Translator created with reasoning=True. Now call run() with:
old code · x or self.x · Lara receivesTrue
fixed · x if x is not None else self.xFalse
ls ~/projects
II.Systems I built: half model, half infrastructure
All team projects: each card says the team size and what I personally built. SHIKRA and ShadowCat came from my Smart India Hackathon 2026 team of 6, which I led; the case studies cover both the ML and the systems side, with baselines and live demos.
~/sih2026/shikra · SIH26249 (Ministry of Defence) · team of 6 · team lead
SHIKRAPredicting engine removals for a 54-aircraft fleet
ML11.64RMSE on FD001 vs 18.45 (Babu 2016 CNN); 81% coverage of 80% bands
My part: most of the React + TypeScript investigation console, the Flask API and event processing (app.py, analyzer.py, processor.py), the ML dataset builder and model registry, and the API and architecture docs.
ML3-way fusionbehaviour 45% · sequence 30% · Random Forest 25%, scaled by operational context
Systems47 testslive detection plane + analyst-feedback learning plane with gated promotion and rollback
~/projects/minierp · Odoo x KAHE Hackathon finalist · team of 2 · Jun 2026
Mini ERP14 business modules in one Django codebase
My part: inventory, purchasing and procurement with Celery background tasks, the audit log via Django signals, and the local-LLM voice assistant API. Teammate Jarshin J S built accounts, manufacturing, blockchain, foreign trade and delivery.
Jul 2026 · Aerothon 2026 (HAL x IIT Indore) · team of 2
HoloTwin
Physics-informed digital twin of a single-spool turbojet. My part: the PINN surrogate in PyTorch, with pressure-monotonicity and power-balance constraints in the loss, exported to ONNX and compared against a Random Forest baseline.
Aug 2026 · Murf AI "10 Days of Voice Agents for Bharat"
ASHA health voice agent
Built on Murf's voice-agent starter: a multilingual assistant for community health workers with consent-based memory, primary health centre lookup, district health alerts, outbound phone calls over LiveKit SIP, human fallback and a live dashboard.
Both run in your browser on real outputs: the first replays SHIKRA's committed model predictions, the second computes real SHA-256 hashes.
i.
Predict an engine's life
SHIKRA
A held-out engine the model never trained or calibrated on. Drag through its life: the band is the conformal 80% interval, and SHIKRA advises removal once the pessimistic edge (q10) reaches R* = 5 cycles.
A registered model, a forecast it made, and the report that cites it. Each entry stores the SHA-256 hash of the one before. Lower the forecast's probability, as someone hiding a missed alert might, and every later entry stops verifying.
A detailed review: how a common Python idiom silently ignored reasoning=False, the root cause, the fix and its regression test, the edge cases it leaves open, and a checklist for any codebase.
cat experience.log
V.Experience
Aug – Oct 2026
Team lead, Smart India Hackathon 2026 · team NOT TODAY, HACKERS (6 members)
Led one team through two problem statements in parallel, SHIKRA (SIH26249) and ShadowCat (SIH26153), splitting the work into data, ML, backend and front-end tracks and reviewing every merge.
Personally built the remaining-life model, data ingestion and audit logs on SHIKRA, and the ingestion and cryptographic audit chain on ShadowCat.
Both projects were shortlisted at the college level and submitted for the national level.