Find Academic Supervisors

Abdullah Al-MamunView profile

Assistant Professor

• High-Performance Computing
• Distributed Systems
• Blockchain Technology
• +5 more

Abdullah Al-Mamun is an Assistant Professor and Director of the High Performance & Secure Data Computing (HPSDC) Lab at Augusta University's School of Computer and Cyber Sciences. His research focuses on resource-efficient distributed systems, high-performance computing, and blockchain-based solutions for secure data management. He holds a Ph.D. from the University of Nevada, Reno, and a double M.Sc. from RWTH Aachen University and the University of Trento under the Erasmus Mundus program. His work has been supported by grants including an NSF CRII award ($165,000) and a Google Cloud Research Grant ($10,000). Education: Ph.D., Computer Science & Engineering (2022), University of Nevada, Reno M.Sc., Computer Science (2013), RWTH Aachen University / University of Trento (Double Degree) B.Sc., Computer Science & Engineering (Summa Cum Laude, 2009), American International University-Bangladesh Research Interests: High-Performance Blockchain Resource-Efficient HPC Extreme-Scale Data Management Secure Data Provenance Edge Computing Selected Awards: NSF CRII Award (2024–2026) Best Paper Award (Cloud'19) Outstanding Graduate Student Scholarship (UNR, 2020–2021) Service & Teaching: ACM Programming SIG Club Advisor (2023–present) Reviewer for IEEE IoT Journal, IEEE Transactions on Consumer Electronics, and others Teaches courses in Low-Level Programming, Computer Architecture, and High-Performance Computing Labs & Teams: Directs the HPSDC Lab, publishing in top-tier venues like SC, ICDE, and IPDPS.

Sam OgdenView profile

Assistant Professor

• Mobile Computing
• Cloud Computing
• Deep Learning
• +3 more

Sam Ogden is an Assistant Professor at California State University, Monterey Bay (CSUMB), where he joined in August 2022. He holds a Ph.D. in Computer Science from Worcester Polytechnic Institute (2022), focusing on mobile-oriented deep learning inference. His academic journey includes degrees in Electrical Engineering, Mathematics, and Computer Science from the University of Vermont, and prior roles as a Product Engineer at IBM and GlobalFoundries. His research bridges mobile devices and cloud computing, emphasizing optimization of machine learning inference for mobile applications. Key areas include edge computing, model execution caching, latency reduction, and energy-efficient distributed systems. Recent work explores mental health screening through smartphone data and text message analysis, expanding into health informatics applications. Research Trends : Recent publications highlight innovations like Layercake (2023) for edge-cloud inference efficiency and MiseEnPlace (2022) for mobile deep learning optimization. Earlier work addresses GPU scheduling (2021), DNN caching challenges (2019), and hybrid mobile-edge frameworks (MODI, 2018). Awards : No scientific awards explicitly mentioned in the provided texts. Advising & Grants : No student advisees or grant details listed. Labs/Teams : Affiliated with CSUMB’s School of Computing & Design, though specific lab affiliations are not detailed.

Michael F. SpearView profile

Associate Professor

• Concurrency
• Programming Languages
• Computer Architecture
• +5 more

Michael F. Spear is an Associate Professor and Master's Program Director in the Department of Computer Science & Engineering at Lehigh University. His research focuses on concurrency, programming languages, and computer architecture, with an emphasis on persistent memory, transactional memory, and concurrent data structures. He leads a lab supported by industry partnerships with Intel, Google, and Oracle, as well as grants from the National Science Foundation and the U.S. Army. Education: Ph.D. and M.S. in Computer Science, University of Rochester M.B.A., University of Alaska, Anchorage B.S. in Computer Science, U.S. Military Academy (West Point) Research Interests: Spear's work aims to simplify concurrent programming through innovative software and hardware designs. He develops open-source frameworks like libLOL/JetLag for mobile game development and contributes to C++ transactional memory standards. His lab explores cloud infrastructure optimization, memory management, and scalable algorithms. Collaborations & Awards: Active collaborations include Arizona State University, Penn State University, and industry leaders in tech. Notable awards include the University of Rochester's Outstanding Dissertation Award and leadership in NSF-funded research initiatives. Labs & Contributions: Spear directs a lab producing tools for persistent/transactional memory systems and advises on C++ technical specifications. His work bridges theoretical computer science with practical industry applications, emphasizing scalability and correctness in multi-core environments.

