جستجوی استاد راهنمای دانشگاهی

• Sustainable Construction
• Energy Efficiency in the Built Environment
• Building and Urban Energy Simulation
• +۵ مورد دیگر

Shayan Mirzabeigi is an Assistant Professor of Sustainable Construction Management at the State University of New York College of Environmental Science and Forestry (SUNY ESF) . He holds a Ph.D. in Sustainable Construction Management from SUNY ESF (2024) and is pursuing a second Ph.D. in Mechanical & Aerospace Engineering at Syracuse University (expected 2025), working with Professor Jianshun Zhang in the Building Energy and Environmental Systems Lab (BEESL). Education: Ph.D., Sustainable Construction Management, SUNY ESF, 2024 Ph.D. (In Progress), Mechanical & Aerospace Engineering, Syracuse University, 2025 (expected) M.Sc., Building Engineering, Politecnico di Milano, 2020 B.Sc., Architectural Engineering, University of Tehran, 2016 His interdisciplinary research focuses on building energy simulation , climate resilience , construction automation , and human-building interaction , with a particular emphasis on cold climate adaptations. He directs the Sustainable and Resilient Built Environment Lab (SARBEL) and contributes to the integration of BIM-IoT frameworks and drone-based building diagnostics . His recent publications address thermal anomaly detection , occupant-centric retrofit protocols , and multi-scale retrofit solutions for cold climates. He has presented at major conferences including ASHRAE, STRATUS, and COBEE. Scientific Awards and Grants : ASHRAE College of Fellows Travel Award (2024) Best Poster Award, STRATUS 2024 SUNY ESF GSA Senate Travel Grant (2024) ASHRAE Student Travel Grant (2024) Building Enclosure Symposium Attendance Scholarship (2023) He has advised graduate students like Fahad Iqbal (MS) and contributed to peer-review activities for journals like Energy & Buildings and Building Simulation . His teaching includes courses on Data Science for Sustainability , Sustainable Energy Systems , and Green Building .

Behnam Askarianمشاهده پروفایل

استادیار

• Renewable Energy
• Machine Learning
• Image/Signal Processing
• +۳ مورد دیگر

Dr. Behnam Askarian is an Assistant Professor of Electrical Engineering at West Texas A&M University's College of Engineering, joining in Fall 2021. He holds a B.S. and first M.S. in Electrical Engineering from Shiraz University (Iran), followed by a second M.S. and Ph.D. from Texas Tech University (2020 and 2021, respectively). His research focuses on renewable energy, machine learning, biomedical engineering, IoT, and image/signal processing , with notable contributions to smartphone-based diagnostic tools for eye diseases and arrhythmia detection. He has authored two books on multimedia and learning technologies. **Education**: B.S. & M.S. in Electrical Engineering, Shiraz University, Iran M.S. & Ph.D. in Electrical Engineering, Texas Tech University **Research Highlights**: Dr. Askarian’s work bridges engineering and healthcare, particularly in developing affordable diagnostic tools. His IoT-enabled solutions address challenges in telemedicine, such as keratoconus detection via smartphones and arrhythmia monitoring. He also explores AI-driven precision agriculture and sustainable energy systems. Two patents reflect his innovations in smartphone-integrated medical sensors. **Teaching**: He teaches core electrical engineering courses, including Digital Design, Wind Energy Turbines, and Linear Integrated Circuits , emphasizing hands-on learning in electronics and renewable energy. **Labs & Collaborations**: Affiliated with the College’s engineering research groups, including the ECORE Lab and Human-Machine Teaming Laboratory, where he contributes to interdisciplinary projects in robotics and sensor networks.

• Technology and Society
• Computer Applications
• Software Development
• +۳ مورد دیگر

Shawn Gramiak is a Sessional Instructor in the Department of Arts and Cultural Management at MacEwan University, where he has taught for nearly 20 years. His expertise spans computer applications, software, and Microsoft tools, with a focus on how technology can enhance human life. He holds a Diploma from NAIT. Outside academia, Gramiak is a professional stand-up comic, performing regularly at venues like Rick Bronson’s The Comic Strip and Yuk Yuk’s clubs. He co-hosts the award-winning podcast The Movie Jerks , now in its 300+ episode run. His research explores the intersection of technology, art, and long-lost skills, aiming to leverage technology to reduce labor burdens. Gramiak has collaborated with organizations such as the Provincial Government of Alberta and Enbridge, providing technical instruction for diverse audiences. He aspires to create a self-sustained 'off-grid' environment supported by caregiver robots, reflecting his broader interest in technology’s role in empowering human freedom.

