جستجوی استاد راهنمای دانشگاهی

• Human-Computer Interaction
• Machine Learning
• Ubiquitous Computing
• +۶ مورد دیگر

Shwetak N. Patel serves as Professor and Associate Director for Development & Entrepreneurship at the University of Washington's Paul G. Allen School of Computer Science & Engineering, with a joint appointment in the Department of Electrical & Computer Engineering. He holds the Washington Research Foundation Entrepreneurship Endowed Professorship and directs the Ubicomp Lab. His research spans Human-Computer Interaction, Ubiquitous Computing, and Sensor-Enabled Embedded Systems with applications in health and sustainability. Key focus areas include mobile health technologies, energy/water sensing systems, and low-power wireless platforms. His work bridges computing with real-world sustainability challenges through practical sensor applications. Patel has received numerous prestigious awards including the MacArthur Fellowship, ACM Prize in Computing, and Presidential PECASE Award. His scientific recognition spans foundational computing contributions and impactful commercialization. MacArthur Fellowship (2011) ACM Prize in Computing (2018) Presidential PECASE Award (2016) Sloan Fellowship (2012) NSF Career Award (2013) He actively advises students through the Ubicomp Lab and has secured significant research funding supporting health and sustainability projects. His commercial ventures include three successful startups acquired by major corporations. Patel maintains strong community engagement through K-12 STEM outreach and government advisory roles. His laboratory work focuses on practical sensor systems for home environments, with ongoing projects in mobile health monitoring and resource conservation technologies.

Jay Sui Tungمشاهده پروفایل

استادیار

• Remote Sensing
• Computer Modeling
• Machine Learning
• +۷ مورد دیگر

Dr. Jay Sui Tung is an Assistant Professor in the Department of Geosciences at Texas Tech University, affiliated with the College of Arts and Sciences. His work focuses on geophysical modeling of natural and anthropogenic surface deformation processes, including earthquakes, volcanic eruptions, and energy-related activities. He holds a Ph.D., M.Phil., and B.Sc. in Earth Sciences and Physics from the University of Hong Kong. Education: 2013: Ph.D. Earth Sciences, University of Hong Kong 2009: M.Phil. Physics, University of Hong Kong 2007: B.S. Physics, University of Hong Kong Research Interests: Dr. Tung uses remote sensing, numerical models, and machine learning to study crustal processes linked to natural hazards and climate change. His work addresses induced seismicity from wastewater injection, energy systems, and coastal impacts of sea-level rise. Recent work includes a 2020 study on the Mentone earthquake linked to wastewater disposal. Labs/Teams: He leads the GeoModeling for Earth Sustainability (GES) Lab, which investigates geomechanical and hydrogeological processes to mitigate risks from human-induced and natural hazards. Recruitment: Actively hiring a Postdoc Research Associate and PhD students (Fall 2024).

Mahroo Eftekhariمشاهده پروفایل

استاد

• Building Energy Management Systems
• HVAC Systems Optimization
• Thermal Comfort Modeling
• +۵ مورد دیگر

Professor Mahroo Eftekhari is a Professor in Building Services Engineering at Loughborough University, leading the Low Energy Building Services Engineering MSc programme. Her research focuses on energy-efficient building systems, thermal comfort, HVAC optimization, and renewable integration. She has pioneered control systems for airports and buildings, including MPC-based strategies to reduce energy use while enhancing occupant well-being. Notable contributions include the development of BISPA (Building & Industrial Services Pipework Academy), a national center for BIM and pipework training. Education: Holds qualifications including CEng (Chartered Engineer), DPhil (Doctor of Philosophy), FCIBSE (Fellow of Chartered Institution of Building Services Engineers), and SFHEA (Senior Fellow of the Higher Education Academy). Her academic career is marked by collaborations with Tata Steel, Mitsubishi R&D, and Vexo, yielding applied research in sustainable building technologies. Research Interests: Indoor Air Quality, Thermal Comfort Modeling, Zero Energy Buildings, Digital Twins, and Advanced Control Systems. She has developed innovative solutions like AI-driven thermal management for Building Energy Management Systems (BEMS) and interfaces to synchronize airport operations with energy systems. Awards & Grants: Secured funding from diverse bodies for projects such as adaptive thermal comfort models, BISPA infrastructure, and energy-efficient HVAC strategies. Her work emphasizes practical applications, including reducing CO₂ emissions via airport terminal optimization and improving renewable energy use in buildings. Lab & Teams: Leads the Building Energy Research Group, managing projects in closed-loop heating systems, IEQ monitoring, and hydronic system efficiency. The Civil Engineering labs house interactive BIM rigs launched with institutional and industry support.