• Optical Fiber Sensing
• Wireless Communication Networks
• Internet of Things
• +7 more

Huan Wu is an accomplished academic researcher with a substantial publication record spanning nearly three decades (1996-2025), comprising 63 indexed publications in the dblp database. Their scholarly work demonstrates expertise across multiple technical domains with significant contributions to optical communication systems, wireless networking, and artificial intelligence applications. Research interests focus on the intersection of electrical engineering and computer science, particularly in developing advanced sensing technologies using optical fibers, creating efficient communication protocols for IoT systems, and applying machine learning techniques to environmental monitoring and biomedical applications. Recent work shows a strong trend toward AI integration for infrastructure monitoring systems, including water pipe leak detection and hydrological modeling, as well as healthcare applications like non-invasive glucose monitoring and medical image analysis. The publication portfolio reveals a clear evolution from foundational work in signal processing and communication systems toward increasingly interdisciplinary research that bridges engineering with environmental science and healthcare. Recent publications (2023-2025) demonstrate particular strength in graph neural networks, distributed sensing systems, and AI-driven solutions for critical infrastructure monitoring. Based on publication patterns including consistent first-author contributions, supervisory roles evident in student collaborations, and extensive research output, Huan Wu appears to hold a senior academic position with significant research leadership. The collaborative nature of the work, involving multiple institutions across China and internationally, suggests active participation in major research initiatives and substantial grant funding, though specific details are not provided in the publication records.

• Computer Science Education
• Programming Education
• Computer Architecture
• +4 more

Sohum Sohoni is a Professor in the School of Computing and Augmented Intelligence within the Ira A. Fulton Schools of Engineering at Arizona State University. His research spans computer science education, programming pedagogy, computer architecture, and image quality assessment with GPU acceleration. He has developed innovative educational approaches for computer architecture courses using the PLP instruction set architecture and has contributed significantly to understanding programming education through analysis of error messages and embedded questions. His research interests focus on Computer Science Education , particularly programming education techniques, computer architecture pedagogy, and engineering education methods. He has made substantial contributions to understanding how students learn programming concepts, develop effective debugging skills, and comprehend computer architecture principles. His work bridges theoretical computer science concepts with practical educational applications, emphasizing hands-on learning experiences and innovative assessment methods. His publication trends reveal a strong focus on computer science education research with particular emphasis on programming education (2015-2018), computer architecture education using PLP (2014-2017), and image quality assessment with GPU acceleration (2012-2018). His work consistently combines theoretical computer science concepts with practical educational applications, demonstrating his commitment to improving how computing concepts are taught and learned. His advising work includes mentoring students like Christopher Mar, Harsha B. M. Kadekar, Shaowen Lu, Thien D. Phan, and Vignesh Kannan, who have co-authored publications with him across various computing education topics. His research has been supported through various educational technology projects focused on online learning environments, software engineering education, and computer architecture instruction. He has been actively involved in developing virtualized learning environments for IoT education, creating innovative approaches for software engineering education, and designing effective methods for teaching computer architecture concepts. His work demonstrates a consistent commitment to improving computing education through evidence-based pedagogical approaches and technological innovation.

• Housing Studies
• Urban Policy
• Social Stratification
• +5 more

Dr. Adriana Mihaela Soaita is an Honorary Senior Research Fellow at the University of Glasgow's School of Social & Political Sciences, specializing in housing studies, urban policy, and qualitative methodologies. She holds a PhD from King's College London and has worked at Tilburg University and the University of St Andrews. Her research focuses on housing as a site of political power, trust, and inequality, with a particular emphasis on post-communist societies, migration, and tenant activism. She has led projects on Romanian migrants in the UK, trust in post-communist Romania, and innovative methodologies like visual elicitation and online questionnaires. Education : PhD in Housing Studies, King's College London MSc in Urban Housing Management (Distinction), Erasmus University Rotterdam & Lund University PG in Real Estate, Project & Property Management (Distinction), IHS Erasmus University Rotterdam BArch/MArch in Architecture & Planning, Ion Mincu University of Architecture and Urbanism, Bucharest Her research interests include housing inequalities, asset-based welfare, and the private rental sector. She has published extensively on topics like tenant activism, affective economies of renting, and rhythmanalysis in migration studies. Her work bridges urban sociology, political science, and policy analysis, with a focus on marginalized communities and global south contexts. Key projects include 'Finding housing, making home' (Romanian migrants post-Brexit/Covid-19), 'Exploring trust and anti-corruption policies in post-communist Romania,' and studies on tenant activism in the UK private rental sector. She is also a chartered architect and urban planner with a focus on residential design. Publications span 126+ works, including articles in Geoforum , Housing Studies , and Environment and Planning A . Her grants include funding from CaCHE, the Regional Studies Association, and the Scottish Founding Council.

