Hi I'm Sai

Major in Electronics and Instrumentation

Graduation in August 2021

At VIT, I specialized in blending physical electronics with intelligent systems. My academic focus emphasized control theory, embedded systems, and neural algorithms — with hands-on courses like Microcontroller Programming, Signal Conditioning, and AI for embedded applications.

In the labs, I got my hands dirty with LabView, SCADA, MATLAB, and edge computing tools like Raspberry Pi and Jetson Nano. I built machine-learning-powered systems to linearize thermocouple readings, automate IoT-based home systems, and create basic hand-gesture-controlled robots.

Midway through college, I took an unusual detour — I spent most of my sophomore year fascinated by the idea of plant consciousness, which admittedly affected my academic performance. It all started after stumbling upon "The Secret Life of Plants" a book that sent me down a rabbit hole of plant cybernetics. It never became a thesis, but I've never looked at consciousness the same way since.

Worked on a Dam Spillway Automation Project

Designed and programmed Siemens S7-1200 PLCs to orchestrate gate actuators, level‐sensing radars, and vibration/flow sensors across the spillway. Built a WinCC SCADA dashboard that streamed real-time telemetry, issued alerts, and let operators execute staged gate sequences from a single HMI.

I led firmware for an edge-AI Industrial Motor predictive-maintenance kit: fused gyroscope, accelerometer, and temperature data on a 32-bit TI MCU, compressed a vibration-analysis model with TinyML, and validated it in a Hardware-in-the-Loop simulator under brown-out conditions.

Prototyped an edge-AI predictive-maintenance system for commercial refrigeration units, fusing vibration, current-draw, and temperature data. Trained a TinyML anomaly-detection model on a 32-bit MCU, flagging early compressor faults with 92% accuracy. Pushed real-time health metrics to a cloud dashboard over MQTT/HTTP, while exposing Modbus/TCP for on-prem PLC integration.

Worked on Android Infortainment System

Juggled roles—from automation engineer to embedded integrator—while driving monthly Google security-patch uptake. Wrote Python tools that merged fresh AOSP drops with our BSP and auto-launched smoke tests.

Containerized the Android tool-chain in Docker and wired Jenkins + GitHub Actions for one-click, reproducible builds, cutting compile time by 40%.

Automated signing and OTA delivery; hardware-in-the-loop rigs now boot patched images within 72 hours of Google's release (down from two weeks).

Master's in Computer Science, Specialized in AI/ML

Graduation in June 2025

Coursework: Reinforcement Learning, Data-Intensive Computing, Data Structures and Algorithms, Data Models and Query Languages, Computer Security, Operating Systems, Deep Learning, Machine Learning, Computer Vision and Image Processing, Sensors and Wearable Devices

Projects: Big Data Visualization and Analytics on the Cloud, Auto Evidence-Retrieval and Claim Labelling, 3D Collision Predictions Based on 2D Images, Parallel Processing of Big Data on High Performance Computers

----------------🔨 Work in Progress .. Brick by Byte 🚀----------------

Aimed at Building a Personalized AI Assistant

How r u Different ? : Long Personalized Context Window, Fast-Fluent-Freakishly Human Voice

Status Update :

- Testing various TTS Models and their latencies

- Finetuning LLaMA Models

- Pet Projects on buliding Voice Agents, hosting MCP Servers, Fast API Development ...