Hello, I'm

Tejaswi Raj

AI Engineer

I build intelligent systems that bridge the gap between data and actionable insights. Passionate about leveraging Machine Learning and Deep Learning to solve real-world problems in healthcare, geospatial analysis, and beyond.

Get In Touch View Projects
class MLEngineer:
    def __init__(self):
        self.name = "Tejaswi Raj"
        self.skills = ["ML", "DL", "CV"]
        self.passion = "∞"
01

About Me

I build machine learning systems and the products that carry them. Right now I'm an AI Engineer at Node2.io, working on an AI‑native property-management platform where the agents act as a working copilot for building managers. Alongside that I built and maintain Scout, an open-source code security scanner with SARIF, GitHub Action and MCP integrations.

The research half is applied, not theoretical. Six months at DRDO segmenting landslides from multispectral Sentinel-2 imagery, reaching a 73% F1-score with U-Net and SegNet. Six months at IIT Mandi pulling usable signal out of EEG recordings. Two IEEE conference papers came out of separate work, one on cardiovascular risk prediction and one on personality analysis from handwriting. I graduated with a Bachelor of Engineering in Computer Science from Chandigarh University in 2025. I'd rather you check the work than take my word for it: the models below are deployed and runnable, and the notebooks are published.

Technical Arsenal

Machine Learning

PyTorch TensorFlow scikit-learn Deep Learning CNNs Computer Vision Image Segmentation

AI & Agents

Transformers Hugging Face NLP AI Agents MCP RAG

Programming Languages

Python C++ Java R SQL HTML CSS JavaScript TypeScript React

Backend & APIs

FastAPI Node.js REST APIs

Databases

PostgreSQL MySQL SQLite MongoDB Supabase

DevOps & Cloud

Git GitHub CI/CD Podman AWS Cloudflare Vercel Netlify Render Heroku
02

Experience

Jan 2026 — Present Ongoing

AI Engineer

Node2.io — Independent Contractor (Remote, Toronto)

Helping Node2.io build BuildingSync, an AI-native property-management platform. The integrated LLMs work as a real copilot for building managers, pulling up analytics, sorting urgent complaints, catching maintenance issues like elevator faults before they escalate, and making sense of legal and financial paperwork. Across 265+ commits, I've shipped governance voting, amenity booking, Postgres RLS hardening, and the BM KPI dashboards.

Next.js 16 Supabase Postgres RLS MCP AI Agents Vercel
View Repository
Aug 2024 — Jan 2025 6 Months

ML Research Intern

Defence Geoinformatics Research EST. (DRDO), Chandigarh

Developed Deep Learning models for landslide detection using multispectral Sentinel-2 data, achieving a 73% F1-score. Enhanced performance through implementation of U-Net, AlexNet, and SegNet architectures for semantic segmentation tasks.

Python TensorFlow U-Net AlexNet SegNet
View Certificate
Feb 2024 — Jul 2024 6 Months

ML Research Intern

Indian Institute of Technology Mandi

Applied Machine Learning and Deep Learning techniques to Electroencephalogram (EEG) data for measuring electrical activity in the brain. Enhanced algorithms for precise information extraction and signal processing from neural data.

PyTorch scikit-learn MATLAB SciPy Signal Processing
03

Projects

Latest Project

Scout — AI-Powered Security CLI

Built a free, local security scanner that finds vulnerabilities before they ship — static analysis for secrets, SQL/command injection and XSS, plus dependency scanning via OSV.dev, with SARIF, GitHub Action, pre-commit and MCP integrations.

Python Security Static Analysis
View on GitHub → Open Live Site →
Featured Project

Inbound Voice Booking Agent

Built a production voice agent that answers inbound home-service calls, classifies the trade, validates the address and returns bookable 2-hour slots — a 12-rule scheduling engine over Google Calendar and Maps drive-times, hardened by 951 pytest cases.

Voice AI Agentic Workflows Retell AI
View on GitHub →
Featured Project

Cardiovascular Disease Prediction & Prevention

Developed an AI system that accurately predicts Cardiovascular disease in patients by analyzing medical reports and daily routines using ML algorithms, achieving 94% accuracy.

Machine Learning Healthcare AI Prediction Model
Open Live App → View Notebook →

Plant Leaf Disease Detection

Created an AI model for plant disease classification using CNN algorithms across 11 distinct plant species, achieving 99% accuracy.

Deep Learning CNN Computer Vision
Open Live Demo → View Notebook →

Coronary Artery Disease Risk Estimator

Built a feature-selection-driven Logistic Regression classifier for coronary artery disease on the UCI Cleveland dataset, achieving 0.89 ROC-AUC with 83% accuracy.

Feature Selection Logistic Regression Healthcare AI
Open Live Demo → View Notebook →
04

Publications

Cardiovascular Disease Prediction and Prevention: Exploring Novel Techniques and Applications Using Machine Learning

2023 12th International Conference on System Modeling & Advancement in Research Trends (SMART) · IEEE

View on IEEE

Personality Analysis using Graphology and Image Processing Techniques

2024 First International Conference on Data, Computation and Communication (ICDCC) · IEEE

View on IEEE
05

Certifications

Specialization 4 courses

IBM Introduction to Machine Learning

IBM · Coursera

View Certificate Verify
Specialization 3 courses

Java as a Second Language

LearnQuest · Coursera

View Certificate Verify
DeepLearning.AI course

Natural Language Processing with Classification & Vector Spaces

DeepLearning.AI · Coursera

View Certificate Verify
AI & Machine Learning
Exploratory Data Analysis for Machine Learning IBM PDF Verify
Supervised Machine Learning: Regression IBM PDF Verify
Supervised Machine Learning: Classification IBM PDF Verify
Unsupervised Machine Learning IBM PDF Verify
Deep Learning and Reinforcement Learning IBM PDF Verify
Introduction to Computer Vision & Image Processing IBM PDF Verify
Decision Tree & Random Forest Classification Coursera PDF Verify
Build Random Forests in R with Azure ML Studio Coursera PDF Verify
SVM Regression, Prediction & Losses Coursera PDF Verify
AutoML Tools for Data Science Coursera PDF Verify
Software Engineering
Algorithmic Toolbox UC San Diego PDF Verify
Data Structures and Performance UC San Diego PDF Verify
Introduction to Java as a Second Language LearnQuest PDF Verify
The Java Language LearnQuest PDF Verify
Writing Java Application Code LearnQuest PDF Verify
Web Development
HTML, CSS & JavaScript for Web Developers Johns Hopkins PDF Verify
Front-End Web UI Frameworks and Tools HKUST PDF Verify
Single Page Web Applications with AngularJS Johns Hopkins PDF Verify
Mobile Development and JavaScript Meta PDF Verify
06

Get In Touch

I'm open to interesting opportunities and collaborations in AI engineering and applied machine learning. Whether you have a question or just want to say hi, I'll try my best to get back to you!

tejaswirajmgr@gmail.com +91 9473219473 LinkedIn
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