ABOUT ME

I am a Senior Machine Learning Engineer at NuBank, working on improving financial prediction using LLMs.

PhD-level Research Scientist and ML Engineer with extensive experience in the end-to-end development of Large Language Models (LLMs) and multimodal systems. Expert in alignment and post-training techniques, including reinforcement learning techniques (e.g., DPO, GRPO, and RLIF), to optimize model reasoning and generation. Proven success collaborating in designing LLMs that significantly reduce latency and compute overhead at a global scale. Skilled in bridging the gap between theoretical research and production-grade deployment, specializing in automated evaluation, model distillation, and high-impact A/B testing.

Projects

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Featured Projects

Meta Smart Glasses: Extended Multimodal Conversation

Multimodal LLM systems for extended, context-aware human–AI conversation across server and on-device experiences.

Graph Integrated Language Transformers for Next Action Prediction in Complex Phone Calls

Graph-integrated language modeling for next-action prediction and reliable automation in complex phone calls, developed at Infinitus Systems.

PhD Thesis

Lehigh University · 2025

What Are Topic Modeling Metrics Measuring?

A Comparison of Topic Modeling Metrics and Human Assessment Approaches

Updates

July 2028Joined NuBank as a Senior Machine Learning Engineer.
June 2026Completed my Research Scientist role at Meta Smart Glasses, focused on deploying multimodal LLM systems for extended conversations.
May 2025Completed a PhD in Computer Science at Lehigh University.
May 2024Published Graph Integrated Language Transformers for Next Action Prediction in Complex Phone Calls at NAACL 2024.
September 2023Completed an NLP Researcher internship at Infinitus Systems, designing an LLM-based AI assistant for call automation.
June 5, 2023Joined Infinitus Systems as a PhD NLP Researcher for a 12-week internship beginning June 19.
May 22, 2023Our paper, An Interdisciplinary Approach to Understanding Cultures of Ethics in STEM, was accepted at BSTS.
July 20, 2022Our paper, One Rating to Rule Them All?, was accepted.

What I am doing in a nutshell

AI assessment and topic modeling visual showing topic clusters, evaluation signals, and a comparison heatmap

AI Assessment & Topic Modeling

I study how AI systems and topic models should be evaluated, connecting quantitative metrics with nuanced human assessment. My work examines model quality across multiple dimensions and improves the interpretability, stability, and usefulness of topic-modeling results.

Audio waveform and language-model representations on an AI research monitor

Multimodal LLMs & Transformers

I build and evaluate multimodal LLM and transformer systems that use audio and text signals to support extended, context-aware human–AI conversations.

Conceptual visual of post-training reinforcement learning feedback loops

Post-training RL Techniques

I use post-training and alignment methods—including DPO, GRPO, and RLIF—to improve model reasoning, response quality, and inference efficiency in practical LLM applications.