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I'm a Mechatronics Engineering student at the University of Waterloo interested in robotics, ML, learned motion, and the software that makes physical systems behave intelligently.

At this stage, I look to optimize for depth over breadth. The intersection of hardware and learned behavior is where I want to build, and I'm spending this window figuring out exactly how to get there.

Currently studying full-time while building foundations in systems programming and ML, with my sights set on robot learning and autonomous systems.

  • 01DisciplinesSoftware · Machine Learning · Robotics
  • 02StackC++ · Python · Pytorch · ROS2
  • 03Looking forSWE / Robotics ML/AI internships, Fall '26
  • 04Lovesautonomous systems · the art of a good meal · carnatic music (performing)
JAN 2026 - APR 2026

AI Software Engineer Intern

CGI Inc.

Trained a priority classifier on 280 ITSM tickets, tuning for weighted F1 and Critical ticket recall under 7% class imbalance Built duplicate detection via sentence embeddings and cosine similarity, calibrating threshold on 90 hand-labeled pairs to 0.86 precision Clustered 240 failure embeddings with DBSCAN, surfacing 3 actionable root causes for Foresters Financial Closed a data flywheel that improved ticket classification from 76% to 84% across retraining cycles

  • SKLEARN
  • DBSCAN
  • PYTHON
  • AZURE/AWS
01
JUL 2025 - AUG 2025

Cloud Engineering Intern

Avanade Canada

Architected a cloud-native AI accessibility platform across 8+ Azure services with a 6-person team Built an intelligent support chatbot covering 15+ disability categories with sentiment analysis and escalation routing Cut provisioning time by 30% with infrastructure as code and automated CI/CD pipelines

  • AZURE
  • DOCKER
  • PYTHON
  • GITHUB ACTIONS
02
OCT 2024 - MAR 2025

Controls Engineer

UWaterloo

Designed a mechanical airbrake system in SOLIDWORKS, validated via MATLAB flight simulation Built a custom PCB airbrake controller in KiCAD with signal processing to filter noisy telemetry during active flight

  • SOLIDWORKS
  • MATLAB
  • KICAD
  • C++
03
  1. 001
    2026

    Smart Pressure Sensing Insoles HACKPRINCETON SPRING ’26 FINALIST

    Clinical pressure mats cost $15,000. We built a directionally accurate version for $77 because our parents are diabetic and can't feel the pressure that destroys feet. Hand-soldered 10 FSR sensors, analog multiplexer, haptic motors, and transistor drivers onto an ESP32, streaming pressure data at 15Hz over BLE Derived clinical metrics — arch index, pronation, heel centering — computed locally on-device, interpreted by a Gemini-powered AI podiatrist Haptic alerts fire when sustained pressure exceeds threshold, running in background via CoreBluetooth

    Github
  2. 002
    APR 2026

    Natural Language  PCB Designer

    PCB design tools cost thousands and assume you already know electronics. Boardsmith doesn't. Describe a circuit in natural language or drop a breadboard photo and Gemini parses intent into a structured circuit, then a custom Lee-algorithm autorouter lays copper on a real board Streams 8 pipeline stages live via SSE: schematic, firmware, BOM, placement, routing, 3D render, Gerber bundle, all manufacturable by JLCPCB Generates pin-aware Arduino firmware, SPICE simulation links, and a real-time cost calculator from 1 to 500 boards

    Github
  3. 003
    APR 2026

    Visual Inventory Catologer

    Shopify merchants spend days manually listing physical inventory online. VisualShelf cuts it to one click. Indexes a merchant's entire Shopify catalog as CLIP embeddings in Qdrant — photograph a product from the stockroom and cosine similarity search finds the match instantly For unmatched products, GPT-4o generates a title, description, and tags from the image and publishes the listing directly via Shopify Admin GraphQL Evaluated against a held-out test set with augmented images, precision@5 above 0.80 and catalog coverage above 0.75

    Github
  4. 004
    FEB 2026

    PR Risk Intelligence Platform

    Engineering teams find out a PR is stuck after it's already been sitting for three days. This flags it before it stalls. 3 decoupled Python microservices on Azure Container Apps ingest 500+ daily GitHub webhook events, deduplicate via Redis, and aggregate PR lifecycle metrics in PostgreSQL Gradient boosting classifier trained on 10,000+ GitHub events predicts merge time risk at 82% accuracy, with features including review assignment lag, code churn, and author velocity At-risk PRs surface in a React TypeScript dashboard before bottlenecks happen, not after

    Github

Let's make something —

s2yeshwa@uwaterloo.ca

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