Systems and open-source engineer focused on AI agent runtimes, machine learning infrastructure, privacy engineering, and high-performance data query engines. Contributor to open-source ecosystems including Apache DataFusion, Hugging Face, Lightning AI, and AI agent infrastructure projects.

• apache/datafusion#26465 — fix(functions): pass correct number_rows in gcd benchmarks (MERGED)
  
  • Problem: In the Apache DataFusion scalar SIMD mathematical benchmark harness (datafusion/functions/benches/gcd.rs), array fixture construction passed mismatched row count arguments, corrupting greatest common divisor throughput measurements.
  • Implementation: Corrected parameter plumbing in the criterion benchmark harness to propagate exact configured row counts across all benchmark matrices. Merged upstream by PMC Chair Andrew Lamb on 2026-10-19.

• Shinraya-Tech-Labs/AgentWatch#753 — feat(contracts): implement sequence-gap detection and dynamic capture profile introspection (MERGED)
  
  • Problem: Telemetry contract evaluation misclassified network transport drops as contract violations (REFUTED) due to static counter heuristics.
  • Implementation: Built SequenceGap and SequenceContinuityTracker in agentwatch/contracts/coverage.py. Dynamically introspected telemetry sequence streams (sensor_id:seq), downgrading false refutations to INCONCLUSIVE during detected drop windows. Verified across 1,256 unit tests with 1%, 5%, and 20% simulated packet drop rates.
• Shinraya-Tech-Labs/AgentWatch#754 — feat(contracts): implement interval temporal logic and happens-before ordering (MERGED)
  
  • Problem: Telemetry evaluator lacked support for multi-agent concurrency and partial-order causal reasoning.
  • Implementation: Built a partial-order causal DAG engine and implemented Allen's Interval Algebra operators (meets, overlaps, during, starts, finishes) in agentwatch/contracts/temporal.py to formally verify concurrent multi-agent executions.
• Shinraya-Tech-Labs/AgentWatch#757 — feat(normalizers): implement OTel GenAI v2 and MCP protocol normalizers (MERGED)
  
  • Problem: Ingestion schema validation failed on emerging telemetry from OpenTelemetry GenAI semantic conventions v2 and Model Context Protocol (MCP / JSON-RPC 2.0) clients.
  • Implementation: Developed zero-dependency protocol normalizers in agentwatch/normalizers/ mapping OTel GenAI spans, token usage, tool invocations, and MCP JSON-RPC payloads into standard internal events.
• existence-master/Sentient#326 — fix(mcp): isolate OAuth credentials by server URL (MERGED)
  
  • Problem: Multi-server MCP configurations shared OAuth credentials across server instances due to a unified credential lookup key.
  • Implementation: Scoped OAuth token storage and refresh routines by normalized MCP server endpoint URL, preventing credentials from being inadvertently shared across server configurations.
• DivyashreeR008/Open-Agents#406 — test(recommendation): add automated scoring tests (MERGED)
  
  • Problem: Recommendation and task routing algorithms lacked regression test suites, risking silent ranking regressions during weight adjustments.
  • Implementation: Authored a 58-test regression harness (+799 LOC) testing mathematical properties: monotonic weight scaling, deterministic tie-breaking, empty pools, and boundary value inputs (0.0, 1.0).

• huggingface/diffusers#14961 — Fix active adapter detection for text encoders (MERGED)
  
  • Problem: Querying pipe.get_active_adapters() failed to detect active LoRA adapters when applied specifically to secondary text encoders (text_encoder_2) in SDXL and Flux pipelines.
  • Implementation: Extended adapter introspection across all registered text encoder submodules, aggregating active adapter names while gracefully bypassing non-PEFT modules.
• Lightning-AI/pytorch-lightning#22006 — fix: set sampler epoch before creating resumed iterator (OPEN — COMMUNITY VERIFIED)
  
  • Problem: In FitLoop, resumed training iterators were instantiated before the sampler epoch was updated, causing non-deterministic data sampling upon checkpoint resumption.
  • Implementation: Corrected execution order to update sampler epoch prior to creating the resumed data iterator. Verified across 12 worker-prefetch traces by community reviewer anishpentyala.
• Lightning-AI/pytorch-lightning#22017 — Improve error message for mixed strategy namespaces (OPEN — 11/11 CI GREEN)
  
  • Problem: Conflicting strategy configuration flags produced ambiguous exceptions during accelerator initialization.
  • Implementation: Enhanced diagnostic messaging in AcceleratorConnector to provide explicit namespace disambiguation and actionable resolution steps. Verified with 165 test cases passing.

