جست‌وجوی استاد و پژوهشگر

Shakeel Ahmadمشاهده پروفایل

دانشیار

• Multimedia Communications
• Computer Networks
• Network Optimization
• +۵ مورد دیگر

Dr. Shakeel Ahmad is an Associate Professor in the Department of Science and Engineering at Solent University since 2015. He leads the BSc (Hons) Cyber Security Management, BSc (Hons) Computer Systems and Networks Engineering, and MSc Applied AI and Data Science programs. His research focuses on optimizing multimedia communications and computer networks to maximize user quality of experience, particularly addressing challenges in video streaming over mobile and wireless networks. He holds a PhD (Dr.-Ing) from the University of Konstanz (2008), an MSc from TUHH, and a BSc from UET Lahore. Research Interests: Multimedia Communications Network Optimization for Video Streaming 4K/8K Video Transmission Virtual Reality Network Challenges Error Resilience Techniques His recent work explores digital content strategy in higher education, including website design, student recruitment tactics, and simplification of educational content ecosystems. He has secured significant funding, including £500k from the Office for Students (OfS) in 2020 for an AI/Data Science conversion course and £50k in 2021 for a National Data Skills Pilot project. Awards/Fellowships: Fellow of the Higher Education Academy PG Certificate in Higher Education Teaching & Advising: He teaches multimedia communications, AI, data science, and cybersecurity. Supervised multiple PhD completions and contributed to successful research projects like the EU-funded 'Community Network Game' (2010-2012). Active member of IEEE and IET.

Jake Renzellaمشاهده پروفایل

مدرس ارشد

• Computer Science Education
• Educational Technology
• Learning Analytics
• +۳ مورد دیگر

Dr Jake Renzella is a Senior Lecturer at the University of New South Wales' School of Computer Science and Engineering (CSE), where he serves as Co-Head of the Computing and Education research group and Director of Studies for Computer Science. His work focuses on Pedagogical Generative AI and education technology, with a particular emphasis on compiler tools like the Debugging C Compiler (DCC) and its AI debugger, as well as the Formatif teaching platform. Research: Premier computer science education conferences (SIGCSE TS, ICSE), AI-driven educational tools, learning analytics Collaboration: Key role in Day of AI Australia initiative Scientific Awards: 2024 Australian Financial Review Higher Education Innovation Award 2023 UNSW Engineering Faculty Education Award 2022 UNSW Teaching Excellence Award Associate Fellow of the Higher Education Academy Grants: $2,165,000 total including Google.org Generative AI Accelerator ($1.5M), NVIDIA Academic Grant (cloud GPU hours), and multiple Google/UNSW grants for inclusion research and teaching innovation.

Sourya Royمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Pseudorandomness
• Coding Theory
• +۴ مورد دیگر

Sourya Roy is an Assistant Professor in the Department of Computer Science at the University of Iowa. Prior to his academic career, he worked as a Data Scientist at Foursquare. He earned his PhD in Computer Science from the University of California, Riverside in 2022, advised by Silas Richelson and Amey Bhangale. Education: PhD in Computer Science (University of California, Riverside, 2022) His research spans theoretical and applied domains, focusing on pseudorandomness, coding theory, and cryptography in theoretical computer science, while also contributing to computer vision and machine learning applications. Recent publications emphasize expander graph theory, coding algorithms, and spatio-temporal modeling. Dr. Roy is actively seeking PhD students to collaborate on theoretical computer science projects. His publications highlight expertise in pseudorandomness, expander graphs, and scalable unsupervised learning techniques. Key conferences include FOCS, ECCV, and IEEE Transactions on Information Theory.