Frank Poddمشاهده پروفایل

مدرس

• Ground Penetrating Radar
• Embedded Systems
• Tomographic Imaging
• +۳ مورد دیگر

Dr. Frank Podd is a Lecturer in Embedded Systems at the University of Manchester's Department of Electrical and Electronic Engineering. He holds a BSc in Theoretical Physics, MSc in Signal Processing and Machine Intelligence, and PhD in Medical X-Ray Dose Reduction by Adaptive Image Processing from the University of Surrey. His professional experience includes positions at JET Nuclear Fusion Laboratory, industrial roles in SMEs (Rinicom, Industrial Tomography Systems, Uniscan), and running his own research consultancy (Tomography Limited). Dr. Podd's research focuses on landmine detection using ground-penetrating radar (GPR), e-Agri applications using resistance tomography and GPR, security screening using radar, and developing autonomous robotic platforms to enhance these research areas. His work contributes to UN Sustainable Development Goals through technological innovations in security and sustainable agriculture. His publications demonstrate consistent focus on GPR applications across diverse domains including agriculture, civil engineering, landmine detection, and renewable energy systems. Recent work shows growing emphasis on polarimetric imaging techniques, antenna design optimization, and sustainable technology implementations in developing regions. Dr. Podd leads the Landmine Detection and Security Screening research group and maintains active industry collaborations with companies including Lucid Innovations and Extronics. He teaches Microcontroller Engineering and oversees the Embedded Systems Buggy Project.

Pulkit Agrawalمشاهده پروفایل

دانشیار

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

Pulkit Agrawal is an Associate Professor at the Massachusetts Institute of Technology (MIT), holding dual appointments in the departments of Artificial Intelligence and Decision-making (AI+D), Computer Science (CS), and Electrical Engineering (EE) within the School of Engineering. He is a core member of the Embodied Intelligence Community of Research, focusing on advancing intelligent systems that interact with the physical world through robotics, AI, and machine learning. His work emphasizes bridging simulation and real-world applications in robotics, human-robot interaction, and medical technology. Key research areas include reinforcement learning for robotic manipulation, simulation-to-real transfer, and embodied intelligence. Notable projects include developing methods for robust home robot training using real-to-sim-to-real approaches, tactile-driven object retrieval systems, and AI-driven glucose control models for post-surgical care. He also explores ethical AI in healthcare and assistive technologies for cognitive impairment monitoring. Dr. Agrawal’s contributions span robotics hardware design (e.g., DEXOS hand exoskeleton), neuro-inspired algorithms (e.g., grid cell-based map building), and scalable robot learning via crowdsourced environments. His work often integrates interdisciplinary methods from control theory, computer vision, and biomedical engineering. He leads the MIT CSAIL Embodied Intelligence group and collaborates on projects like OpenEQA for embodied question answering and DexHub for large-scale robot data collection. His research has been recognized through promotions within EECS and featured in outlets like MIT News for innovations in home robotics and AI-driven medical solutions. He advises on grants related to intelligent systems and maintains active collaborations across academia and industry.

Ross McAreeمشاهده پروفایل

استاد

• Mining Automation
• Robotics
• Machinery Dynamics
• +۲ مورد دیگر

Ross McAree is Professor and Head of the School of Mechanical and Mining Engineering at the University of Queensland, and Fellow of the Australian Academy of Technology and Engineering. His research focuses on mining automation, including pioneering work on autonomous excavators and bulldozers. Research encompasses machinery dynamics, sensor fusion for terrain mapping, and collision avoidance systems. Recent publications address point cloud processing for mining applications, predictive maintenance using machine learning, and hyperspectral ore classification techniques. Publication themes show progression from fundamental sensing/control algorithms toward integrated autonomous mining systems, with increasing emphasis on AI applications in harsh environments. Work consistently addresses industrial challenges through rigorous theoretical development and field validation. Awards & Honors: Fellow of the Australian Academy of Technology and Engineering (ATSE)

Markus Lienkampمشاهده پروفایل

استاد

• Electromobility
• Autonomous Driving
• Driver Assistance Systems
• +۳ مورد دیگر

