جست‌وجوی استاد و پژوهشگر

Jay Aikatمشاهده پروفایل

استاد پژوهشی

• Computer Networking
• Data Science Education
• Cloud Computing Security
• +۳ مورد دیگر

Jay Aikat is the Vice Dean of the School of Data Science and Society at the University of North Carolina at Chapel Hill since July 2022, and a Research Professor in the Department of Computer Science. She previously served as Chief Operating Officer at RENCI (2016–2022) and held leadership roles in IT at UNC-Chapel Hill’s School of Information and Library Science. Aikat holds a Ph.D. in Computer Science from UNC-Chapel Hill, with earlier degrees in Electrical and Electronics Engineering and Computer Science. Her research focuses on experimental methods in networking, Internet traffic modeling, cloud security, and data science education. Notable contributions include work on airborne network topology management, cloud computing security frameworks, and pedagogical innovations in big data training. She has collaborated with institutions like NIEHS (National Institute of Environmental Health Sciences) and contributed to national-scale research infrastructure projects through GENI and COMBINE initiatives. Her publication trends reflect deep engagement with network experimentation, cybersecurity challenges in cloud environments, and scalable solutions for dynamic wireless systems. Aikat has also authored foundational work on web traffic evolution and protocol benchmarking, emphasizing reproducible methodologies in networking research. Her professional trajectory includes bridging academic research with applied IT leadership, fostering interdisciplinary collaborations across computer science, environmental health, and data science domains. Current efforts focus on expanding data science education and driving innovation through the School of Data Science and Society.

Fred Langerakمشاهده پروفایل

استاد

• Product Development & Management
• New Product Development (NPD)
• Innovation Management
• +۹ مورد دیگر

Fred Langerak is a Full Professor and Chair of Product Development & Management at Eindhoven University of Technology (TU/e), within the Department of Industrial Engineering and Innovation Sciences. He serves as Vice-Dean of the department and has held roles such as chairman of the Innovation, Technology Entrepreneurship & Marketing (ITEM) group. His research focuses on enhancing the efficiency and effectiveness of product development processes, including fuzzy front end management, portfolio management, accelerated product development, and launch strategies. Academically, Langerak holds an MSc (1993) and PhD (1997) from the Erasmus School of Economics. Before TU/e, he worked as an Assistant and Associate Professor at Erasmus School of Economics and Rotterdam School of Management. He is an editorial board member of the Journal of Product Innovation Management and co-founded the Dutch PDMA chapter. His awards include the Christer Karlsson Best Paper Award (2017), Best Reviewer Award (2015), and a bronze listing in the JPIM Hall of Fame (2018). He has contributed to projects like Freight Traffic Management as a Service (2020–2023) and the Brabant Center of Entrepreneurship (2008–2013). His work addresses sustainable development goals through innovation in product lifecycle management and cross-industry collaborations.

Benjamin Ezeمشاهده پروفایل

استاد مدعو

• Big Data Analytics
• Cloud Data Warehousing
• Health Data Analytics and Integration
• +۸ مورد دیگر

Benjamin Eze is a part-time and adjunct professor at the School of Engineering Design and Teaching Innovation within the University of Ottawa . He holds a PhD in Digital Transformation and Innovation, an MSc in Electronic Business Technologies, and a BSc in Computer Engineering. Professionally, he serves as Lead Architect at Next Pathway Inc. and Business Intelligence Partner with Champlain Ontario Health at Home. Education: PhD – Digital Transformation and Innovation (University of Ottawa) MSc – Electronic Business Technologies (University of Ottawa) BSc – Computer Engineering Benjamin specializes in Big Data Analytics , Healthcare Data Privacy , Cloud Computing , and AI in Software Engineering . His work bridges technology and healthcare, focusing on secure data integration and digital transformation. Scientific Awards: Holds two patents in Canada and the United States Benjamin's research spans healthcare data governance, cloud infrastructure (DevOps, DevSecOps), and privacy-preserving technologies. His publications emphasize systematic approaches to data anonymization, cloud-based healthcare monitoring, and ethical AI frameworks. He teaches in upskilling programs at the University of Ottawa’s Professional Development Institute, FxInnovation, and CENGN CloudCampus DevOps programs, while collaborating with organizations like Cisco, Montfort Hospital, and Accreditation Canada.

