Find Academic Supervisors

• Linked Data
• Data Management
• Ontology Engineering
• +4 more

Dr. Ronald Maria Siebes serves as Assistant Professor at the Faculty of Science, Vrije Universiteit Amsterdam, with affiliations to the Network Institute and Business Web and Media department. His research focuses on knowledge organization systems, semantic web technologies, and FAIR data principles. He leads projects involving interoperability frameworks for restricted data access, IoT-enabled smart buildings, and historical chronicle analysis. Current roles include managing Open Data Infrastructure initiatives and guiding PhD research in data governance. Education details are not explicitly provided in the text. Research interests emphasize ontology engineering, knowledge graph applications, and data management standards. Recent work explores FAIR Implementation Profiles for research data, IoT sensor integration in office environments, and dynamic knowledge graph embeddings. Active in 6 collaborative projects including smart grid integration and historical source analysis. Labs/Teams: Involved in Network Institute initiatives and Open PHACTS Foundation projects. Supervised 2 PhD theses (names not specified in text). Grant activities span €2.1M in EU Horizon and national funding for data infrastructure and knowledge engineering research.

Masum BillahView profile

Senior Lecturer

• Data Analytics
• Telecommunications
• Artificial Intelligence
• +4 more

Dr. Masum Billah is a Senior Lecturer at Staffordshire University, affiliated with the Digital, Tech, Innovation & Business School. He joined the university in 2022 after teaching full-time at other universities since 2019. His academic journey includes a B.Sc. in Engineering from Bangladesh, an M.Sc. in Computer & Network Engineering from the University of Greenwich (UK), and a PhD in Electrical and Electronic Engineering from Staffordshire University. He also holds postgraduate certificates in Higher Education and Research Methods. As a course leader for the B.Sc. Embedded Electronic Systems Design and Development Engineer program, he teaches both undergraduate and postgraduate courses such as IoT Devices, Artificial Intelligence, and Communications. His research focuses on data analytics, telecommunications, IoT security, and healthcare research, with a particular interest in wireless sensor networks and machine learning applications. He actively promotes STEM education as a STEM Ambassador and contributes to initiatives like university competitions and school outreach. Masum’s professional memberships include Fellow of The Higher Education Academy (FHEA), IEEE, and roles in academic leadership. His work integrates flipped learning methodologies and spans engineering consultancy, short courses, and enterprise-focused projects. Recent recognitions include Whatuni Student Choice Awards 2023 for Facilities and Social Inclusion, reflecting his commitment to educational excellence.

Thomas HeldtView profile

Associate Professor

• Computational Physiology
• Neuromonitoring
• Critical Care Informatics
• +2 more

Thomas Heldt is Associate Professor of Electrical and Biomedical Engineering in the Department of Electrical Engineering and Computer Science at MIT, and a Principal Investigator at MIT's Research Laboratory of Electronics. He leads the Integrative Neuromonitoring and Critical Care Informatics Group and serves as Associate Director of the Institute for Medical Engineering and Science. Research focuses on: Noninvasive intracranial pressure monitoring Computational models of cerebrovascular dynamics Sepsis detection algorithms Wearable physiological monitoring Clinical decision support systems Recent publications (2022-2024) demonstrate advances in hemodynamic modeling, diagnostic algorithms for critical care, and AI applications for physiological monitoring. Key innovations include open cranium models for intracranial hypertension studies, deep learning frameworks for fatigue assessment, and mobile-based neurocognitive tracking. Professor Heldt collaborates with Boston Children's Hospital, Beth Israel Deaconess Medical Center, and Boston Medical Center to translate research into clinical practice. His work has been recognized through the W.M. Keck Career Development Professorship and IEEE EMBS Distinguished Lectureship.