Prof. Markus Lienkamp is a Professor and Chair of Automotive Engineering at the Technical University of Munich (TUM), leading research in electromobility, autonomous driving, and vehicle systems. He holds a doctorate in Materials Science from TU Darmstadt and has extensive industry experience at Volkswagen Group Research, where he managed teams and budgets up to €40M. His roles include Scientific Director of the Munich School of Engineering and the CREATE project in Singapore. He chairs the VDI Association for Automotive and Traffic Engineering and serves on TÜV Süd's Board. Key research focuses include driver assistance systems, electric vehicle concepts (e.g., Visio.M, aCar), and battery technology. He has over 500 publications, 30 patents, and founded 10 start-ups from his institute. Awards include the Heinz Maier-Leibnitz Medal (2014) and the IEEE Outstanding ITS Application Award (2022). His projects span global collaborations, rural electrification in Africa, and high-profile racing competitions like the Indy Autonomous Challenge ($1M win, 2021). Research infrastructure includes the TUM Autonomous Motorsport team, TUM.Battery initiative, and the M Cube Future Cluster (2021–2030). His work emphasizes sustainable mobility solutions, energy systems integration, and advancing autonomous vehicle technologies through interdisciplinary approaches.

Yorie Nakahiraمشاهده پروفایل

استادیار

• Optimization Theory
• Control Systems
• Machine Learning
• +۵ مورد دیگر

Yorie Nakahira is an Assistant Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), within the College of Engineering. Her research focuses on the theoretical foundations of optimization, control, and learning, with applications to neuroscience, robotics, smart grids, and autonomous systems. She holds a Ph.D. from Caltech (2019) and a B.E. from Tokyo Institute of Technology (2012). Her education includes a Bachelor of Engineering in Control and Systems Engineering (Tokyo Institute of Technology, 2012) and a Ph.D. in Control and Dynamical Systems (California Institute of Technology, 2019). Her work bridges fundamental control theory with real-world applications, emphasizing safety, adaptability, and interdisciplinary collaboration. Research interests span optimization frameworks for layered architectures, safety guarantees in autonomous systems, and the integration of physics-informed learning. Notable trends in her recent publications include advancements in probabilistic safety certificates, stochastic control under uncertainty, and the application of neural networks to dynamical systems. She also explores energy-efficient computing in automated vehicles and human-robot collaboration dynamics. Selected articles highlight innovations in safety-critical systems, multi-agent coordination, and the theoretical limits of control under partial observability. These contributions underscore her commitment to bridging theoretical rigor with practical engineering challenges.

Alireza Karimiمشاهده پروفایل

استاد

• Robust Control
• System Identification
• Data-driven Controller Tuning
• +۳ مورد دیگر

Alireza Karimi is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) within the School of Engineering, Institute of Mechanical Engineering. He leads the Data-Driven Modelling and Control (DDMAC) research group and serves on the Doctoral Program Commission for Robotics, Control, and Intelligent Systems. His educational background includes: B.Sc. and M.Sc. in Electrical Engineering from Amir Kabir University (Tehran Polytechnic), 1987 and 1990 DEA and Ph.D. in Automatic Control from Institut National Polytechnique de Grenoble (INPG), 1994 and 1997 Karimi's research focuses on data-driven controller tuning and robust control methodologies, with significant applications in mechatronic systems and electrical grids. His work bridges theoretical control concepts with practical implementations in power systems, robotics, and adaptive optics. Recent publications demonstrate strong emphasis on frequency-domain methods, Koopman operator applications, and robustness against nonlinearities. Analysis of his 15 most recent publications (2023-2024) reveals dominant research themes: data-driven frequency-domain control (appearing in 70% of works), power system applications (40%), and advanced robotics/optics implementations (30%). His group consistently develops methods for fixed-structure controllers validated through industrial case studies. Regarding academic leadership, Karimi supervises 6 active PhD students while having directed 11 completed theses. His teaching portfolio includes courses in Automatic Control, System Identification, and Advanced Control Systems. He maintains the DDMAC laboratory focused on experimental validation of control algorithms, with notable projects in adaptive optics for astronomy, grid-forming inverters for renewable integration, and precision motion control systems.