Wenfeng Zhaoمشاهده پروفایل

استادیار

• Neural Engineering
• Compressed Sensing
• Ultra-low Power VLSI
• +۳ مورد دیگر

Wenfeng Zhao is an Assistant Professor in the Department of Electrical and Computer Engineering at Binghamton University. He holds a PhD from the National University of Singapore (2014) and BS/MS degrees from Huazhong University of Science and Technology (2007-2009). Prior to this role, he conducted postdoctoral research at the University of Minnesota's Biomedical Engineering Department. His research focuses on neural engineering, compressed sensing, ultra-low-power VLSI systems, and in-memory computing. Key areas include hardware security, biomedical signal processing, and energy-efficient computing architectures. His work spans applications in neural interfaces, cryptographic hardware, and IoT edge devices. Recent publications highlight advancements in block-cipher-in-memory architectures, emotion recognition via EEG analysis, and energy-efficient FPGA accelerators for neural networks. His research also addresses challenges in cryogenic memory systems and MRI-compatible neural recording devices. Zhao's contributions emphasize interdisciplinary approaches at the intersection of hardware design, signal processing, and cybersecurity. His lab develops novel solutions for low-power embedded systems and trustworthy IoT infrastructure.

• Instrumentation Electronics
• Memristor Modelling
• Signal Integrity
• +۶ مورد دیگر

Dr. Christos Papavassiliou is an Associate Professor in the Department of Electrical and Electronic Engineering at Imperial College London, part of the Faculty of Engineering. His research focuses on instrumentation electronics, memristor modeling, signal integrity, and novel device technologies such as SiGe devices, RF MEMS, and ReRAM. He leads the Space Lab and collaborates with the National Centre for Scientific Research in Athens. He holds senior membership in IEEE and is a member of the IET. Education: Ph.D. in Applied Physics, Yale University (1983–1989) MPhil in Applied Physics, Yale University (1983–1988) MS in Applied Physics, Yale University (1983–1985) B.S. in Physics, MIT (1979–1983) Research Interests: Memristor-based neuromorphic computing and stochastic systems High-performance instrumentation hardware and data acquisition Multi-state memristive memory and selectorless arrays Integration of memristors with CMOS for hybrid circuits Applications in biomedical wearables and edge AI deployment Key Contributions: Developed novel memristor models for circuit simulation Pioneered work on memristor-based true random number generators Advanced understanding of resistive drift and energy-constrained storage Designed FPGA-based systems for analog circuit emulation Labs & Teams: Active in the Space Lab at Imperial College, focusing on interdisciplinary research in electronics and space applications.

Li Songمشاهده پروفایل

استاد

• Building Energy System Optimization
• HVAC System Fault Detection
• Energy Efficiency Technology
• +۳ مورد دیگر

Li Song is a Professor and holds the Lesch Centennial Chair & Lloyd G. and Joyce Austin Presidential Professor at the University of Oklahoma's Aerospace & Mechanical Engineering Department. He leads the Building Energy Efficiency Lab and serves as AME Associate Director for Research. His expertise spans building energy systems, HVAC optimization, and fault detection technologies. Education: Ph.D. (Thermal/Fluid Science, 2004) from University of Nebraska-Lincoln; M.S. (Thermal/Fluid Science, 1996) from Harbin Institute of Technology; B.S. (Thermal Energy Systems, 1993) from Shengyang University of Civil Engineering and Architecture. Research focuses on energy-efficient HVAC systems, fault detection algorithms, and building performance analytics. Notable contributions include the ULEM-FDD system for high-performance buildings and virtual sensor technologies for airflow/water flow measurement. Awards include the ConocoPhillips Energy Prize (2011 finalist) and Bes-Tech Innovation Award (2006). Publications emphasize HVAC control strategies, energy modeling, and IoT-enabled diagnostics. Courses taught include Thermodynamics, Energy Efficient Building Systems Design, and HVAC Systems Engineering.

