Find Academic Supervisors

Seyed Ziae Mousavi MojabView profile

Assistant Professor

• Data Mining
• Machine Learning
• Evolutionary Algorithms
• +6 more

Seyed Ziae Mousavi Mojab is an Assistant Professor (Teaching) in Computer Science at Wayne State University's James and Patricia Anderson College of Engineering. He holds a B.S.E. in Computer Science from the University of Michigan Ann Arbor, and both M.S. and Ph.D. degrees in Computer Science from Wayne State University. His research focuses on evolutionary computation, optimization methods, workflow scheduling, medical image processing, data analytics, and business intelligence. Key investigations include cultural algorithms for big data workflows, deep learning ensembles for medical diagnostics, and neural architecture synthesis techniques. Recent publications demonstrate applications in robotic surgical segmentation (2023), COVID-19 detection via chest X-ray analysis (2020-2021), and optimization frameworks for cloud-based big data systems (2019-2022). Research consistently integrates evolutionary computation with deep learning architectures across medical and data-intensive domains.

• Computer Systems Performance Analysis
• Autonomic Computing
• Cloud Computing
• +5 more

Daniel Brazier is a part-time Research Affiliate at George Mason University, focusing on advanced computing systems research. His work intersects autonomic computing, cybersecurity, and distributed systems optimization. He specializes in performance modeling for cloud/fog environments, dynamic reconfiguration strategies, and resilience engineering. Key research areas include: Autonomic resource management in edge and cloud systems Stochastic optimization algorithms Security mechanisms like moving target defense Performance-security tradeoff analysis Decentralized runtime system modeling His recent work emphasizes practical frameworks for distributed system trustworthiness and adaptive elasticity control under variable workloads. Outputs include novel meta-heuristic algorithms for virtual network optimization and analytic models for parallel server architectures. Publications highlight contributions to fog/cloud computing, manufacturing process optimization, and security-aware system design. Current efforts focus on applying decision analytics to smart manufacturing and autonomic emergency department frameworks.

Lav GuptaView profile

Assistant Professor

• Cybersecurity
• Networking
• Cloud Computing
• +5 more

Lav Gupta is an Assistant Professor of Computer Science at the University of Missouri–St. Louis. He holds a Ph.D. and MS from Washington University in St. Louis, and BS/MS degrees from Indian Institute of Technology Kanpur and Roorkee. His research focuses on cybersecurity, networking, cloud computing, and AI applications in critical infrastructure like healthcare and finance. Research interests include secure multi-cloud management, AI-driven fault detection in virtual networks, and resilient healthcare systems. He has published 13+ first-author papers in journals/conferences, with work on hierarchical deep learning for cybersecurity and edge-cloud AI. His funded projects include NSF/SaTC grants and UM System Broadband Research initiatives. Current work involves standardization efforts at ITU-T Geneva for inter-cloud service management frameworks. Notable awards include the 2015 Broadcom Foundation Research Award and Vodafone’s 2014 Wireless Innovation Prize. He leads the Cybersecurity and Networking Lab, offering GRA positions in multi-cloud security and 5G/6G systems. Students can contact via email or office hours (Wednesdays in-person/Zoom). Grants and collaborations highlight industry ties through Sony and ITU-T. Future work emphasizes socially impactful applications like smart cities and critical patient monitoring systems.

• Computer Networks
• Edge Computing
• Quantum Computing
• +5 more

Xiaojun Shang is an Assistant Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington. His research focuses on distributed computing environments, including edge computing, quantum computing, and network optimization for AI applications. PhD in Computer Engineering from Stony Brook University (2023) MS in Electrical Engineering from Columbia University (2016) BS in Information and Communication Engineering from Zhejiang University (2014) Research interests span computer networks , edge computing , edge AI , and quantum computing , with emphasis on algorithm development for distributed environments. Recent work includes quantum interconnection networks and edge AI co-design , with applications in connected vehicles and 6G systems. Publications demonstrate trends in service function chain deployment , quantum entanglement routing , and mobility-aware edge computing . His team's work on blockchain-based O-RAN optimization and distributed quantum computing topology has won Best Paper Awards at ICDCS 2024 and INFOCOM 2020. Best Paper Award, IEEE ICDCS 2024 UT System STARs Award 2023 Best Paper Award, IEEE INFOCOM 2020 As a Faculty Mentor for OurCS Workshop and committee member for CSE PhD Admissions, he advises PhD students including Wei Lin and Wentao Dexter Gao . Reviewer roles include IEEE TPDS, ACM Computing Surveys, and IEEE IoT Journal.