Ke ChenView profile

Senior Lecturer

• Machine Learning
• Artificial Intelligence
• Computational Cognitive Science
• +9 more

Dr. Ke Chen is a Senior Lecturer in the School of Computer Science at The University of Manchester, leading the Machine Learning and Perception (MLP@UoM) Lab. His research focuses on machine learning, deep learning, reinforcement learning, and their applications in intelligent systems, computer vision, and audio/speech processing. He has supervised over 50 PhD students and holds editorial roles in journals like Neural Networks and IEEE Transactions on Neural Networks . Dr. Chen has received awards such as the NSFC Distinguished Principal Young Investigator Award (2001) and JSPS Research Award (1993). Education: PhD in Computer Science (1990), with academic positions at institutions including Peking University, The Ohio State University, and Kyushu Institute of Technology. His professional activities include roles in IEEE Computational Intelligence Society committees and external examiner roles at universities like Essex. Research interests span computational cognitive systems, biometric authentication, and video game AI. Key contributions include advancements in deep architectures, reinforcement learning, and speaker-specific feature extraction. His lab, MLP@UoM, explores topics like explainable AI and transfer learning. Recent publications (2024) include work on goal-conditioned reinforcement learning and bias-resilient algorithms. He is actively involved in international conferences, serving as a keynote speaker and program committee member.

Vivienne SzeView profile

Professor

• Energy-Efficient Machine Learning
• Computer Vision
• Video Compression/Processing
• +7 more

Vivienne Sze is a Professor at MIT's Department of Electrical Engineering and Computer Science (EECS), part of the School of Engineering. Her research focuses on energy-efficient computing systems for machine learning, computer vision, and video compression, with applications in autonomous systems, healthcare, and IoT. She leads projects integrating algorithmic innovations with hardware design to achieve low-power solutions for embedded and mobile devices. Her work has been recognized through prestigious awards, including the Primetime Engineering Emmy Award for co-developing the HEVC video compression standard and multiple faculty awards from tech giants like Google and Qualcomm. She co-authored the book *Efficient Processing of Deep Neural Networks*, emphasizing practical hardware-software co-design strategies. Research Interests: Energy-Efficient Machine Learning Accelerators Video Coding and Compression Standards Embedded Systems and Mobile Computing Processing-in-Memory (PIM) Architectures AI for Health Monitoring and Digital Health Sustainability in AI Infrastructure Publications highlight trends in: Optimizing DNNs for edge devices Innovations in entropy coding and CABAC Memory-efficient Gaussian-based algorithms Energy-aware design for photonic computing Awards include IEEE conference best paper awards and industry recognitions for her contributions to video coding and hardware acceleration. Her lab's collaborative efforts span academia and industry, aiming to bridge theoretical research with real-world deployable systems.

Mark HooverView profile

Lecturer

• Mathematics Education
• Social Justice in Education
• Teacher Professionalization
• +5 more

Mark Hoover is an Associate Research Scientist and Intermittent Lecturer at the University of Michigan's Marsal Family School of Education, Department of Mathematics Education. His work focuses on disrupting systemic educational inequities through mathematics teaching and teacher professionalization, emphasizing social justice and ethical pedagogy. He draws inspiration from civil rights activist Robert Moses and education researcher Deborah Ball, whose collaborations are highlighted in his research. Hoover has held roles in both research and teaching, contributing to the development of practice-based approaches to studying teaching demands and advocating for curricula that promote civic participation. His research bridges mathematics content and pedagogy, exploring how teaching practices can address historical injustices embedded in educational systems. Research Interests: Equity in STEM education, mathematical knowledge for teaching (MKT), teacher professionalization, curriculum development, assessment design, and the intersection of mathematics education with social justice movements. He critiques oppressive educational standards and accountability systems while investigating how teaching can be reimagined to center justice. His work also explores the role of mathematicians in shaping mathematics education and the importance of tasks for assessing teaching proficiency. His scholarly output reflects a sustained engagement with equity and justice, analyzing classroom practices and teacher education through critical frameworks. Recent publications emphasize collaborative research initiatives (e.g., TWG19) and the moral dimensions of pedagogy. Grants: Recipient of the Communicating Mathematically Across Difference in the Work of Teaching Award (2018-2025). Advising: No formal advisees listed in provided materials, but his work supports professional learning communities across disciplines. Hoover is affiliated with the Connected Mathematics Project, contributing to curriculum development and its impact assessment. His contributions span both research and practical teaching, aiming to create inclusive and just educational environments.

