Jayasurya Sakthivel

4Hackathon wins

4.00GPA · MS @ ASU

1Peer-reviewed paper

Jayasurya Sakthivel standing in a black suit with a yellow graduation honor stole

Open to full-time roles · MS graduate, May 2026

Data Science & AI/ML Engineer.

I build data systems and AI products that hold up in production — from LLM extraction pipelines and credit-risk models to federated learning research and real-time industrial digital twins.

4.00: GPA, MS @ ASU
4: Hackathon wins
1: Peer-reviewed paper
11+: Shipped projects

Machine Learning✦LLMs✦LangChain✦RAG✦PyTorch✦FastAPI✦MLOps✦PySpark✦BigQuery✦Power BI✦AWS✦Azure✦Databricks✦

About

My background and focus areas.

MS in Data Science, Analytics & Engineering at Arizona State (4.0 GPA). I bridge research-grade modeling with the engineering it takes to ship — pipelines, APIs and dashboards that real teams depend on.

LLM & Agent Pipelines

Document AI, OCR and Gemini/GPT structured extraction with consensus checks, RAG and multi-agent workflows that run daily in production.

Predictive Modeling

Credit-risk, forecasting and anomaly models — XGBoost, LSTM, SARIMA — with SHAP explanations people can trust.

Data Engineering & BI

ETL/ELT on PySpark, Databricks and BigQuery, star-schema warehouses and Power BI dashboards leadership actually uses.

Applied Research

Federated learning under adversarial corruption and published deep-learning work on underwater image enhancement.

Experience

Where I've worked.

Aug 2026 — Present
AI/ML Engineer
Vizzda
Arizona
3-sourceconsensus extraction
2counties automated
- Built and deployed end-to-end pipelines for automated real estate document processing, orchestrating Google Document AI, Tesseract OCR and Gemini 2.5 Flash in a 3-source consensus extraction system across Maricopa and Miami-Dade.
- Created entity resolution and skip-trace systems using fuzzy matching, Bizapedia and the Enformion API — with tuned similarity thresholds, cost-control layers and multi-hop LLC traversal — to identify beneficial owners at scale.
- Developed a modular multi-county Python pipeline combining external APIs, Playwright automation, LLM structured extraction and rules-based enrichment to produce contact-ready commercial real estate intelligence daily.
PythonGemini 2.5Document AITesseractPlaywrightEntity Resolution
May 2026 — Present
Research Assistant
Ira A. Fulton Schools of Engineering, ASU
Tempe, AZ
432experiments run
6FL algorithms
- Implemented 6 federated learning algorithms combining FedAvg/FedGmd aggregators with SGD, ASS and SASS trainers, running 432 experiments across IID and non-IID MNIST and medical datasets (REFUGE, LAG) with up to 80% corruption.
- Diagnosed why FedGmd hurt accuracy by up to 6% at high corruption — the geometric median collapses toward the corrupt majority past 50% — and confirmed it theoretically via RFA breakdown-point analysis.
PyTorchFederated LearningFedAvgMedical Imaging
Aug 2025 — May 2026
Instructional Aide & Grader
Arizona State University
Tempe, AZ
100+students supported
- Supported 100+ students across Principles of Programming Languages and Operations Research Models through office hours and exam reviews.
- Developed rubrics and solution sets, grading via Gradescope and Canvas to keep academic standards consistent.
Operations ResearchGradescopeCanvas
May 2023 — Jul 2023
Data Analyst Intern
Amrutanjan Health Care Ltd
Chennai, India
300+staff hours saved / yr
1M+records processed
90%forecast accuracy
- Automated ETL and reporting with PostgreSQL, PySpark on Databricks and Python over 1M+ sales records, with anomaly checks flagging data errors before executive reporting.
- Engineered 14 demand and seasonality features with DBSCAN and statistical methods; built LSTM and Seasonal ARIMA forecasts at 90% accuracy, lowering stock-out risk.
- Delivered Power BI variance dashboards that shaped procurement strategy for senior leadership.
PostgreSQLPySparkDatabricksLSTMSARIMAPower BI

M.S. Data Science, Analytics & Engineering

Arizona State University

4.00 / 4.00 · 2024 — 2026

B.Tech Computer Science & Engineering (AI & ML)

Vellore Institute of Technology, Chennai

3.53 / 4.00 · 2020 — 2024

Projects

Problems, approaches, results.