Kerry WardView profile

Associate Professor

• Enterprise Resource Planning
• Information Technology in Law Enforcement
• Information Warfare
• +3 more

Kerry Ward is an Associate Professor in the Department of Information Systems and Quantitative Analysis at the University of Nebraska Omaha's College of Information Science & Technology. He holds a Ph.D. in Management Information Systems from Indiana University, an MBA from the University of Notre Dame, and dual bachelor's degrees in Accounting (Indiana University-Indianapolis) and Psychology/Religion (Wabash College). His professional background includes seven years in public accounting with firms like Deloitte and PriceWaterhouseCoopers, followed by seven years as an officer with the Indianapolis Metropolitan Police Department. Dr. Ward teaches courses on Enterprise Resource Planning (using Epicor's Kinetic), Risk Management in IT, Information Warfare, and Research Methods. His research focuses on ERP systems, IT in law enforcement, information warfare, and research methodologies. His work has appeared in top journals such as the Journal of the AIS, European Journal of Information Systems, and IEEE IT Professional. He has served as co-chair for research methods tracks at AMCIS and HICSS, and as an ad hoc reviewer for multiple journals. Dr. Ward has received the UNO Alumni Outstanding Teaching Award (2010) and has contributed to academic service through roles on committees like the Doctoral Program Committee and Judicial Committee. His research emphasizes organizational adaptation, IT governance, and knowledge management. He has explored topics ranging from SaaS adoption to regulatory impacts on IS strategy, reflecting a blend of theoretical rigor and practical relevance.

Adnan RashidView profile

Assistant Professor

• Network Security
• IoT Protocols
• Low and Lossy Networks
• +3 more

Adnan Rashid is an Assistant Professor in the Department of Electrical and Information Engineering at Polytechnic University of Bari. He holds a Ph.D. in Telecommunication and Telematics from the University of Florence and Master's/Bachelor's degrees in Computer Engineering and Computer Science from Pakistani institutions. His research focuses on: IoT network architectures and protocol design Security in low-power lossy networks (LLN) Cloud/fog computing integration Standardization of IPv6 performance metrics He actively contributes to IETF standardization efforts, particularly in the IPv6 Performance and Diagnostic Metrics (ippm) working group. His work on 6LoWPAN neighbor discovery protocols includes collaboration with ns-3 simulator developers. Recent publications address lawful interception architectures, intelligent reflecting surfaces for 5G/6G, and spectrum efficiency in cognitive networks.

Carlos Molina ClementeView profile

Associate Professor

• Computer Architecture
• Mobile and Sensor Networks
• Cloud Computing
• +8 more

Carlos Molina Clemente is an Associate Professor of Computer Architecture at Rovira i Virgili University in Tarragona, Spain. He holds a M.Sc. in Computer Engineering (Universitat Politècnica de Catalunya, 1996) and a Ph.D. in Computer Science (UPC, 2005). His research focuses on Computer Architecture, Mobile/Sensor Networks, and Cloud Computing. He leads the Cloudlab research group and coordinates initiatives like GTDAWIN and BIOGEI. Key research areas include multicore scheduling, LoRaWAN protocols, LIDAR data analysis, and serverless computing. He has published over 50 articles in top-tier conferences/journals and supervised three doctoral theses. His work spans projects on cache architectures, real-time systems, and educational multicomputing solutions. Affiliations include the Department of Computer Engineering and Mathematics (DEIM) at URV, with offices at Campus Sescelades (Avinguda Països Catalans 26, Tarragona). Research highlights include contributions to non-uniform cache policies, predictive mobile network algorithms, and energy-efficient sensor networks.

Samiya KhanView profile

Lecturer

• Data Science
• Artificial Intelligence
• Edge Computing
• +4 more

Dr. Samiya Khan is a Lecturer in Computer Science at the University of Greenwich, UK, affiliated with the School of Computing and Mathematical Sciences within the Faculty of Engineering and Science. She holds a PhD in Computer Science from Jamia Millia Islamia, India (2020), and is an alumna of the University of Delhi, India. Previously, she served as a postdoctoral research fellow at the University of Wolverhampton, UK. Her expertise spans data science, artificial intelligence, edge computing, IoT, and digital health. Her research contributions include over 25 publications in high-impact journals and conferences, as well as authored/co-edited books such as 'Big Data and Analytics' and 'Internet of Things (IoT): Concepts and Applications' (Springer Nature). She has also contributed as an Associate Editor for Scientific India Magazine and a reviewer for multiple journals and conferences. Samiya’s work emphasizes interdisciplinary applications, including cybersecurity for industrial systems, smart healthcare solutions, and sustainable computing. Her recent research explores XR (Extended Reality) for clinical training, IoT in urban sustainability, and AI-driven telehealth services. Her publications highlight advancements in anomaly detection for critical infrastructure, blockchain-enabled IoT security, and AI frameworks for medical imaging. She has also authored works on big data preprocessing and cloud computing challenges in academia and industry. Key contributions include a book on 'Extended Reality for Healthcare Systems' (Elsevier, 2024) and frameworks for low-cost green computing services. Her research bridges theoretical innovation with practical applications in healthcare, education, and environmental sustainability.