Edoardo SerraView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Cybersecurity
• +5 more

Edoardo Serra is an Associate Professor in the Department of Computer Science at Boise State University (BSU), a role he has held since July 2021. He previously served as an Assistant Professor at BSU from 2015 to 2021 and holds a joint appointment as a Senior Researcher at Pacific Northwest National Laboratory (PNNL) since June 2021. Since January 2023, he has co-directed the Computing Ph.D. Program at BSU and serves as General Chair of the 2024 ACM CIKM Conference. His academic journey includes a Ph.D. in Computer Science Engineering from the University of Calabria, Italy (2012), followed by postdoctoral positions at the University of Calabria and the University of Maryland. He also served as a Visiting Researcher at UCLA (2010–2011). His research focuses on AI/ML applications in cybersecurity, graph representation learning, generative AI, and robust AI systems. Notable projects include: NSF-funded cybersecurity curriculum integration Department of Defense-funded analysis of terrorist networks Idaho Department of Commerce precision agriculture initiatives Key research areas include graph neural networks, adversarial robustness, and ML-driven security solutions. His work has been recognized with awards such as Best Application Paper (2021) and Best Paper Award (2018). He actively contributes to professional service roles, including program chairs and editorial boards. Current projects emphasize AI ethics, generative models, and scalable graph algorithms. He advises on applied AI consulting for industry and government, focusing on model interpretability and cybersecurity implications.

Eric GamessView profile

Associate Professor

• Network Performance Evaluation
• IPv6
• Cybersecurity
• +4 more

Eric Gamess is an Associate Professor in the Department of Mathematical, Computing, and Information Sciences at Jacksonville State University (JSU), Alabama. He holds a Ph.D. in Computer Science from the Central University of Venezuela (2000), an M.Sc. in Industrial Computing from INSA Toulouse (1989), and an Engineering Degree in Automatics, Computer Science, and Electronics from the same institution (1989). His academic career spans roles at universities in South America and the U.S., including Universidad del Valle (Colombia) and the University of Puerto Rico. Dr. Gamess specializes in network performance evaluation, cybersecurity, vehicular networking, and IoT. He has authored over 80 publications, edited 27 conference proceedings, and directs the Venezuelan Journal of Computing. His leadership roles include Vice-President of the Venezuelan Society of Computing and steering committee member of the ACM Southeast Conference. At JSU, he leads the Center of Academic Excellence in Cyber Defense Education (CAE-CD) and coordinates the Master of Science in Computer Systems and Software Design (CSSD) program. His research emphasizes network simulation, IPv6, and embedded systems performance (e.g., Raspberry Pi). Recent work explores containerization technologies, MQTT resilience, and IoT protocol optimizations. He teaches courses ranging from programming fundamentals to advanced cybersecurity and networking.

Sheheeda Mariam ManakkaduView profile

Associate Professor

• Robotics
• Data Analytics
• Machine Learning
• +4 more

Sheheeda Mariam Manakkadu is an Associate Professor in the Department of Computer Science at Southern Illinois University Carbondale. She teaches graduate courses in Data Structures, Object-Oriented Programming, Data Mining, Text Mining, and Cloud Architecture, along with undergraduate courses in Operating Systems and Data Analytics. Ph.D., Computer Engineering M.E., Biomedical Engineering Her research spans robotics, data analytics, and parallel computing. Key areas include adaptive control of robotic manipulators, big data processing via MapReduce, IoT resource allocation, and computational bioinformatics for protein networks. Recent publications focus on neuro-sliding mode control, cloud architecture, and scalable recommender systems. She actively participates in academic service as a committee member for graduate courses and the IEEE Erie Section. Her work integrates machine learning, optimization algorithms, and distributed systems across diverse domains.

Iti ChaturvediView profile

Lecturer

• Signal Processing
• Artificial Intelligence
• Social Media Analysis
• +5 more

Iti Chaturvedi is a Lecturer in the Department of Information Technology at James Cook University (JCU). She holds a Ph.D. in Computer Engineering from Nanyang Technological University, Singapore. Her research focuses on signal processing and AI applications in social media, including emotion recognition, speech analysis, and sentiment analysis. She has been recognized as a Top 2% Most Cited Researcher globally (2022) and received the JCU CSE Early Career Researcher Award (2020). She teaches courses such as Machine Learning and Data Science, Programming III, and Design Thinking I. Current research projects include sentiment prediction from social media (since 2020). She serves as an Associate Editor for the Expert Systems journal (2023) and has been an ARC Assessor (2020). Key contributions include work on speech emotion recognition, constrained manifold learning for videos, and multimodal emotion recognition systems. Her research outputs span journals like Expert Systems , Signal Processing , and conferences including IJCNN and AAAI.

