Assistant Professor

Dr Syed Sameen Ahmad Rizvi

Department of Computer Science and Engineering

Interests

  • Affective Computing
  • Image Enhancement (Super-resolution, Image Refinement)
  • Fairness in AI Systems

Education

2019

Jamia Hamdard
India
B.Tech. CSE

2025

Birla Institute of Technology & Science, Pilani.
India
Ph.D.

Experience

  • February to March 2025- Research Scientist | Computer Age Management Services (CAMS)
  • 2020 to 2024- Teaching Assistant | Birla Institute of Technology & Science

Research Interest

  • Dr Rizvi’s research is centred around building intelligent, equitable, and practical AI systems with a focus on affective computing, image enhancement, and algorithmic fairness. His work integrates foundational methods in computer vision and deep learning with applications that are societally relevant and technologically impactful.
  • In affective computing, he develops models that can accurately perceive and interpret human emotional expressions, especially under real-world constraints such as low-resolution or noisy visual input. His contributions include large-scale dataset development (e.g., InFER, InFER++) and robust FER pipelines.
    In the domain of image enhancement, Dr Rizvi focuses on emotion-aware super-resolution and refinement techniques that improve visual quality while preserving semantic and affective cues—ensuring downstream tasks like emotion recognition remain reliable in practical deployments.
  • His work on fairness in AI systems is directed toward mitigating demographic and representational biases in facial analysis. Through techniques like latent alignment and fairness-aware learning, he aims to ensure that AI models perform equitably across diverse populations and do not propagate societal inequalities.

Publications

Journal Publications

  • Rizvi, S. S. A., Seth, A., & Narang, P. (2025). Balancing the Scales: Enhancing Fairness in Facial Emotion Recognition with Latent Alignment. International Conference on Pattern Recognition (ICPR), Springer, pp. 113–128. https://doi.org/10.1007/978-3-031-78354-8_8
  • Rizvi, S. S. A., Seth, A., Challa, J. S., & Narang, P. (2024). InFER++: Real-World Indian Facial Expression Dataset. IEEE Open Journal of the Computer Society, 406–417. https://doi.org/10.1109/OJCS.2024.3443511
  • Rizvi, S. S. A., Seth, A., & Narang, P. (2024). FAIR-FER: A Latent Alignment Approach for Mitigating Bias in Facial Expression Recognition. AAAI Conference on Artificial Intelligence, 38(21), 23633–23634. https://doi.org/10.1609/aaai.v38i21.30503
  • Rizvi, S. S. A., Agrawal, P., Challa, J. S., & Narang, P. (2023). InFER: A Multi-Ethnic Indian Facial Expression Recognition Dataset. 15th International Conference on Agents and Artificial Intelligence (ICAART), INSTICC. https://doi.org/10.5220/0011699400003393
  • Rizvi, S. S. A., Kumar, A., Rajput, A. S., & Narang, P. (2022). EraisNET: An Optical Flow based 3D ConvNET for Erasing Obstructions. IEEE TENCON 2022. https://doi.org/10.1109/TENCON55691.2022.9977584
  • Rizvi, S. S. A., Singh, U., & Narang, P. (2022). MFDN: Multiception Feature Distillation Network. IEEE TENCON 2022. https://doi.org/10.1109/TENCON55691.2022.9977652

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