Find Academic Supervisors

Joshua BarbourView profile

Professor

• Communication and Health
• Communication and Organizations
• Automation Policy and Research
• +3 more

Joshua Barbour is a Professor in the Department of Communication at the University of Illinois Urbana-Champaign. He directs the Automation Policy and Research Organizing Network (APRON) Lab, founded in 2018, which focuses on data-intensive automated work systems and communication strategies. His research explores how institutional structures shape organizational communication and collaborative efforts, emphasizing macromorphic perspectives that bridge micro-level practices and macro-level frameworks. Barbour’s work spans health communication, risk management, and digital innovation, with a focus on communication design logics and institutional moorings. Education details are not explicitly listed, but his career demonstrates advanced academic qualifications in communication studies. His research interests include automation policy, organizational analytics, and conflict of interest frameworks in biomedical research. He has published extensively on topics like emergency communication infrastructure, temporal dominance in workplace cycles, and interdisciplinary collaboration in healthcare settings. Barbour’s APRON Lab collaborates across disciplines to address future-of-work challenges, particularly in healthcare and organizational resilience. His work emphasizes practical solutions for navigating regulatory constraints and fostering reliable communication systems in dynamic institutional environments. Grants and advising details are not explicitly mentioned, but his role as a professor and lab director suggests involvement in academic mentorship and funded research initiatives. The APRON Lab serves as a hub for interdisciplinary projects addressing automation and organizational communication challenges.

• Service-oriented Computing
• Web Services
• Workflow Technology
• +7 more

Jun Yan is a Professor at the University of Wollongong's School of Computing and Information Technology within the Faculty of Engineering and Information Sciences. His roles include academic leadership and research supervision, with active involvement in committees like the Student Academic Experience Sub-Committee and Quality Assurance Review Group. Current research focuses on service-oriented computing, workflow technology, adaptive process management, and AI-driven systems. His work intersects with IoT, UAV systems, federated learning, and multi-agent reinforcement learning. Research interests span service-oriented software engineering, decentralized workflow management, and cybersecurity challenges in autonomous systems. Notable projects include an ARC-funded initiative on robust defenses against adversarial ML for UAV systems (2025–2027). He supervises Masters/PhD projects on topics like diffusion model-based MRI, graph prompt learning, and industrial defect detection. His publications from 2023–2025 emphasize scalable multi-agent systems, federated learning with non-IID data, and UAV applications in intelligent transportation. Key areas of contribution include trust models for e-commerce, privacy-preserving cloud computing, and fault-tolerant service architectures.

Zhongyuan ZhaoView profile

Academic

• Wireless Communications and Networking
• Machine Learning
• Signal Processing
• +7 more

Zhongyuan Zhao is a Research Assistant Professor at Rice University's Department of Electrical and Computer Engineering, affiliated with the George R. Brown School of Engineering. He holds a Ph.D. in Computer Engineering from the University of Nebraska-Lincoln and completed his postdoctoral studies at Rice under Prof. Santiago Segarra. His research integrates graph-based neuro-symbolic approaches with domain-specific models to address challenges in wireless communications, edge computing, and networked systems. Dr. Zhao has over a decade of industry experience in 4G base-station development at Ericsson and ArrayComm, followed by academic research roles focusing on distributed algorithms and machine learning applications. His education includes a B.Sc. and M.S. in Electronic Engineering from the University of Electronic Science and Technology of China, where he also worked as a teaching assistant for national design contests. He earned a minor in Finance (15 credits) during his Ph.D. and is completing the CFA Level III program in 2024. Zhao has contributed to large-scale wireless testbeds like NEXTT and authored/co-authored 25+ peer-reviewed publications, 2 patents, and delivered academic service roles including conference session chair and journal reviewer. Research interests span autonomous networking, graph-based machine learning, stochastic optimization, and their applications in infrastructureless wireless systems. His work emphasizes distributed solutions for resource allocation, scheduling, and edge intelligence. Awards include the Future Faculty Fellowship (2023) and IEEE travel grants. He has mentored over 40 students through research internships, hackathons, and undergraduate projects, showcasing his commitment to education. Recent projects focus on scalable computation offloading, generalized backpressure routing in tactical networks, and neuro-symbolic AI frameworks for networked systems. His lab work involves open-source contributions to tools like the Actor-Twin Framework and SelR algorithm, promoting reproducibility and collaboration in the field.

