جست‌وجوی استاد و پژوهشگر

Daniel Sousaمشاهده پروفایل

دانشیار

• Remote Sensing
• Wildfires
• Terrestrial Ecology
• +۷ مورد دیگر

**Daniel Sousa** is an **Associate Professor of Geography** at **San Diego State University (SDSU)**, affiliated with the **College of Arts and Letters**. His research focuses on remote sensing applications for Earth surface processes, integrating sensor engineering and data analysis methods like manifold learning. Key areas include wildfires, ecology, agriculture, climate variability, water quality, and geologic mapping. Sousa holds a **PhD in Earth & Environmental Sciences (Geophysics)** from Columbia University, with prior roles at NASA JPL, Ames Research Center, and the NOAA Knauss Fellowship on Capitol Hill. **Education**: BS from UC Davis (Natural Sciences), MA and PhD from Columbia University (Climate & Society, Earth & Environmental Sciences). **Research Interests**: Sousa develops novel methods to synthesize multiscale remote sensing data, addressing challenges in spectral and spatial analysis. His lab’s work spans geologic mapping, agricultural monitoring, and environmental health risk assessment, funded by NASA, NSF, USDA, and binational initiatives. **Publications**: Over 30 refereed articles (e.g., in *Remote Sensing of Environment*, *Science of the Total Environment*) and contributions to AI-driven ecosystem assessments. Recent work includes EMIT mission applications and global land cover analysis. **Awards**: SDSU Sustainability Seed Award, NSF NEON Early Career Scholar, and multiple Outstanding Reviewer Awards. **Grants**: $5.8M extramural funding, including NASA projects on geogenic arsenic exposure and coastal wastewater monitoring. **Teaching**: Courses include *Advanced Remote Sensing*, *Research Design in Geography*, and *Intermediate Remote Sensing*. Supervises graduate and undergraduate students in projects like plastic debris mapping and wildfire analysis. **Service**: Editorial Board Member of *Remote Sensing Applications: Society and Environment*, NASA SARP Faculty Advisor, and contributor to the Rockefeller Foundation’s Pandemic Prevention Institute.

• Control Systems Engineering
• Biomedical Engineering
• Aerospace Engineering
• +۳ مورد دیگر

Professor Paul Stewart is affiliated with the University of Derby's College of Science and Engineering, specializing in Control and Systems Engineering. His research focuses on biomedical monitoring systems, nuclear reactor optimization, airport operations, and aerospace propulsion. Notable projects include developing real-time blood pressure estimation systems for dialysis patients and advancing modular nuclear reactor designs using genetic algorithms. He collaborates across disciplines, addressing challenges in energy efficiency, control systems, and transportation logistics. His work integrates advanced algorithms and engineering principles to solve complex problems in healthcare, aerospace, and sustainable energy. Research interests span hemodialysis monitoring technologies, genetic algorithm applications in modular systems, and multi-objective optimization for airport ground movements. His contributions also include pioneering studies on solar-powered high-altitude aircraft and energy-efficient electric propulsion systems. Despite no explicitly listed awards or grants, his prolific publications reflect sustained academic and industrial engagement. Key collaborations involve institutions like the University of Derby and international teams in nephrology, aerospace, and transportation engineering fields. While no labs or formal research teams are named, his work indicates involvement in interdisciplinary research networks focused on practical engineering solutions with societal impact.

Roshan Ayyalasomayajulaمشاهده پروفایل

استادیار

• Wireless Systems
• Machine Learning
• Internet of Things (IoT)
• +۵ مورد دیگر

Roshan Ayyalasomayajula is an Assistant Professor in the Department of Computer Science and Engineering at the State University of New York's School of Engineering and Applied Sciences. His research focuses on wireless systems, machine learning, and IoT applications at the intersection of wireless sensing and robotics. He holds a PhD in Electrical and Computer Engineering from the University of California, San Diego (2023), following an MS from the same institution in 2019. His work emphasizes designing scalable and reliable systems to bridge the digital and physical worlds, with notable contributions including Bluetooth localization protocols incorporated into the BLE5.1 standard and collaborations with Cisco DNA-Spaces for indoor localization systems. Dr. Ayyalasomayajula’s research spans WiFi-based SLAM optimization, UWB tag tracking, and privacy-preserving wireless systems. Key research areas include resource-efficient localization algorithms, adversarial network security, and deep learning applications in acoustics and robotics. His projects address challenges in indoor navigation, edge computing, and cross-platform sensor fusion. His publications highlight advancements in WiFi and UWB systems, privacy mechanisms for wireless devices, and novel multi-task learning approaches. He actively contributes to both theoretical and applied research in wireless communication protocols and IoT architectures.

