This is a long virtual resume that contains everything I did since I chose Software Engineering, Applied Research and overall Product Building as a career for the time being. Might become a goose farmer later in life, who knows :)
Work Experience
Protocol Enginnering Grantee
Ethereum Foundation
Cooking with the EF Protocol Consensus Team on implementing the Fast Confirmation Rule in Lighthouse Consensus Client
Software Engineer Intern
Cloud-Native Computing Foundation
- Designed and implemented mTLS via HBONE tunneling for metrics endpoints in Istio's Ambient Mesh aligning with zero-trust principle. Became a Member of Istio's Networking Working Group upon the completion of the internship work.
- Implemented admin operations security controls in Thanos UI that restricts critical admin-level operations at both API and UI levels, improving production security posture for large-scale monitoring deployments - PR
- Added comprehensive network security policies for Kubernetes-deployed Thanos components using NetworkPolicy resources to establish network isolation and reduce attack surface in multi-tenant environments
- Developed dynamic, color-coded query result visualizations in the Thanos Query UI to enhance operational efficiency for monitoring teams analyzing distributed Prometheus time-series data.
Skills involved - Rust, Go, Typescript, React.js, Docker, Kubernetes, Helm, Prometheus, Grafana
Check out my blog on contributing to Istio to learn more.
Open Source Maintainer
Jenkins
Maintaining the Jenkins GitLab Plugin used by over 60,000+ developers worldwide
- Migrated the Jenkins GitLab Plugin from RESTEasy Library to GitLab4J-API with Reverse Proxy support
- Adapted the Docker Maven Plugin for GitLab4J-API library
- Improved the Docker-based test suite by Migrating 500+ Unit and Integration tests and improved overall code coverage
as a Google Summer of Code mentee
Mentoring Google Summer of Code contributors in Jenkins since 2024 for the development of a vertical self-learning multi-agent AI workflow to automate build failure diagnosis
Skills involved - Java, Python, Ngnix, Docker, LightRAG, Pydantic, MCP and A2A, list just goes on...
Open Source Contributor
uv
- Added support for GitLab as a trusted publisher, implementing secure OIDC token discovery to enable passwordless authentication with PyPI - PR
- Added CLI flag to display compressed package sizes aiding dependency analysis - PR
- Added authoritative constraint of local pin over global in the UV CLI, prioritizing project-scoped .python-version files over global user preferences when conflicts arise - PR
- Added a context-aware warning in CLI to help with conflicting VIRTUALENV - PR
Skills involved - Rust, Python
Software Engineer Intern - Summer of Bitcoin
Fedi
- Designed and Implemented the Escrow Module for the Fedimint ecosystem based on trustless and dispute-resistant private escrow scheme
- Upgraded the module template to support latest long term stable Fedimint protocol, while maintaining the backward compatibility, for easing the process of module creation for the Fedimint ecosystem
- Refactored the codebase for reducing redundant dependencies and improving maintainability and added some UI features.
Checkout my journey of contributing to Fedimint in my blog - Spent my Summers with Fedimint!
Skills involved - Rust, TypeScript, Docker, Prometheus, OpenTelemetry, WASM, Bitcoin, Lightening Network
Research Engineer Intern
Pragma
- Integrated Pragma oracle protocol with Polygon Miden, thus creating the first oracle on the Polygon Miden Network, in collaboration with Miden VM team at Polygon.
- Researched on Mysticeti-FPC and other DAG based consensus protocol along with Sparse Nodes in collaboration with Mysten Labs to reduce the latency of oracle data layer.
Skills involved - Rust, Python, BFT Consensus Algorithms, gRPC, pyO3, Prometheus, Grafana
Undergraduate Research and Projects :
Undergraduate Research
Advisors: Prof. Dibakar Ghosal and Subhajit Roy (Department of Earth Science & Computer Science)
Modelling of Forward and Inverse Waveform Inversions via Finite Basis Physics-Informed Neural Networks for Seismic Data Interpretation on an actual Supercomputer!
