جست‌وجوی استاد و پژوهشگر

Huan Xuمشاهده پروفایل

دانشیار

• Control Systems
• Formal Methods
• Autonomous Systems
• +۶ مورد دیگر

Huan Xu is an Associate Professor in the Department of Aerospace Engineering at the University of Maryland, College Park, with a joint appointment at the Institute for Systems Research. Her work focuses on formal methods for multi-agent autonomous systems, particularly in cyber-physical systems and UAVs. Ph.D., Mechanical Engineering, California Institute of Technology (2013) M.S., Mechanical and Civil Engineering (2008) S.B., Mechanical and Materials Sciences and Engineering, Harvard University (2007) Her research interests lie in control and dynamical systems, formal methods, and optimization, with applications in autonomy, planning, and system identification. She develops robust cyber-physical systems that perform complex tasks in dynamic environments, emphasizing rigorous theory and real-world applications. Her recent publications focus on collision avoidance algorithms, swarm robotics, and autonomy certification. These works integrate formal logic with practical implementations for UAVs and multi-agent systems. DARPA Cooperative Agreement (2018) AIAA Awards for UAS Collision Avoidance (2020) DoD SMART Scholarship (2023) She advises current Ph.D. and MS students in aerospace engineering and robotics, including John Schmidt, Sarah Wielgosz, and Estefany Carrillo. Her lab (MATRIX Lab) collaborates on autonomous drone racing, hazard mitigation, and swarm tactics projects. Facilities like the USMSM SMART Building and UROC support her research on autonomous aerial systems and flight software validation.

• Electrical and Computer Engineering
• Deep Learning
• Image Processing
• +۵ مورد دیگر

Fatema Albalooshi is an Assistant Professor in the Computer Engineering department at the University of Bahrain since 2015. She holds a Ph.D. in Electrical and Computer Engineering from the University of Dayton (2015) and an MSc in Electrical Engineering from the University of Nottingham (2009). Education: PhD, Electrical and Computer Engineering, University of Dayton (2015) MSc, Electrical Engineering, University of Nottingham (2009) BSc, Electrical Engineering, University of Nottingham (2009) Research Interests: Deep Learning Image Processing Computer Vision Biometrics Machine Olfaction Environmental Remote Sensing Peer Review Contributions: Applied Intelligence (5 reviews) Signal, Image and Video Processing (16 reviews) Electronics (1 review) Computers in Biology and Medicine (1 review) Email: falbalooshi@uob.edu.bh

• Artificial Intelligence
• Robotics
• Motion Planning
• +۸ مورد دیگر

Maxim Likhachev is a Professor at the Robotics Institute and National Robotics Engineering Center , both within the School of Computer Science at Carnegie Mellon University (CMU). His research focuses on Artificial Intelligence and Robotics , particularly in real-time graph search algorithms , planning under uncertainty , and high-dimensional mobile manipulation . He co-founded TravelWits.com and RobotWits (acquired by Waymo), and his lab develops the Search-based Planning Library (SBPL), integrated into ROS. Research Themes : Graph search-based planning for deterministic and probabilistic domains Decomposition of hard planning problems into sequential graph searches Incremental algorithms for dynamic environments Experience-driven heuristic optimization Scientific Awards : Gold Edison Award (2013) for industrial mobile manipulator project DARPA Urban Challenge Winner (2007) for autonomous SUV navigation Students : Supervises current PhD students including Itamar Mishani , Muhammad Suhail Saleem , and Rishi Veerapaneni , alongside Masters students like Gabriel Olin . Past advisees include Dhruv Saxena (now at Uber), Michael Phillips (now at Uber), and Shivam Vats (now at Waymo). Lab & Projects : Leads the Search-based Planning Laboratory at CMU, working on systems like K-MAX helicopter , PR2 robots , and industrial mobile manipulators for tasks including autonomous paint stripping and aerial navigation.