Hung Laمشاهده پروفایل

دانشیار

• Robotics
• Computer Vision
• Control Systems
• +۲ مورد دیگر

Hung La is an Associate Professor in the Department of Computer Science and Engineering at the University of Nevada, Reno's College of Engineering. He directs the Advanced Robotics and Automation Lab, focusing on robotic systems for infrastructure inspection (culverts, bridges), autonomous navigation, and control systems. His research integrates computer vision, machine learning, and multi-agent systems to develop field-deployable robotic solutions. La's publications demonstrate expertise in robotic perception (3D registration, SLAM), control systems (quadrotors, climbing robots), and secure machine learning. Recent work emphasizes practical applications in civil infrastructure inspection, warehouse automation, and medical robotics. His research consistently combines theoretical advances with hardware implementations for real-world deployment.

Martial Hebertمشاهده پروفایل

استاد

• Computer Vision
• Robotics
• Autonomous Systems
• +۶ مورد دیگر

Martial Hebert is the Dean and University Professor of Robotics at Carnegie Mellon University's School of Computer Science (SCS), leading since August 2019. His career spans decades at CMU's Robotics Institute (RI), where he served as Director (2014-2019) and Professor (1999-present). Broad research interests in computer vision, perception for autonomous systems, and 3D environment modeling. Current PhD advisees include Zhipeng Bao, with numerous past PhD and Master's students listed. Editor-in-Chief of the International Journal of Computer Vision and member of IEEE Robotics and Automation Society. His research focuses on computer vision and robotics , emphasizing 3D data interpretation, object recognition, and machine learning applications. Recent articles highlight advancements in 3D vision , diffusion models , and disaster response robotics , reflecting a trajectory from foundational algorithms to applied autonomous systems. Notably, he pioneered the first master's program in computer vision in the U.S. Hebert's leadership in academic and research spheres includes directing the RI and securing an operating budget peak during his tenure. His work bridges perception, intelligence, and autonomous systems, with applications in disaster scenarios , LiDAR point cloud detection , and video forecasting .

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

Shahid Awan is a Lecturer at the School of Computing, Engineering and Physical Sciences. He holds a Ph.D. in Computer Science, specializing in Machine Learning, with a focus on applying intelligent systems to United Nations Sustainable Development Goals (UNSDGs), particularly in circular economy, IoT-enabled smart agriculture, and health informatics. His work emphasizes innovation, as seen in projects like 'Cricket Video Scene Categorisation' (Rector’s Award for Innovation, 2018) and predictive models for electric demand and dengue fever spread. Education: Ph.D. in Computer Science. Professional Development: Completed the 'Innovation Strategy Course' by KTN UK and 'Leadership and Management Training Modules' from Ashorne Hill Management College, UK. Research Interests: Machine Learning applications, Deep Learning, IoT, and Data Science in healthcare, sustainability, and smart systems. His publications highlight contributions to blockchain security, medical imaging analysis, and education technology. Notable Projects: Led projects on electric demand forecasting (collaborating with National Grid) and dengue fever prediction (health department). Founded the circular economy startup Circulayo, focusing on innovation strategy. Scientific Awards: Rector’s Award for Innovation (2018). Advising and Grants: Accepting PhD students and secured funding for startups like 'Electrical Demand Forecasting' through Silicon Valley pitches. Collaborates with industry partners like Crickingif and the National Grid. Labs/Teams: Active in interdisciplinary teams addressing SDGs through tech solutions, though no specific lab names are provided.