Murat Kantarciogluمشاهده پروفایل

استاد

• Data Privacy
• Computer Security
• Machine Learning
• +۵ مورد دیگر

Murat Kantarcioglu is an Ashbel Smith Professor of Computer Science at the University of Texas at Dallas within the Erik Jonsson School of Engineering and Computer Science. He holds visiting appointments at UC Berkeley and Harvard University, focusing on data privacy and security. With a Ph.D. in Computer Science from Purdue University (2005), he has made significant contributions to privacy-preserving data mining, blockchain analytics, and secure machine learning. Education: Ph.D. in Computer Science (Purdue, 2005) Current Roles: Ashbel Smith Professor (2021-present), Visiting Scholar at UC Berkeley (2020-present), Affiliate at Harvard (2013-present) Past Roles: Assistant (2005-2011), Associate (2011-2015), and Full Professor (2015-2021) at UTD His research focuses on data privacy , computer security , and machine learning , particularly addressing challenges in privacy-preserving distributed data mining , blockchain analytics , and adversarial machine learning . He has pioneered techniques for secure federated learning , topological analysis of blockchain networks , and privacy-utility tradeoffs in health data systems. Recent publications reveal a strong emphasis on IoT security , graph neural network vulnerabilities , and blockchain data structures . His work combines theoretical rigor with practical implementations using technologies like Intel SGX and homomorphic encryption. Notable Awards NSF CAREER Award (2009) IEEE Technical Achievement Award (2017) AMIA Homer Warner Best Paper Award (2014) Fellow of IEEE (2022), AAAS (2020), and ACM (2016) Key Projects Privacy-Preserving Genomics Data Sharing Adversarial Learning Frameworks Smart Contract Security Medical Data Protection Systems Labs Director of Data Security and Privacy Lab Collaborations with Vanderbilt, UC Berkeley (RISE Lab), and Harvard (Data Privacy Lab)

Andrew Longstaffمشاهده پروفایل

استاد

• Machine Tool Metrology
• Manufacturing Systems
• Industrial Sensors
• +۴ مورد دیگر

Andrew Longstaff is a Professor of Machine Tool Metrology at the University of Huddersfield, affiliated with the Department of Engineering and School of Computing and Engineering. He serves as Research Director at the Centre for Precision Technologies and is an Associate Member of the Behavioural Research Centre. His research focuses on improving machine tool performance through advanced metrology, thermal error modeling, sensor technology, and precision manufacturing processes. He holds a PhD from the University of Huddersfield and has led multiple high-value European and UK research projects, including Innovate UK initiatives and Knowledge Transfer Partnerships. Longstaff’s expertise includes machine tool calibration, vibration analysis, and the application of artificial intelligence for data processing in manufacturing. He is deeply involved in industry collaboration, working with machine tool manufacturers and end-users to address technical challenges. His work aligns with UN Sustainable Development Goals related to industrial innovation and infrastructure (SDG 9). He is a Fellow of the Higher Education Academy and a member of professional bodies such as the IET and CMI. His recent research trends emphasize thermal error compensation, ultrasonic core temperature measurement, and advanced sensor integration. Over 124 publications highlight contributions to precision engineering, with a focus on metrology, manufacturing systems, and sensor development. Awards include the EPSRC High Value Manufacturing Catapult Fellowship (2014). He supervises PhD students and teaches the MSc in Engineering Control Systems and Instrumentation, embedding his research into education.

Jonas Braaschمشاهده پروفایل

استاد

• Acoustic Virtual Reality
• Binaural Hearing
• Auditory Modeling
• +۳ مورد دیگر

Jonas Braasch is a Professor at Rensselaer Polytechnic Institute's School of Architecture and Associate Director for Research at the Experimental Media and Performing Arts Center (EMPAC). He teaches in the Graduate Program in Architectural Acoustics and leads research on collaborative virtual reality, binaural hearing, auditory modeling, and sensory substitution devices. His work has been funded by NSF, NSERC, and European agencies, and he holds dual PhDs in Electrical Engineering/Information Science and Musicology. His research integrates acoustic virtual reality systems, immersive museum soundscapes, telematic music, and assistive instrument design. Recent publications focus on networked immersive environments, spatial audio techniques, museum acoustics classification, and innovations in wind instrument design for accessibility. Publications emphasize the application of deep learning to acoustic prediction and multisensory integration.