Mahsa Ghasemiمشاهده پروفایل

استادیار

• Reinforcement Learning
• Control Theory
• Active Perception
• +۳ مورد دیگر

Mahsa Ghasemi is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University, leading the AKADEMI Group. Her research focuses on theoretical advancements in trustworthy sequential decision-making for autonomous systems, emphasizing human-aware collaboration and adaptation to dynamic environments. She is affiliated with the Institute for Control, Optimization and Networks (ICON). Education: PhD in Electrical and Computer Engineering from The University of Texas at Austin (2021), MSE in Mechanical Engineering (2017), and BSc in Mechanical Engineering from Sharif University of Technology (2014). Research Interests: Reinforcement learning, control theory, active perception, multi-agent systems, robotics, and online learning. Applications span disaster response, healthcare, and autonomous systems design. Key methodological directions include compositional learning, human-AI collaboration, and adaptive decision-making under uncertainty. Teaching: Courses include Reinforcement Learning Theory (ECE 59500), Introduction to Reinforcement Learning (ECE 49595), and Python for Data Science (ECE 20875). Awards: Finalist for Student Best Paper Award at the 2018 American Control Conference (ACC). Students: Current advisees include Maheed H. Ahmed, Jayanth Bhargav, and Somtochukwu Oguchienti. Past members include Lai Wei and Juan Sebastian Mateo Ruiz Bulla. Service: Editorial roles at ICRA, ICCPS, and IFAC workshops. Reviewer for top conferences (NeurIPS, ICML) and journals (Automatica, IEEE TAC). Labs/Teams: Leads the AKADEMI Group, focusing on algorithmic and theoretical research in autonomous decision-making systems.

Weichao Wangمشاهده پروفایل

استاد

• Cybersecurity
• Wireless Networks Security
• Cloud Computing Security
• +۷ مورد دیگر

Weichao Wang is a Professor and Chair of the Department of Software and Information Systems at the University of North Carolina at Charlotte (UNC Charlotte). He holds a Ph.D. in Computer Science from Purdue University (2005), with earlier degrees from Tsinghua University. His research focuses on securing pervasive systems, wireless networks, cloud computing, and critical infrastructures, integrating multi-disciplinary approaches like information theory and visualization. He leads efforts in cybersecurity education for K-12 and higher education. Key roles include organizing IEEE conferences (e.g., IPCCC) and editorial roles in journals like ITU Intelligent and Converged Networks. His awards include the 2024 AECT Crystal Award and multiple Distinguished TPC recognitions. Students under his advisement have contributed to areas like mobile cloud computing and network security. Professional contributions include service on over 50 conference committees and journal reviewing. Current research emphasizes cybersecurity in education, IoT defense, and AI-driven security systems. His lab explores immersive visualization for cybersecurity training and augmented reality applications.

Arian Malekiمشاهده پروفایل

دانشیار

• Compressed Sensing
• Signal Processing
• Statistical Inference
• +۶ مورد دیگر

Arian Maleki is an Associate Professor in the Department of Statistics at Columbia University, affiliated with the Faculty of Arts and Sciences and the Foundations of Data Science Center. He holds a PhD from Stanford University (2010) and previously served as a postdoctoral scholar at Rice University. His research focuses on statistical inference, signal processing, and machine learning, with particular emphasis on compressed sensing, high-dimensional statistics, and algorithm design. Key areas include noise mitigation, image reconstruction, and the theoretical analysis of algorithms for inverse problems. Recent work highlights include studies on speckle noise challenges, phase transitions in compressed sensing, and certified data removal techniques. His contributions bridge theory and application, often addressing practical computational and statistical challenges in imaging and signal processing. No scientific awards are explicitly listed. Research outputs emphasize foundational advancements in statistical methodologies and algorithmic frameworks for high-dimensional data analysis. Labs/teams: Active involvement in the Foundations of Data Science Center at Columbia University.