• ThreeMoonsLab/agents-shipgate#1106 — fix(privacy): redact AWS path keys and URL-safe Basic credentials (OPEN — 13 PASSING, 1 SKIPPED)
  
  • Problem: AWS secret access keys inside URL/filesystem paths (path/<key>, s3://.../<key>) bypassed redaction due to / exclusion in regex lookarounds. Basic credentials using URL-safe Base64 (-, _) or unpadded strings caused false negatives or decoding crashes.
  • Implementation: Hardened regex lookarounds in src/agents_shipgate/core/privacy.py to permit path separators while preserving token entropy checks. Added RFC 4648 Base64 character normalization, safe repadding, and len % 4 == 1 rejection. Verified across 32 targeted regression tests; CI reports 13 passing jobs and 1 expected skipped job.
• ThreeMoonsLab/agents-shipgate#1105 — fix(host-grants): handle YAML timestamps in config hashing (OPEN — 13 PASSING, 1 SKIPPED)
  
  • Problem: Host grant configurations containing date or timestamp scalars crashed cryptographic hashing with TypeError: Object of type date is not JSON serializable.
  • Implementation: Implemented deterministic ISO 8601 formatting for date and datetime scalars in _canonical() within src/agents_shipgate/core/host_grants.py while strictly preserving secret redaction precedence. Balanced test partition runtime weights in tests/shard_seconds.json. Verified across 9 targeted regression tests; CI reports 13 passing jobs and 1 expected skipped job.
• ionfwsrijan/PatchPilot#354 — fix(findings): persist triaged status across page reloads (OPEN — CI GREEN)
  
  • Problem: Security findings triaged as accepted or ignored silently reset to open upon browser reload due to client-side hydration dropping backend state.
  • Implementation: Synchronized TypeScript contracts in api.ts and updated hydration mapping in frontend/src/app/lib/mappers.ts to preserve database status with "open" fallback. Added 217 LOC backend test suite and frontend unit tests.

Repository: Subodh-17/marine-pollution-intelligence
Autonomous satellite radar (SAR) oil spill segmentation, hydrodynamic drift hindcasting, and vessel attribution.

• SAR Oil Slick Segmentation: Implemented adaptive local Gaussian thresholding (detection.py:287) preceded by 7x7 Lee speckle filtering to suppress radar sea clutter while preserving dark slick boundaries.
• Hydrodynamic Drift Hindcasting: 2D Euler trajectory hindcasting model integrating surface wind shear (3% rule) and NOAA/HYCOM ocean current vectors (drift/model.py).
• AIS Vessel Attribution: Multi-factor attribution engine (scoring/attribution.py) computing spatial-temporal proximity, vessel type weights, speed anomalies, and draft variances.
• Inference Runtime: ONNX Runtime for optimized local model inference with SQLite/PostgreSQL metadata persistence.

SAR Imagery (Sentinel-1) ──> Lee Speckle Filter (7x7) ──> Adaptive Local Gaussian ──> Slick Polygons
                                                                                            │
AIS Vessel Feeds         ──> Speed / Proximity Anomaly ──> 2D Euler Drift Hindcast <────────┘
                                                                   │
                                                      Attribution Probability Score

Repository: Subodh-17/Predictive_Logistics_SIH_26251
Terrain- and weather-aware dynamic multi-modal freight routing and priority dispatching system.

• Dynamic Multi-Modal Routing: Terrain- and weather-aware graph traversal engine incorporating elevation gradients and severe weather penalties with an enforced 8 km/h speed floor (terrain.py).
• 7-Factor Priority Dispatching: Algorithmic queue weighting perishability, medical criticality, contract SLAs, transport costs, and route reliability (priority.py).
• Geospatial Storage: PostgreSQL with PostGIS extension and GeoAlchemy2 spatial queries (models.py). 483 automated unit/integration tests passing.

Consignment Orders ──> 7-Factor Priority Engine ──> Ranked Dispatch Queue
                             │
Weather / DEM Feeds ──> Elevation & Storm Penalties ──> Dynamic Graph Routing (A*)
                                                              │
                                                Constrained Path (>= 8 km/h Floor)

Repository: Subodh-17/stockvision-scilab-gui
Quantitative time-series modeling and walk-forward algorithmic trading backtester in pure Scilab.

• Algorithmic Quantitative Engine: Implemented in pure native Scilab (model_engine.sce).
• Time-Series Models: Ordinary Least Squares (OLS) polynomial trend fitting, Autoregressive AR(p) modeling, and Holt double exponential smoothing.
• Execution Simulation: Walk-forward backtesting engine incorporating realistic bid-ask slippage and transaction cost modeling.

Price & Volume Data ──> OLS Polynomial Trend ──> Residual Detrending
                                                        │
Execution Engine    <── Walk-Forward Backtester <── AR(p) + Holt Smoothing
(Slippage + Costs)

Repository: Subodh-17/Blueledger
Decentralized MRV (Measurement, Reporting, and Verification) registry for blue carbon credits.

• Smart Contract Layer: Solidity 0.8.20 credit registry contract (BlueCarbonRegistry.sol) with role-based access control (verifier, admin, registrar) and permanent certificate retirement mechanics.
• Web3 Integration: Ethers.js v6 for transactional signing, event listener subscriptions, and gas estimation.
• Decentralized Storage: IPFS integration (Kubo RPC & Pinata) for immutable audit evidence and satellite MRV proof pinning (storage.js).

Satellite / In-Situ MRV ──> IPFS Evidence Ingestion ──> Cryptographic Hash CID
                                                               │
Independent Verifier    ──> Role-Based Auditor Verification ──> Traceable Credit Issuance
                                                               │
                                                   On-Chain Retirement Event

Every technology, programming language, and framework listed below is verified by direct commits, PR diffs, or architecture implementations across my original systems and open-source work.

• GitHub Profile: @Subodh-17
• LinkedIn Profile: Subodh
• Instagram: @subodh17_
• Primary Contact: subodh171011@gmail.com
• Verification Statement: Linked upstream pull requests and cited merge commits can be independently verified through their respective repositories.