Find Academic Supervisors

Jeffrey K. HollingsworthView profile

Professor

• High Performance Computing (HPC)
• Parallel Programming
• Operating Systems
• +5 more

Jeffrey K. Hollingsworth is a Professor in the Computer Science Department at the University of Maryland and serves as Vice President for Information Technology and Chief Information Officer (CIO) for the university. He holds appointments in CS, UMIACS (University of Maryland Institute for Advanced Computer Studies), and ECE (Electrical and Computer Engineering). His research focuses on High Performance Computing (HPC), parallel programming environments, and system architecture. He received a Ph.D. from the University of Wisconsin at Madison (1994) and a B.S. in Electrical Engineering from UC Berkeley. Hollingsworth leads the university’s IT infrastructure, overseeing critical services like networking, cybersecurity, and support for research and teaching. He has held leadership roles in professional organizations, including past chair of the ACM Special Interest Group on HPC (SIGARCH) and board positions with Internet2 and the Computing Research Association. His awards include IBM Faculty Partnership Awards (2016, 2001), an NSF CAREER Award (1997), and IEEE Senior Member status (2003). Key contributions include advancing HPC education through programs like the SC Student Cluster Competition and developing tools for performance analysis (e.g., PIPER, Chapel profilers). He has authored over 150 papers and has been cited for innovations in auto-tuning, parallel algorithms, and system optimization.

Florentin RochetView profile

Assistant Professor

• Anonymous Communication
• Network Security
• Transport Protocols
• +5 more

Florentin Rochet is an Assistant Professor at the University of Namur's Faculty of Computer Science. His research focuses on anonymous communication , network security , and encrypted transport protocols , with a particular emphasis on improving privacy-enhancing technologies and protocol design. He holds a PhD in Applied Cryptography and has contributed to projects like TCPLS (TCP/TLS integration) and CLAPS (Tor path selection). Key academic milestones include joining UNamur in 2022 as an Assistant Professor, completing a postdoc at the University of Edinburgh (2021), and serving on program committees for Usenix Security, ACM CCS, and PoPETs. He has received the Usenix Security Noteworthy Reviewer Award (2023) and the 2020 Alan Berman Research Publication Award. His research spans flexible anonymous networks , secure transport protocols , and authentication technologies , with notable work on improving Tor's resilience against attacks through location-aware path selection and enhancing TLS/TCP integration for modern networks. He also leads a research group exploring eBPF security and WebAssembly runtime protections. Teaching responsibilities include computer security and privacy courses, with a 6-year teaching assistant position involving bachelor's/master's instruction and PhD supervision. His lab focuses on applied cybersecurity, network protocol innovation, and privacy-preserving systems design.

• High-Performance Computing
• Energy-Efficient Computing
• Parallel and Distributed Systems
• +5 more

Ravi Reddy Manumachu is an Assistant Professor in the School of Computer Science at University College Dublin (UCD), Ireland. He holds a B.Tech from IIT Madras (1997) and a PhD in Computer Science from UCD (2005), specializing in high-performance heterogeneous computing and energy-efficient systems. His research focuses on optimizing performance and energy efficiency in modern heterogeneous platforms like clouds, grids, and supercomputers through novel models and algorithms. Key contributions include functional performance/energy models, energy-prediction frameworks, and extensions like Heterogeneous MPI and ScaLAPACK for heterogeneous clusters. He has published over 69 articles in top journals/conferences, with recent works addressing data transfer energy measurement, scalable allreduce algorithms (SUARA), and portable programming models (OpenH). Professional roles include Assistant Professor at UCD (2023–present), SEAI Research Fellow (2022–2023), and prior industrial experience at Ansys, Siemens, and IONA Technologies. He has certifications in university teaching, GDPR, and research integrity. Languages include English (fluent), Telugu, and Hindi. Research trends emphasize bi-objective optimization (performance-energy), hardware heterogeneity challenges, and scalable communication algorithms for deep learning. His work addresses energy non-proportionality in CPUs and GPU-CPU interactions, with practical solutions for real-world applications like matrix operations and gene sequencing.

