Open to full-time opportunities

AI/ML Engineer · Data Scientist · Mechanical Engineer · Researcher

Building AI that knows
when to be certain.

I design reliable AI systems that combine multimodal learning, retrieval, and confidence-aware decision making—grounded in an interdisciplinary foundation spanning data science and engineering.

6+AI, data science & engineering projects
E2Eproblem framing, modeling, evaluation & deployment
3.95graduate GPA in Data Science
IEEEpublished research at SIEDS 2026

01 / Perspective

My work sits at the intersection of machine intelligence and engineering judgment. I build models that do more than predict—they measure uncertainty, retrieve evidence, and know when to step back.

Making confidence
measurable.

Research on trustworthy multimodal systems, evidence retrieval, calibration, and selective decision making.

03 / Project portfolio

Ideas made
practical.

Projects across multimodal AI, computer vision, applied machine learning, analytics, recommendation, and intelligent agents.

View all on GitHub ↗
01Computer Vision · Deep Learning

SmartLeafNet

Hybrid plant-disease classification using EfficientNetB3 and ResNet50 feature fusion, PCA, SMOTE, and Optuna-tuned XGBoost.

98% accuracy · 0.95 macro-F1

  • TensorFlow
  • EfficientNet
  • ResNet
  • XGBoost
02Multimodal Learning · Embeddings

UniBind

Unified multimodal learning with contrastive embeddings, similarity-based retrieval, and LLM-supported reasoning across modalities.

Retrieval + confidence-aware decisioning

  • CLIP
  • ImageBind
  • Vector Retrieval
  • LLMs
03Applied ML · Molecular Data

Shear Viscosity Prediction

Regression analysis for alkane shear viscosity using thermophysical features, statistical exploration, and ensemble machine-learning models.

Random Forest RMSE 0.0493

  • Python
  • Random Forest
  • XGBoost
  • EDA
04Predictive Analytics · Classification

Customer Churn Analytics

A statistically validated churn-classification workflow that transforms customer signals into actionable retention insights.

Test error approximately 1.21%

  • R
  • Classification
  • Statistics
  • Evaluation
05Recommender Systems · Applied AI

Product Recommendation

A recommendation-system project focused on matching product choices with user preferences and behavioral data.

Personalized, data-driven discovery

  • Python
  • Recommendation
  • Similarity
  • Analytics
06Agentic AI · Predictive Maintenance

Maintenance Intelligence Agent

An AI agent concept that brings together equipment signals, maintenance history, manufacturer knowledge, and confidence-aware recommendations.

From prediction to actionable inspection

  • LangChain
  • RAG
  • Time Series
  • Agent Design

04 / Mechanical Engineering & MBSE

Where systems thinking
became second nature.

My mechanical engineering background shapes how I approach AI: define the system, understand constraints, validate every interface, and design for real-world operation.

Featured engineering project · 01

Eco-Friendly E-Bike Taxi

A multidisciplinary vehicle-development project connecting requirements, mechanical design, system architecture, analysis, and sustainable mobility into one traceable engineering concept.

Recognized by Capgemini Engineering for the effective application of MBSE to an eco-friendly urban mobility solution.

View MBSE project on GitHub ↗
Model-Based Systems EngineeringSystem ArchitectureRequirements & TraceabilityMechanical Design
01

CAD & product design

Autodesk · SolidWorks · CATIA V5 · PTC Creo · Product development

02

Simulation & analysis

ANSYS · Mechanical systems · Engineering analysis · Verification & validation

03

MBSE

CATIA MagicGrid · Requirements analysis · Functional decomposition · Traceability · System architecture

04

Systems thinking

Interface definition · Trade-off analysis · System reliability · Sustainability-oriented design · Technical documentation

05 / Experience

Research depth.
Engineering discipline.

Jan—May 2026

University of Massachusetts Dartmouth

Graduate Research Assistant

Built confidence-calibrated multimodal pipelines, embedding-based evidence retrieval, and offline evaluation safeguards for reliable AI decision making.

Mar—May 2023

Dr. Mahalingam College of Engineering and Technology

Learning & Development Associate — Data & Analytics

Created Python analytical pipelines and automated reporting workflows, translating financial and operational data into stakeholder decisions.

06 / AI & data toolkit

How I
build.

01

LLM & agentic AI

LangChain · RAG · LLM agents · Tool use · Prompt engineering · Structured outputs

02

ML & deep learning

PyTorch · TensorFlow · Hugging Face · XGBoost · Model evaluation · Calibration

03

Data & engineering

Python · SQL · Pandas · NumPy · PySpark · REST APIs · Docker · Git

04

Analytics

Statistical validation · Hypothesis testing · Tableau · Power BI · Excel

07 / Education

2026

M.S. Data Science

University of Massachusetts Dartmouth · GPA 3.95

2024

Post Graduate Program, Data Science

VIT Bangalore · GPA 3.68

2023

B.E. Mechanical Engineering

Dr. Mahalingam College of Engineering and Technology · GPA 3.56

Selected certifications

Generative AI for Project Managers · PMIProject Management · IIT KanpurModel-Based Systems Engineering · SUNY Buffalo

08 / Contact

Have a hard problem
worth solving?

I'm exploring full-time opportunities in AI/ML engineering, data science, applied AI research, and interdisciplinary engineering.