Chamitha De Alwisمشاهده پروفایل

مدرس ارشد

• AI Security
• Cybersecurity
• Network Security
• +۵ مورد دیگر

Dr. Chamitha De Alwis is a Senior Lecturer in the School of Computer Science & Technology at the University of Bedfordshire, within the Faculty of Creative Arts, Technologies & Science. He holds a B.Sc. (First Class Honors) in Electronic and Telecommunication Engineering from the University of Moratuwa, Sri Lanka, and a Ph.D. in Electronic Engineering from the University of Surrey, UK. He is a Senior Member of the IEEE and a Fellow of the Higher Education Academy. Research Interests: Dr. De Alwis focuses on AI Security, Cybersecurity, Network Security, 5G/6G technologies, Blockchain, and Edge Computing. His work spans cutting-edge areas such as quantum technologies for next-gen networks, smart grid security, and healthcare applications of edge computing. He has secured competitive research grants and contributes to high-impact projects in collaboration with industry and academia. Teaching Areas: Cybersecurity, Network Security, and Mobile Communication. He actively supervises PhD students in these domains, including Mr. Mohammad Ahmad, Mr. Ahmad Kanbour, and Ms. Charithri Nanayakkara. Publications: His recent work explores Edge AI, 6G architectures, blockchain in energy systems, and eHealthcare innovations. Notable trends include integrating AI with edge computing for real-time applications and addressing security challenges in 6G networks. Awards/Honors: Fellow of the Higher Education Academy (2024) Senior Member, IEEE (2021) Grants & Collaborations: Secured multiple research grants supporting projects in Edge Computing, 6G technologies, and Smart Grid applications. Engaged with interdisciplinary teams in the Institute for Research in Applicable Computing (IRAC) and the Institute for Research in Engineering and Sustainable Environment (IRESE). Labs & Teams: Affiliated with the School’s research institutes, contributing to initiatives in robotics, AI, and sustainable engineering. Involved in collaborative projects with industry partners to advance edge computing and cybersecurity solutions.

Senem Velipasalarمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Wireless Smart Camera Networks
• +۸ مورد دیگر

Senem Velipasalar is a Professor in the Department of Electrical Engineering and Computer Science (EECS) at Syracuse University, affiliated with the Smart Vision Systems Laboratory and the Aging Studies Institute. She holds a Ph.D. and M.A. from Princeton University, an M.S. from Brown University, and a B.S. from Bogazici University. Her research focuses on machine learning, computer vision, and wireless smart camera systems, with applications in human activity classification, driver behavior analysis, and defense against adversarial attacks. Her honors include the NSF CAREER Award (2011), 2021 IEEE Technological Innovation Award, and multiple doctoral prizes for her advisees. She leads grants totaling over $4M, including ARPA-E projects on occupancy detection and DOE-funded research on aerial energy modeling. Research interests span embedded vision, distributed multi-camera tracking, and energy-efficient algorithms. Her lab develops technologies like wearable camera-based fall detection and autonomous UAV navigation. Notable publications include works on adversarial attacks, fNIRS brain activity analysis, and thermal pedestrian detection.

• Autonomous Vehicles
• Robotic Perception
• Sensor Fusion
• +۲ مورد دیگر

Eduardo Nebot is Emeritus Professor and former Patrick Chair in Automation and Logistics at the University of Sydney, where he founded the Australian Centre for Robotics. His research develops perception and navigation systems for autonomous vehicles, focusing on robust operation in complex environments. Nebot's work enables autonomous systems for mining, transportation, and field robotics applications. Research interests include sensor fusion, cooperative perception, probabilistic tracking, and validation methods for autonomous systems. Current projects investigate V2X-enabled cooperative driving, pedestrian trajectory prediction, and robust localization under environmental changes. Publication trends highlight multi-sensor perception systems, with recent work emphasizing domain adaptation for 3D detection, safety validation frameworks, and human-robot interaction in autonomous driving. Articles consistently address real-world deployment challenges in industrial and urban settings. Fellow of the Australian Academy of Technology and Engineering (2016) Fellow of the IEEE (2016) The Australian Centre for Robotics collaborates with industry partners on autonomous haulage systems and intelligent transportation. Nebot has supervised numerous PhD candidates in robotics and maintains research partnerships with mining and automotive sectors.

