About
I am a Senior Research Scientist at Sony Interactive Entertainment (PlayStation) in London, part of the Gaming, Developer & Future Technology (GDFT) team. My work focuses on visual anomaly and glitch detection in games using Vision Language Models (VLMs), image and video quality assessment for AI-enhanced gaming content, Qualit of Experience modelling and encoding optimization for cloud gaming applications.
Previously, I was a Principal Video Systems Engineer (Research) at Brightcove, working on encoding optimization and advanced quality metrics for video streaming, and a Lecturer in Applied Computer Science at Kingston University, where I taught data science to postgraduate and final-year undergraduate students. I began my research career as a Marie Skłodowska-Curie Fellow on the EU Horizon 2020 QoE-Net project, with research visits to Deutsche Telekom / TU Berlin and Yonsei University, and earlier research positions at Nokia Bell Labs.
I am a Fellow of the Higher Education Academy (FHEA), a Senior Member of IEEE, and a board member of the Video Quality Experts Group (VQEG), where I co-chair activities in the Computer Generated Imagery (CGI) and Emerging Technologies (ETG) groups. I hold a PhD in Computer Science and an MBA from Kingston University, an MSc in Information Technology from the University of Stuttgart, and a B.Tech in Electronics Engineering from NIT Surat.
Experience
Senior Research Scientist · Sony Interactive Entertainment (PlayStation)
London, United Kingdom
Research on quality assessment of AI-enhanced gaming content, AI-driven game bug/glitch detection for automated QA, and encoding optimization for cloud gaming. Contributed 21 filed patents, in-house VQA/QoE models, and academic collaborations, challenges, and publications at major venues (NeurIPS, CVPR, ECCV, WACV, ICASSP, ICIP).
Principal Video Systems Engineer, Research · Brightcove
London, United Kingdom
Encoding optimization and advanced quality metrics for streaming: parametric quality models for multiscreen delivery, optimal rendition selection for web players, context-aware encoding, and open-source QoE datasets — resulting in nine publications.
Lecturer, then Adjunct Lecturer in Applied Computer Science · Kingston University
London, United Kingdom
Led and taught Applied Data Programming (MSc) and Computing Fundamentals (UG): statistics, data analysis, machine learning, and data structures & algorithms. Research on UGC quality assessment, deepfakes, and blockchain in media.
Marie Skłodowska-Curie Fellow & Postdoctoral Researcher · Kingston University
London, United Kingdom (EU Horizon 2020 QoE-Net)
PhD and postdoctoral research on QoE of video streaming services (Netflix, YouTube, Twitch): codec comparison, subjective/objective quality assessment, gaming video datasets, and ML-based quality metrics.
Visiting Researcher · Deutsche Telekom (TU Berlin) & Yonsei University
Berlin, Germany · Seoul, South Korea
Quality assessment and standardization for passive and cloud gaming services (Quality & Usability Lab, TU Berlin); comparative quality assessment of gaming content (Multi-dimensional Insight Lab, Yonsei).
Research Assistant · Nokia Bell Labs
Stuttgart, Germany
Master's thesis and internship on wireless link quality prediction for vehicular users and context-aware resource allocation in cellular networks.
Education
PhD, Computer Science
Kingston University, London · 2016–2019
MBA
Kingston University, London · 2018–2019
MSc, Information Technology
University of Stuttgart, Germany · 2011–2014
B.Tech, Electronics Engineering
NIT Surat, India · 2007–2011
Publications
Selected from 60+ publications · Full list on Google Scholar
Recent Highlights
VideoGameQA-Bench: Evaluating Vision-Language Models for Video Game Quality Assurance
Taesiri, Ghildyal, Zadtootaghaj, Barman, Bezemer — NeurIPS, 2025
Quality Assessment of AI-Generated and AI-Enhanced Content: Challenges and Opportunities
Ghildyal, Chen, Zadtootaghaj, Barman, Bovik — ACM Mile-High Video (MHV), 2025
Foundation Models Boost Low-Level Perceptual Similarity Metrics
Ghildyal, Barman, Zadtootaghaj — IEEE ICASSP, 2025
LAR-IQA: A Lightweight, Accurate, and Robust No-Reference Image Quality Assessment Model
Avanaki, Ghildyal, Barman, Zadtootaghaj — ECCV Workshops, 2024
Quality Prediction of AI-Generated Images and Videos: Emerging Trends and Opportunities
Ghildyal, Chen, Zadtootaghaj, Barman, Bovik — arXiv, 2024
Bjøntegaard Delta (BD): A Tutorial Overview of the Metric, Evolution, Challenges, and Recommendations
Barman, Martini, Reznik — arXiv, 2024
Most Cited
QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey
Barakabitze, Barman, Ahmad, Zadtootaghaj, Sun, Martini, et al. — IEEE Communications Surveys & Tutorials, 2019 · 309 citations
QoE Modeling for HTTP Adaptive Video Streaming: A Survey and Open Challenges
Barman, Martini — IEEE Access, 2019 · 246 citations
No-Reference Video Quality Estimation Based on Machine Learning for Passive Gaming Video Streaming
Barman, Jammeh, Ghorashi, Martini — IEEE Access, 2019 · 96 citations
GamingVideoSET: A Dataset for Gaming Video Streaming Applications
Barman, Zadtootaghaj, Schmidt, Martini, Möller — NetGames, 2018 · 96 citations
User-Generated HDR Gaming Video Streaming: Dataset, Codec Comparison, and Challenges
Barman, Martini — IEEE Transactions on Circuits and Systems for Video Technology, 2021 · 36 citations
H.264/AVC, H.265/HEVC and VP9 Codec Comparison for Live Gaming Video Streaming
Barman, Martini — QoMEX, 2017 · 60 citations
Patents: 21 patents filed (US applications) in video streaming, gameplay video encoding, visual quality assessment, and game anomaly detection.
Awards & Service
- Best Paper Award — ACM MMSys NetGames, 2018
- Brightcove Research Recognition Award
- Marie Skłodowska-Curie Fellowship — EU Horizon 2020 QoE-Net
- Fellow of the Higher Education Academy (FHEA)
- Senior Member, IEEE
- Board Member, Video Quality Experts Group (VQEG) — Computer Generated Imagery (CGI) & Emerging Technologies (ETG) groups
- Standardization contributor — ITU-T Study Group 12 (gaming QoE, P.BBQCG, G.OMG)
- Challenge organizer & reviewer — AIS (CVPR) and AIM (ECCV) quality assessment challenges; reviewer for IEEE journals
Skills
Research
VQA / IQA / QoE · Subjective & objective quality assessment · Codec analysis & comparison · Visual anomaly detection · Dataset design
AI & ML
LLMs · VLMs / LMMs · Deep learning · CNNs · Pytorch · Data science & statistics
Tools
Python · MATLAB · FFmpeg · Bash · LaTeX
Professional
Standardization (ITU-T/MPEG, BSI, VQEG) · Research writing & publishing · Teaching & supervision · Industry–academic collaboration
Contact
Email: nabajeetbarman4@gmail.com
LinkedIn: linkedin.com/in/nabajeetbarman
GitHub: github.com/NabajeetBarman
Google Scholar: Profile