science and Senior Lecturer in Geomatics at the University of Gävle, Sweden, within the Department of Computer and Geospatial Sciences under the Faculty of Engineering and Sustainable Development. His research focuses on flood risk mapping uncertainties, agent-based modeling of pedestrian movement, and spatial decision-support systems for sustainable urban planning. He holds a PhD in Physical Geography from the University of Copenhagen and has extensive international collaboration experience. Education: PhD in Physical Geography (University of Copenhagen, Denmark), focusing on fluvial geomorphology of Costa Rica’s Reventazón River Master’s Degree in Physical Geography (Uppsala University, Sweden) Research Interests: Brandt’s work addresses uncertainties in flood modeling, spatial decision analysis, and geospatial data applications for urban resilience. His projects include the 'Big Data Methodology for Experiential and Cognitively Sustainable Urban Growth' initiative, emphasizing ecosystem service mapping and spatial MCDA methods. His agent-based modeling research explores emergent urban path systems to optimize pedestrian infrastructure. Publications Trends: Recent work spans flood risk visualization, blue-green infrastructure roles in climate resilience, and urban form complexity metrics. His 2025 papers highlight innovative applications of agent-based modeling and systematic reviews of climate hazard mitigation strategies. Advising & Grants: While no formal advisee list is provided, his collaborative publications suggest involvement in student projects. His grants include international initiatives like Mongolia’s land administration capacity-building programs. Labs/Teams: Co-founded GeoVega , a consulting firm specializing in flood risk mapping and geospatial solutions. Active in educational initiatives like harmonizing GIS curricula in Swedish universities.

• Geospatial Information Science
• Flood Risk Mapping
• Uncertainty Analysis in Environmental Modeling
• +۶ مورد دیگر

Dr. Saidi Siuhi serves as an Associate Professor of Civil Engineering at South Carolina State University, where he teaches undergraduate and graduate courses while conducting research and providing institutional service across departmental and university levels. His academic credentials include: Ph.D. in Civil Engineering from the University of Nevada, Las Vegas (2009) M.Sc. in Civil Engineering from Florida State University (2006) B.Sc. in Civil Engineering from the University of Dar-es-Salaam (2003) Specializing in transportation engineering, Dr. Siuhi's research focuses on traffic safety, transportation planning, and microscopic traffic simulation. His work addresses critical transportation challenges including distracted driving/walking behaviors, traffic management during special events (notably the 2017 solar eclipse), and the application of advanced computational methods to transportation networks. He integrates emerging technologies like virtual reality, machine learning, and deep learning to develop innovative safety solutions for complex transportation systems. Analysis of his recent publications (2021-2025) reveals a strong trajectory toward computational transportation safety, with increasing emphasis on AI-driven solutions for pedestrian safety, driver behavior analysis, and infrastructure monitoring. His work consistently bridges theoretical transportation models with practical safety applications, particularly in distracted behavior analysis and event-based traffic management. Dr. Siuhi actively mentors students through senior design projects (CE 459/460) and graduate coursework, though specific advisee names aren't documented. His service contributions span departmental, college, and university committees, supporting academic operations and strategic initiatives within the engineering program.

• Transportation Engineering
• Traffic Safety
• Transportation Planning
• +۳ مورد دیگر