Sherief RedaView profile

Professor

• Machine Learning
• Computer Architecture
• Energy Efficiency
• +5 more

Sherief Reda is a Professor of Engineering and Computer Science at Brown University's School of Engineering. He leads the SCALE lab, focusing on energy-efficient computing, digital chip design, embedded systems, and machine learning applications. His research bridges hardware design and combinatorial optimization, with over 130 publications and five US patents. Reda has secured $21M+ in research funding from NSF, DoD, DARPA, and industry partners like Samsung and Intel. Education: PhD in Computer Science & Engineering, UC San Diego (2006) MS in Computer Science, Ain Shams University (2000) BS in Computer Science, Ain Shams University (1998) Research Interests: His work spans resource-efficient AI, approximate computing, and interdisciplinary applications in social sciences. Recent projects include chemical-based computing and thermal management for high-performance chips. Reda's lab explores machine learning for combinatorial optimization, with practical applications in logistics and hardware design. Publications & Awards: Over 130 articles in top venues like IEEE Transactions and Nature Communications. Recipient of the NSF CAREER Award (2021) and IEEE Fellow (2020). His work on energy-efficient computing earned him the AAIA Fellowship. Grants & Collaborations: Principal Investigator on NSF, DoD, and industry-funded projects. Collaborators include Prof. Kim (Chemistry) and Prof. Rose (Engineering). Reda also serves as an Amazon Scholar and expert witness in patent litigation. Labs & Teams: Directs the SCALE lab, which develops open-source EDA tools and novel thermal simulation frameworks like PACT. His team pioneered techniques like ABACUS for approximate circuit synthesis and LoCool for energy efficiency in servers.

Liang ZhangView profile

Assistant Professor

• Artificial Intelligence
• Mobile Edge Computing
• UAV Communications
• +3 more

Dr. Liang Zhang is an Assistant Professor in the Department of Engineering and Aviation Sciences at the University of Maryland Eastern Shore (UMES). He holds a Ph.D. in Electrical Engineering from New Jersey Institute of Technology (NJIT) and an M.S. in Information and Communication Engineering from the University of Science and Technology of China (USTC). His research focuses on machine learning, mobile edge computing, UAV communications, wireless communications, and IoT, with an emphasis on resource optimization and algorithm design. Education: Ph.D., Electrical and Computer Engineering, NJIT (2014–2020) M.S., Information and Communication Engineering, USTC (2011–2014) B.S., Electronic Science and Technology, Huazhong University of Science and Technology (HUST) Research Highlights: Dr. Zhang has pioneered work on deep reinforcement learning algorithms for UAV-assisted edge computing, caching optimization, and latency reduction in IoT systems. His contributions include the BRIDGES testbed project at George Mason University (GMU), supported by a $2.5M NSF grant, and the development of QoE-optimized frameworks for wireless VR and airborne networks. Awards & Recognition: Outstanding Dissertation Award (NJIT, 2023) Hashimoto Prize (NJIT, 2020) IEEE GLOBECOM Travel Grant (2016) Best Paper Award (IEEE ICNC, 2014) Professional Contributions: He has published 32 peer-reviewed articles and serves as a reviewer for IEEE journals. His work integrates machine learning with networking challenges, addressing practical issues like spectrum sharing in 5G, energy-efficient VM management, and dynamic resource allocation in optical networks.

Jae PattersonView profile

Associate Professor

• Augmented Feedback
• Repetition Scheduling
• Error Detection and Correction
• +5 more

Jae Patterson, PhD, is an Associate Professor in the Department of Kinesiology at Brock University. His primary research focuses on motor skill acquisition across the lifespan, emphasizing practice variables such as augmented feedback, learner-controlled practice, and error detection. His work has implications for sport, rehabilitation, and vocational training. He is affiliated with the Motor Skills Acquisition Laboratory and the Centre for Neuroscience at Brock University. Research interests include augmented feedback mechanisms, repetition scheduling, observational learning, and cognitive effort during skill acquisition. His studies explore how practice conditions influence learning outcomes in diverse populations, including athletes and individuals with movement disorders. Publications span peer-reviewed journals and book chapters, addressing topics like self-controlled learning protocols, focus of attention in sports, and the impact of concussion on athletic performance. His work emphasizes practical applications in rehabilitation and sports training. Professional affiliations include the Canadian Society for Psychomotor Learning and Sport Psychology, and the North American Society for the Psychology of Sport and Physical Activity. The Motor Skills Acquisition Lab actively seeks graduate and undergraduate students for research projects.