Markus NüttgensView profile

Professor

• Information Systems
• Business Process Management
• Digital Transformation
• +4 more

Prof. Markus Nüttgens is a Professor at the University of Hamburg Business School's Department of Information Systems. His research focuses on digital transformation, business process management, sustainability management, and blockchain applications in Industry 4.0. He leads projects like smartTCS and EMOTEC , developing platforms for customer integration in technical services and mobile assistance systems. Notable contributions include frameworks for data-driven sustainability management, semantic verification in process modeling, and standards like DIN SPEC 33451 for service catalogs. His work bridges theory and practice, emphasizing hybrid value chain strategies, mobile service support systems, and process audits. He has pioneered methodologies for service engineering and smart service ecosystems, with a particular focus on empowering technical customer services through IT innovations. Prof. Nüttgens has contributed to over 50 peer-reviewed publications and actively participates in academic conferences, editing volumes on service modeling and process auditing. His research portfolio spans IT governance, cybersecurity awareness in enterprises, and the diffusion of Web 2.0 in healthcare and SME networks. He collaborates with industry partners to design productivity-enhancing solutions for hybrid service systems, ensuring alignment between technological advancements and organizational efficiency.

Sezana FahmidaView profile

Assistant Professor

• Internet of Things
• Real-time & Embedded Systems
• Wireless Networks
• +1 more

Sezana Fahmida is an Assistant Professor of Teaching in the Computer Science Department at Wayne State University's College of Engineering. She earned her PhD from Wayne State University in 2023. Her research focuses on Internet of Things (IoT), real-time embedded systems, wireless networks, and cyber-physical systems. She investigates communication protocols, energy efficiency, and network optimization techniques for IoT applications. Her recent publications explore real-time communication protocols, battery optimization in low-power networks, and machine learning solutions for network coexistence. She received the Wayne State University Graduate Student Travel Scholarship Award in 2023 and has presented her work at international conferences including CPS-IoT Week and ICDCS.

Vasilios KelefourasView profile

Lecturer

• Compiler Optimizations
• Deep Neural Networks
• Matrix/Tensor Computations
• +2 more

Dr. Vasilios Kelefouras is Lecturer in Computer Science at the University of Plymouth's School of Engineering, Computing and Mathematics. His research optimizes software applications for execution time, energy consumption, and memory footprint across CPUs, GPUs and FPGAs. Notable contributions include analytical methodologies accelerating convolution layers in Deep Neural Networks (x1.1-7.2 speedup over Intel oneDNN) and optimization techniques for image processing algorithms (x2.8-40 speedup over Intel IPP). His compression work for Deep Neural Networks includes Tensor Train Decomposition methodologies for edge devices. Honors include HiPEAC Technology Transfer Award (2022) and Best Paper at SAMOS XXII. Teaches Parallel Computing, Computer Systems, and Computing Practice. Current PhD supervision focuses on accelerating ML algorithms on heterogeneous architectures.

Marco GrangettoView profile

Professor

• Computer Vision
• Image Processing
• Artificial Intelligence
• +5 more

Marco Grangetto serves as Full Professor in the Department of Computer Science at the University of Turin, coordinating research in image processing and computer vision. His expertise spans wavelets, image/video coding, data compression, error resilient video coding, and biomedical image processing, with significant contributions to ISO JPEG2000 standardization and editorial roles in IEEE Transactions on Multimedia. His educational background includes a PhD in Electrical and Communications Engineering (2003) and MSc in Telecommunications Engineering (1999), both from Politecnico di Torino. His research integrates Artificial Intelligence and Deep Learning with medical imaging and fundamental compression theory , producing innovations in neural network pruning, capsule networks, and entropy-based models. Recent work focuses on Covid-19 diagnosis from chest X-rays and efficient 3D scene modeling. His publication trends reveal dual trajectories: applied medical AI (Covid-19 diagnostics, lung cancer segmentation) and theoretical advances (learned compression, contrastive learning, bias mitigation). This bridges clinical validation with information-theoretic foundations, particularly in resource-constrained environments. Scientific recognition includes: Premio Optime by Unione Industriale di Torino (2000) Fulbright Grant for research at UC San Diego (2001) He maintains leadership through IEEE editorial positions, ISO standardization participation, and MPAI membership. His research group develops medical datasets (UniToChest, UniToPatho) while advancing neural network efficiency for clinical deployment. Current projects focus on entropy minimization techniques and unbiased representation learning for healthcare applications.

Rasha KarakchiView profile

Lecturer

• High Performance Computing
• Reconfigurable Computing
• Embedded Systems
• +3 more

Rasha Karakchi serves as a Lecturer in the Department of Computer Science and Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing, where she teaches diverse courses while maintaining an active research program in hardware acceleration and embedded systems. Her academic foundation includes: Ph.D. in Computer Science and Engineering, University of South Carolina (2020) M.E. in Computer Engineering, University of South Carolina (2016) Dr. Karakchi's research centers on high-performance reconfigurable embedded systems, with particular focus on hardware acceleration for automata processing, spiking neural networks, and genomic sequence alignment. Her work bridges theoretical computer science with practical hardware implementation, emphasizing energy efficiency and real-time performance in security-critical applications. Analysis of her 2023-2025 publications reveals a dominant research trajectory applying machine learning to optimize hardware configurations for domain-specific tasks. Key thematic clusters include ML-enhanced automata processors for pattern matching, lightweight encryption engines for embedded security, and specialized architectures for spiking neural network acceleration—all demonstrating consistent innovation in hardware-software co-design for computationally intensive workloads. Her research excellence has been recognized through: SPARC Award (South Carolina's Program to Advance Research and Creativity)