Anthony Clark is an Assistant Professor of Computer Science at Pomona College, where he has been teaching since 2020. Previously, he served as an Assistant Professor at Missouri State University from 2016 to 2020. He directs the ARCS (Autonomous Robotics and Complex Systems) Lab, which focuses on improving the robustness and adaptability of autonomous robots, particularly small-scale systems that can navigate unpredictable terrain and adapt to potential damage. Clark earned his Ph.D. in Computer Science from Michigan State University in 2016, where he worked under Dr. Philip K. McKinley, and his B.S. in Computer Engineering from Kansas State University, graduating magna cum laude. His research centers on making autonomous robots more robust and adaptive through optimization algorithms and multimodal systems. He specializes in evolutionary robotics, computer vision, neural networks, and simulation methods for developing control systems that leverage multiple locomotion mechanisms. His recent work demonstrates strong trends across several domains: developing hybrid locomotion systems (wheel/leg transformations), applying deep learning to terrain classification and pathfinding, using simulation environments for training, and exploring pretraining techniques for evolutionary robotics. His research shows a consistent focus on bridging simulation and real-world applications while addressing challenges in robot adaptability and robustness. Faculty Excellence in Teaching, Missouri State University (2018) Best Paper Award, Workshop on Evolutionary and Reinforcement Learning (2013) Best Paper Award, ALIFE Conference, Behavior and Intelligence Track (2012) Outstanding Reviewer, Elsevier (2018) Master Advisor Certification, Missouri State University (2017) Clark has advised numerous undergraduate and graduate students through the ARCS Lab, with current research involving projects like the Adabot (a robot with multiple locomotion mechanisms) and thermal semantic segmentation for aerial field robots. His teaching portfolio includes courses on data structures, algorithms, neural networks, computer systems, and mobile robotics. He has also served as a Visiting Associate at Caltech's ARC Lab from 2023-2024, working with Dr. Soon-Jo Chung. The ARCS Lab develops simulation environments, optimizes control systems, and fabricates physical robots. Current projects include the Adabot with its geared coaxial shaft mechanism for hybrid locomotion, thermal semantic segmentation using satellite data, and creating dynamic simulation environments with Unreal Engine 5. The lab emphasizes practical applications of theoretical research while training students in both hardware and software aspects of robotics.

• Autonomous Robotics
• Evolutionary Robotics
• Computer Vision
• +۷ مورد دیگر

David Serfass is a Lecturer at the National Institute of Oriental Languages and Civilizations (INALCO) specializing in Chinese studies. He serves as Co-manager of international mobility, Tutoring Manager, and Referent to the Cross-functional Commission at the institution. His teaching portfolio includes courses on the History of East Asia (19th-20th centuries), Communication and Media in East Asia, Introduction to Ancient Chinese History, Sinological Culture and Practice, Republican China through Texts and Media, and History of Taiwan. Dr. Serfass's research focuses on the History of the Japanese Occupation of China (1931-1945), the History of the Modern Chinese State, Sino-Japanese Relations, and the History of the Sino-Japanese War. His work examines state-building processes during wartime, particularly through the lens of the Wang Jingwei regime and collaboration governments in occupied China. He approaches these topics through spatial history, bureaucratic documentation, and memory studies, revealing how territorial control, administrative practices, and historical narratives shaped wartime China. His scholarly contributions demonstrate a consistent focus on the complexities of political authority during periods of fragmentation and occupation. Rather than viewing the Wang Jingwei regime as merely a Japanese puppet government, Serfass's research reveals the regime's internal dynamics, state-building efforts, and complex negotiations of sovereignty. His work challenges teleological narratives of central state formation in Republican China, highlighting instead the fragmented and contested nature of political authority during this period. Member of editorial board, Études chinoises (2014-2024) Member of editorial board, Terrains de Taiwan Member, ERC project Elites, Networks and Power in Modern China Member, French Taiwan Studies Project Member, Occupation Studies Research Network Dr. Serfass is an active contributor to academic discourse through conference presentations, editorial work, and collaborative research projects. His approach combines traditional historical research with spatial analysis and attention to bureaucratic practices, drawing on Chinese, Japanese, and Western archival sources to provide multi-perspective understanding of wartime China. His work has established him as a significant voice in the field of modern Chinese history, particularly regarding the complex dynamics of occupation, collaboration, and state formation during the Sino-Japanese War period.

• History of East Asia
• History of Modern China
• History of Republican China
• +۵ مورد دیگر

Won Dong Shin is a Postdoctoral Researcher at the Laboratory of Intelligent Systems (LIS) within the School of Engineering (STI) at EPFL. His research focuses on bio-inspired robotics, particularly in the design and control of drones and multi-modal robots. He explores topics such as avian-inspired flight mechanisms, morphological control systems, and autonomous navigation strategies. His work integrates vision-based control, biomimetic principles, and reinforcement learning to enhance the agility and accuracy of winged drones in urban environments. He has contributed to developing robots capable of transitioning between ground and air, perching, and adapting to complex terrains through energy-efficient designs. Selected projects include studies on elastic actuation for repetitive hopping, multi-modal locomotion systems, and bio-inspired claws for perching. His research often emphasizes practical applications in robotics for civilian tasks, such as urban exploration and environmental monitoring. Shin collaborates with the LIS group, which is part of EPFL’s Institute of Microengineering (IGM). His contact information includes the email won.shin@epfl.ch and a physical office at MED 1 1612 in Lausanne.