• Multimedia Computing
• Computer Vision
• Computer Graphics
• +۷ مورد دیگر

Professor Zhiyong Wang is a faculty member at the School of Computer Science, University of Sydney, serving as Deputy Director of Sydney Informatics Hub and Director of the Multimedia Computing Laboratory. His research focuses on multimedia computing, including information retrieval, computer vision, AI, and applications in agriculture, healthcare, and environmental monitoring. He holds a B.Eng., M.Eng. from South China University of Technology, and a Ph.D. from The Hong Kong Polytechnic University. His work bridges theoretical advancements and real-world applications, with over 200 peer-reviewed publications. He is a member of IEEE and former President of Australia Pattern Recognition Society (APRS). Research Interests: Enabling computers to understand and create multimedia content, with emphasis on human-centric computing, remote sensing, and interdisciplinary applications. Notable areas include action recognition, medical image analysis, and environmental monitoring. Current Roles: Leads the Multimedia Computing Lab, collaborates with Sydney Institute of Agriculture and Brain and Mind Centre. Teaches COMP5216 (Mobile Computing), COMP5405 (Digital Media Computing), and COMP5425 (Multimedia Retrieval). Students: Supervises 9 Ph.D. students focusing on topics like precision agriculture, biomedical engineering, and AI-driven video analytics. Key projects include soil moisture forecasting, biomechanical risk analysis for knee osteoarthritis, and explainable machine learning.

Xin Xiaمشاهده پروفایل

پژوهشگر ارشد

• Recommender Systems
• Machine Learning
• Graph Neural Networks
• +۳ مورد دیگر

Dr. Xin Xia is a Postdoctoral Research Fellow at the School of Electrical Engineering and Computer Science, University of Queensland. His research focuses on advancing machine learning techniques, particularly in the domain of recommender systems, with an emphasis on on-device deployment, graph-based learning, and self-supervised methods. He has contributed to optimizing recommendation systems for edge computing environments and improving their efficiency in resource-constrained settings. Key research areas include: On-device recommendation systems and edge AI Graph neural networks for recommendation Self-supervised learning and contrastive techniques Efficient model optimization and knowledge distillation His publications analyze trends such as transitioning cloud-based systems to on-device applications, reducing communication overhead in distributed models, and simplifying graph contrastive learning frameworks. These contributions highlight his expertise in bridging theoretical advancements with practical, deployable solutions. Dr. Xia’s work has been presented at top-tier conferences such as SIGIR, CIKM, and AAAI, reflecting the academic rigor and industry relevance of his research.

Waylon Brunetteمشاهده پروفایل

استادیار

• Mobile Computing
• Computing for Development
• Ubiquitous Computing
• +۵ مورد دیگر

Waylon Brunette is an Assistant Professor in the Department of Computer & Cyber Sciences at Augusta University. His research focuses on mobile computing, computing for development, ubiquitous computing, and edge computing, with an emphasis on creating systems that integrate seamlessly into users' environments to support global health and humanitarian efforts in resource-constrained settings. He leads the development of the Open Data Kit (ODK) framework, designed to simplify mobile application development for disconnected environments. Education: Ph.D. (Computer Science, University of Washington, 2020), MS (Computer Science, UW, 2012), BSE (Computer Engineering, UW, 2002). Research interests include wireless sensor networks, sensor-enhanced systems, and frameworks for non-programmers to deploy robust applications in low-resource areas. He serves as Chair of the Research Computing Infrastructure Committee (RCIC) and Editor for the ACM Journal on Computing and Sustainable Societies. Previously, he was a co-founder of the ODK Project at UW's Allen School. Service activities include mentoring junior researchers and organizing the Southeastern Collegiate Penetration Testing Competition. His work emphasizes practical, deployable solutions for global challenges in healthcare, logistics, and international development.