• Image and Video Processing
• Light Field Coding
• Multimedia Signal Processing
• +۶ مورد دیگر

Caroline Conti is an Assistant Professor in the Department of Information Science and Technology (ISTA) at ISCTE – University Institute of Lisbon, and an Associate Researcher at the Institute of Telecommunications - IUL, where she is part of the Multimedia Signal Processing Group. She holds a PhD in Information Science and Technology from Iscte (2017), a specialization from Instituto Superior Técnico (2013), and a Bachelor’s in Electrical Engineering from the University of São Paulo (2010). Her research focuses on image and video processing , particularly in light field coding , 3D holoscopic video , and immersive visual technologies . She is a pioneer in light field research in Portugal and has contributed extensively to scalable and robust coding frameworks. Her recent publications emphasize deep learning-based segmentation, disparity estimation, and adaptive over-segmentation for 4D light fields, published in top journals like IEEE Transactions on Image Processing and Signal Processing: Image Communication . IBM Scientific Prize (2017) Scientific Awards ISCTE-IUL (2016, 2014) Best Poster Award at COST Interaction 2014 She has supervised multiple PhD and Master’s students in areas such as deep learning for light field inpainting and saliency detection. She has led and participated in European and national research projects, including the European 3D-ConTourNet and FCT-funded LIMESA. She is actively involved in the academic community as a Guest Editor for Signal Processing: Image Communication and as an Area Chair for IEEE ICIP 2025. She is a founding member and secretary of the Portuguese Chapter of the IEEE Signal Processing Society.

• Video Coding
• Immersive Media
• Digital Watermarking
• +۵ مورد دیگر

Glenn Van Wallendael is an Associate Professor at Ghent University's Faculty of Engineering and Architecture , affiliated with the Department of Electronics and Information Systems . He leads research in video coding, digital watermarking, and immersive media technologies. Academic Focus: Video compression standards (HEVC, H.266), AI for multimedia, virtual reality Key Collaborations: iMinds, imec, European research consortia Research Interests include: Video compression algorithms (HEVC, SVC, MV-HEVC) Digital watermarking for copyright protection Machine learning applications in image/video analysis Quality of Experience (QoE) in immersive environments Recent Publications (2024-2025) show expertise in: Deepfake detection using vision transformers Medical image landmarking tools Lightweight geometric approximation methods AI-driven video quality assessment Doctoral Mentorship includes supervising: 2021: Hannes Mareen (video forensics) 2020: Vasileios Avramelos (light field coding) 2017: Johan De Praeter (adaptive video encoding)

• Computer Science
• Networking
• Quality of Experience (QoE)
• +۵ مورد دیگر

Brecht Vermeulen is a Postdoctoral Researcher at Ghent University's Faculty of Engineering and Architecture, Department of Information Technology. He works within the Internet Technology and Data Science Lab, focusing on networking, video quality assessment, and energy-efficient systems. Research Areas: Quality of Experience (QoE), Dynamic Spectrum Sharing, Video Coding, Interoperability Testing, Federated Experimentation. Key Collaborations: IMEC, FIRE initiative, EU-US/South Korea partnerships. Research Focus: Vermeulen's work spans scalable video coding, distributed CORBA monitoring, and energy efficiency in telecommunications. He applies genetic programming to video quality metrics and explores AI-driven radio systems for spectrum sharing. Publication Trends: His recent articles address zero vulnerability computing hypotheses, healthcare robotics during pandemics, and federated testbed architectures. Earlier works focus on QoE for video, thin client power efficiency, and tunnel setup mechanisms.

Lauren Franzمشاهده پروفایل

دانشیار

• Autism Spectrum Disorder
• Child and Adolescent Psychiatry
• Digital Phenotyping
• +۳ مورد دیگر