• Robotics
• Unmanned Aerial Vehicles (Drones)
• Vision-Based Control
• +۵ مورد دیگر

Leonardo Lanari is an Associate Professor at the Department of Computer, Control and Management Engineering (DIAG) of Sapienza University of Rome. His research focuses on robotics, particularly humanoid motion generation, model predictive control, and nonlinear control systems. He has contributed to advancements in gait stability, underactuated robotics, and remote robotic experiments through the REAL Lab. PhD in Systems Engineering from Sapienza University Visiting Scholar at Rensselaer Polytechnic Institute Research Interests Robotics (humanoid locomotion, flexible manipulators, underactuated systems), control theory (MPC, robust control), and large-scale system control. His work integrates geometric approaches with practical robotic implementations. Recent Article Trends Focus on model predictive control for humanoid stability, stair navigation, and cooperative transportation systems. 2025 studies emphasize feasibility-driven motion planning in complex environments. Scientific Awards 2020 IEEE Robotics and Automation Magazine Best Paper Award Teaching & Grants Teaches Control Systems and Multivariable Feedback Control at Sapienza. Has developed courses on underactuated robots and control problems in robotics. Involved in grants for healthcare AI platforms like CADUCEO and humanoid applications in aircraft manufacturing. Labs & Teams Membro del Robotics Lab at DIAG. Collaborates with international institutions including MIT, Rensselaer Polytechnic Institute, and Airbus on humanoid robotic projects.

• Robotics
• Humanoid Locomotion
• Model Predictive Control (MPC)
• +۴ مورد دیگر

Dr. Pedro Trapero Fernandez is a Postdoctoral Researcher at the University of Cádiz, affiliated with the Department of History, Geography and Philosophy and the Institute of Viticulture and Agri-Food Research (IVAGRO). He leads the HUM240 Historical Heritage of Andalusia in Antiquity research group and specializes in Ancient History, with particular focus on Roman viticulture, landscape archaeology, and geospatial analysis. PhD in Ancient History and Archaeology (2020) with thesis on Roman Viticulture in the Hasta Regia and the Guadalquivir Estuary Research expertise in non-invasive techniques: GIS, drones, ground-penetrating radar, magnetometry Active academic collaborations with international institutions including FORTH (Greece) His research integrates classical agronomic texts like Columella with modern geospatial technologies to reconstruct ancient agricultural practices and mobility networks. Key projects include Roman road network analysis, viticulture modeling, and archaeological applications of GIS in Spain and Portugal. He has contributed to coastal and inland connectivity studies in Roman and Medieval contexts. Scientific publications demonstrate technical proficiency in geophysical prospecting and historical modeling. Notable works include: GIS applications for Roman property surveying, multidisciplinary analysis of wine production, and innovative methodologies for studying ancient transportation networks. As an educator, he has taught at undergraduate and master's levels through predoctoral contracts and developed flipped classroom methodologies for humanities teaching. Current affiliations include the Agustín de Horozco Seminar on Economic Studies and multiple international research partnerships.

• Ancient History
• Landscape Archaeology
• Geographic Information Systems (GIS) in Archaeology
• +۳ مورد دیگر

Daniel Leidner is a Cooperation Professor at the University of Bremen and a researcher at the German Aerospace Center (DLR) where he has been contributing to the Institute of Robotics and Mechatronics since 2011. He earned his doctorate in Artificial Intelligence and Robotics from the University of Bremen in 2017. Since 2017, he has led the Semantic Planning Group and the Fault-Tolerant Autonomy Architectures group at DLR, focusing on advanced task planning for autonomous robotic systems and enhancing the reliability of robotic operations in dynamic environments. Leidner's research interests span multiple areas in robotics and artificial intelligence. His work emphasizes developing robust and resilient robotic systems capable of autonomous operation in complex environments. He specializes in creating systems that can not only handle predictable scenarios but also flexibly respond to unforeseen events. His ERC Starting Grant project RECOVER.ME aims to equip robots with metacognitive abilities to autonomously manage hardware malfunctions by integrating formal reasoning with Vision-Language Models. This innovative approach enhances the resilience and efficiency of space robots, reducing the need for manual intervention during missions and leveraging insights from cognitive psychology for improved problem-solving capabilities. Leidner's research portfolio includes significant projects such as RECOVER.ME, FUTURO, EASE, OPERA, Smile2gether, Surface Avatar, and CoViPa. His publications demonstrate a strong focus on autonomous task planning, human-robot interaction, fault tolerance, and metacognitive capabilities in robotic systems. Recent publications highlight advancements in space teleoperation, assistive robotics, and cognitive reasoning for resilient robotic systems. ERC Starting Grant (2024) for project RECOVER.ME Georges Giralt PhD Award (Best European PhD Thesis in Robotics) Helmholtz Doctoral Prize MIT Technology Review Innovator under 35 Award Leidner has served as an advisor to the German Federal Government from October 2023 to July 2024, where he played a crucial role in developing a national strategy for AI-based robotics. His leadership in the Semantic Planning Group and Fault-Tolerant Autonomy Architectures group at DLR demonstrates his significant contributions to advancing robotic capabilities in challenging environments. His work bridges theoretical advances in cognitive robotics with practical applications in space exploration, healthcare, and industrial automation.

