جست‌وجوی استاد و پژوهشگر

Mustafa Abdallahمشاهده پروفایل

استادیار

• Cybersecurity
• Artificial Intelligence
• Game Theory
• +۷ مورد دیگر

Mustafa Abdallah is an Assistant Professor at the Computer and Information Technology (CIT) department of Purdue University in Indianapolis, with a courtesy appointment at the Purdue Polytechnic Institute. He holds a PhD in Electrical and Computer Engineering from Purdue University (2022) and prior degrees from Cairo University (MS: 2016, BS: 2012). His research focuses on game theory, behavioral decision-making, explainable AI, and deep learning, applied to cybersecurity, autonomous systems, and IoT anomaly detection. His work has been recognized by the prestigious Bilsland Fellowship and grants from IEEE and IUPUI. Industrial collaborations include Adobe Research (meta-learning for time-series forecasting), Principal Financial Group (financial risk prediction using Kalman filters), and RDI Company (deep learning for pronunciation systems, resulting in a US patent). He has published extensively in top venues like IEEE S&P, IEEE TCNS, and ACM AsiaCCS.

• Artificial Intelligence
• Machine Learning
• Signal and Image Processing
• +۴ مورد دیگر

Dr. Salim Bouzerdoum is a Senior Professor of Computer Engineering at the University of Wollongong (UOW), affiliated with the School of Electrical, Computer & Telecommunications Engineering. He holds a Ph.D. and M.Sc. in Electrical Engineering from the University of Washington. His roles include former Associate Dean for Research (2007–2013) and Head of School (2004–2006). He has served on the Australian Research Council panels and held visiting professorships globally. Education: Ph.D. in Electrical & Computer Engineering, University of Washington, Seattle, USA M.Sc. in Electrical Engineering, University of Washington, Seattle, USA Research Interests: His work focuses on Artificial Intelligence , Machine Learning , and Signal & Image Processing , with applications in radar imaging, computer vision, and smart sensors. Key areas include neural networks, object detection/tracking, and compressive sensing. Recent projects include assistive navigation tools for vision-impaired individuals and underwater mine detection via sonar imaging. Grants & Funding: He leads or co-leads over 30 funded projects, including: AI-based SAR Satellite Imaging System for Oceanic Waves (AGO, 2024–2025) A portable AI-guided navigation tool for vision-impaired people (KONEKSI, 2024–2026) Deep Learning for Vessel Surveillance using Satellite Imagery (NSW Space Research Network, 2022–2023) Teaching & Supervision: With 30+ years of experience, he has supervised 38 Ph.D. and 22 master’s students, mentored 12 early-career researchers, and delivered courses like Applied Data Analytics and Neural Networks . Current supervision includes projects on deep learning for obstacle detection and semantic segmentation. Awards: Eureka Prize (2011) for Defence Science ARC College of Experts Member (2009–2011) Multiple Vice-Chancellor Research Awards (1998–1999)

• Computer Vision
• Applied Machine Learning
• Computer Graphics
• +۳ مورد دیگر

Fahim Hasan Khan is an Assistant Professor in the Computer Science and Software Engineering Department at California Polytechnic State University, San Luis Obispo (Cal Poly). His research focuses on computer vision, applied machine learning, and citizen science applications, with a special emphasis on environmental monitoring and education. He holds a PhD in Computer Science and Engineering from UC Santa Cruz, where he was advised by Professors Alex Pang and James Davis, and a Master's in Computer Science from the University of Calgary. Key research contributions include real-time rip current detection systems (RipFinder, RipScout), mobile citizen science platforms (SmartCS), and educational tools to engage high school students in STEM research. His work has received media attention for innovations in drowning prevention and environmental safety. Notable awards include the Best Poster Presentation Award at ICIAR 2019 and the Best of the Baskin School of Engineering Award at UC Santa Cruz in 2022. Dr. Khan collaborates extensively with industry and academic partners to develop practical solutions for challenges in marine safety, autonomous systems, and healthcare diagnostics. He actively mentors students and seeks to democratize access to machine learning tools through no-code platforms.