Enzo MastinuView profile

Associate Professor

• Biomedical Engineering
• Prosthetics and Neuroprosthetics
• Embedded Systems
• +4 more

Enzo Mastinu is an electronic engineer specialized in embedded systems for biomedical applications, holding an Associate Professor qualification in Bioengineering. He earned his bachelor's and master's degrees in electronic engineering from the University of Cagliari and a PhD in biomedical signals and systems from Chalmers University of Technology, Sweden. His research focuses on advanced prosthetics and neuroprostheses for upper limb amputations, incorporating embedded systems design, control algorithms, sensory feedback, signal processing, AI, and osseointegration. Key projects include the HAND and HAND2 initiatives, funded by the EU and the Italian Ministry of Research, aiming to develop semi-autonomous prosthetic hands. He has published 25 journal articles (75% in Q1) and 21 conference papers, contributing to a PCT patent. Mastinu is a Senior Member of IEEE EMBS and RAS, reviews for ~90 journals/conferences, and edits Transactions on Medical Robotics and Bionics (IEEE) and Scientific Data (Nature). He has supervised ~40 students across PhD, master's, internships, and postdocs, and teaches courses in biomedical engineering and STEM education. His scientific awards include the Marie Skłodowska-Curie Fellowship (2021), National Qualification as Associate Professor (2024), and a Young Researcher Grant (2025). Research emphasizes clinical implementation of prosthetics with neural feedback and intuitive control, as highlighted in high-impact journals like the New England Journal of Medicine.

Elena PanteleyView profile

Researcher

• Nonlinear Control Systems
• Networked Systems
• Multi-Agent Systems
• +5 more

Elena Panteley is a Research Director at the CNRS and a member of the Laboratoire des Signaux et Systèmes (L2S) at CentraleSupélec. She holds a PhD in Applied Mathematics from Saint Petersburg State University (1997) and has extensive experience in research, including roles at the Institute of Problems in Mechanical Engineering, Russian Academy of Sciences (1986–1998). She co-chairs the International Graduate School of Control at the European Embedded Control Institute (EECI-IGSC) and serves as a Book-reviews Editor for Automatica and Associate Editor for IEEE Control Systems Letters . Education: PhD in Applied Mathematics, Saint Petersburg State University, 1997 MSc/BSc in relevant fields (implied by career progression) Research Interests: Focuses on stability and control of nonlinear dynamical systems, networked systems, multi-agent systems, and their applications. Her work emphasizes robust control, consensus algorithms, synchronization, and distributed control strategies for autonomous systems. She explores theoretical frameworks like Lyapunov methods and adaptive control, with practical applications in robotics and communication networks. Publications: Over 100 peer-reviewed articles in top journals like IEEE Transactions on Automatic Control and Automatica . Recent trends include advancements in consensus algorithms for multi-agent systems, synchronization of nonlinear oscillators, and control under communication delays. Awards: No specific awards mentioned, but contributions to control theory and networked systems are widely recognized. Grants/Advising: Leads research on adaptive control, network synchronization, and robotics. Collaborates internationally and advises on projects involving autonomous vehicles and distributed systems. Labs/Teams: Active in L2S and affiliated with CNRS, contributing to teams like MODESTY, COMEDY, and SYCOMORE. Engaged in transverse research on energy, industry automation, and healthy systems.

