Current
Head of AI Foundry
Evergreen, an Insight Global company
2021–2024
VP, Data & AI
Truist Financial
2011–2020
Sr. Manager, ML
Quinnox Inc
THE JOURNEY
From classical ML foundations to enterprise-scale multi-agent systems.
Machine Learning Nanodegree era — classical ML, supervised learning, model evaluation
Survival prediction using decision trees and feature engineering — my entry into applied machine learning.
Early warning system predicting student dropout risk, comparing SVM, ensemble methods, and neural approaches.
Regression model for housing price prediction with cross-validation and rigorous model evaluation pipelines.
CNN-based digit classifier using Keras/Theano — built before TensorFlow 2.0 dominated the landscape.
Stanford CS231N era — computer vision, CNNs, financial time-series analysis
End-to-end deep learning portfolio: sentiment analysis with RNNs, image classification with CNNs, sequence modeling.
Deep learning for financial time series — predicting market movements using convolutional architectures. Stanford CS231N research project, later published in ADaSci Lattice Journal.
VP at Truist Financial — AI/ML at scale, compliance systems, production ML infrastructure
CLI tool for automated customer evaluation scoring — production utility for enterprise sales intelligence.
Primary work during this period: proprietary enterprise AI systems at Truist Financial — AI-driven compliance solutions, volatility dashboards, and microservices infrastructure serving regulated financial operations.
Head of AI Foundry — multi-agent systems, RAG architectures, responsible AI at enterprise scale
Multi-agent system for autonomous document generation. Published at IEEE ICMLA 2025: "Retrieval-Augmented Multi-Agent System for Rapid Statement of Work Generation."
Research into LLM reasoning patterns — evaluating chain-of-thought and multi-step inference capabilities.
Computer vision model detecting utility infrastructure from aerial imagery — infrastructure monitoring at scale.
Proximity-based transit notifications — location-aware mobile app delivering real-time bus schedules when near stops.
PUBLICATIONS & SPEAKING
IEEE ICMLA 2025
Published research on multi-agent architectures for enterprise document automation.
ADaSci Lattice Journal, Vol. 1 • 2021
Research on CNN-based financial time-series analysis for market prediction.
Stanford CS231N • 2019
Research paper on applying computer vision techniques to financial data.
April 2025
3rd Annual Atlanta Technology Summit
Panelist: "Cultivating Culture in the Age of AI"
April 2025
University of Texas at Dallas
Guest Lecturer: Enterprise Agentic AI Solutions
March 2025
ADaSci Webinar
AI-Driven Risk Management in Derivatives Trading
October 2020
Deep Learning Developers Conference
Keynote: AI Use Cases in Capital Markets
RECOGNITION & AFFILIATIONS
IEEE ICMLA 2025 • Generative AI Track
Invited to chair sessions and evaluate peer submissions at the IEEE International Conference on Machine Learning and Applications.
2022
Recognized for highest innovative contributions in financial solutions across the bank.
Member since 2023
Harvard Business Review Advisory Council member contributing to business and technology thought leadership.
Member since 2019
Active member and contributor to ADaSci, including journal publications and webinar presentations.
2019
Stanford University
CS231n, Artificial Intelligence
2017
MIT Professional Education
Data Science & Big Data Analytics
2016
Georgia Tech / Udacity
Machine Learning Nanodegree
2004
BITS Pilani
M.S., Software Systems