Pere Millán MarcoView profile

Associate Professor

• Computer Communications
• Mobile and Sensor Networks
• Internet of Things
• +3 more

Pere Millán Marco is an Associate Professor in the Department of Computer Engineering and Mathematics (DEIM) at Universitat Rovira i Virgili (URV), Tarragona, Spain. He serves as coordinator for Non-permanent lecturers. His research focuses on computer communications, mobile/sensor networks, and IoT, with emphasis on quality prediction and performance optimization in wireless environments. Education: M.Sc. in Computer Engineering (Polytechnic University of Catalonia, 1992); PhD in Computer Engineering (URV, 2018). Research Interests : Specializes in mobile and sensor network architectures, underwater acoustic networks, real-time communication protocols, and low-cost hardware solutions for educational and environmental applications. His work integrates time series analysis, predictive modeling, and social behavior patterns to enhance network efficiency. Publications Trends : Recent work emphasizes IoT applications in environmental monitoring (e.g., deep aquifer pumping systems), optimization of underwater acoustic networks, and low-cost multicomputer systems for teaching. Consistently explores predictive techniques for network topology and quality-of-service improvements in ad hoc and community networks. Awards & Recognition : Holds a granted US patent related to location-based information systems. Advising & Infrastructure : Involved in DEIM's teaching laboratory development. Active in organizing international conferences like UCAmI and VISIGRAPP. Member of the CloudLab research group, advancing cloud and distributed computing solutions.

John LoganView profile

Associate Professor

• Psychology
• Speech Perception
• Cognitive Science
• +3 more

John Logan is an Associate Professor in the Department of Psychology at Carleton University, affiliated with the Faculty of Arts and Social Sciences. He holds a Ph.D. from Indiana University. His research focuses on spoken language perception, non-native speech perception, and word recognition in children. His work bridges cognitive psychology, forensic psychology, and linguistics, examining how personality traits like psychopathy influence speech perception and emotional processing. Dr. Logan's research explores the interplay between personality variables and speech perception mechanisms, particularly in contexts involving psychopathic traits, trauma, and non-native language acquisition. His recent studies investigate how psychopathy affects emotional recognition in spoken language and domestic abuse dynamics, while also analyzing disfluency patterns and vowel acoustics in speech production. His research has contributed to understanding deficits in prosodic perception among individuals with psychopathic characteristics and developing interventions to improve emotion recognition. He also studies cognitive constraints in acquiring non-native phonemes and employs neuroimaging techniques to explore decision-making processes in gambling scenarios. Though no specific awards or grants are listed, his extensive publication record reflects sustained contributions to speech perception, forensic psychology, and developmental cognitive science. Dr. Logan's work integrates experimental methods with computational analysis, addressing both theoretical and applied questions in language processing and mental health.

Olayinka LewisView profile

Senior Lecturer

• Immigration Law
• Nationality Law
• Asylum Law
• +7 more

Olayinka Lewis is a Senior Lecturer at Essex Law School, University of Essex. He holds a PhD in Law from the University of Aberdeen, specializing in legal pluralism and land/mineral ownership, alongside an LLM in Oil and Gas Law and an LLB (Hons). A Fellow of the Higher Education Academy and English-qualified solicitor, he specializes in UK Immigration Law, legal pluralism, customary law, and energy law. His current roles include Director of Community and Outreach at Essex Law School and Immigration Lead at the Essex Law Clinic. Education: PhD in Law, University of Aberdeen LLM in Oil & Gas Law, University of Aberdeen LLB (Hons) Research Interests: Lewis focuses on immigration, nationality, and asylum law, with interdisciplinary work on legal pluralism in land ownership and mineral rights. He explores customary law’s role in legal systems and energy law’s intersection with resource governance. Recent studies also address the UK’s migration policies and post-Brexit legal frameworks. Publications: His work spans legal critiques of migration policies, land rights in Nigeria, and interdisciplinary analyses (e.g., machine learning in mental health). Key themes include human rights implications of immigration laws and the tensions between legal systems. Awards & Grants: Fellow of the Higher Education Academy Young Universities for the Future of Europe grant (2022) for Refugee Rights Awareness Professional Roles: Member of the Law Society of Scotland’s Immigration & Asylum Sub-committee, academic reviewer for Routledge, and External Examiner for Universities of Bradford and Wolverhampton. Active in societies like the Society of Legal Scholars and Law Society of England and Wales. Teaching & Outreach: Previously Academic Director of the Law Clinic at Robert Gordon University and Visiting Professor at ESC Clermont (2016–2019). Leads efforts to address access-to-justice gaps through clinical legal education.

