A HEAD FULL OF DREAMS
Jayin Khanna
I hold a BSc (Research) in Mathematics from Shiv Nadar Institution of Eminence (Batch Topper, 2026), and I'm concurrently completing an online BS in Data Science from IIT Madras.
I am currently working as a Project Associate at the Deep Representation Learning Lab, IISc (Dr. Prathosh A. P.)
My current research interests are in
- Generative models (Diffusion and Flow matching) — their applications and core theory.
- Interpretability, alignment & safety in LLMs
I am more interested in developing a theory of Deep Learning and understanding why methods work before scaling them. My current work is on safety alignment in text-to-image/video diffusion and trustworthiness repair in fine-tuned LLMs.
I'm looking for a long-term research project aimed at publication at ICLR, ICML, NeurIPS, or TMLR.
Publications
Kumar Shubham, Devendra Vyas, Vidushi Agarwal, Jayin Khanna, Prathosh AP. Repairing the Trustworthiness of Distilled Language Models. AI4GOOD Workshop @ NeurIPS 2026 [Under Review].
Current Research
Safety-guided flow matching for T2I/T2V diffusion — AI Institute of South Carolina (Dr. Amit Sheth, Dr. Amitava Das). Developing a safety-potential-guided rectified flow-matching formulation in CLIP embedding space to reduce harmful generations, benchmarked on the DETONATE dataset against TRCE, CURE, SAEUron, and DoCo.
Post-hoc trustworthiness repair in LLMs — Deep Representation Learning Lab, IISc (Dr. Prathosh A. P.). Combining EK-FAC curvature estimation with targeted gradient ascent to mitigate bias, unethical outputs, and toxicity in fine-tuned models — a compute-efficient alternative to retraining or RLHF, evaluated across Qwen2 and Pythia with submodular subset selection for non-redundant repair signals.
Education
- BSc (Research) in Mathematics — SNIoE, May 2026
Minor in CSE · Specialisations: AI & ML · Mathematical Finance - BS in Data Science & Applications — IIT Madras (ongoing)
Honours & Credits
- Program Batch Topper — SNIoE
- 2nd Prize, Best Thesis — SNIoE
- 238 credits across 4 years (176 SNIoE + 52 IIT Madras) — view course list
My Research Interests
- Core & applications of Generative Models (DDPMs, Flow Matching); T2I and T2V models
- AI Interpretability and Alignment
- Representation learning
- Unsupervised and self-supervised learning
Exploring and Self Reading
- Theory of Deep Learning (slow steady reading)
- Mechanistic Interpretability
- Geometric Deep Learning
My undergraduate thesis on generative models for unsupervised speech time-scale modification, under the joint supervision of Prof. Prasanta Kumar Ghosh (SPIRE Lab, IISc) and Prof. Niteesh Sahni (SNIoE), won 2nd Prize for Best UG Thesis. I document this work as detailed technical notes rather than leaving it in notebooks, posted on my Research page (DDPMs, VAEs, GANs, contrastive learning).
My prior research spans:
- Generative models for Unsupervised TSM (UG Thesis)
- Depth-Conditioned Video Generation using ControlNet & AnimateDiff
- Attribution/interpretability methods (IIT Kharagpur, Prof. Niloy Ganguly)
- Developing ML models for sEMG at DRDO-INMAS
- Statistical time-series modeling (UC Santa Cruz ISRP, Prof. Bruno Sansó)
- Summer research programs: MTTS 2024 and Polymath Jr. 2024, 2025
I love doing research! Check out my Academic Development & Projects.
My Experience
Research Assistant
Deep Representation Learning Lab, Indian Institute of Science (IISc), Bangalore
Supervisor:Dr. Prathosh A. P.
Period: Jun 2026 – Present
Working on enhancing trustworthiness in fine-tuned LLMs by implementing the EK-FAC preconditioned gradient ascent pipeline for post-hoc bias repair in Qwen2 and Pythia LLMs using Dolly for curvature estimation and CrowS-Pairs for targeted repair gradients.
Research Intern
IRT Group, AI Institute of South Carolina | DETONATE Group
Supervisor:Dr. Amit Sheth & Dr. Amitava Das
Period: Feb 2026 – Present
Working on safety alignment of Text-to-Image & T2V diffusion and flow matching models using a neurosymbolic approach called scene graphs.
Machine Learning Research Fellow
SPIRE Lab, Indian Institute of Science (IISc) Bangalore
Supervisor:Prof. Prasanta Kumar Ghosh
Period: Jul 2025 – Present (Summer Research Fellowship 2025)
Research on unsupervised speech TSM using Generative Models. Working with VAEs, GANs, Diffusion, and Flow Matching based speech TSM models to preserve speaker identity, naturalness and intelligibility.
Deep Learning Research Intern
Indian Institute of Technology (IIT) Kharagpur
Supervisor:Dr. Niloy Ganguly
Period: 2025
Worked on developing attribution techniques using Integrated gradients, Manifold IG, Guided IG towards neural network interpretability.
Machine Learning Research Intern
Institute of Nuclear Medicine and Allied Sciences-DRDO, Ministry of Defence
Supervisor:Dr. Shilpi Modi
Period: 2024
Developed a Convolutional Neural Network (CNN) ResNet model for classifying sEMG stress measurements, focusing on improving accuracy and generalization.
Machine Learning Research Intern
Institute of Nuclear Medicine and Allied Sciences-DRDO, Ministry of Defence
Supervisor:Dr. Shilpi Modi
Period: Present
Working on the application of network control theory to understand cognitive state transitions in the brain.
Statistics Research Intern
University of California Santa Cruz, CA (ISRP)
Supervisor:Prof. Bruno Sansó
Period: 2024
Conducted advanced research in Analysis of Time-Varying Quantiles for Environmental Variables, under the mentorship of Professor Dr. Bruno Sansó.
Machine Learning Intern
RightProfile by Syntellect
Period: Dec 2024 – Present
Part of the Research and Development team to develop Computer Vision and Deep Learning models to automate the annotation of 10,000+ raw images.
Machine Learning Intern
The Habitats Trust
Period: Dec 2024 – Present
Conducting research and development on modern Computer Vision and object detection models such as MegaDetector, Zamba, and Timelapse to classify and analyze wildlife in camera trap images.