Samantha PettiView profile

Assistant Professor

• Bioinformatics
• Computational Biology
• Machine Learning
• +4 more

Samantha Petti is an Assistant Professor in both the Department of Mathematics (School of Arts and Sciences) and the Department of Computer Science (School of Engineering) at Tufts University. She is based at 177 College Avenue, Medford, MA. Her research focuses on computational biology, bioinformatics, and machine learning, with particular emphasis on protein structure analysis, genotype-phenotype mapping, and algorithm design for biological sequence analysis. She teaches courses such as Master's Thesis supervision, PhD Thesis guidance, and specialized topics in mathematics and computer science. Her work integrates interdisciplinary approaches, combining statistical methods, deep learning, and probabilistic models to address challenges in genomics, structural biology, and network science. Recent projects include developing end-to-end protein alignment tools and exploring sparse graph models for biological systems. Teaching: Supervises graduate thesis work (Master’s/PhD) and advanced courses in mathematics and computer science at Tufts. Lab/Team: Engages in collaborative research at the intersection of computational methods and biological systems.

• Water Modelling
• Hydrologic and Hydraulic Modelling
• Irrigation Modelling
• +5 more

Dr. Sydur Rahman is a Lecturer and Researcher in Engineering at the Faculty of Science and Engineering, Southern Cross University. He holds a PhD in Environmental Engineering from SCU, a Master of Water Resources Engineering from Bangladesh University of Engineering and Technology, and a Bachelor of Agricultural Engineering (First Class Honours). His expertise spans water resources engineering, hydrology, and sustainable water management. Dr. Rahman's research focuses on water modeling, irrigation systems, wastewater management, and groundwater sustainability. He has led projects addressing integrated water resources management, crop water productivity under climate change, and contaminated land remediation. Notably, he is currently involved in an industry-funded project to develop techniques for removing chlorocresol from tannery waste. He has extensive teaching experience, instructing courses such as Hydraulic Engineering Fundamentals, Hydrogeology, and Engineering for Resilient Catchments. His work integrates holistic approaches, including geochemical and ecological tools, to assess environmental risks and refine water management practices. Dr. Rahman has authored over 20 peer-reviewed publications on topics ranging from arsenic sorption in soils to crop water modeling. His contributions aim to enhance water use efficiency and sustainable resource management across field, farm, and regional scales.

Rand RaheemView profile

Lecturer

• Wireless Communication Systems
• Mobile and Vehicular Networks
• Femtocells Technology
• +3 more

Dr. Rand Raheem is a Lecturer in Computer Science at Middlesex University's Faculty of Science and Technology, London. She specializes in wireless communication systems, vehicular networks, and interference management in future mobile networks. Her research focuses on improving performance in safety-critical wireless sensor networks and 4G/5G/6G technologies. Education: Diploma in Electrical and Computer Engineering (Dhofar University, Oman, 2009) BSc Computer Communication Engineering (Dhofar University, 2010) MSc Telecommunication Engineering (Middlesex University, 2011) PhD on interference management in small cell networks (Middlesex University, 2016) Research Interests: Mobile and vehicular network optimization Bio-inspired algorithms for network scheduling Dependable safety-critical systems Cooperative femtocell technology Machine learning applications in wireless networks Teaching: CST4540 - Network Management CST3570 - Network Management and Disaster Recovery CST2560 - Project Management and Professional Practice CST2531 - Compliance and Project Management CST1500 - Computer Systems Architecture and Operating Systems Key Research Trends: Recent work emphasizes bio-inspired algorithms (bird flocking, bat algorithms) and neural networks for enhancing wireless sensor network dependability. Earlier research focused on femtocell interference management in LTE networks and vehicular environments. Advising & Grants: No specific grants or supervisees listed. Active collaborator with researchers like Dr. A. Lasebae on multiple projects. Labs/Teams: Participates in network research initiatives at Middlesex University's Computer Science Department, though specific lab affiliations are unspecified.