Qun Liمشاهده پروفایل

استاد

• Edge Computing
• Operating Systems
• Distributed Systems
• +۳ مورد دیگر

Qun Li is a Professor of Computer Science at the College of William and Mary, leading the Edge Computing Laboratory. He holds an IEEE Fellow distinction and has served as Graduate Director (2010-2011). His research focuses on edge computing, operating systems, distributed systems, and security & privacy, with over 100 publications in top venues like ACM CCS, ICSE, and NSDI. Li has advised numerous PhD students, including Zhengrui Qin and Ed Novak, who now hold academic positions. He chairs conferences including ACM/IEEE Symposium on Edge Computing (SEC'22) and has editorial roles at IEEE Internet Computing and Transactions on Computers. Key awards include an NSF Career Award. His work emphasizes building prototype systems and addressing real-world challenges in edge computing and quantum networks. Education: PhD from Dartmouth College under Daniela Rus Research interests span edge computing architecture, secure deep learning, federated learning, and quantum computing applications. His Edge Computing Group explores scalable solutions for distributed systems and privacy-preserving technologies. Recent publications (2022-2024) focus on quantum networks, federated learning robustness, and privacy-preserving algorithms. A notable trend is integrating quantum computing with edge systems for enhanced security and efficiency. Awards: NSF Career Award (year unspecified), IEEE Fellow (year unspecified) Advised students have transitioned to academia and industry roles, reflecting Li's mentorship impact. Active in conference organization, he has led program committees for ACM SEC and IEEE ICDCS, while steering editorial boards in computer networks and systems. Current projects include quantum network routing and Byzantine-tolerant federated learning.

Sidi Luمشاهده پروفایل

استادیار

• Edge Computing
• Autonomous Vehicles
• Artificial Intelligence
• +۳ مورد دیگر

Sidi Lu is an Assistant Professor in the Department of Computer Science at William & Mary. His research focuses on edge computing, autonomous vehicles, and applied AI, emphasizing reliable and efficient computing systems for transportation and IoT. He joined William & Mary in August 2023 after completing his PhD at Wayne State University, where he specialized in vehicle computing and edge intelligence. Education: PhD in Computer Science, Wayne State University (2023) Exchange Undergrad in Electrical and Computer Engineering, University of California, Riverside B.Eng in Electronic Information Engineering, Xidian University Research Interests: Sidi explores edge computing frameworks for connected vehicles, teleoperation in autonomous systems, and AI-driven solutions for real-world challenges. His work bridges theory and practice, addressing scalability, security, and efficiency in vehicle-edge-cloud ecosystems. Awards & Recognition: Class of 2024 Influencer Recognition (William & Mary) NSF CRII Award (2023) Ralph H. Kummler Award (2022) Dr. Michael E. Conrad Graduate Research Award (2021) Grants & Services: Sidi leads NSF-funded projects and serves on technical committees for top conferences like ACM/IEEE SEC and IEEE MOST. He mentors students in research and organizes events at Grace Hopper Celebrations. Labs & Teams: Director of the Vehicle Computing Lab at William & Mary, focusing on advancing autonomous systems and edge-enabled applications.

• Information Systems
• Organizational Studies
• Digital Transformation
• +۳ مورد دیگر

Lapo Mola is an Associate Professor at SKEMA Business School, specializing in Management of Projects, Information Systems, and Supply Chains. He serves as Co-Director of the Digital DBA (DDBA) program and Scientific Coordinator of the M2 Apprentissage in Business Process Management. His roles include membership in research centers like KTO and GREDEG, and involvement in initiatives such as the Trasformazione Digitale e Sostenibile delle PMI Venete project. His research focuses on the impact of Information Technologies (e.g., ERP, Business Intelligence) on organizational design, inter-organizational relationships, and institutional change. Key areas include digital transformation, IT-driven organizational capabilities, and international business models. He has published in journals like the European Journal of Information Systems and Information Systems Journal. Mola teaches modules such as Business Intelligence, Digital Transformation, and Generative AI for Management. He advises on doctoral programs and is a referent for Erasmus and digitalization initiatives. His work bridges theory and practice, emphasizing digital innovation in SMEs and sustainable practices. He leads projects like the Trasformazione Digitale e Sostenibile initiative, supporting Venetian SMEs in digital and sustainability transitions. His contributions span academic research, executive education, and applied projects, reflecting a commitment to advancing organizational and technological resilience.