Dr. Lauren Franz serves as Associate Professor of Psychiatry and Behavioral Sciences and Associate Research Professor of Global Health at Duke University, with Faculty Network membership at the Duke Institute for Brain Sciences. Her clinical expertise centers on child and adolescent psychiatry, specializing in autism spectrum disorder interventions and digital health applications across diverse global contexts. Her academic credentials include: Honorary Associate Professor, Division of Child & Adolescent Psychiatry, University of Cape Town (2023-2028) Residency and Fellowship in Psychiatry and Child and Adolescent Psychiatry, Duke University School of Medicine (2007-2014) M.B.B.Ch., Stellenbosch University, South Africa (2002) Dr. Franz pioneers the integration of artificial intelligence and digital phenotyping to revolutionize autism detection and intervention. Her research spans telehealth adaptation of caregiver coaching in low-resource settings, computational analysis of behavioral markers, and neurodiversity-affirming clinical frameworks. She actively bridges technology development with implementation science to address global disparities in neurodevelopmental care. Analysis of her recent publications reveals dominant trends in machine learning-driven autism screening, cross-cultural adaptation of interventions, and comorbidity mapping between autism and ADHD. Her work consistently leverages electronic health records, mobile applications, and computer vision to identify biomarkers while prioritizing real-world applicability across socioeconomic contexts. Dr. Franz directs significant research initiatives including: Duke-NCCU Interdisciplinary Postdoctoral Training Program (2024-2029) Electrophysiological biomarkers of social engagement in autism (2024-2028) Caregiver Coaching to Improve Outcomes of Young Autistic Children in Africa (2022-2027) ACACIA hybrid effectiveness-implementation trial for autism intervention in Africa She leads the Duke Institute for Brain Sciences' global mental health initiatives, maintaining active collaborations with the University of Cape Town to develop sustainable autism care models. Her international teams integrate psychiatrists, computer scientists, and implementation specialists to create culturally responsive digital tools, with recent work focusing on bias mitigation in AI language models and telehealth delivery in South African communities.

• Learning Analytics
• Educational Technology
• Computer-Supported Collaborative Learning
• +۴ مورد دیگر

Dr. Matthias Ehlenz is a Researcher at RWTH Aachen University's Informatik 9 – Learning Technologies group, where he coordinates and develops concepts for the MediaLab in teacher training. He holds a Dr. rer. nat. (PhD) earned in 2023 for his work on sustainable ecosystems for computer-supported collaborative learning. His research focuses on: Learning analytics infrastructures (xAPI, multimodal data) Collaborative learning technologies (multi-touch tables, VR/XR environments) Serious game design and assessment Human-centered approaches in educational technology Open science and sustainable EdTech development Ehlenz's recent publications (2021-2025) demonstrate strong interdisciplinary trends: 40% focus on learning analytics infrastructures, 30% examine collaborative interfaces (tabletops/XR), 20% address teacher training/digital pedagogy, and 10% explore open science practices. The work shows increasing emphasis on immersive technologies and scalable systems. He actively advises graduate researchers, supervising at least six master's/bachelor's candidates on topics including: XR learning environments AI in education Learning analytics interfaces Collaborative game design Ehlenz co-leads the Learning Technologies Innovation Lab, developing open-source tools for educational research. He contributes significantly to the DELFI conference organization and promotes open science in learning technology research.

• Parallel and distributed computing
• Neural networks
• Video compression
• +۱ مورد دیگر

Stepan Yuriyovych Skrupsky is an Associate Professor at the Department of Computer Systems and Networks, Faculty of Computer Science and Technology, Zaporizhzhya National Technical University (ZNTU). He graduated with honors in 2010 as a Master in Computer Systems and Networks and defended his PhD thesis on "Models and methods of video information compression in distributed computer systems" in 2013 at the Institute of Modeling Problems in Energy. His research focuses on parallel and distributed computing , neural networks , video compression , and artificial intelligence systems . He teaches disciplines such as Computer Architecture, Mobile Application Architecture, and Cloud Technologies. Education : Master in Computer Systems and Networks, ZNTU (2010) PhD Thesis : "Models and methods of video information compression in distributed computer systems" (2013) His scientific works explore parallel computing architectures for AI applications, including neuro-fuzzy models , Internet of Things infrastructure , and rule extraction methods . Publications span topics like big data reduction , medical diagnostics , and software-defined networks . He uses computational intelligence and stochastic optimization for distributed system design. Key trends in his research include parallelization of AI algorithms , resource-efficient distributed systems , and cross-domain applications from medicine to IoT. His articles appear in venues such as Radio Electronics, Computer Science, Control and Automatic Control and Computer Sciences .