Giridhar Reddy BojjaView profile

Assistant Professor

• Business Analytics
• Machine Learning
• Deep Learning
• +7 more

Giridhar Reddy Bojja is an Assistant Professor of Information Systems & Analytics at the College of Business, Michigan Technological University. His academic office is located in Academic Office Building G018. He holds a strong focus on interdisciplinary research and teaching in data-driven fields. Research Interests: Information Systems Capabilities and Firm Performance Social Media Analytics and Healthcare Applications Econometric Modeling in Technology Impact Design Science Research Methodologies Teaching Specializations: Business Analytics (ML, DL, Text Mining) Generative AI and Its Applications Management Science and Social Network Analysis Research Themes: His work spans AI-driven IoT security frameworks, healthcare data analytics, blockchain-enabled healthcare systems, and organizational impact of IT investments. Recent projects include predictive models for patient outcomes and frameworks for resilient IoT networks. Professional Background: His research has been published in top-tier journals and conferences, with a focus on healthcare IT, cybersecurity, and AI applications. He actively contributes to both theoretical and applied research in information systems.

Kui WuView profile

Professor

• Computer Networks
• Wireless and Mobile Networking
• Mobile Computing
• +5 more

Prof. Kui Wu is a Professor in the Department of Computer Science at the University of Victoria, affiliated with the Faculty of Engineering and Computer Science. His research focuses on computer networks, wireless and mobile networking, mobile computing, and network security. He is part of the Parallel, Networking and Distributed Computing (PANDA) research group. Key areas of expertise include distributed learning frameworks, autonomous systems, IoT anomaly detection, and edge computing architectures. His work integrates machine learning techniques with network optimization, addressing challenges in real-time systems, security, and resource allocation. Notable contributions include advancements in federated learning, privacy-preserving distributed systems, and UAV-based monitoring solutions. Prof. Wu's research also explores edge computing innovations, such as smart contract-aided IoT resource sharing and energy-efficient edge data centers. He has contributed to over 50 peer-reviewed publications, with recent work emphasizing AI-driven network design, anomaly detection in IoT, and reinforcement learning applications in autonomous driving safety. His research has practical implications for improving the reliability and efficiency of next-generation communication and computing infrastructures.

Jaeung SimView profile

Assistant Professor

• Information Systems
• Digital Marketing
• Online Platforms
• +4 more

Jaeung Sim is an Assistant Professor at the University of Connecticut's School of Business, Department of Operations and Information Management. His research focuses on understanding consumer interactions with information technology, digital platforms, and energy systems, with emphasis on sustainable operations and policy implications. He holds a Ph.D. in Management Engineering from KAIST and a B.S. in Industrial & Management Engineering (Summa Cum Laude) from POSTECH. Prior to academia, he served in the Republic of Korea Army as a sergeant and published data analytics work on music streaming trends. Research interests include: Online platform governance and consumer behavior Digital marketing strategies Energy economics and policy analysis Econometric field experiments Data-driven decision-making in operations Recent work explores topics like AI ethics in knowledge sharing, autocomplete impact on search behavior, smart metering effectiveness, and racial disparities in energy burdens. His music analytics research examines pandemic effects on streaming consumption and live-streaming economies. Teaching includes courses on data mining/business intelligence (OPIM 5671) and Python-based data science (OPIM 5512). Active in UConn's Stamford campus, he contributes to initiatives like decentralized AI education programs.

Sabur H BaidyaView profile

Assistant Professor

• Autonomous Systems
• Cyber-Physical Systems
• Internet-of-Things (IoT)
• +4 more