Boyang WangView profile

Associate Professor

• Hardware and embedded system security
• Wireless security
• Binary analysis
• +8 more

Dr. Boyang Wang is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Cincinnati, with a secondary appointment in Computer Science. He holds a Ph.D. from the University of Arizona and has conducted research at institutions like Xidian University and the University of Toronto. His research focuses on hardware security, embedded systems, wireless security, and privacy-preserving technologies. He has secured significant NSF funding, including CRII and REU Site grants, and leads projects on side-channel attacks, radio fingerprinting, and smart speaker privacy. Dr. Wang earned his B.S. in Information Security from Xidian University (2007), followed by dual Ph.D.s in Electrical and Computer Engineering (University of Arizona, 2017) and Cryptography (Xidian University, 2014). He has collaborated with industry partners like Bosch Research and Sandia National Lab. His teaching spans courses on cybersecurity, network security, and data privacy. His research interests include hardware security, embedded systems, wireless security, machine learning for security, and applied cryptography. He has published over 50 peer-reviewed papers, with notable works on side-channel attacks using neural networks and defenses against cache-based website fingerprinting. His lab actively mentors undergraduate and graduate students, many of whom have won awards and internships at top institutions like MITRE and Sandia. Key honors include the Best Student Paper Award at IEEE HOST’24, NSF awards, and teaching excellence recognitions. His funded projects include NSF IUCRC CHEST initiatives and collaborations with universities like Northeastern and the University of Nebraska. Dr. Wang also chairs organizing committees for major conferences like IEEE INFOCOM and ICNC.

• Computer Architecture
• Heterogeneous Parallel Systems
• GPU Computing
• +4 more

Juan Luis Aragon Alcaraz is a Full Professor in Computer Architecture at the University of Murcia (Spain), affiliated with the Faculty of Informatics and the Department of Computer Engineering and Technology. He obtained his PhD in Computer Engineering from the University of Murcia in 2003 and held a postdoctoral position as a Visiting Assistant Professor and Researcher at the University of California, Irvine. He has held visiting researcher positions at EPFL (2013) and Princeton University (2015–2022). His research focuses on computer architecture, emphasizing heterogeneous parallel systems, GPUs, memory hierarchies, and energy-efficient microarchitecture design. He has advised 7 PhD theses and co-authored over 60 publications in top-tier conferences and journals. His work includes contributions to GPU-accelerated medical imaging, energy-efficient graphics pipelines, and hardware-software co-design for parallel systems. Key research trends in his articles include optimizing GPU performance for real-time applications, energy efficiency in graphics rendering, and scalable latency tolerance in manycore systems. His patents include innovations in presbyopia correction devices leveraging GPU and FPGA technologies. Dr. Aragón has taught numerous courses in computer architecture and design, including Computer Architecture and Organization, Advanced Aspects in Multicore Architectures, and Embedded Systems Technologies. His labs and collaborations span academic-industrial partnerships, emphasizing practical applications of his theoretical contributions.