André BrinkmannView profile

Professor

• Data Center Management
• Cloud Computing
• Storage Systems
• +5 more

André Brinkmann is a full professor at the Department of Computer Science, Johannes Gutenberg University Mainz, leading the Efficient Computing and Storage Group. He previously served as head of the university's data center (2011–2021) and was an assistant professor at Paderborn University (2008–2011). He holds a Ph.D. in Electrical Engineering from Paderborn University (2004) and managed the Paderborn Centre for Parallel Computing (PC²). His research focuses on algorithm engineering for data center management, cloud computing, storage systems, and high-performance computing (HPC). Notable projects include: Development of ad hoc file systems like GekkoFS and IO-SEA for exascale architectures Optimization of storage systems (e.g., hybrid RAID, SSD garbage collection) Quantum computing compiler research for trapped-ion architectures Leadership in initiatives like the I/O Trace Initiative and BINARY (Big Data in Atmospheric Physics) He serves as Senior Associate Editor of ACM Transactions on Storage and co-chairs major conferences like FAST 2026 and ARCS 2026.

Thomas FroeseView profile

Professor

• Project and Construction Management
• Sustainable Building and Infrastructure
• Building Information Modeling (BIM)
• +5 more

Dr. Thomas Froese is the Department Chair and Professor of Civil Engineering at the University of Victoria (UVic), within the Faculty of Engineering and Computer Science. He specializes in project and construction management, sustainable infrastructure, and the integration of information technologies such as Building Information Modeling (BIM), IoT, and digital twins into building and infrastructure systems. His work emphasizes sustainability assessment, energy efficiency, and innovation in construction processes. He actively contributes to advancing sustainable building practices through applied research and education. Research Interests: Froese’s expertise spans sustainable building and infrastructure design, digital twin-enabled post-occupancy evaluations, timber-concrete composite systems, and the application of BIM in high-performance construction. He explores how technologies like GIS, IoT, and surrogate modeling can optimize building envelopes and enhance infrastructure resilience. His educational focus includes curriculum development for sustainability-centered civil engineering and fostering innovation in construction management. Articles Trends: His recent publications emphasize sustainability in construction, digital twin applications, and innovative materials like bio-inspired auxetics. He frequently examines case studies such as Brock Commons Tallwood House and UVic’s Engineering Expansion Project, highlighting practical implementation of sustainable technologies. His work bridges theory and practice, addressing challenges in thermal comfort, energy efficiency, and lifecycle assessment. Awards and Grants: No specific awards or grants are listed in the provided texts. Froese’s contributions are primarily reflected in his research output and academic leadership roles. He oversees the Civil Engineering Department and collaborates on projects promoting sustainable development, such as the UBC Living Lab initiative. Labs/Teams: As a department chair, Froese likely leads or collaborates with UVic’s civil engineering research groups focused on sustainable infrastructure and digital construction technologies. His work aligns with UVic’s broader commitment to environmental stewardship through applied engineering solutions.

Paul PopView profile

Professor

• Embedded Systems
• Systems Engineering
• Time-Sensitive Networking
• +7 more

Paul Pop is a Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). He holds the position of Professor within the Embedded Systems Engineering group at DTU Compute. His academic journey includes a Ph.D. in Computer Systems from Linköping University, Sweden (2003), followed by roles as an Assistant Professor there before joining DTU in 2006. Dr. Pop's research focuses on systems engineering methodologies for embedded and cyber-physical systems, with emphasis on modeling, analysis, optimization, and real-time guarantees. His work addresses challenges in time-sensitive networking (TSN), automotive systems, industrial automation, and fog computing. Key application areas include safety-critical systems, mixed-criticality architectures, and sustainable industrial IoT solutions aligned with UN SDGs. He leads major research projects such as G3C (Green Computing & Communication Continuum), TRANSACT (Safety-Critical Cyber-Physical Systems), and AgroRobottiFleet (Agricultural Robotics). His contributions span 194 publications in journals/conferences and 31 active/completed projects, emphasizing interdisciplinary collaboration. Dr. Pop advises doctoral students in embedded systems and serves as Principal Investigator on EU-funded initiatives. His technical expertise includes TSN configuration tools (TSNConf), fog computing platforms (FORA), and microfluidic biochip design. He actively contributes to industry standards through IEEE 802.1 TSN working groups and collaborates internationally with institutions like Nordic Innovation and EU Horizon programs.