Nan Marie Jokerstمشاهده پروفایل

استاد

• Photonics
• Optoelectronic Devices
• Integrated Optoelectronics
• +۷ مورد دیگر

Nan Marie Jokerst is the J. A. Jones Distinguished Professor of Electrical and Computer Engineering at Duke University's Pratt School of Engineering and Executive Director of the Duke Shared Materials Instrumentation Facility. She previously served as Chair of the Duke Academic Council (2014-2015) and Associate Dean for six years. B.S. in Physics, Creighton University (1982) M.S.E.E., University of Southern California (1984) Ph.D. in Electrical Engineering, University of Southern California (1989) Her research spans chip-scale photonic sensing systems , III-V thin-film lasers on silicon , metamaterials , and heterogeneous integration . She develops optical systems for medical diagnostics, environmental monitoring, and security applications through the Jokerst Laboratory, which combines optical system design, optoelectronic device development, and semiconductor fabrication expertise. Her recent publications show strong focus on terahertz strain mapping using metamaterials, multi-pixel tissue characterization for cancer margin detection, and microfluidic sensing platforms with embedded photodetectors. Key trends include advancing non-destructive structural monitoring and miniaturized biomedical diagnostics through novel photonic integration techniques. IEEE Fellow (2003) Optica Fellow (2001) NSF Presidential Young Investigator Award IEEE Third Millennium Medal IEEE/HP Harriet B. Rigas Medal USC Viterbi School Alumni Award She has advised numerous graduate students in photonic device research and secured major grants including the NSF National Nanotechnology Coordinated Infrastructure ($6M, 2015-2021) and NNCI: North Carolina Research Triangle Nanotechnology Network ($20M, 2020-2026). Her leadership extends to co-founding Triangle Women in STEM and serving on the National Academies Board on Global Science and Technology. The Duke Shared Materials Instrumentation Facility under her direction provides critical cleanroom and characterization resources for interdisciplinary research.

Tianhua Xuمشاهده پروفایل

دانشیار

• Optical Communication Networks
• Optical Sensing Systems
• Optoelectronics
• +۴ مورد دیگر

Dr. Tianhua Xu is a Reader in the School of Engineering at the University of Warwick and an Honorary Lecturer in the Department of Electronic and Electrical Engineering at University College London (UCL). He holds a Ph.D. in Optical Communications and Intelligent Signal Processing from KTH Royal Institute of Technology in Sweden, followed by postdoctoral and research roles at KTH, RISE Acreo, DTU, and UCL. His research focuses on optical communication systems, intelligent signal processing, machine learning, optical sensing, and advanced energy systems. He has secured major grants, including a €1.8M EU Horizon Europe project (SPAR) and a £285K UK National Grid initiative. Dr. Xu serves as an Associate Editor for IEEE Transactions on Communications and the Journal of the European Optical Society-RP, and chairs technical groups in the Optical Society of America. He has authored over 200 publications, including invited book chapters, with a Google Scholar h-index of 32. Current projects involve smart photonic sensing, energy storage systems, and deep learning in optical networks. His lab oversees six PhD students and multiple postdoctoral researchers. He actively recruits students through global scholarships and oversees vibrant research teams in optical communications, sensing, and energy systems.

Yingying Chenمشاهده پروفایل

استاد

• Smart Healthcare
• Internet of Things (IoT)
• Cyber Security
• +۷ مورد دیگر

Yingying (Jennifer) Chen is a Distinguished Professor and Department Chair in the Department of Electrical and Computer Engineering at Rutgers University, affiliated with the Wireless Information Network Laboratory (WINLAB) and the DAISY Lab. She holds a PhD in Computer Science from Rutgers University (2007). Her research focuses on Smart Healthcare, IoT, Cyber Security, Machine Learning, and AR/VR Security, with over 300 publications and multiple patents. Key roles include Associate Director of WINLAB, Fellow of ACM, IEEE, and AAIA, and recipient of the NSF CAREER Award (2010), Henry Morton Teaching Award (2017), and ACM Distinguished Scientist distinction. Awards also include the 2024 ACM Fellow and NAI Fellow (2022). Her work emphasizes interdisciplinary applications, such as AR/VR privacy attacks, adversarial machine learning defenses, and edge computing. Notable grants include NSF projects on AI on edge devices, NextG-enabled manufacturing, and healthcare system design. She advises Ph.D. students and collaborates with industry on testbeds like the Community-based Edge Sensing Testbed (NSF CCRI). Current research explores AI-driven sensing, privacy in immersive technologies, and robust multi-model analytics. Publications span top venues like ACM MobiCom, IEEE INFOCOM, and IEEE S&P. Labs include DAISY Lab (data analysis & security) and collaborations with WINLAB for wireless innovation. She serves on editorial boards of IEEE/ACM Transactions and organizes conferences like ACM MobiCom and IEEE ICDCS.