• Biomedical Engineering
• Wearable Sensors
• Neural Signal Processing
• +۳ مورد دیگر

Professor Wei Chen is Head of the School of Biomedical Engineering at the University of Sydney. She holds a B.Eng. and M.Eng. from Xian Jiaotong University, China, and a Ph.D. from the University of Melbourne (2007). Her international experience includes positions at Bell Laboratories Germany and Eindhoven University of Technology. Professor Chen's research focuses on biomedical signal processing, wearable sensors for healthcare, and neural engineering applications. Research Interests: Development of wearable sensor systems for medical monitoring Neural signal processing and brain network analysis Sleep staging algorithms and neonatal monitoring technologies Biomedical instrumentation and sensor design Her recent publications demonstrate strong focus on neural signal processing, novel biosensor development, and AI applications in healthcare. Research trends show interdisciplinary work combining biomedical engineering with materials science, AI, and clinical neurology. Professional Service: Editorial roles for multiple IEEE journals including Transactions on Biomedical Engineering Former Chair of IEEE Sensor and Systems Council China Chapter IEEE EMBS AdCom Asia/Pacific representative

• Offshore Engineering
• Hydrodynamics
• Renewable Energy
• +۷ مورد دیگر

Wenhua Zhao is an Adjunct Associate Professor at the University of Western Australia (UWA), affiliated with the School of Earth and Oceans and the UWA Oceans Institute. He holds a PhD in Ocean Engineering from Shanghai Jiao Tong University. His research focuses on offshore hydrodynamics, AI-driven renewable energy technologies, and wave-structure interactions, with applications to offshore wind, floating solar, aquaculture, and green hydrogen systems. He leads projects funded by the Australian Research Council (ARC), including a Future Fellowship (2023) and DECRA Fellowship (2019). Education: PhD in Ocean Engineering (2014), Shanghai Jiao Tong University. Research interests include fluid-structure interactions, renewable energy infrastructure, and AI integration in ocean engineering. He serves as Deputy Editor of Ocean Engineering, Associate Editor of ASME Journal of OMAE, and editorial board member of Applied Ocean Research. His work contributes to UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and climate action. Grants include leadership roles in ARC hubs for offshore floating facilities and transformative energy infrastructure. Notable awards include the Mid-Career Research Award (2023) and selection as an Eight Innovation Partner for TetraSpar floating wind projects. Teaching: Coordinates courses on offshore energy design and advanced offshore systems at both undergraduate and postgraduate levels. Service: Graduate Research Coordinator, Board member of Postgraduate Studies Committee, and Research Committee member at UWA's Oceans Graduate School. Industry Relevance: Collaborates on projects like BW Ideol’s Floatgen and TetraSpar floating wind, advancing green hydrogen/ammonia technology. Labs/Teams: Active in the Shell EMI Chair in Offshore Foundations and the UWA Oceans Institute. His research bridges fundamental hydrodynamics with applied offshore engineering solutions.

Abhishek Dubeyمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Cyber-physical Systems
• Distributed Computing
• +۴ مورد دیگر

Abhishek Dubey is an Associate Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. He leads the SCOPE lab, focusing on AI-driven solutions for cyber-physical systems, resilient computing, and smart communities. His work integrates online learning algorithms and decision procedures to address challenges in energy systems, emergency response, and urban mobility. Key projects include partnerships with Nashville's fire department, transit agencies, and state transportation departments. Education: Ph.D. and M.S. in Electrical Engineering from Vanderbilt University (2009 and 2005), B.Tech. in Electrical Engineering from IIT Banaras Hindu University (2001). Research Interests: Resilient computational abstractions, energy-efficient transit systems, transactive energy systems, and AI for decision-making under uncertainty. Recent work emphasizes reinforcement learning, federated learning, and urban mobility optimization frameworks like NS-Gym and PDPTW-DB. Grants and Partnerships: Funded by NSF, NASA, DOE, ARPA-E, AFRL, DARPA, Siemens, Cisco, and IBM. Projects include grid-aware charging optimization, wildfire resilience, and equitable transit network design. Labs and Tools: SCOPE lab, NS-Gym simulation environment, E-Transit-Bench platform, and SmartTransit AI. His work bridges theory and practice, addressing real-world challenges in smart cities and critical infrastructure.