Swarun Kumarمشاهده پروفایل

استاد

• Low-Power Wide-Area Networks (LP-WANs)
• Battery-Free IoT
• Future Wi-Fi
• +۷ مورد دیگر

Swarun Kumar is the Sathaye Family Foundation Professor at Carnegie Mellon University (CMU) in the Electrical and Computer Engineering (ECE) department, with affiliate appointments in the Computer Science (CS) department, Human-Computer Interaction (HCI) Institute, and CyLab. He leads the Emerging Wireless Technologies (WiTech) lab, focusing on next-generation wireless network protocols and services. Ph.D., Computer Science, MIT (George Sprowls Award winner) B.Tech., IIT Madras (President of India Gold Medal) His research spans Low-Power WANs , Battery-Free IoT , mmWave Sensing , and Soft Robotics . Key projects include MetaMorph (robotic signal enhancers), WASER (RF-powered soft robots), and Hydra (multi-bounce mmWave sensing). He pioneered wireless actuation, body-frame tracking, and whale rendezvous frameworks using autonomous robots. His recent work explores wireless systems for high-temperature materials (Viton), microwave energy optimization (MicroSurf), and dental health sensing (ToMoBrush). Articles reflect trends in Robotics , Material Science , and Wireless Systems . 2024 ACM SIGMOBILE Rockstar Award 2021 ACM SIGBED Early Career Researcher Award NSF CAREER Award George Sprowls Award (MIT Best Ph.D. Thesis) President of India Gold Medal (IIT Madras) He has advised numerous Ph.D. students, including alumni joining universities like University of Washington, UC San Diego, and NUS. His teaching includes courses on Computer Networks , Wireless Systems , and Telecommunication Networks .

• Neuromorphic Engineering
• Edge AI
• Computer Architecture
• +۴ مورد دیگر

Dr. A. Yousefzadeh is an Assistant Professor in Edge AI at the University of Twente (joined February 2024), affiliated with the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) within the Department of Computer Architecture Design and Test for Embedded Systems. He holds a Ph.D. in Neuromorphic Engineering from IMSE (Instituto de Microelectrónica de Sevilla), where his thesis focused on bio-inspired vision processing. His research specializes in neuromorphic computing systems, with emphasis on: Designing ultra-low-power AI processors and event-based vision systems Developing hardware accelerators for spiking neural networks (SNNs) Edge AI deployment for sensor-based applications Hardware-software co-design for energy-efficient computing His publication trends (2015-2025) reveal core foci on neuromorphic processor architectures (e.g., SENECA, NeuronFlow), event-based vision processing, hardware-aware neural network optimization, and 3D integration techniques. Recent work explores activation sparsification in transformers and hybrid analog-digital neuromorphic systems. Prior to academia, he contributed to industry neuromorphic projects: Architected the NeuronFlow processor at GrAI Matter Labs (acquired by Snap) Led SENECA processor development at imec's Hardware Efficient AI group He currently leads research on next-generation edge AI processors at UT's Embedded Systems lab.

• Geomatics
• Digital Cultural Heritage
• Photogrammetry
• +۶ مورد دیگر

Lorenzo Teppati Lose' is a Fixed-term Researcher at the Polytechnic University of Turin , affiliated with the Department of Architecture and Design (DAD) . He specializes in Geomatics within the domain of Civil Engineering and Architecture (CEAR-04/A - Scientific Disciplinary Sector). Research Interests : 360° cameras, 3D modeling, Digital cultural heritage, Emergency mapping, Geospatial data, Laser scanner, Photogrammetry, SLAM-based modeling, UAV photogrammetry ERC Skills : PE8_3 (Civil engineering, architecture), SH5_12 (Cultural digitization), PE6_8 (Computer graphics), PE10_14 (Remote sensing), PE2_17 (Metrology) His research focuses on photogrammetry and SLAM systems for cultural heritage documentation , with a strong emphasis on UAV technology , direct georeferencing , and 3D modeling . He has developed methodologies for metric surveys using 360° images and cloud platforms , and tested LiDAR sensors for heritage digitization . The trends in his 15 most recent articles highlight expertise in SLAM validation , UAV photogrammetry , HBIM (Historical BIM), and low-cost 3D tools for heritage documentation . His work bridges terrestrial and aerial surveying , with applications in underwater photogrammetry (POSER platform) and emergency mapping (e.g., flood analysis in Limone Piemonte). Scientific Awards : Quality of research activity (2019, 2018) - Doctoral School, Polytechnic University of Turin Best Poster Award SIFET2017 (2017) - Italian Society of Photogrammetry and Topography He serves as a Course Lecturer and Collaborator for modules on Geomatics , Point Clouds , and HBIM in degree programs related to Architecture for Sustainability and Heritage Conservation . His leadership in commercial research projects includes 3D metric surveys of cultural sites in Assisi and the development of a white paper on digital surveying for heritage protection .