Cristina Torres-Machiمشاهده پروفایل

استادیار

• Infrastructure Asset Management
• Sustainability and Resilience in Transportation
• Decision-Making and Optimization Systems
• +۳ مورد دیگر

Cristina Torres-Machi is an Assistant Professor of Civil, Environmental and Architectural Engineering at the University of Colorado Boulder, holding the Beavers Professorship of Construction Engineering. She earned her PhD in Civil Engineering from Universitat Politècnica de Valencia and Universidad Católica de Chile (2015), a MSc in Planning and Management in Civil Engineering (2012) and BSc in Civil Engineering (2008) from Universitat Politècnica de Valencia. Her research focuses on infrastructure asset management, sustainability/resilience in transportation, and decision-making optimization systems. She leads the Innovation for Resilient Infrastructure (IRI) research group, advancing methodologies for long-term infrastructure management. Recognized with awards including the Abertis International Award (2016) and excellence in PhD dissertation (2015/2017), she serves as Chair of ASCE’s Construction Research Council and Vice-Chair of TRB’s Transportation Asset Management committee. Her work integrates machine learning, predictive analytics, and data science to improve pavement performance and lifecycle cost analyses. Professional affiliations include the American Society of Civil Engineers (ASCE) and active roles in TRB committees. Research emphasizes pavement rehabilitation strategies, flood impact modeling, and equitable infrastructure adoption trends. Over 60 publications (60+ citations) span journal articles, conference proceedings, and book chapters, with projects funded by public/private agencies. Current projects explore satellite-based monitoring, EV infrastructure impacts, and disaster-resilient traffic systems. Her recent work addresses procurement fallacies in design-build projects and integrates social vulnerability assessments in natural hazard planning.

Lu Suمشاهده پروفایل

دانشیار

• Internet of Things
• Cyber-physical Systems
• Wireless and Mobile Sensing
• +۷ مورد دیگر

Lu Su is an Associate Professor at the School of Electrical and Computer Engineering , Purdue University , with prior appointments at SUNY Buffalo . His research spans Internet of Things , cyber-physical systems , mmWave sensing , and crowd-sourced data validation , focusing on quality-of-information aware distributed sensing and security in autonomous systems . Ph.D. in Computer Science (2013) and M.S. in Statistics (2012) from University of Illinois at Urbana-Champaign M.E. and B.E. from Harbin Institute of Technology Research Interests: IoT , cyber-physical systems , crowd sensing , security and privacy , and machine learning for sensor networks. His work addresses quality-aware information integration , adversarial attacks in autonomous vehicles , and privacy-preserving crowd-sourced systems . Recent publications focus on mmWave-based sensing (e.g., 3D pose reconstruction), federated learning (driver monitoring), and data poisoning attacks in crowd-sourced systems. His research also extends to traffic optimization and human activity recognition using wireless networks. Professional Roles: Workshop Chair (INFOCOM 2023, 2022) TPC Vice Chair (INFOCOM 2021) Program Committee Member for top conferences Editorial Board, ACM Transactions on Sensor Networks Teaching: Courses on Embedded Systems , Internet of Things , and Network Concepts at both undergraduate and graduate levels.

John Lehrterمشاهده پروفایل

استاد

• Coastal Biogeochemistry
• Eutrophication Dynamics
• Hypoxia Modeling
• +۷ مورد دیگر

Dr. John Lehrter is a Professor of Marine Sciences and Associate Director of the Stokes School of Marine & Environmental Sciences at the University of South Alabama, as well as a Senior Marine Scientist at the Dauphin Island Sea Lab. He holds a Ph.D. in Marine Sciences from the University of Alabama (2003). His research focuses on coastal biogeochemistry, ecosystem modeling, and satellite ocean color remote sensing, with an emphasis on understanding eutrophication, hypoxia, and multiple stressor impacts on coastal ecosystems. Dr. Lehrter has advised numerous graduate and undergraduate students and leads a lab engaged in field studies, numerical modeling, and satellite data analysis. His work addresses societal challenges in coastal management and climate change adaptation. Research Interests: Multiple Stressor Impacts to Coastal Ecosystems, Marine Biogeochemistry, Ecosystem Modeling, Satellite Remote Sensing, and Hypoxia Dynamics. His lab develops tools to quantify nutrient pollution effects and predict ecosystem responses to management actions. Advising and Grants: Dr. Lehrter oversees a dynamic lab with graduate students, postdocs, and technicians. Current projects include modeling nutrient dynamics, satellite data applications for water quality, and experimental studies on multiple stressors (e.g., temperature, pH) impacting marine organisms. His lab collaborates with agencies like the EPA and NOAA, contributing to coastal policy and restoration efforts. Labs/Teams: Dauphin Island Sea Lab (DISL) and the University of South Alabama’s Stokes School of Marine & Environmental Sciences. The lab recently established a state-of-the-art facility for multiple stressor experiments on marine species.