ML Researcher · NIT Kurukshetra · Class of 2027
I work on state-space models, hyperspectral vision, and efficient sequence modeling — building systems that are both mathematically principled and practically deployable on real hardware.
Currently collaborating with two universities across continents, interning at a startup, and building my own company.
About me
I'm a second-year undergraduate at NIT Kurukshetra working on applied machine learning research. My interests are efficiency and robustness — I believe in models that are surgically precise, ones that understand underlying structure rather than memorize surface statistics.
This philosophy drives everything from LightMedSeg (3D medical segmentation in 0.48M params) to SCAF (hyperspectral classification via optimal transport). I'm interested in work where mathematical elegance translates to practical performance.
Beyond research I'm building Reflara, an execution-intelligence platform for autonomous AI agents, and shipping agentic pipelines at Qten.ai. I've contributed 25+ merged pull requests to Lightning AI and OpenCV. I'm also an Operations Team Member at SIGPLAN-M, organizing international mentoring for programming languages researchers.
Research experience
Efficient, robust models that work on real hardware under real constraints. Each project approaches the same core challenge from a different angle.
Sapienza University of Rome · May 2026 – Present · with Paulo Russo
Proposed AbSpec-Mamba and VolMamba v2 — models that condition selective state transitions on per-pixel material abundance, using prototype-guided reconstruction to recover fine spectral detail without hallucinating physically implausible spectral signatures.
Building content-adaptive multidimensional scanning and progressive coarse-to-fine reconstruction so the model restores high-resolution hyperspectral images under severe sensor degradation and spectral corruption.
University of Tübingen · Sep 2025 – Present · with Andreas Zeigler
Formally characterized how leading event-vision GNNs (AEGNN, SlideGCN, Voxel-GNN, HUGNet2+PA) leak future information backward in time, violating the causality required for true real-time inference on event-camera streams.
Designing CE-GNN to enforce strict causal constraints via O(k log N) incremental graph construction, directed temporal attention, and predictive edge insertion. Manuscript in preparation.
IIT Ropar · May – Aug 2025 · with Dr. Puneet Goyal
Identified that standard HSI pipelines discard recoverable inter-band correlation by treating bands independently. Recovered this signal using differentiable optimal-transport grouping with balanced Sinkhorn assignments.
Per-group Mamba processors isolate sensor noise to individual groups, converting spectral redundancy into a graceful-degradation mechanism — achieving +11.6% accuracy under 20–30% band dropout against Transformer baselines.
NIT Kurukshetra · Sep 2024 – May 2025 · with Dr. Vishwas Rathi & Dr. Shweta Sharma
Built parameter-efficient 3D segmentation models targeting deployability on memory-constrained hardware, work that became LightMedSeg and RefineFormer3D. Concurrently developed hybrid frameworks for ransomware detection combining static binary features with NLP-based code representations, leading to the ICDAM 2025 paper.
What I'm building
Research is one side. The other is building things people actually use.
Founder & AI Systems Engineer · Ongoing
A replay-native execution-intelligence platform for autonomous AI agents. Multi-agent systems are often black boxes — once something breaks, you can't go back. Reflara fixes that by deterministically recording and re-running agent trajectories, reconstructing orchestration state, retrieval influence, and memory evolution over time.
View on GitHub →AI Engineer Intern · May 2026 – Present
Building agentic orchestration for grounded conversational content generation at scale. Multi-layer pipelines that verify every claim against retrieved evidence and self-repair low-quality output.
Selected project · Jan 2026 – Present
Replaced fixed routing temperature with a regret-driven adaptive controller, letting the model tune its own exploration vs. exploitation as conditions shift.
Publications & preprints
LightMedSeg: Lightweight 3D Medical Image Segmentation with Learned Spatial Anchors
84.8% Dice on BraTS · 93.5% on ACDC · 0.48M parameters · 14 GFLOPs. Parameter-efficient 3D segmentation for memory-constrained clinical hardware with strong label efficiency.
SCAF: Robust Hyperspectral Classification via Optimal Transport-Based Spectral Grouping
Differentiable optimal-transport grouping with balanced Sinkhorn assignments. Mamba backbone cuts complexity from quadratic to linear. +11.6% accuracy under band dropout.
RefineFormer3D: Hierarchical Multi-Scale Transformer for Parameter-Efficient 3D Medical Segmentation
86% Dice on BraTS 2017 · Outperforms SegFormer3D in efficiency and label efficiency for low-annotation settings.
Ghidra-Assisted Static Analysis and Ensemble Learning with Differential-Privacy GANs for Ransomware Detection
Hybrid framework combining static binary features with NLP-based code representations and differential-privacy GANs.
Open source
Not just forks. Actual merged work reviewed and adopted by core maintainers.
Improved model compilation pipelines, fixed argument parsing edge-cases across training configurations, and hardened training stability under distributed settings. Changes reviewed and adopted by core maintainers.
Targeted bug fixes and API robustness improvements across core computer-vision pipelines. Hardened edge-case handling in critical image processing routines used by thousands of applications.
Technical skills
State Space Models (Mamba, S6) · Causal & Event-Based GNNs · Hyperspectral Classification · 3D Medical Segmentation · Parameter-Efficient Vision Transformers · Optimal Transport
PyTorch (AMP, custom modules) · PyTorch Lightning · TensorFlow · Keras · Scikit-learn
OpenCV · NiBabel · TorchIO · Albumentations · NumPy · Pandas · Matplotlib
Git · Docker · CUDA · Google Cloud Platform · Linux · Ghidra (Jython) · Jupyter
Python · C++ · SQL · LaTeX · Jython
Get in touch
I'm always interested in conversations about research, collaborations, or ideas worth pursuing. Drop me a message — I read everything.