• Edge Computing
• Wireless Networks
• Cognitive Radio Systems
• +3 more

Suzan Bayhan is an academic affiliated with the University of Twente in Enschede, The Netherlands. Her research focuses on edge computing, wireless networks, and cognitive radio systems, with a strong emphasis on energy efficiency and cross-technology communication. She has contributed significantly to the development of strategies for optimizing network performance, resource allocation in edge environments, and interference management in heterogeneous networks. Her work spans theoretical analysis and practical implementations, addressing challenges in cellular networks, federated learning, and smart infrastructure security. Bayhan has collaborated with leading institutions and researchers globally, contributing to conferences like MobiCom and SIGCOMM. Her doctoral studies at Boğaziçi University (Turkey) laid the foundation for her expertise in cognitive radio networks and spectrum management. While her current position isn't explicitly stated, her extensive publication record and academic contributions align with a senior researcher or faculty role. Education: PhD in Electrical and Electronics Engineering, Boğaziçi University, Turkey (2012) Research focus: Spectrum Sharing and Energy Efficiency in Cognitive Radio Networks Research Interests: Edge Computing and Federated Learning Energy-efficient networking strategies Interference mitigation in multi-technology systems Wireless communication protocols Cross-technology communication design Advising & Grants: While specific grants aren't detailed in the provided texts, her involvement in collaborative projects (e.g., EdgeSys, NFDI4DataScience) suggests active participation in funded initiatives. No student advisees are explicitly listed. Labs/Teams: Collaborates with interdisciplinary teams on edge computing and network research, including contributions to platforms like ExEC and Elastic Edge Cloud frameworks.

Francisco Miguel CruzView profile

Researcher

• Cloud Computing
• Distributed Systems
• NoSQL Databases
• +3 more

Francisco Miguel Cruz is an External Research Collaborator and postdoctoral researcher at INESC TEC's High-Assurance Software Centre since January 2012, holding a PhD from the University of Minho (2016) where he completed all academic degrees. His research trajectory spans cloud infrastructure and distributed database systems with emphasis on practical scalability solutions. Educational background: B.Sc. in Computer Science, University of Minho (2007) M.Sc. in Computer Science, University of Minho (2009) Ph.D. in Informatics Engineering, University of Minho (2016) His research focuses on bridging theoretical database concepts with cloud deployment realities, particularly in NoSQL ecosystems. Key contributions include predictive resource modeling for key-value stores, transactional middleware development, and workload-aware data partitioning techniques that address critical bottlenecks in massive-scale data management. His work demonstrates consistent innovation in enhancing elasticity and performance characteristics of distributed databases. Analysis of his 2014-2016 publications reveals a cohesive research thread targeting practical optimization of NoSQL systems through novel prediction mechanisms and architectural innovations. The publications collectively advance understanding of cache behavior, resource allocation, and transactional guarantees in cloud-native data stores, showing strong alignment with industry scalability challenges. Dr. Cruz supervised João Pedro Nóbrega Rei's 2018 thesis on IoT medical sensor platforms and contributed to the HPLabs-funded DC2MS project (Dependable Cloud Computing Management Services). His research methodology combines rigorous experimental validation with real-world system implementation, as evidenced by throughput impact measurements in transactional middleware development. As a core member of HASLab (High-Assurance Software Laboratory) at INESC TEC, he participates in developing dependable software systems with emphasis on cloud infrastructure reliability and performance predictability.

Anton DignösView profile

Associate Professor

• Temporal Databases
• Time Series Data
• Data Analytics
• +3 more

Anton Dignös is a tenured Associate Professor at the Free University of Bozen-Bolzano, Faculty of Engineering, where he leads the Database Systems Research Group. He holds a PhD from the University of Zurich (2014) and has been a faculty member since 2014. His research focuses on temporal databases, time series data, and data analytics, with contributions to indexing, query optimization, and benchmarking tools like TSM-Bench and SEER. Education : BSc and MSc (Computer Science) - Free University of Bozen-Bolzano (2008, 2010) PhD (Dr. sc. in Computer Science) - University of Zurich (2014) Research Interests : Dignös specializes in temporal database systems, time series management, and efficient query processing. He develops novel indexing techniques (e.g., RD-INDEX) and tools for benchmarking time series systems (SEER, TSM-Bench). His work addresses challenges like anomaly detection, sparse data summarization, and parallel join algorithms. Awards : Best Paper Award at SSDBM 2023 Best Paper Award at ADBIS 2022 ACM Computing Reviews Best of Computing (2017) Teaching & Advising : Teaches Data Management and Applied Informatics courses at both BSc and MSc levels. Advises ~25 students (PhD/MSc/BSc) on topics like temporal databases and machine learning applications. Active in thesis supervision and course development. Labs/Teams : Leads the Database Systems Research Group, collaborating on projects like the Period Index for temporal data and VISOR for data visualization tools.