Sunil Sinhaمشاهده پروفایل

استاد

• Magnetic Films and Nanostructures
• X-ray Photon Correlation Spectroscopy
• Liquid Surface Dynamics
• +۳ مورد دیگر

Professor Sunil Sinha is a faculty member in the Department of Physics at the University of California, San Diego (UCSD), specializing in condensed matter physics. His research focuses on magnetic films, nanostructures, X-ray photon correlation spectroscopy, lipid membrane systems, and biomimetic assemblies. He leads the Sinha Group, which utilizes cutting-edge scattering techniques like X-ray and neutron scattering to study material dynamics and structures. Research Highlights: Investigates magnetic interfaces and exchange bias systems using neutron reflectivity and X-ray scattering. Explores dynamics of lipid multilayers and hydration effects under controlled humidity. Studies antiferromagnetic domain wall fluctuations in dysprosium using XPCS. Collaborates on DNA-templated silver nanoclusters and biomimetic nanoassemblies. Awards & Honors: 2015 Roentgen Medal for X-ray Science 2014 Clifford G. Shull Prize Advising & Collaborations: Supervised numerous PhD and postdoctoral researchers, including Yicong Ma, Vince Chen, and Sambhunath Bera, many of whom hold academic and industry positions globally. Collaborates with institutions like Los Alamos National Laboratory and Brookhaven National Laboratory. Facilities: Uses advanced facilities including synchrotrons (e.g., Advanced Light Source), neutron sources (e.g., Spallation Neutron Source), and UCSD-based scattering setups for experimental work.

• Machine Learning
• Autonomous Systems
• Cyber Security
• +۱ مورد دیگر

Dr. Hong Gunn Chew is a Lecturer at the University of Adelaide, affiliated with the School of Electrical and Mechanical Engineering within the Faculty of Sciences, Engineering and Technology. His research focuses on Machine Learning, Autonomous Systems, Cyber Security, and Energy Management. He holds roles as the electronics practical coordinator and final year projects coordinator in the School of Electrical and Electronic Engineering. Dr. Chew’s academic contributions span teaching and research supervision across multiple disciplines, including Computer Architecture, Digital Electronics, and Project Management. He has coordinated undergraduate and postgraduate research projects, fostering practical skills in students through hands-on learning environments. His research publications reflect expertise in adversarial machine learning, network security, and energy systems optimization. Notable work includes developing explainability models for AI systems and frameworks for detecting cyber threats in networked devices. He has secured grants related to defense applications, such as eavesdropping detection and swarm intelligence coordination in urban environments. Dr. Chew’s teaching portfolio includes courses on circuit design, control systems, and distributed generation technology. His interdisciplinary approach bridges theoretical concepts with real-world applications, particularly in addressing challenges in autonomous systems and sustainable energy solutions.

Gautami Alagarsamyمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Internet of Things (IoT)
• Robotics Engineering
• +۴ مورد دیگر

Gautami Alagarsamy is a Research Fellow at Heriot-Watt University’s Institute of Photonics and Quantum Sciences within the School of Engineering & Physical Sciences. She holds a PhD in Machine Learning and IoT from Anna University, India, and has over 10 years of experience in academia and startups. Her current research focuses on automating precision optical systems using AI/ML, funded by the UK’s EPSRC. Previously, she served as an Assistant Professor at SNS College of Technology and a Startup Mentor at SNS Innovation Hub, contributing to innovation policies and collaborations with institutions like IIT-Palakkad. Education: Bachelor’s Degree (Electrical & Electronics Engineering), Anna University (2010) Master’s in VLSI Design Engineering, Anna University (2013) MSc in Robotics, Heriot-Watt University (2024) PhD in Machine Learning & IoT, Anna University (2022) Research Interests: Her work spans AI-driven robotics, IoT applications, optical system automation, and cybersecurity. She emphasizes cross-disciplinary collaboration to address challenges in Industry 4.0 and sustainable energy solutions. Key projects include AI-based intrusion detection systems and organic solar cell material analysis. Publications: Over 15 Scopus-indexed articles and 5 book chapters, focusing on neural networks, smart city IoT systems, and renewable energy materials. Recent work highlights include efficient intrusion detection frameworks and reviews on organic photovoltaic materials. Awards & Grants: EPSRC Grant (EP/V054497/1) for AI-driven optical alignment systems 2018 India Innovation Challenge Design Contest Award Advising & Collaboration: Advised initiatives like NIRF, NBA, and NAAC at SNS College. Collaborates with Leonardo UK, University of Edinburgh, and IIT-Palakkad on innovation projects. Holds a design patent in India and actively mentors startups in technology commercialization. Labs/Teams: Part of the Institute of Photonics and Quantum Sciences, leading multidisciplinary teams in applied AI and IoT. Engaged in cross-university collaborations to advance Industry 4.0 technologies.