Sukrit Jindal
Joint Secretary, DSG IIT Roorkee
Education
- B.Tech, Data Science and Artificial Intelligence, IIT Roorkee (2022–2026)
- Minor in Computer Science Engineering
Research Interests
- Machine Learning and Deep Learning
- Machine Learning Security, Interpretability and Robustness
- Graph Neural Networks
- AI for Cybersecurity
Projects
- Diffusion Everything
Developed visual demonstrations of diffusion processes using 2D/3D datasets and implemented DDPM/DDIM sampling techniques. - PikaBot RL
Trained battle bots using reinforcement learning algorithms like DDQN for an online Pokémon battle simulator. - Steganography with GNNs
Proposed an improved universal deep hiding technique using graph neural networks over traditional CNNs. - Web-Based Saliency Demos Explore the interpretability offered by various saliency-map based models like IG, BlurIG and VG and their extensions (IDGI and SmoothGrad).
Publications
- Jindal, S., Bhardwaj, D., & Kumari, A. (2024). Rethinking Randomized Smoothing from the Perspective of Scalability. Third Workshop on New Frontiers in Adversarial Machine Learning (NeurIPS ‘24). (Co-Author)
- Mittal, A., Pandey, A., Tiwari, A., Jindal, S., & Swain, S. (2025). Revisiting CroPA: A Reproducibility Study and Enhancements for Cross-Prompt Adversarial Transferability in Vision-Language Models Under Review at TMLR 2025 (Co-Author)