Nabajeet Barman
PhD | MBA | MSc | B.Tech | FHEA | SM-IEEE
About Me
I am currently a Senior Research Scientist at Sony Interactive Entertainment (PlayStation) based in London, United Kingdom, where I work on (Visual) Anomaly Detection in Games using VLMs, Quality Assessment of AI-enhanced gaming content and encoding optimization of our cloud gaming application. Previously, I worked at Brightcove as a Principal Researcher on video quality metrics and encoding optimization. I obtained my PhD in Computer Science and MBA from Kingston University, my Master's in Information Technology (2014) from Universität Stuttgart, Germany, and a Bachelor of Technology (2011) in Electronics Engineering from the National Institute of Technology, Surat, India.
I am a Fellow of the Higher Education Academy and previously was a full-time Lecturer in Applied Computer Science at Kingston University, where I primarily taught Data Science related subjects to master and UG final year students. I am also a board member of the Video Quality Expert Group (VQEG) as part of CGI and ETG projects. My research interests include multimedia streaming and data science.
Experience
- Sony Interactive Entertainment – Senior Research Scientist (2023–Present)
- Brightcove Inc. – Principal Video Systems Engineer (2021–2023)
- Kingston University – Lecturer in Applied Computer (Data) Science (2020–2023)
- QoE-NET, Horizon 2020 – Marie-Curie Research Fellow (2015–2020)
Education
- PhD, Computer Science – Kingston University, London, United Kingdom
- MBA – Kingston University, London, United Kingdom
- MSc, IT – Universität Stuttgart, Germany
- B.Tech, Electronics – SVNIT Surat, India
Recent Publications
Quality Prediction of AI Generated Images and Videos
Ghildyal, Chen, Zadtootaghaj, Barman, Bovik (2024) – arXiv. Discusses challenges and future directions in AI-generated content quality assessment.
Bjøntegaard Delta (BD): A Tutorial Overview
Barman, Martini, Reznik (2024) – Under Review in IEEE Access. Comprehensive tutorial on BD metrics in codec evaluations.
Quality Assessment of AI-Enhanced Content
Barman et al. (2025) – ACM MHV’25. Presents approaches for measuring and improving quality in low-level perceptual similarity.
More at Google Scholar
Skills
- VQA/IQA/QoE, Streaming, Codec Analysis, (Visual) Anomaly Detection
- Python, MATLAB, FFmpeg, Bash, TensorFlow
- LLMs, VLMs, Deep Learning, CNNs, Data Science, Statistics
- Standardization, Research Writing
Contact
Email: nabajeetbarman4@gmail.com
LinkedIn: Profile
GitHub: NabajeetBarman