Shreyash S. Bhatkar

Computer Engineer • Software Developer • AI/ML • Cloud-Native

We engineers are not solely computer scientists, philosophers, physicists, or analysts. We are a mosaic of our knowledge, applying what we know like painting with colors we have on our palette, to blend into one masterpiece. A solution.

A solution that reflects who we are.

I build reliable systems and applied ML solutions. Below are selected projects and a quick peek at my experience.

Portrait

Featured Projects

Selected work with outcomes & tech details.

Patent Project : Stun Shoe (Low-Power IoT Wearable for Women’s Safety)

  • Piezo-triboelectric energy harvesting ~10–50 mW/stride (bench-verified).
  • ARM-M0 + BLE board (32 kB) powering non-lethal actuator from EDLC + Li-Po hybrid stack.
  • Captured 40k+ footfall samples (FlexiForce + Data Logger) for training.
  • On-device RL (DQN/PPO) classifies routine vs high-risk; 93% F1; triggers only if risk > 0.8.
  • Indian Provisional Patent App. No. 2025/XXXXXX — filed Mar 2025 (full spec in preparation).

Real-time Cloud Performance Analytics & Optimization App

  • Python Flask (CORS) ingesting 8+ GB real-time logs; Spark MLlib predictive analytics.
  • +22% resource efficiency; downtime −15%; OJET + Node.js dashboard with −33% load time.
  • Deployed on Oracle Cloud (OKE) for scalability and performance.

Forest Fire Detection & Prediction via RCNN (Publication)

  • 10k+ images with OpenCV augmentation; custom RCNN in PyTorch achieving 97.3% mAP.
  • Novel “RTH Index” blending humidity, temperature & visual cues for stratification.
  • Kafka + Flink pipeline for real-time anomaly detection.

Real-time Bus Route Detection for the Visually Impaired

  • 6.5k+ images; SIFT/ORB yielding 500k+ descriptors; deep CNNs (ResNet).
  • UMAP/t-SNE for dimensionality reduction; custom Tesseract OCR for route numbers.
  • 93.5% accuracy with optimized feature extraction.

More Projects

A few more experiments & apps.

Performance Evaluation and Prediction Tool (PEP)

Evaluates product performance, predicts challenges, and highlights improvement areas with scenario forecasts.

Hybrid Emergency Audio Analyzer

Emergency audio interaction analysis and categorization.

CarBMI

DL study: carbohydrate intake vs. workout and physical performance.

R3ND3R

3D model rendering desktop app with Blender-authored supershapes (Python core).

eSKIMo

Text skimmer & labeling tool (TensorFlow + React).

CryptOpus

Web3 NFT/Crypto market interactions with a ledger of transactions.

BuRD

Bus Route Detector & Classifier for visually impaired users.

Black Box

UV sterilizer box with stepper-mounted absorbent; BT control via Arduino.

FireCart

Full shopping app: cart, checkout, and typed forms; transactions ready.

EmbedroW

t-SNE / UMAP / PCA projector for custom datasets (see demo in repo).

Spacebar (Coming Soon)

Self-learning shuttle that learns to land autonomously.

Motion DA

Browser-based motion capture driving a live animated character.

EdibleInsight

Food classification ML aiming to outperform DEEPFOOD (2016).

RollBall

Endless-runner game built with Pygame.

Publication & Patents

Forest Fire Detection and Prediction via RCNN (ICEPTP’22, Lisbon)

Custom RCNN (PyTorch), 10k+ images with OpenCV augmentation; 97.3% mAP; introduced ‘RTH Index’; Kafka + Flink streaming pipeline.

“Stun-Shoe” women’s-safety wearable – Indian Provisional Patent App. No. 2025/XXXXXX, filed Mar 2025 (full spec in preparation)

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Suggestions, feedback, or just say hi.

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