Stefan Schulteمشاهده پروفایل

استاد

• Data Engineering
• Blockchain Technologies
• Internet of Things (IoT)
• +۴ مورد دیگر

Prof. Dr.-Ing. Stefan Schulte is a Full Professor at Hamburg University of Technology, leading the Institute for Data Engineering and the Christian Doppler Laboratory Blockchain Technologies for the Internet of Things (CDL-BOT). He holds a diploma in Economics and a Bachelor's in Computer Science from the University of Oldenburg, followed by a Master's in Information Technology (with Merit) from the University of Newcastle. After completing his PhD at TU Darmstadt in 2010, he held roles as Postdoctoral Researcher at TU Wien, Assistant Professor (tenure-track), and eventually Associate Professor before joining TU Hamburg in 2021. His research focuses on data engineering, blockchain technologies applied to IoT, elastic computing, and quality-of-service (QoS) aspects in smart systems. Notable contributions include work on fog computing, federated learning, and cross-blockchain interoperability. He has published over 140 papers in top-tier venues like IEEE Transactions on Services Computing and ACM Computing Surveys. Key awards include Best Paper Awards at the IEEE International Conference on Blockchain (2020) and the European Conference on Service-Oriented and Cloud Computing (2023). Prof. Schulte chairs major conferences such as the IEEE International Conference on Fog and Edge Computing (ICFEC 2025) and serves on editorial boards for journals like IEEE Transactions on Services Computing. He leads CDL-BOT, a lab exploring blockchain applications in IoT and manufacturing. His industrial collaborations include projects like SIMPLI-CITY (smart mobility) and CREMA (cloud-based manufacturing). Current research emphasizes blockchain interoperability, federated learning frameworks, and edge-AI systems. He actively reviews proposals for the German Research Foundation, EU programs, and industry initiatives.

Cory Simonمشاهده پروفایل

دانشیار

• Machine Learning
• Bayesian Optimization
• Computational Materials Science
• +۳ مورد دیگر

Cory Simon serves as Associate Professor in the Department of Chemical, Biological, and Environmental Engineering within Oregon State University's College of Engineering. His research integrates machine learning, optimization, and chemical engineering to advance materials discovery and environmental sensing systems. His academic foundation includes a Ph.D. in Chemical Engineering from the University of California, Berkeley and a B.S. in Chemical Engineering from The University of Akron. Simon's work centers on Bayesian methodologies for scientific challenges, featuring: Bayesian optimization for adaptive materials synthesis Statistical inversion of physical systems with uncertainty quantification Computational design of nanoporous sensor arrays Stochastic algorithms for robotic environmental monitoring Recent publications demonstrate accelerating focus on multi-fidelity optimization for molecular design and atmospheric water harvesting, bridging chemical engineering with computational science through data-driven approaches. Leading The Simon Ensemble research group, Simon champions a versatile 'buffet-style' research philosophy—drawing from mathematics, statistical mechanics, and machine learning to address interdisciplinary problems across chemistry, materials science, and environmental engineering.

Qin Linمشاهده پروفایل

استادیار

• Autonomous Systems
• Control Systems
• Robotics
• +۵ مورد دیگر

Qin Lin is an Assistant Professor in the Department of Engineering Technology at the University of Houston's Cullen College of Engineering. Their research focuses on autonomous systems, control theory, and safety-critical applications. Lin holds a Ph.D. in Computer Science from Delft University of Technology (2015-2019) and completed a postdoctoral fellowship at Carnegie Mellon University's Robotics Institute (2019-2021). Research interests include safe reinforcement learning, fault-tolerant control systems, and cybersecurity for industrial control systems. Lin has published extensively on topics like vehicle autonomy, exoskeleton safety, and disturbance rejection in robotics. Their work emphasizes practical applications of control theory in autonomous driving, robotics, and human-robot interaction. Recent publications highlight advancements in control barrier functions, latency-aware autonomous systems, and data-driven anomaly detection in ICS environments. Lin has been recognized for contributions to curriculum development in engineering technology and maintains active collaborations in automotive and robotics domains.