- Explored FBPINNs for subsurface modelling, solving 2D acoustic wave equations using JAX's JIT compilation for 2x performance improvements in neural network training and automatic differentiation, implementing domain decomposition with partition-of-unity windows and SIREN} architectures for tackling spectral bias during full waveform inversion
- Built numerical analysis toolkit including 4th-order finite difference methods, CPML absorbing boundary conditions, and analytical solutions for validation
- Implemented 6× spatial oversampling in CPML reference solver with nearest-neighbor decimation to preserve sharp circular wavefronts and eliminate numerical dispersion artifacts in ground-truth comparisons
- Reduced memory usage by 40 percent through chunked evaluation and adaptive sampling strategies
- Implemented various JAX optimization including XLA compilation caching, bfloat16 precision for matrix operations, and custom PRNG implementation (threefry2x32) for faster random number generation achieving significant performance gains
- Built monitoring system with real-time loss tracking, resource monitoring, and seismological visualization suite including wiggle plots, shot gathers, spatial/temporal slice comparisons, and error analysis plots for training progress analysis
Skills - Python, Linux, JAX
Undergraduate Project
Advisors: Prof. Arnab Bhattachrya (Department of Computer Science)
Working on a novel generative model to produce clinically accurate synthetic images across various medical
modalities and organs
- Developed a multi-modal text-to-image generative model for producing synthetic medical images across modalities using diffusion-based architectures with cross-attention mechanisms
- Engineered end-to-end training pipeline supporting image-text datasets with CSV-based data ingestion, BERT tokenization for multi-modal inputs, and U-Net architecture with progressive noise scheduling for diffusion model training
- Built two-stage RLHF pipeline to iteratively refine synthetic medical images utilizing a custom Vision Transformer model built with multi-head self-attention and dropout regularization, leveraging radiologist ratings to serve as an automated quality-assessment reward model
- Optimized Stable Diffusion fine-tuning with mixed precision (FP16/BF16), gradient checkpointing, cosine annealing learning rate scheduling, EMA model averaging, and SNR-weighted loss computation with gamma parameter for noise prediction training
- Achieved 40 percent memory reduction through 8-bit Adam optimization}, attention slicing, VAE tiling, and gradient accumulation
- Developed evaluation metrics including FID, Inception Score, SSIM, and custom medical quality metrics
- Implemented multi-GPU distributed training with Accelerate framework, automatic device detection and allocation, gradient synchronization across processes, checkpoint management with automatic resumption, mixed precision coordination, and batch size scaling
Skills - Python, PyTorch, Vision Transformers, Diffusion Models, Reinforcement Learning, Accelerate
Undergraduate Project
Advisor: Prof. Yatinder Nath Singh (Department of Electrical Engineering)
An asynchronous multidimensional in-memory non-persistent distributed hash table implementation based on Chord - Pikachu
- Engineered an asynchronous, in-memory distributed hash table with multi-dimensional keyspace support with an efficient Chord overlay network, including finger tables and recursive lookup logic, achieving average O(log N) hop count for key resolution
- Built a resilient routing maintenance subsystem with periodic stabilization, successor/predecessor checks, and finger-table repairs to ensure network consistency under churn
- Engineered connection-pooled gRPC layer with backpressure handling and bounded buffers, reducing con- nection churn and ensuring stable performance during high-volume key transfers
- Implemented robust server lifecycle management with readiness signalling, bounded startup timeouts, and graceful shutdown for clean drain of in-flight requests
- Introduced streaming handoff APIs for efficient ownership transfer of large key ranges during join/leave, reducing tail latencies and avoiding head-of-line blocking
Skills - Rust, gRPC, libp2p, Distributed Systems, Consistent Hashing
Undergraduate Project
Advisor: Prof. Adithya Vadapalli (Department of Computer Science)
A privacy-preserving discovery service. - Rumi
- Engineered a privacy-preserving contact discovery service using double-sided blinding over elliptic curves, a Path Obilivous RAM backend store, and zero-knowledge set-membership proofs to ensure the server learns nothing about queries, matches, or access patterns
- Built end-to-end blinding protocol using domain-separated hash-to-curve and compressed point encodings
- Designed prefix-based bucket selection paired with fixed dummy accesses and constant response shaping on top of Path ORAM for efficient server-side filtering while maintaining indistinguishability; tunable privacy/performance balance
- Benchmarked ORAM performance across read/write, sequential/random patterns, and variable payload sizes
- Hardened sensitive data handling with explicit secure wiping of ORAM blocks, stash, and internal buffers; minimized side-channels via fixed-size responses and uniform access paths
Skills - Rust, Cryptography