Sabur H Baidya is an Assistant Professor in the Department of Computer Science and Engineering at the University of Louisville's J.B. Speed School of Engineering. He leads the Autonomous Intelligent Mobile Systems Lab (AIMS Lab) and is affiliated with the Louisville Automation & Robotics Research Institute (LARRI). His research focuses on autonomous systems, cyber-physical systems, IoT, edge computing, and distributed intelligence. Education: B.S. in Communication Engineering, West Bengal University, 2007 M.S. in Computer Science, University of Texas at Dallas, 2013 Ph.D. in Computer Science, University of California, Irvine, 2019 Research Interests: His work integrates sensing, communication, and computing systems to develop intelligent distributed systems. Key areas include IoT security, optimization of edge computing architectures, and autonomous drone/robotics applications. He explores machine learning techniques for resource-constrained environments and cybersecurity in containerization platforms. Awards & Recognition: No specific awards listed, though his research has been published in top-tier venues across autonomous systems, IoT, and cybersecurity domains. Advising & Grants: While no student names or grant details are provided, his lab actively engages in collaborative projects with industry partners like Nokia Bell Labs and Huawei, and academic collaborations at Rutgers WINLAB and UC San Diego. Labs & Teams: Directs the AIMS Lab, collaborating with the Louisville Automation & Robotics Research Institute (LARRI) to advance robotics and automation technologies. His work also intersects with the Jacobs School of Electrical and Computer Engineering (UCSD) and WINLAB (Rutgers).

Sean ChoiView profile

Assistant Professor

• Computer Networking
• Programmable Hardware
• Machine Learning Infrastructure
• +3 more

Sean Choi is an Assistant Professor in the Department of Computer Science and Engineering at Santa Clara University. He holds a Ph.D. in Electrical Engineering from Stanford University (2020), M.S. in Computer Science from Stanford (2013), and a dual B.S. in Computer Science and Business Economics & Management from Caltech (2011). His research focuses on programmable network hardware, including smartNICs, and their applications in machine learning, blockchain, and cloud computing. Education: Ph.D. in Electrical Engineering, Stanford University (2020) M.S. in Computer Science, Stanford University (2013) B.S. in Computer Science & Business Economics, California Institute of Technology (2011) Research Interests: Programmable Network Switches, SmartNIC Acceleration, Cloud Infrastructure, Serverless Computing, Blockchain Optimization, and Privacy-Preserving Machine Learning . Recent Work: Explores leveraging programmable hardware for low-latency machine learning inference, blockchain scalability via NIC-assisted consensus, and privacy-preserving federated learning through homomorphic encryption offload. His NSF-funded project develops ultra-low-latency ML systems using programmable networks. Awards: NSF CRII 2023 Award Hewlett Packard Enterprise Grant Labs/Teams: Leads research on network programmability and hardware acceleration within Santa Clara University's School of Engineering. Collaborates with industry on data center network optimization and cloud infrastructure projects.

Liang HongView profile

Professor

• Wireless Communications
• Signal Processing
• Network Security
• +2 more

Liang Hong is a Professor in the Department of Electrical and Computer Engineering at Tennessee State University. He earned his Ph.D. in Electrical Engineering from the University of Missouri-Columbia in 2002, following industry experience at Siemens Corporate Research. His research encompasses wireless communications, signal processing, network security, and embedded systems. Hong has led multiple federally funded projects including a $599,800 Office of Naval Research initiative on embedded system security and a $310,000 Air Force Research Laboratory program on spectrum communication. His extensive publications demonstrate consistent focus on cognitive radio networks, beamforming techniques, cybersecurity, and networked control systems. Recent work emphasizes AI applications for threat detection, cloud security, and adaptive resource management in wireless environments. Hong received the TSU Faculty Research Award (2005) and was nominated for Teacher of the Year (2010). He has chaired technical committees for IEEE conferences and guided award-winning student research.

Maryam ElahiView profile

Associate Professor

• Distributed Systems
• Network Performance Analysis
• Computer Architecture Optimization
• +4 more

Maryam Elahi is an Associate Professor in the Department of Mathematics & Computing at Mount Royal University (MRU), part of the Faculty of Science and Technology. She holds a PhD in Computer Science from the University of Calgary (2017), an MSc in Software Engineering of Distributed Systems from KTH Royal Institute of Technology (2009), and a BSc in Computer Engineering from Azad University of Mashhad (2005). Her research focuses on networked and distributed systems, emphasizing performance analysis, dynamic bandwidth allocation, and speed-scaling systems. She has secured grants including the Petro-Canada Young Innovators Award (2022) and the Provost’s Teaching and Learning Enhancement Grant (2023). Education: PhD in Computer Science, University of Calgary (2017) MSc in Software Engineering of Distributed Systems, KTH (2009) BSc in Computer Engineering, Azad University of Mashhad (2005) Her research interests span network performance modeling, real-time systems optimization, and energy-efficient computing. She actively contributes to academic committees for major conferences and has participated in leadership programs like WISE Planet Change Leadership (2021/22). Maryam is passionate about mentoring students, particularly through Mitacs Globalink Internships, fostering their growth in academic and professional careers. Her articles explore topics such as frequency scaling in multilevel queues, fair dynamic bandwidth allocation, and turbocharged speed-scaling mechanisms. These contributions reflect her expertise in optimizing resource allocation in distributed environments while balancing fairness and efficiency.