Wei Shiمشاهده پروفایل

استاد

• Distributed computing
• Cloud computing
• Data center networks
• +۶ مورد دیگر

Professor Wei Shi is a faculty member at the School of Computer Science, Carleton University. His research focuses on distributed computing, cloud networks, algorithm design for sensor/actuator systems, big data analytics, and data privacy. Notable projects include federated learning optimizations, blockchain-enabled edge intelligence for IoT/vehicle networks, and AI-driven cybersecurity solutions. His work addresses challenges in dynamic resource allocation, anomaly detection, and privacy-preserving techniques. Research Interests: Distributed Computing: Optimizing federated learning and client selection algorithms for wireless networks. Blockchain & Edge Intelligence: Developing decentralized systems for IoT and vehicular networks using AI large models. Security & Privacy: Innovating methods to detect AI-generated content, combat cyber-physical attacks, and protect user data privacy. Publications: Recent works emphasize federated learning applications, blockchain integration with edge computing, and cybersecurity for vehicular/IoT ecosystems. Key themes include energy-efficient algorithms, dynamic resource allocation, and intrusion detection in constrained environments. Email: wei.shi@carleton.ca

Munir Nazzalمشاهده پروفایل

استاد

• Transportation Engineering
• Civil Engineering
• Pavement Engineering
• +۴ مورد دیگر

Dr. Munir Nazzal is a Professor of Civil Engineering and Director of the Center for Smart, Sustainable & Resilient Infrastructure (CSSRI) at the University of Cincinnati. His research focuses on sustainable transportation infrastructure, pavement engineering, and innovative materials technology. He leads over $13M in grants from federal and state agencies, specializing in asphalt mixtures, pavement performance, and smart infrastructure. He serves as Principal Investigator (PI) on numerous projects, including optimizing maintenance equipment tracking, evaluating micro-surfacing bond strength, and developing AI-driven pothole detection systems. Nazzal is an editor for the ASCE Journal of Materials in Civil Engineering and Buildings Journal, and a licensed professional engineer in Ohio and Louisiana. His work integrates emerging technologies like IoT and autonomous vehicles for infrastructure monitoring. Key contributions include field validation of robotic crack sealing, analysis of aramid fibers in asphalt, and lifecycle cost studies of winter pothole patching methods. His research emphasizes cost-effective, environmentally friendly solutions for local and state transportation systems. Recent grants include a $600,000 federal project for district highway maintenance research, and a $1.2M study on robotic crack sealing methods. He collaborates with industry partners like Honda on vehicle-based roadway data pilots. Nazzal's lab explores nanoscale asphalt properties, thermal expansion effects, and recycled material utilization in pavements.

• Autonomous Driving
• Machine Learning
• Wireless Communication
• +۱۱ مورد دیگر

Dr. Tao (Kevin) Huang is a researcher at James Cook University's College of Science and Engineering, with expertise spanning autonomous driving, wireless communication systems, and medical imaging applications. His work integrates machine learning, sensor fusion, and multimodal data analysis to address complex challenges in vehicular networks, environmental monitoring, and healthcare technology. Research Interests: Dr. Huang's research focuses on Autonomous driving perception systems IoT-enabled vehicular networks AI for medical diagnostics and environmental sensing Signal processing and privacy-preserving communication protocols Recent Publications: His 2025 work emphasizes advancements in V2X cooperative perception, radar-LiDAR-camera fusion, and diffusion models for medical imaging. Key trends include cross-modal robustness, real-time processing for autonomous systems, and AI applications in sustainability.

Mikael Eklundمشاهده پروفایل

استاد

• Autonomous Systems
• Nonlinear System Identification and Control
• Health Informatics
• +۳ مورد دیگر