Filip MarkovicView profile

Assistant Professor

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +4 more

Filip Markovic is an Assistant Professor at the Max Planck Institute for Software Systems (MPI-SWS), focusing on real-time systems, algorithms, and verification. His research spans cyber-physical systems, distributed/networked systems, security, and privacy. He contributes to advancing probabilistic analysis techniques for real-time applications, with a particular emphasis on deadline miss probability estimation and system resilience under transient overload. His work integrates formal methods, stochastic modeling, and Bayesian techniques to address challenges in resource allocation, task scheduling, and system reliability. Notable contributions include frameworks like LiME for real-time task modeling in Linux and methodologies to handle task correlations and Markov chain dynamics. Publications highlight advancements in deadline-bound analysis, Markov chain modeling, and adaptive runtime estimation. His research often bridges theoretical foundations with practical implementations, such as improving cache-aware response time analysis and developing correlation-tolerant scheduling algorithms. No awards or grants are explicitly listed in the provided text. His academic focus aligns closely with MPI-SWS’s mission in software systems research, contributing to both theoretical insights and applied solutions in real-time computing domains.

Jared HansenView profile

Associate Professor

• Marketing Strategy
• Business Analytics
• Consumer Behavior
• +5 more

Dr. Jared M. Hansen is an Associate Professor in the Marketing and Strategy Department at the Jon M. Huntsman School of Business, Utah State University. He joined USU in 2018 after over a decade at the University of North Carolina at Charlotte, where he earned teaching awards and research grants. His expertise spans business strategy, analytical modeling, and marketing with a focus on consumer behavior, B2B markets, and technology-driven decision-making. Education: PhD in Marketing, Texas Tech University (2007) MBA, Brigham Young University (2005) BS in Facilities Management, Brigham Young University (2001) Research Interests: Dr. Hansen explores the intersection of marketing strategy, innovation, and ethics. His work addresses challenges in B2B markets, SME growth, CSR motivations, and technology adoption. He actively publishes in top journals like the Strategic Management Journal and Journal of Retailing , and his recent studies examine AI’s role in consumer decisions, pandemic impacts on businesses, and student engagement through digital tools. Teaching & Engagement: He teaches courses on B2B marketing, big data analytics, and competitive intelligence. His executive education and consulting extend to companies globally, focusing on strategy and innovation. He is also a recipient of the Undergraduate Research Mentor of the Year award (2022, 2025). Grants & Labs: His research has been supported by grants from the Shingo Institute and other initiatives. He collaborates with the Huntsman School’s Analytics Solutions Center and contributes to the university’s outdoor-focused community in Cache Valley.

Jess LuceroView profile

Associate Professor

• Housing Justice
• Community-Based Research
• Violence Prevention
• +2 more

Dr. Jess Lucero serves as Department Head of Social Work and Associate Professor at Utah State University, where she also directs the Transforming Communities Institute and the Full-Time MSW Program. She holds a PhD from Wayne State University (2012), MSW (2008) and BSW (2007) from the University of Wyoming. Her interdisciplinary research focuses on violence prevention, housing justice, refugee experiences, and community-engaged methodologies. Current projects examine neighborhood effects on violence, housing discrimination, and refugee service integration. As Board President for Cache Refugee and Immigrant Connection and commissioner for the Logan City Planning Commission, she bridges academic research with community action. Her teaching emphasizes community-engaged approaches to social work practice and research methods.

Anirudh Mohan KaushikView profile

Assistant Professor

• Cyber-Physical Systems
• High-Performance Computer Architecture
• Compiler Design
• +1 more

Anirudh Mohan Kaushik is an Assistant Professor in the Electrical Engineering & Computer Science (EECS) department at York University's Lassonde School of Engineering. He holds a Ph.D. from the University of Waterloo (2021) and has prior industry experience at Intel, AMD, and IBM in research and design roles focused on software performance analysis, compiler design, and hardware micro-architecture. Research Interests : Cyber-physical systems, high-performance computer architecture, compiler design, and software performance analysis with a focus on timing predictability in multi-core systems. Key Publications : His work addresses predictable cache coherence (2021), shared cache optimization (2024), GPU wavefront splitting (2023), and hardware prefetching for graph analytics (2021). Industry Experience : Contributions to compiler design and hardware micro-architecture at Intel, AMD, and IBM prior to academia.