Case 01

LoanLens

Credit risk decision intelligence · Capstone

1.1M

loan records

Problem — Lenders need default predictions that are accurate on imbalanced data and explainable to borrowers.

Approach — Trained XGBoost, LightGBM and Random Forest on 1.1M LendingClub records with class weighting for a 4:1 imbalance. Added SHAP per-applicant explanations and live FRED macro data at inference.

Result — AUC-ROC 0.703 · 0.67 recall on held-out data, served via FastAPI + React dashboard with a GPT plain-language explainer.

XGBoostSHAPFastAPIReactFRED APIGPT

Case 02

Industrial 3D Digital Twin

1st place · HackAZona, Cognite track

50+

assets modelled

Problem — Plant operators lack a single live view of assets, sensor health and maintenance history.

Approach — Modelled 50+ assets from 2D SVG diagrams into a real-time React Three Fiber scene, wired 20+ sensor streams with anomaly alerts, and added a Gemini/Groq agent with RAG over maintenance logs and SOPs.

Result — Won 1st of 25+ teams. Explainable answers with citations, plus voice-AI callouts to field staff on critical events.

Three.jsR3FNext.jsRAGGroqSupabase

Code ↗Live ↗

Case 03

Retail Sales Analytics Platform

BigQuery warehouse + Power BI

4 yrs

of sales data

Problem — Four years of retail data with no reliable view of performance, segments or margins.

Click any skill group below to put it at the center of the orbit.

SQL

LLMs

Power BI

BigQuery

React

ETL/ELT

Tableau

RAG

ML Modeling

Pipelines

Big Data

Azure

Three.js

PyTorch

Python

Research & Certifications

Published work and credentials.

Publication · 2025

UWE-Net: A Deep Learning Framework for Underwater Image Enhancement Integrating CBAM and Charbonnier Loss

Procedia Computer Science · ScienceDirect

A hybrid CNN combining a VGG16 encoder with a custom decoder and CBAM attention in skip connections, trained with Charbonnier loss for robust underwater image restoration.

Google Advanced Data Analytics

Google · Professional Certificate

Microsoft Certified: Azure Fundamentals

Microsoft

Hackathons

Wins under pressure.

1st

HackAZona v1.0 — Cognite Track

Industrial Digital Twin · out of 25+ teams · 2026

Winner

Principled Innovation Academy Problem Solving Event, ASU

out of 40+ teams · 2025

Best Security

Opportunity Hack

out of 40+ teams · 2025

People's Choice

HackAZona v0.1

out of 30+ teams · 2025

Gallery

The moments behind the resume.

Hackathon stages, demo tables, the paper presentation and the convocation — 10 photos from 2023 to 2026.

Contact

Let's build something that ships.

Open to full-time roles · MS graduate, May 2026. The fastest way to reach me is email.

Jayasurya Sakthivel

Data Science & AI/ML Engineer.

My background and focus areas.

LLM & Agent Pipelines

Predictive Modeling

Data Engineering & BI

Applied Research

Where I've worked.

AI/ML Engineer

Research Assistant

Instructional Aide & Grader

Data Analyst Intern

M.S. Data Science, Analytics & Engineering

B.Tech Computer Science & Engineering (AI & ML)

Problems, approaches, results.

LoanLens

Industrial 3D Digital Twin

Retail Sales Analytics Platform

AI Task Management System

Smart ML Framework

SkillForge

UWE-Net

BusBuddy

ChatBot Intervention System

Path2Pro

Voices of History

PathWiseAI

Everything orbits Python.

AI & Machine LearningShow in orbit

Data & AnalyticsShow in orbit

Cloud & PlatformsShow in orbit

Engineering & ToolsShow in orbit