Dr. Mikael Eklund is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, within the Faculty of Engineering and Applied Science. He holds a PhD (2003), MSc (1996), and BSc (1989) in Electrical and Computer Engineering from Queen’s University. His research focuses on Autonomous Systems , Nonlinear System Identification and Control , Health Informatics , and Pervasive and Mobile Computing . He has expertise in medical image processing, robotic vehicles, and smart sensors for assisted living. Education and Work Experience : - PhD (Electrical and Computer Engineering), Queen’s University (2003) - MSc and BSc from Queen’s University (1996, 1989) - Visiting Postdoctoral Scholar at UC Berkeley (2003–2006) - Adjunct Assistant Professor at Queen’s University (2003) - Former Teaching Fellow at Queen’s University (1996–2001) - Industrial experience in flight control system engineering (CAE Inc., 1989–1996) Research Contributions : - Developed SensorNet, a wireless infrastructure for assisted living. - Advanced methods for nonlinear system identification in chemical processes and aerospace systems. - Pioneered real-time UAV safety protocols and model predictive control algorithms for aerial pursuit-evasion games. - Explored EMG signal processing for hand force estimation and MEG signal source localization in neuroscience. Teaching and Outreach : - Teaches courses like Medical Image Processing and Electric Circuits. - Active in interdisciplinary projects like the ITALH initiative for elder tech integration. - Presented at conferences such as IEEE EMBC, ACC, and CDC, emphasizing healthcare IT and autonomous systems.

Delphine Périé-Curnierمشاهده پروفایل

استاد

• Biomedical Technology
• Biomechanics
• Solid Mechanics
• +۶ مورد دیگر

Delphine Périé-Curnier is a Full Professor in the Department of Mechanical Engineering at Polytechnique Montréal and Director of Graduate Studies. Her research focuses on developing quantitative MRI techniques for non-invasive characterization of living tissue mechanical properties, particularly in cardiotoxicity detection and musculoskeletal mechanobiology . She leads the Bioperformance Analysis and Innovation Laboratory (LIAB) and contributes to the Institute of Biomedical Engineering. Education: Ph.D. from Paul Sabatier University, Toulouse, France Her work bridges medical imaging , biomechanical modeling , and finite element analysis to predict disease progression through pathomechanism understanding. Key projects include exercise-induced cardiac changes in childhood cancer survivors and spinal biomechanics in scoliosis. Recent publications (2023-2024) emphasize cardiovascular MRI for childhood cancer survivorship and hemodynamic modeling in left ventricle analysis. She supervises 26 graduate students, with completed theses spanning topics like doxorubicin cardiotoxicity , knee replacement stability , and spatial cardiac MRI protocols . Teaching includes graduate courses in biomedical design , advanced biomechanics , and modeling techniques .

H.F. Machiel Van der Loosمشاهده پروفایل

دانشیار

• Rehabilitation Robotics
• Roboethics
• Design Methodology
• +۳ مورد دیگر

H.F. Machiel Van der Loos is an Associate Professor and Associate Head – External at the Department of Mechanical Engineering, University of British Columbia. He holds a PhD from Stanford University (1992) in human-robot interaction and a Diplôme d'Ingénieur from École Polytechnique Fédérale de Lausanne (EPFL). As Director of the CARIS Lab, his research focuses on rehabilitation robotics, roboethics, design methodology, and human-robot interaction in industrial contexts. He has authored over 50 peer-reviewed journal articles and 100 conference papers, and serves as Associate Editor for the Journal of Assistive Technology . His teaching includes core design courses such as the Capstone Design Project and cross-disciplinary 'Designing for People' courses spanning Computer Science, Applied Science, and Library Science. Van der Loos organized major conferences including IEEE ICORR 2013 and ICED17 at UBC. His work includes developing assistive technologies like power-assisted wheelchairs, AR interfaces for human-robot collaboration, and rehabilitation robots. The CARIS Lab emphasizes ethical considerations in corporeal robotics and user-centered design principles. Current research projects involve multimodal robot programming through AR, gesture-based interaction, and adaptive wheelchair control systems. His lab has collaborated with industry partners like JDQ Systems Inc. and Tableau to advance practical robotics solutions.