Almuatazbellah Bokerمشاهده پروفایل

استادیار

• Autonomous Systems
• Robotics
• Machine Learning
• +۲ مورد دیگر

Almuatazbellah Boker is an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. He earned his PhD in Electrical Engineering from Michigan State University in 2013. His research focuses on autonomous systems, machine learning for robotic decision-making, and distributed control optimization. Key research areas include Koopman operator-based control, sparse controller design, and human-supervised autonomous systems. His research explores: Nonlinear control strategies for robotic and motion systems Data-driven approaches for optimal control Human-robot interaction in autonomous navigation Publication analysis shows strong focus on Koopman operator applications for system modeling and control, with recent extensions to digital twins and fault detection. Work consistently addresses practical implementation challenges in robotic systems and industrial automation. Dr. Boker has supervised PhD candidate Muhammad Al Saaideh to graduation. His research receives support from the US Department of Energy and Siemens USA, including a $300,000 subaward for sensor placement optimization in solar systems (2024-2027).

Geng Baiمشاهده پروفایل

استاد مدعو

• Advanced Plant Phenotyping
• Precision Agriculture
• Remote Sensing in Agriculture
• +۳ مورد دیگر

Geng Bai is an Adjunct Professor in the Department of Biological Systems Engineering at the University of Nebraska-Lincoln. He holds a Ph.D. in Environmental Science and Technology from Niigata University (Japan), alongside M.E. and B.E. degrees in Agricultural Engineering from China Agricultural University. His research focuses on advanced plant phenotyping in field and greenhouse environments, precision agriculture, and the development of automated sensing systems for agricultural applications. Education: Ph.D., Environmental Science and Technology, Niigata University, Japan (2014) M.E., Agricultural Soil and Water Engineering, China Agricultural University (2010) B.E., Hydraulic and Hydro-Power Engineering, China Agricultural University (2008) Research interests include integrating robotics and remote sensing technologies for crop monitoring, with a focus on soybean and wheat breeding. His recent work explores solar-induced chlorophyll fluorescence (SIF) for plant phenotyping and proximal sensing for crop management in the Great Plains. Funding highlights: ORED Grant (2019-2019): $20,000 for SIF-based phenotyping research IIC Grant (2020-2020): $94,659 for precision agriculture automation EPA Grant (2019-2022): $150,000 for saline wetland monitoring Collaborates extensively with interdisciplinary teams across Nebraska's agricultural research community, emphasizing field-based phenotyping and sustainable agronomic practices.

• Hardware-Software Co-design
• Deep Learning Security
• Intellectual Property Protection
• +۵ مورد دیگر

Huili Chen is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California San Diego's Jacobs School of Engineering. Her research spans the intersection of hardware security, deep learning, and human-robot interaction, with a particular focus on intellectual property protection for AI systems and socially interactive robotics for education and family settings. Her research interests focus on hardware-software co-design for secure and robust deep learning systems, with specific expertise in neural network watermarking, hardware Trojan detection, and privacy-preserving AI. She has made significant contributions to federated learning security, developing frameworks like GALU for logic unlocking and AdaTest for hardware Trojan detection. In human-robot interaction, she investigates long-term multi-person interactions, particularly in home environments with children and parents, exploring how robots can enhance engagement and learning through adaptive role-playing. Her publication trends reveal a dual research trajectory: one branch focused on deep learning security and hardware co-design (accounting for approximately 60% of her recent work), and another dedicated to socially assistive robotics and human-robot interaction (40%). The security research often involves innovative approaches combining reinforcement learning with hardware constraints, while her HRI work emphasizes longitudinal studies of robot-child-parent dynamics in naturalistic settings. Dr. Chen actively collaborates with leading researchers including Farinaz Koushanfar at UC San Diego and Cynthia Breazeal at MIT Media Lab. Her work has been published in top-tier venues including IEEE Transactions on Affective Computing, ACM Transactions on Embedded Computing Systems, International Conference on Computer Vision (ICCV), and the ACM/IEEE International Conference on Human-Robot Interaction (HRI). She is a key contributor to the DAMI-P2C project, which has developed datasets and models for analyzing parent-child multimodal interactions, and leads research on hardware security frameworks for deep neural networks. Her laboratory combines expertise in computer architecture, machine learning, and social robotics to develop systems that are both technically secure and socially effective.