Markos AnastasopoulosView profile

Associate Professor

• Optical Communications
• Wireless Networks
• Mobile Computing
• +3 more

Markos Anastasopoulos is Associate Professor at the National and Kapodistrian University of Athens, specializing in optical/wireless networks and mobile computing. His research focuses on 5G/6G network convergence, intent-based management, and AI-driven optimization for telecommunications. Recent publications address THz-optical integration, federated learning in transport networks, and semantic-aware radio systems. Applied work includes intelligent asset management for railways and techno-economic analyses of network deployments. Recognized with best dissertation and best paper awards, his research bridges theoretical networking with industrial applications in transportation and cloud infrastructure.

Dong ChenView profile

Associate Professor

• Cyber-Physical Systems (CPS)
• Internet of Things (IoT)
• Embedded AI
• +5 more

Dong Chen is an Associate Professor in the Department of Computer Science at the Colorado School of Mines. His research focuses on building data-driven experimental systems in Cyber-Physical Systems (CPS), IoT, Embedded AI, and Embodied AI, with applications in smart devices, homes, cities, and renewable energy systems. He leads the Next Generation Cyber-Physical Systems Laboratory (CPSLab), emphasizing open-source systems and datasets. Dr. Chen holds PhDs in Electrical and Computer Engineering (2018, University of Massachusetts Amherst) and Computer Science (2014, Northeastern University). His work addresses security, privacy, sustainability, and efficiency in smart environments. Notable contributions include SolarFinder, SolarTrader, PrivacyGuard, and VoiceAttack, which tackle challenges in IoT privacy, energy trading, and adversarial attacks. He received the NSF CAREER Award (2023) and is a member of Sigma Xi, ACM, AAAI, and IEEE. His research spans system design, AI applications, and cross-cutting domains like solar energy modeling and edge computing. Current projects include AgileDART (edge stream processing) and SolarDetector (satellite-based PV array identification). Advising and collaborations: Dr. Chen seeks PhD and undergraduate students with strong CS/EE backgrounds. His lab focuses on CPS/IoT security, energy systems, and AI-driven solutions. He has published extensively on topics ranging from smart grid optimization to adversarial machine learning.

Ylva SjöbergView profile

Associate Professor

• Arctic Hydrology
• Permafrost Dynamics
• Climate Change Impact on Water Resources
• +2 more

Ylva Sjöberg is an Associate Professor at the Department of Ecology, Environment and Geoscience, Umeå University. Her research focuses on Arctic hydrology, permafrost dynamics, and climate change impacts on water resources, employing numerical modeling and field-based methods across northern Fennoscandia, Greenland, and Alaska. Key research areas include: Mechanistic understanding of Arctic river methane emissions (ARIMETH project, 2025) Cryospheric impacts on water quality and flow paths Development of standardized permafrost thaw monitoring protocols Science communication through Frozen-Ground Cartoons Her publications emphasize interdisciplinary approaches, linking groundwater-surface water interactions, permafrost thaw cascades, and biogeochemical processes in Arctic catchments. She actively collaborates with Indigenous communities and contributes to Arctic policy frameworks.

• Telecommunications
• Signal Processing
• Wireless Communications
• +4 more

George Alexandropoulos is an Associate Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on telecommunications, signal processing, and reconfigurable intelligent surfaces (RIS) for next-generation wireless networks. He has contributed to advancements in integrated sensing and communications (ISAC), 6G technologies, and holographic beamforming. His work includes experimental validation of RIS prototypes, optimization of RIS-assisted systems, and analysis of secure communication strategies. Research interests include RIS hardware design, channel modeling, and applications in IoT, UAV communications, and disaster recovery networks. He explores topics like energy-efficient RIS operation, multi-RIS coordination, and RIS-enabled localization. His studies often address challenges at sub-THz frequencies, mutual coupling effects, and hardware impairments. Publications emphasize practical implementations of RIS in both indoor and outdoor settings, with a focus on real-world performance evaluation. Awards and grants are not explicitly mentioned, but his extensive publication record indicates significant academic contributions. His research often integrates machine learning for RIS configuration and reinforcement learning for resource optimization in dynamic networks.