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Emmanual Antony Clement

Software developer building full-stack apps and real-time AI systems.

Mysore, Karnataka, India

ABOUT

I'm Emmanual, an AI and Data Science student at Mysore University School of Engineering. I like understanding how things work and figuring out how to make them work better. If something doesn't work, I want to know why. If I see a problem worth solving, I usually end up building something around it. My interests sit between AI/ML and software engineering.

I started at a coffee roastery as a waiter, so I've seen the business from the ground up. Eventually I began building software for the operational problems I'd noticed firsthand. It taught me that good engineering doesn't always start with technology. Sometimes it starts with paying attention.

Outside of tech, I work out a lot, which has taught me consistency and patience. I also enjoy music and literature.

Emmanual Antony Clement

EDUCATION

Bachelor of Engineering in Artificial Intelligence and Data Science

Mysore University School of Engineering, Mysore · Expected June 2027

9.709 CGPA / 10

Coursework: Data Structures and Algorithms · Artificial Intelligence · Database Management Systems · Operating Systems

EXPERIENCE

Aug 2026 - Present

Software Developer

Vui Coffee Roasters , Mysore

Building and maintaining the software a working coffee roastery runs on, live with real production data.

  • Built the inventory system end to end: green bean lots, roast batches, blends, recipes and stock movements.
  • Added JWT and bcrypt authentication, with a signup flow where the owner approves new accounts.
  • Built a barrel event ledger, analytics endpoints and Excel exports.
  • Moved the database to Alembic migrations and deployed on Render, Netlify and Supabase, with a cron keep-alive.
  • Built a CRM for the same business that tracks B2B cafes and B2C customers with tags, follow-ups and a going-cold view.
  • Running exploratory data analysis on the business's sales data.

FastAPI · PostgreSQL · React · TypeScript · Alembic · Render · Netlify · Supabase

May 2026 - Jul 2026

AI and Software Engineering Intern

Excelsoft , Mysore

Designed and built ProctorSense, an AI exam-proctoring system where all detection runs in the candidate's browser.

  • Built a three-worker pipeline: YOLO26 object detection (ONNX Runtime, WebGPU), MediaPipe face and iris gaze tracking, and a custom frame-differencing motion detector. Each runs on its own throttle so the interface never blocks.
  • Built a zero-copy frame pipeline using MediaStreamTrackProcessor and Transferable objects.
  • Wrote a risk-scoring engine across six signals that builds risk quickly and decays it slowly, to cut down false positives.
  • Built a live dashboard with score explanations and an exported audit trail.
  • No video stream leaves the device. Only risk events and still evidence snapshots of flagged moments reach the proctor console.
  • Recognized by senior management as a top internship contribution, and being advanced toward production.

YOLO26 · ONNX Runtime · WebGPU · MediaPipe

Jul 2025 - Aug 2025

Data Science Intern

CodeAlpha Technologies

  • Analyzed COVID-era unemployment trends in Python, cleaning and visualizing the data to find patterns.
  • Built and benchmarked supervised classifiers on the Iris dataset to pick the best-performing model.

Python · Pandas · Matplotlib · Seaborn · Scikit-learn

PROJECTS

ProctorSense

· Excelsoft internship

A phone enters the frame with its screen off. Phone Visible reaches 100%, a low-severity phone flag opens alongside the resolved gaze flag, and the risk score settles at 54 (Elevated).

1 / 5

A privacy-first, client-side AI proctoring engine where all computer vision runs locally in the browser—no continuous video stream ever leaves the device, and only structured risk telemetry and still evidence snapshots reach the proctor console. The system orchestrates three isolated Web Workers running on independent throttles so the UI stays locked at 60 FPS: YOLO26 (ONNX Runtime + WebGPU) for object and multi-person detection, MediaPipe FaceLandmarker for 3D head-pose and iris gaze tracking, and a candidate-masked frame-differencing worker for foreign-object and background anomaly detection. Built on a zero-copy video pipeline (MediaStreamTrackProcessor and Transferable VideoFrames), it feeds a six-signal hysteresis risk engine that accumulates temporal evidence and filters transient noise into an explainable live dashboard and exportable audit trail.

ONNX Runtime · WebGPU · YOLO26 · MediaPipe · JavaScript · Web Workers

Vui Inventory System

Roastery overview with live totals for green beans, roasted batches and low-stock alerts, plus recent transfers and critical alerts

1 / 4

Full-stack inventory management for a working coffee roastery, live with production data. Tracks green bean lots, roast batches, blends, recipes, and stock movements with a barrel event ledger, JWT/bcrypt auth with an owner-approval signup flow, analytics endpoints, and Excel exports.

FastAPI · PostgreSQL · React · TypeScript · Alembic · Render · Netlify · Supabase

Vui CRM

Dashboard with follow-ups grouped as overdue, due today and this week, plus quick access to cafes and customers

1 / 4

A full-stack B2B and B2C CRM built for Vui Coffee Roasters to replace scattered notes with a fast, follow-up-driven sales workflow. The team can log wholesale cafe visits, coffee samples, customer taste profiles, and orders in seconds—while the app automatically surfaces overdue follow-ups, going-cold leads, and repeat buyers falling behind their usual order cadence.

FastAPI · PostgreSQL · React · TypeScript

macOS PDF Annotation App

Freehand highlighting on a scanned, image-only page, saved as editable PDF annotations

Emphasis is a native macOS PDF reader built with SwiftUI and PDFKit to fix macOS Preview’s biggest pain point: annotating scanned, image-only PDFs. Instead of flattening ink onto the page, Emphasis stores free-form highlights and text boxes as real, standard PDF annotation objects—making every mark individually editable, movable, erasable, and compatible with other PDF readers. It includes a toggle between free-form and text-snapping highlights, resizable text boxes, on-device OCR search for scanned pages, Book View, and 2-up A4 export. You can also drag and drop either the annotated PDF or any single page rendered as an image straight into browsers, notes, or chat apps, with full multi-window support and native Finder integration.

Swift · PDFKit · Xcode

SKILLS

Languages

Python · JavaScript · TypeScript · Swift · C · C++ · SQL

Frameworks & tools

React · FastAPI · PostgreSQL · Pandas · Scikit-learn · XGBoost · Docker · Git · Linux

Certifications

CS50x and CS50P — HarvardX

Data Analytics and Software Engineering Job Simulations — Deloitte & Wells Fargo (Forage)

CONTACT