Yu Liuمشاهده پروفایل

استاد

• Sustainable Computing
• Energy-Efficient Software
• Programming Languages
• +۳ مورد دیگر

Yu Liu is a Professor at the School of Computing, Binghamton University, where he has been a faculty member since 2008. His research focuses on sustainable computing, energy efficiency, and security in emerging software systems, with significant contributions to programming languages, robotics, and software-hardware interfaces. Education: MSE, Johns Hopkins University PhD, Johns Hopkins University Professor Liu's research centers on sustainable computing and energy-aware software systems. He investigates programming language designs for energy prediction, develops reliable robotics software through managed languages, and creates secure software-hardware interfaces. His work bridges theoretical foundations with practical applications in data centers, UAV systems, and multi-threaded environments, emphasizing verifiable sustainability metrics and energy-efficient resource management. His publication trends reveal a consistent focus on sustainable computing evolution, with recent work advancing verifiable sustainability frameworks in data centers (2023-2024), energy accounting for multi-threaded applications (2020), and secure cache management techniques (2022). The research spans programming language theory, robotics safety, and hardware security, demonstrating interdisciplinary integration across computer science subfields. Scientific Awards: NSF CAREER Award Google Faculty Research Award Fulbright Scholarship Professor Liu has secured significant research funding through his NSF CAREER Award and Google Faculty Research Award, supporting innovations in sustainable computing infrastructure. His Fulbright Scholarship enabled international collaboration in Slovenia, advancing global research in energy-efficient software systems. He regularly teaches core courses including Programming Languages (CS471/571) and Sustainable Computing (CS680G), mentoring the next generation of computer scientists. While specific lab affiliations aren't detailed in the source text, his research on UAV software (Jcopter) and cache security (Composable cachelets) suggests active involvement in robotics and systems security research groups at Binghamton University.

Iain Couzinمشاهده پروفایل

استاد

• Collective Behavior
• Animal Behavior
• Neuroscience
• +۳ مورد دیگر

Professor Iain Couzin is a leader in the study of collective behavior at the University of Konstanz and director of the Max Planck Institute of Animal Behavior. He holds roles in the Cluster of Excellence Centre for the Advanced Study of Collective Behaviour (CASCB) and the Department of Biology. His research integrates biology, robotics, and computational science to understand how groups of animals (e.g., locusts, fish, birds) coordinate decisions and movements. Key tools include virtual reality for animals, automated tracking systems like TRex, and the Centre for Visual Computing of Collectives (VCC) facility. Research focuses on emergent collective phenomena, such as swarming in locusts, schooling in fish, and cooperative hunting. He emphasizes interdisciplinary approaches, collaborating with neuroscientists and engineers to bridge scales from neural circuits to global migration patterns. Notably, his work on locust swarms has societal implications for predicting agricultural threats. Awards: Highly Cited Researcher (Clarivate Analytics, 2018-2022). Facilities: Imaging Hangar, VCC research building, and novel VR setups for animal studies. Future Goals: Exploring collective memory, cross-species communication, and neuron-to-society-level decision-making. His grants and collaborations support cutting-edge experiments, including multi-scale locust studies and the development of algorithms for collective sensing in robotics. Leadership in bridging theory, experiment, and application positions him at the forefront of this interdisciplinary field.

Mato Baotićمشاهده پروفایل

استاد

• Control Systems
• Model Predictive Control
• Renewable Energy Systems
• +۵ مورد دیگر

Prof. Mato Baotić is a Full Professor and Head of the Department of Control and Computer Engineering at the University of Zagreb's Faculty of Electrical Engineering and Computing (FER). His research focuses on advanced control systems, model predictive control (MPC), renewable energy systems, and power engineering. He leads projects in distributed power systems, microgrid control, wind turbine optimization, and mechatronics. His work integrates theoretical advancements with practical applications in energy efficiency, robotics, and smart grids. Key research areas include MPC for wind turbines, grid reconfiguration, and omnidirectional mechatronic systems. He has contributed to the LARES laboratory for renewable energy systems and collaborates on international projects like DYMASOS and MICROGRID. His publications span control algorithms, grid optimization, and energy storage solutions. Prof. Baotić teaches courses on control systems synthesis, predictive control, and automatic control. He advises numerous research initiatives and oversees labs developing systems for energy and robotics applications.