Nasser Kehtarnavazمشاهده پروفایل

استاد

• Signal and Image Processing
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Nasser Kehtarnavaz is an Erik Jonsson Distinguished Professor and Director of the Embedded Machine Learning (EML) Laboratory at the University of Texas at Dallas's Erik Jonsson School of Engineering and Computer Science. He holds a PhD from Rice University (1987) and has over 40 years of academic and industrial experience. His research focuses on signal/image processing, machine learning, biomedical applications, and real-time embedded systems. He has authored/co-authored 11 books and over 450 publications, and supervised 37 PhD and 35 MS students. Leadership roles: Editor-in-Chief of Journal of Real-Time Image Processing , SPIE Conference Chair, IEEE Fellow (2013), AAIA Fellow Industrial collaborations: Texas Instruments, AT&T Bell Labs, US Army TACOM Research Lab Key contributions: Smartphone-based signal processing labs, hearing aid amplification algorithms, and FPGA-based embedded systems Research interests include real-time implementation on embedded processors, biomedical signal analysis, and smartphone-based laboratories. He has pioneered educational tools like anywhere-anytime labs using smartphones for signal processing education. Recipient of numerous awards including IEEE Region 5 Professional Leadership Award (2015), Outstanding Engineering Educator Award (2013), and community recognition from SPIE (2020-2021). His funded projects (62 as PI/Co-PI) span healthcare tech, energy systems, and semiconductor manufacturing. Director of the EML Lab and previously the Signal and Image Processing Lab. Teaches graduate courses like Machine Learning and Pattern Recognition and undergraduate courses in signals and systems.

Craig Glennieمشاهده پروفایل

استاد

• Kinematic Remote Sensing
• Lidar Processing
• 3D Change Detection
• +۶ مورد دیگر

Craig Glennie is a Professor in the Civil and Environmental Engineering department at the Cullen College of Engineering , University of Houston . He serves as the Director of the National Center for Airborne Laser Mapping (NCALM) and Director of Engineering Defense Research Initiatives . His research focuses on kinematic remote sensing, lidar processing, 3D change detection, and open-source software development. Education: Ph.D. and B.Sc. in Geomatics Engineering from the University of Calgary (1999, 1996). Professional Experience: Faculty member at the University of Houston since 2010, with prior industry roles at Terrapoint USA Inc. and Aerotec LLC. Research Trends: His recent publications emphasize advancements in lidar technology, flood modeling, volcanic CO2 monitoring, and applications of machine learning to geospatial data. Notably, he has contributed to NASA's Surface Topography and Vegetation missions and developed methods for ICESat-2 data analysis. Labs & Teams: Leads NCALM, a national facility for airborne lidar data acquisition and processing, and collaborates on defense research initiatives.

Cong Shiمشاهده پروفایل

استادیار

• Applied Machine Learning
• Security and Privacy for Mobile Systems
• Robust and Trustworthy ML/AI
• +۴ مورد دیگر

Cong Shi is an Assistant Professor in the Department of Computer Science at New Jersey Institute of Technology (NJIT). His research focuses on applied machine learning, security and privacy for mobile systems, and robust/trustworthy AI. Specific interests include adversarial machine learning, WiFi sensing, and AR/VR security. Education: Ph.D. in Electrical and Computer Engineering from Rutgers University (2022), M.S. in Electrical Engineering from Stevens Institute of Technology (2015), B.S. in Electrical Engineering and Automation from Guangdong University of Technology (2013). Research highlights include developing methods for vital sign monitoring using motion sensors, backdoor defense mechanisms in AI models, and privacy leakage prevention in AR/VR ecosystems. Recent work explores attacks on RF signal classification and vibration-based speech reconstruction. His publications appear at venues like IEEE S&P, ACM CCS, and AAAI. Teaching responsibilities include courses like CS 645 (Security and Privacy in Computer Systems) and CS 785 (Seminar in Computer Science).