• Higher Education Pedagogy
• Academic Development
• Blended Learning
• +4 more

Dr Alison Gilmour is a higher education academic specializing in learning and teaching enhancement. Currently serving as Lecturer in Learning Transformation at the University of the West of Scotland (since 2021), she previously held roles as Associate Professor and Lecturer in Learning and Teaching at the University of Greenwich, and Educational Advisor at Queen Mary University of London. Her career includes seven years in Learning Enhancement roles at the Open University in Scotland. She is an External Examiner at the University of Essex (since 2021) and PhD Supervisor at the University of Greenwich (since 2020). Her research focuses on pedagogies of care, blended learning strategies, and embedding wellbeing in curricula. She has led cross-sector projects on Scottish HE teacher professional development (2012-14), student feedback analysis (2018), and retention/progression data (2019), and contributed to national initiatives like the Advance HE Embedding Wellbeing in the Curriculum project (2019-2020) and QAA Collaborative Enhancement Project (2021-2022). Education: PhD in Sociology/Economic History (focused on post-war Scottish industrial relations) and postdoctoral fellowship with the Economic History Society Teaching: Module leader on Advance HE-accredited programs, mentor for fellowship pathways, and Open University Associate Lecturer since 2009 Dissemination: Prioritizes practice-oriented outputs including blogs, workshops, OERs, and peer-reviewed articles Key research interests include compassionate-focused pedagogy, online community-building, and the agency of academic developers. She actively engages with international higher education networks through invited speaking engagements and podcast contributions.

Jean PonceView profile

Professor

• Computer Vision
• Machine Learning
• Robotics
• +3 more

Jean Ponce is a Professor of Computer Science at Ecole Normale Superieure (ENS) in Paris and a Part-Time Global Distinguished Professor at New York University's Courant Institute of Mathematical Sciences and Center for Data Science (CDS). He previously served as Director of the ENS Computer Science Department (2011-2017) and held positions at Inria (2017-2022), University of Illinois at Urbana-Champaign (1998-2006), MIT, Stanford, and Inria (1982-1985). Academic Leadership: Scientific Director of PRAIRIE Interdisciplinary AI Research Institute in Paris Startup Involvement: Co-founder and CEO of Enhance Lab (2022) Editorial Roles: Senior Editor-in-Chief of International Journal of Computer Vision (2019-2022) Conference Leadership: Chair of IEEE CVPR (1997,2000), ECCV (2008), and upcoming ICCV (2023) Research Focus: Computer vision, machine learning, robotics, and AI with applications in exoplanet imaging, 3D reconstruction, and image quality assessment. His work bridges statistical learning and deep learning approaches. Awards: IEEE Fellow (2003) ELLIS Fellow (2019) ERC Advanced Grant (2011) IEEE CVPR Longuet-Higgins Prizes (2016,2020) ICML Test-of-Time Award (2019) Patents & Publications: Co-author of influential textbook Computer Vision: A Modern Approach (translated into Chinese, Japanese, Russian). Holds two US patents and one pending French patent. Google Scholar h-index of 78 with over 55,000 citations.

IMRAN BashirView profile

Senior Lecturer

• Acoustic Metamaterials
• Aeroengine Acoustics
• Condition Monitoring
• +3 more

Dr. IMRAN Bashir is a Senior Lecturer in Instrumentation & Control Engineering at Teesside University's SCEDT Engineering Centre for Sustainable Engineering. He holds a PhD in Acoustics Metamaterials from an EU-FP7 funded project and has extensive postdoctoral experience across the University of Bath, Southampton, and Exeter. His research focuses on acoustic metamaterials, aeroengine acoustics, and condition monitoring. Education: PhD in Acoustics Metamaterials (EU-FP7 HOSANNA Project) MSc in Data Communication (University of Sheffield) BEng in Electrical Engineering (COMSATS University, Pakistan) His research interests span acoustic metamaterials, aeroengine acoustics, vibration control, and signal processing. He leads projects like the EU Horizon 2020 AERIALIST initiative for noise reduction in aeronautics. Current work includes smart bearing systems for aeroengines and condition monitoring for wave energy devices. Collaborations include multi-university projects on hydrogen production and sustainable engineering. He has published extensively in peer-reviewed journals and conferences, with a focus on battery diagnostics, acoustic modeling, and smart systems. As a Co-Investigator in the Hydrogen Production Life-Cycle project (2024–2026), he contributes to knowledge transfer for emerging energy markets. His interdisciplinary approach bridges engineering disciplines, emphasizing practical applications in aerospace, energy, and environmental acoustics.