• Robotics
• Artificial Intelligence
• Autonomous Systems
• +۵ مورد دیگر

Corina Sandu is the Robert E. Hord Jr. Professor in the Department of Mechanical Engineering at Virginia Tech. She leads the Terramechanics, Multibody, and Vehicle Systems Laboratory, focusing on advanced modeling of multibody dynamics, vehicle-terrain interaction, and tire performance optimization. Her research integrates computational methods, experimental validation, and interdisciplinary approaches to address challenges in off-road mobility, autonomous systems, and vehicle dynamics. Dr. Sandu holds a Ph.D. (2000) and M.S. (1995) in Mechanical Engineering from the University of Iowa, complemented by an Engineering Diploma in Mechanics from the Bucharest Polytechnic Institute (1991). She serves as the President of the International Society for Terrain-Vehicle Systems and chairs the SAE Fellow Committee, underscoring her leadership in automotive and mechanical engineering fields. Her research interests span: Uncertainty quantification in multibody systems Optimization of vehicle dynamics and tire performance Terramechanics and terrain-vehicle interaction modeling Sensitivity analysis and adjoint methods for complex systems Recent publications highlight innovations in tire-ice interface models, hydroplaning risk estimation, and advanced multibody system simulation frameworks. She has pioneered experimental methodologies for tire performance evaluation on ice and soft soils, linking material science with mechanical engineering principles. Her work impacts automotive safety, off-road vehicle design, and autonomous systems, with applications in both industry and academia. Awards include recognition for her contributions to terrain-vehicle systems research and leadership in professional societies.

• Multibody Dynamics
• Vehicle Systems Engineering
• Terramechanics
• +۵ مورد دیگر

Laura Treers is an Assistant Professor in the Department of Mechanical Engineering at the University of Vermont (UVM), affiliated with the UVM CREATE Center. She holds a PhD from UC Berkeley (2023) and a B.S. from MIT (2018). Prior to UVM, she was a postdoctoral scientist at Georgia Tech in Physics and Biological Sciences. Her research focuses on robotic mobility in complex terrains, combining robotics, physics, and biomechanics. The Interact Lab at UVM explores terramechanics, experimental robotics, and complex terrains, with key interests in granular media modeling, mechanism design, and 'robophysics' principles. Her work bridges robotics, biology, and environmental systems. Her academic awards include the 2023 Outstanding Graduate Student Instructor Award, 2019 National Defense Science Fellowship, and MIT's Thomas Sheridan Prize. She teaches courses like Control Systems (ME 3320A) and Mechatronics (ME 2990). Committed to equity in STEM, she mentors underrepresented students in robotics and science outreach programs. Key research themes include collective behavior in robotic and biological systems, granular material manipulation, and field robotics applications. Her lab's projects emphasize interdisciplinary innovation, leveraging biological insights to enhance robotic performance in unstructured environments.