Amit Kumar Mishraمشاهده پروفایل

استاد

• Machine Learning
• Radar Technology
• Synthetic Aperture Radar (SAR)
• +۷ مورد دیگر

Amit Kumar Mishra is a Professor of Communications Engineering and Director of the National Spectrum Centre at Aberystwyth University, UK. His primary affiliation is within the Faculty of Business and Physical Sciences. He leads interdisciplinary research in radar technology, machine learning, and cognitive architectures with applications in environmental monitoring, biomedical engineering, and cybersecurity. His research interests include Synthetic Aperture Radar (SAR) imaging, AI-driven environmental sensing (e.g., agricultural monitoring, biodiversity tracking), and advanced communication systems like IRS-enhanced NOMA networks. Recent work focuses on developing symbiotic AI-human cognitive systems for attention management and sensor data assimilation in industrial environments. Over 200+ publications span journals like Sensors , IEEE Transactions , and conference proceedings. Notable collaborations include projects on oil spill detection, underwater object recognition, and patient-specific medical modeling. He co-led the SMART Expertise project (2025) focused on innovation bridging. Media highlights include reports on medical imaging applications (Coarctation of Aorta studies) and the Aberystwyth University Technology Centre's innovation initiatives. His work aligns with UN SDGs related to sustainable cities and responsible consumption patterns.

Donghoon Kimمشاهده پروفایل

استادیار

• Autonomous Systems Design
• Fault-Tolerant Control
• Health Monitoring of Autonomous Systems
• +۳ مورد دیگر

Dr. Donghoon Kim is an Assistant Professor at the University of Cincinnati's Department of Aerospace Engineering and Engineering Mechanics, part of the College of Engineering and Applied Science. He leads the Intelligent Autonomous Systems Research Laboratory (IASSRL), focusing on autonomous systems, fault-tolerant control, and celestial mechanics. Prior to academia, he worked at LG Electronics as a Senior Research Engineer, developing service robotic platforms. His professional affiliations include senior membership in AIAA and IEEE, and roles in technical committees for Astrodynamics and Robotics. Education: PhD in Aerospace Engineering (Texas A&M University, 2013) MS and BS in Aerospace & Mechanical Engineering (Korea Aerospace University, 2010 and 2008) Research Interests: Dr. Kim's work centers on intelligent autonomous systems , including robotic control, spacecraft dynamics, and machine learning integration. He emphasizes fault-tolerant control systems and health monitoring for autonomous platforms. His projects span celestial mechanics applications and deep learning-driven solutions for aerospace challenges. Grants & Awards: Recipient of the Neil Wandmacher Teaching Award (2022) $2.3M Air Force Research Lab grant for space robotics technologies (2024) $569K DoD grant for multi-agent trajectory planning (2024) Labs & Teams: Directs the IASSRL , collaborating on projects like the LEOPARDSAT-1 orbital platform and IntroSat educational spacecraft. Engages in industry partnerships with companies like Gimbal Innovations and CincyTech .

• Optical Communications
• Quantum Cryptography
• Fiber Optic Sensing
• +۵ مورد دیگر

Nikas Thomas is an External Instructor at the Department of Informatics (DI) of the National and Kapodistrian University of Athens (NKUA). His work spans multiple interdisciplinary areas including quantum cryptography, fiber optic sensing technologies, and seismic monitoring. Key roles include advancing secure communication protocols through quantum key distribution (QKD) and developing novel Li-Fi transceivers using perovskite photodiodes. He also pioneers applications of Distributed Acoustic Sensing (DAS) for urban earthquake monitoring in Athens, leveraging existing fiber-optic infrastructure for environmental and geophysical studies. His research bridges theoretical frameworks (e.g., phase transmission analysis) with practical implementations in optical communication systems and seismic detection. Research interests focus on: Secure optical communication systems leveraging quantum principles Fiber optic-based seismic and acoustic sensing Emerging Li-Fi technologies for high-speed wireless networks Phase-sensitive fiber optic analysis for geophysical applications Publications from 2022-2024 highlight trends in: Quantum security protocols for optical and radio-over-fiber systems Urban DAS applications for earthquake monitoring Microwave frequency interferometry for low-cost seismic sensors No scientific awards are explicitly listed in the provided materials. His work often involves collaborative projects with industry and academic partners, though specific grants are not detailed here. Current projects include optimizing DAS for real-time urban seismic networks and exploring novel modulation formats for secure optical transmission.