Matthew Oliverمشاهده پروفایل

استاد

• Phytoplankton oceanography
• Biogeography
• Remote sensing
• +۵ مورد دیگر

Matthew Oliver is the Patricia and Charles Robertson Distinguished Professor of Marine Science and Policy at the University of Delaware. He holds appointments in the School of Marine Science & Policy and the Department of Geography and Spatial Sciences within the College of Earth, Ocean & Environment. His research focuses on phytoplankton oceanography, biogeography, remote sensing, and polar marine ecosystems. He leads the Ocean Exploration, Remote Sensing, and Biogeography (ORB) Lab, which develops technologies like robotic systems and satellite data to study marine organisms' distributions and ecosystem dynamics. Oliver earned a Ph.D. in Oceanography from Rutgers University (2006), an M.S. in Biology from Cal Poly (2001), a B.S. in Ecology from Cal Poly (1999), and an A.A. in Natural Sciences from Cerritos College (1996). His work emphasizes understanding how physical ocean processes influence biological systems, with applications to conservation and fisheries management. His research interests span satellite-driven ecological forecasting, marine predator behavior, and Antarctic ecosystem studies. The ORB Lab's innovations include real-time ocean data platforms (e.g., Atlantic Sturgeon risk maps) and partnerships with agencies like NOAA and Delaware Sea Grant. Oliver's publications highlight interdisciplinary approaches linking oceanography with ecology, with recent work exploring submesoscale transport, Lagrangian coherent structures, and the role of eddies in biological hotspots. Advising focuses on students with quantitative skills, particularly in spatial analysis and programming. His lab actively collaborates with international teams on projects like Project CONVERGE (Antarctic ecosystem dynamics) and robotic ocean glider deployments. Current initiatives include advancing dynamic ocean management tools and integrating animal telemetry with remote sensing data. Labs/Teams: ORB Lab (lead), Robotic Discovery Laboratories. Key projects involve developing seascapes frameworks for marine conservation and improving ecological forecasting models for climate-sensitive species.

Arron Carterمشاهده پروفایل

استاد

• Wheat Breeding
• Plant Genetics
• Molecular Biology
• +۶ مورد دیگر

Arron Carter is a Professor and O.A. Vogel Endowed Chair of Wheat Breeding and Genetics at Washington State University (WSU), part of the College of Agricultural, Human, and Natural Resource Sciences (CAHNRS) and the Department of Crop and Soil Sciences . He leads the winter wheat breeding and genetics program, focusing on developing high-yielding, disease-resistant wheat varieties with superior end-use quality for Pacific Northwest agriculture. Education: PhD in Crop Science (WSU, 2009), MS and BS in Plant Science (University of Idaho, 2006 and 2003). Research Interests: Winter wheat genetics, molecular breeding, high-throughput phenotyping (UAVs/sensors), stripe rust resistance, water-use efficiency, and end-use quality traits like baking performance. His work integrates genomic selection, remote sensing, and biotechnology to enhance wheat adaptation to climate variability. Awards: 2023 Outstanding Paper-Original Research (co-author) for editorial on crop genetics advancements. Advising & Grants: Supervises graduate students and postdocs; leverages USDA grants for phenotyping and genomic technologies. Collaborates with USDA-ARS and industry on breeding programs. Labs/Teams: Leads the WSU Winter Wheat Breeding Lab, Spillman Agronomy Farm trials, and interdisciplinary teams in precision agriculture and genomics.

Emily Dolsonمشاهده پروفایل

استادیار

• Artificial Life
• Evolutionary Computation
• Eco-Evolutionary Dynamics
• +۵ مورد دیگر

Emily Dolson is an Assistant Professor in the Department of Computer Science and Engineering (CSE) at Michigan State University's College of Engineering, and core faculty in the Ecology, Evolution, and Behavior program. Her research focuses on developing algorithmic approaches to control evolutionary trajectories in complex ecological communities through computational experiments, spanning simple models to artificial life systems. This work bridges evolutionary medicine, computational theory, and empirical biology through collaborations with wet-lab scientists. Education: Ph.D., Computer Science & Engineering and Ecology, Evolutionary Biology, & Behavior, Michigan State University (2019) B.A., Computer Science and Biology, Swarthmore College (2013) Her research interests emphasize computational tools for evolutionary dynamics, including phylogenetic tracking, open-ended evolution measurement (via the MODES toolbox), and ecological theory integration into evolutionary algorithms. Recent work explores fitness seascapes, counterdiabatic driving in evolutionary systems, and scalable phylogenetic analysis. Awards: International Society for Artificial Life Outstanding Service Award (2019) International Society for Artificial Life Outstanding Student Research Award (2019) Publications highlight innovations in evolutionary computation techniques, phylogenetic informatics, and interdisciplinary applications of artificial life. Ongoing efforts include developing high-performance tools for tracking evolutionary processes at scale and exploring evolutionary mechanisms relevant to medical and environmental contexts.