• Wireless Communication
• Network Optimization
• Machine Learning
• +3 more

Athanasios Gkelias is a Research Fellow in the Department of Electrical and Electronic Engineering at Imperial College London's Faculty of Engineering. His research focuses on advanced wireless communication systems, network optimization, machine learning applications, and quantum computing methodologies. He contributes to interdisciplinary projects involving IoT coalitions, adversarial signal detection, and cognitive behavior analysis. Key research areas include: (1) Network resource management in Software-Defined Networks (SDN), (2) Localization systems for indoor environments, (3) 3D reconstruction using photometric stereo and origami-based modeling, and (4) distributed optimization frameworks for ad-hoc networks. His recent work explores quantum approaches to combinatorial optimization and self-supervised learning methods. Publications span 20+ years with notable contributions in network coding, vehicular ad-hoc networks (VANETs), and cross-layer design for wireless mesh networks. His work emphasizes practical implementations through frameworks like iVisher for caller ID spoofing detection and cooperative MAC protocols for multi-antenna systems. No scientific awards are listed in the provided information. His research has been applied in healthcare technology through emotion understanding systems for Alzheimer’s patients and in battlefield communication through IoBT coalitions. Active participation in Imperial College's Engineering faculty reflects his commitment to advancing telecommunications and network science.

Laurens DeboView profile

Professor

• Operations Management
• Supply Chain Management
• Operations Strategy
• +5 more

Laurens Debo is the C.V. Starr Professor of Operations Management and Area Chair in the Operations and Management Science Department at Tuck School of Business, Dartmouth College. He holds a PhD (2002) and MSc (2000) from INSEAD, France, and dual MSc degrees in Operations Management (1995) and Electrical Engineering (1994) from Université Catholique de Louvain, Belgium. Prior to Tuck, he taught at Carnegie Mellon University and the University of Chicago Booth School of Business. Research Interests: Debo specializes in service operations, strategic consumer behavior, and discretionary service management. His work explores how consumer decisions shape service demand and how providers optimize service delivery in contexts where value increases with service duration. Recent focus areas include queueing systems, tipping behavior, and pandemic-era retail operations. Awards & Editorial Roles: He received the MSOM Meritorious Service Award (2008, 2010) and served as associate editor for Management Science , Manufacturing & Service Operations Management , and Operations Research . He currently edits Production and Operations Management and advises the IIE Transactions . Grants & Impact: NSF-funded research has informed his work on discretionary service design and retail safety protocols during pandemics. His tipping behavior studies have been featured in WSJ , Harvard Business Review , and Marketplace . Labs & Collaborations: Collaborates with global institutions like MIT, Stanford, and the Chinese Academy of Sciences on behavioral operations projects. Active in presenting at leading business schools including Wharton, Kellogg, and INSEAD.

Bryan WardView profile

Assistant Professor

• Real-Time Systems
• Embedded Systems Security
• Cyber-Physical Systems
• +3 more

Bryan Ward is an Assistant Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on enhancing the security and resilience of real-time and embedded systems in critical domains such as industrial control systems and space systems. Ward holds a Ph.D. in Computer Science from the University of North Carolina at Chapel Hill, along with dual bachelor's degrees in Computer Science and Engineering and Mathematics from Bucknell University. His academic contributions span multiple areas including operating system security, real-time scheduling, and hardware-software co-design for safety-critical systems. Key research themes include control-flow integrity, secure resource management in multi-core environments, and mitigating timing-based attacks in real-time embedded systems. Ward's work has explored advanced defense mechanisms like dynamic address space randomization, tagged architecture implementations, and retry-free transactional memory models. He has also investigated vulnerabilities in kernel scheduling and cache-sharing behaviors in multi-core platforms, proposing novel solutions to ensure predictability and security. Current projects emphasize securing cyber-physical systems through adaptive defenses that maintain strict timing guarantees required for safety-critical applications.