José Luis Chávezمشاهده پروفایل

استاد

• Agricultural Water Management
• Hydrologic Science
• Remote Sensing Applications
• +۴ مورد دیگر

José Luis Chávez is a Professor in Civil and Environmental Engineering at Colorado State University. He specializes in irrigation engineering, water management, and remote sensing applications in agriculture. His academic career includes a B.S. from Universidade Federal da Paraiba (1992), an M.S. in Irrigation Engineering (Utah State University, 1999), and a Ph.D. in Biological and Agricultural Engineering (Utah State University, 2005). Dr. Chávez’s research focuses on optimizing irrigation practices through evapotranspiration (ET) modeling, remote sensing technologies, and precision irrigation strategies. He explores crop water use efficiency, soil moisture dynamics, and the integration of multispectral imaging for irrigation scheduling. His work bridges hydrology, agronomy, and engineering to address water scarcity challenges in agricultural systems. Key contributions include advancing SEBAL-A algorithms for ET estimation under advective conditions, developing crop coefficient models using remote sensing, and improving irrigation management techniques in semi-arid regions. He teaches courses on irrigation systems design, water management, and drainage engineering. His professional affiliations include the American Society of Civil Engineers and the U.S. Commission on Irrigation and Drainage. While no awards are explicitly mentioned, his extensive publications reflect significant contributions to agricultural water management and remote sensing science.

• Control systems
• Mechatronics
• Precision engineering
• +۳ مورد دیگر

Chun-Yi Su is a Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University. His research focuses on advanced control systems, mechatronics, robotics, and precision engineering. He specializes in nonlinear control, hysteresis compensation, and adaptive systems applied to soft actuators, UAVs, and smart materials. Key research areas include: Control of dielectric elastomer actuators Fault-tolerant cooperative control of unmanned aerial vehicles (UAVs) Adaptive neural network-based control for nonlinear systems Data-driven approaches for power electronics and energy systems Recent work emphasizes: Soft robotics actuation mechanisms Fractional-order control strategies Resilient control under cyber-physical attacks Biomimetic robotic systems His lab develops innovative solutions for smart materials, mechatronic systems, and autonomous robotics. Applications span renewable energy systems, biomedical devices, and aerospace engineering. Active in collaborative research with industry partners.

Mudassir M. Rashidمشاهده پروفایل

استادیار

• Process Control
• Biomedical Engineering
• Pharmaceutical Engineering
• +۲ مورد دیگر

Mudassir M. Rashid serves as Assistant Professor of Chemical Engineering and Director of the Pharmaceutical Engineering Program at Illinois Institute of Technology's Armour College of Engineering. His work bridges chemical engineering fundamentals with cutting-edge applications in biomedical systems and pharmaceutical manufacturing. His academic credentials include: Ph.D. in Chemical Engineering from McMaster University, Hamilton, Canada (2016) B.Eng. in Chemical Engineering from McMaster University, Hamilton, Canada (2011) Dr. Rashid's research program centers on three interconnected domains: Data-driven modeling and control for biological/chemical systems, specializing in recursive identification and adaptive control of nonlinear time-varying processes with variable delays Diabetes technology development through metabolic modeling, simulation of physiological pathways, and automated closed-loop insulin delivery systems Pharmaceutical manufacturing innovation via process analytical technology for real-time monitoring, control, and optimization of drug production quality attributes His methodology integrates advanced control theory with practical healthcare and industrial applications, demonstrating particular expertise in artificial pancreas systems and pharmaceutical process optimization. Analysis of his 15 most recent publications (2016-2019) reveals a dominant research trajectory in adaptive control systems for diabetes management, constituting over 80% of his output. Key themes include glucose prediction algorithms, plasma insulin estimation techniques, and disturbance-handling strategies for meals/exercise within artificial pancreas frameworks. The remaining publications address economic model predictive control applications in chemical batch processes and metallurgical systems, showcasing methodological versatility across biomedical and industrial contexts. No scientific awards are documented in the provided materials. While specific advising activities and grant funding details are absent from the source text, his leadership of the Pharmaceutical Engineering Program indicates significant academic administrative responsibilities. Dr. Rashid directs the Pharmaceutical Engineering Program at Illinois Tech, though the source material does not specify dedicated laboratory facilities or research team structures beyond his program oversight role.