Education

• Ph.D in Computer Science, Arizona State University, 2028 (expected)
• M.S. in Computer Science (Big Data Systems), Arizona State University, 2024
• B.E. in Computer Engineering, Netaji Subhas Institute of Technology (now NSUT), 2018

Research & Work Experience

• Graduate Research Assistant, Arizona State University — May 2023 – Dec 2023
  • Designed an automated QA/QC pipeline reducing noisy downstream data by ~90%.
  • Developed semantic segmentation models for crop phenotyping and benchmarked depth-estimation models in outdoor environments.
• Research Intern, Carnegie Mellon University (remote) — Feb 2021 – Sep 2021
  • Benchmarked image manipulation methods using latent-space perturbations.
  • Reduced training time by ~70% via efficient sampling strategies.
• Other projects & competitions
  • DARPA AI for Critical Mineral Assessment 2022 — 8th in map feature extraction challenge.
  • Smart India Hackathon 2020 — National winner (real-time eye-gaze correction for video conferencing).

Teaching

• Teaching Assistant, CSE 475: Foundations of ML — Spring 2026
• Teaching Assistant, CSE 475: Foundations of ML — Fall 2024
• Teaching Assistant, CSE 579: Intro to ML for Remote Sensing — Spring 2024
• Grader, CSE 475: Foundations of ML — Fall 2023
• Grader, CSE 572: Data Mining — Spring 2023

Skills

• Languages: Python, C++
• Machine Learning / Frameworks: PyTorch, TensorFlow / Keras, Hugging Face, scikit-learn, OpenCV
• Data & Analysis: Pandas, NumPy, Matplotlib
• Web / Tools: Flask, Selenium
• Systems & DevOps: Git, Linux, Docker

Publications

A Woman with a Knife or A Knife with a Woman? Measuring Directional Bias Amplification in Image Captions

Nair, R., Tokas, B., & Kerner, H. (2026). A Woman with a Knife or A Knife with a Woman? Measuring Directional Bias Amplification in Image Captions. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (pp. 255-264).

DPA: A one-stop metric to measure bias amplification in classification datasets

Bhanu Tokas, Rahul Nair, & Hannah Kerner (2025). DPA: A one-stop metric to measure bias amplification in classification datasets. In The Thirty-ninth Annual Conference on Neural Information Processing Systems.

Classification Drives Geographic Bias in Street Scene Segmentation

Nair, R., Tokas, B., Tseng, G., Rolf, E., & Kerner, H. (2025). Classification Drives Geographic Bias in Street Scene Segmentation. In Proceedings of the Computer Vision and Pattern Recognition Conference (pp. 629–638).

Helmets Labeling Crops: Kenya Crop Type Dataset Created via Helmet-Mounted Cameras and Deep Learning

Nakalembe, C., Zvonkov, I., Kerner, H., Frimpong, D., Mwangi, K., Kioko, J., Tokas, B., Jawanjal, K., Smith, I., Paliyam, A., & others (2025). Helmets Labeling Crops: Kenya Crop Type Dataset Created via Helmet-Mounted Cameras and Deep Learning. Scientific Data, 12(1), 1496.

HEVC based tampered video database development for forensic investigation

Singla, N., Singh, J., Nagpal, S., & Tokas, B. (2023). HEVC based tampered video database development for forensic investigation. Multimedia Tools and Applications, 1–34.