I am a Final Year B.Tech Computer Science student at Jaypee Institute of Information Technology, Noida. I specialize in Compiler Engineering, High-Performance Computing (HPC), and Scientific Software Architecture.

I contribute to the C++ cores of industry-standard scientific frameworks:

• Clad (Cern) (Auto-Differentiation Compiler):

  • Focus: Compiler Plugins & Symbolic Math.
  • Win: Implemented symbolic derivatives for C++17 Elliptic Integrals (std::comp_ellint_1) in BuiltinDerivatives.h, enabling exact gradients over slow numerical fallbacks (PR #1674).
  • Systems: Reverse-engineered CMake build scripts to patch shell expansion failures for local builds.

• SU2 Foundation (CFD Solver):

  • Architecture: Prototyping Dynamic Weight Injection (MLPCpp refactoring) to enable real-time Neural Network updates during MPI-parallel simulations.
  • Contribution: Author of the Hybrid PyTorch-SU2 Coupling workflow.
  • PRs: Implemented the "Read-Only" Physics-ML tutorial and documentation (PRs #71, #189).

• Brian2 Simulator (Spiking NNs):

  • Optimization: Implemented compilation overrides to decouple synapse generation from the global build target.
  • Impact: Reduced interactive development latency by ~99% (20s → <1s) for Windows/MSVC users (PR #1744).

• Math: Implemented analytical pullbacks for Elliptic Integrals: $\frac{dK}{dk} = \frac{E(k) - (1-k^2)K(k)}{k(1-k^2)}$.
• Research: Author of "Dynamic Memory Graph Modeling with Quantum Feature Encoding" (Accepted at ICAICS 2025).
• Startup: Building a Stealth AI/ML MVP (Full Stack).

• Compiler & Core: C++17 (STL, Templates), CMake, Ninja, LLVM/Clang Logic.
• Scientific: PyTorch, Clad (Auto-Diff), MPI, NumPy.
• DevOps: Docker, GitHub Actions, Linux/WSL.

• B.Tech in Computer Science & Engineering (2022 - 2026)
  • Jaypee Institute of Information Technology, Noida

I believe in "Brutally Honest" engineering: whether it's patching a CMake build or deriving a C++17 math formula, I fix the root cause, not just the symptom.