Kenn Oldhamمشاهده پروفایل

استاد

• Controls
• Mechatronics and Robotics
• Micro/Nano Engineering
• +۳ مورد دیگر

Professor Kenn Oldham is a tenured faculty member in the Department of Mechanical Engineering at the University of Michigan, Ann Arbor, where he leads the Vibration and Acoustics Laboratory: Microsystems. His research spans Controls, Mechatronics and Robotics, and Micro/Nano Engineering with applications in medical imaging and autonomous systems. Education Ph.D. in Mechanical Engineering, University of California at Berkeley (2006) B.S. in Mechanical Engineering, Carnegie Mellon University (2000) His work focuses on micro-mechatronic systems for endoscopic imaging, micro-robotic manipulation, physiological feedback identification, and MEMS modeling. Current projects include NIH-funded development of cellular-resolution endoscopic microscopes for neurological disease detection and leadership in a $6M National Center for Biomedical Imaging and Bioengineering. Awards & Recognition NSF CAREER Award (2010) DARPA Young Faculty Award (2008) ASME Fellow (2025) ORAU Post-Doctoral Fellowship (2006-2007) ADPET Fellowship, UC Berkeley (2005-2006) NSF Graduate Research Fellowship (2000-2003) Professor Oldham mentors students through weekly individual meetings and collaborative lab sessions, emphasizing hands-on prototyping in physical systems development. He requires at least one GSI assignment during doctoral studies, supports summer internships, and funds conference attendance at venues including the American Control Conference and IEEE Conference on Advanced Intelligent Mechatronics. His lab maintains flexible scheduling with expectations for 4-5 year PhD completion.

Javier Irizarryمشاهده پروفایل

استاد

• Unmanned Aerial Systems (Drones) in Construction
• Construction 4.0
• Reality Capture Technology
• +۳ مورد دیگر

Javier Irizarry is a Professor and Interim Chair in the School of Building Construction at Georgia Tech's College of Design. He also serves as Associate Dean for Academic Affairs and Outreach , overseeing academic programs, diversity initiatives, and recruitment efforts. As Director of the CONECTech Lab, he pioneers research in Construction 4.0 and UAV applications for infrastructure challenges. Education : Ph.D. (Civil Engineering), Purdue University Masters in Engineering Management, Polytechnic University of Puerto Rico B.S. (Civil Engineering), University of Puerto Rico, Mayagüez Research Focus : Irizarry’s work integrates cutting-edge technologies into construction, including Unmanned Aerial Systems (UAS), Reality Capture, Virtual/Augmented Reality, and Human Factors in Robotics. His lab develops frameworks for Construction 4.0 , emphasizing technology-driven solutions for safety and efficiency. Lab & Impact : The CONECTech Lab focuses on Construction 4.0 , advancing drone-based inspection systems, digital twins, and safety analytics. His research has led to over 100 publications, with applications in infrastructure monitoring, safety management, and educational tools. Leadership : As Associate Dean, Irizarry drives academic innovation and outreach, including pre-college programs and diversity strategies. He is a licensed Professional Engineer (PE) and FAA-licensed drone pilot, bridging academia and industry.

Christopher Gilliamمشاهده پروفایل

استادیار

• Signal Processing
• Radar Systems
• Sampling Theory
• +۵ مورد دیگر

Dr. Christopher Gilliam is an Assistant Professor in Applied Signal Processing at the University of Birmingham's Department of Electronic, Electrical and Systems Engineering. He holds an MEng (1st Class Hons) in Electrical & Electronic Engineering (2008) and a Ph.D. in Signal Processing (2013), both from Imperial College London. Prior to joining Birmingham in 2022, he was a Postdoctoral Fellow at The Chinese University of Hong Kong (2013–2017) and a Research Fellow at RMIT University, Australia (2017–2022). Research Interests: Sensor signal processing, radar imaging, sampling theory, motion estimation, quantum navigation, and medical imaging. Labs: Microwave Integrated Systems Laboratory (MISL). Committees: Member of IEEE Signal Processing Society and APSIPA Technical Committees. His work focuses on advancing signal processing techniques for radar systems, navigation, and medical imaging. Recent research highlights include drone-based SAR imaging, motion correction in MRI, and fusion of classical/quantum sensors for inertial navigation. He is actively supervising PhD students and contributes to projects sponsored by DSTG. Publications span radar SLAM, probabilistic navigation algorithms, and deep learning-driven medical imaging solutions. His research bridges theoretical signal processing with practical applications in autonomous systems and healthcare.