• Robotic locomotion in complex terrains
• Physics of granular materials
• Robophysics
• +۴ مورد دیگر

Kartikeya Singh is a Ph.D. candidate and Researcher in the Department of Computer Science at the University at Buffalo, affiliated with the College of Engineering and Applied Sciences. His work focuses on autonomous systems, particularly SLAM and risk-aware navigation for robots operating in complex terrains. Current research emphasizes enabling legged robots to traverse challenging environments via advanced visual perception and dynamic motion planning. His approach integrates theoretical rigor with practical deployment, collaborating with industry partners to test solutions in real-world scenarios. Recent publications (2021–2025) span legged robot navigation, payload-aware path planning, and visual feature learning using motion. Key themes include environmental monitoring, off-road mobility, and sensor fusion technologies. 2025: Autonomous Culvert Inspection 2024: PANOS (Offroad Navigation), L-DYNO (Visual Perception) 2021: OFFSEG (Semantic Segmentation), Offroadtranseg (Transformer Models) 2020: Shoplifting Detection via Contour Analysis Scientific recognition includes: Top 10 emerging researcher at ICRA 2025 Best paper nomination at ICRA 2025 He has served as a Research Assistant (2023–Present) and Teaching Assistant (2022–2023), mentoring in courses like Robotic Algorithms and Data Intensive Computing . His work is conducted in the DRONES Lab under Professor Karthik Dantu.

• Autonomous Systems
• Simultaneous Localization and Mapping (SLAM)
• Risk-Aware Navigation
• +۷ مورد دیگر

Mitchell Pryor is a Research Professor in the Department of Nuclear and Radiation Engineering at the University of Texas at Austin. He specializes in applied robotics and automation, particularly in hazardous environments such as nuclear facilities, energy sectors, and defense applications. Pryor earned his BSME from Southern Methodist University (1993), followed by an MS (1999) and PhD (2002) in Mechanical Engineering from UT Austin. His research focuses on robotics for hazardous environments, including nuclear waste management, autonomous systems, and human-robot collaboration. He leads the Nuclear & Applied Robotics Group (NRG) and co-founded RAPID, an industry affiliate program supporting automation in energy sectors. His work spans robotics in extreme environments, augmented reality interfaces, and task planning frameworks. Key collaborations include Army Futures Command (AFC), NASA, DARPA, and DOE national labs such as INL, LANL, and ORNL. Pryor’s contributions include developing the TeMoto software framework for robotic autonomy, virtual fixture systems, and radiation surveying methodologies. He chairs the ANS Robotics & Remote Systems Division and actively participates in IEEE, ASME, and other professional societies. His research emphasizes interdisciplinary approaches to deploy robotics in complex, uncertain environments for tasks like material handling, mobile manipulation, and environmental monitoring. Notable projects include AR-STAR for real-time robot data modification, MaRMOT for object tracking, and TeMoto 2.0 for task execution formalisms. His work bridges theoretical robotics with practical applications in nuclear safety, energy infrastructure, and defense systems.

• Robotics
• Automation
• Nuclear Engineering
• +۴ مورد دیگر

Benjamin Suger is a researcher in the Department of Computer Science at the University of Freiburg, affiliated with the Autonomous Intelligent Systems group within the Faculty of Engineering. His work centers on robotics and intelligent systems, particularly in autonomous navigation and environment modeling. Diploma in Mathematics, University of Freiburg (2003–2011) PhD Student, Autonomous Intelligent Systems Group, University of Freiburg (2011–2017) His research interests include traversability analysis, SLAM, 3D modeling, and mobile robotics. He applies machine learning and computer vision techniques to enable robust robot navigation in complex and dynamic environments. His work often integrates sensor data from 3D lidar and visual systems to improve perception and localization. The recent publications highlight a strong focus on long-term autonomy, outdoor navigation, and memory-efficient SLAM algorithms. Key themes include handling perceptual changes, terrain adaptability, and integration of open geospatial data like OpenStreetMap. His work bridges theoretical algorithm development with real-world robotic applications. Scientific recognition includes being a finalist for the Best Conference Paper Award. This reflects the impact and quality of his contributions to the robotics community. Best Conference Paper Award Finalist Benjamin Suger has contributed significantly to research projects such as LifeNav and has served as a teaching assistant for the Introduction to Mobile Robotics course. While no direct advising of students is listed, his collaborative work with prominent researchers like Wolfram Burgard indicates active participation in a larger academic and research team. He has not received external grant mentions in the provided text. He is part of the Autonomous Intelligent Systems lab at the University of Freiburg, a leading group in robotics research, where he contributes to advancing the state of the art in autonomous navigation and environmental understanding for mobile robots.

• Robotics
• Autonomous Systems
• Traversability Analysis
• +۶ مورد دیگر