Shreya Singhal
Shreya Singhal works in Generative AI Research & Development at Aristocrat Gaming and is a Graduate Research Assistant at the University of Texas at Austin. Her work spans large language models (LLMs), reinforcement learning, and optimization for scalable and interpretable AI systems.
Shreya has hands-on experience fine-tuning open-source models like Gemma 2B for under-resourced languages, deploying compressed generative models in low-resource environments, and implementing bias and fairness evaluation pipelines using interpretable subspace analysis. She has previously worked at Dell Technologies, Charles Schwab, Deloitte, and Accenture, contributing to AI-powered solutions across gaming, finance, and enterprise automation.
Her current research focuses on efficient LLM training and evaluation pipelines, fairness-aware model design, and bringing generative AI to edge and enterprise use cases. She is passionate about making AI more inclusive, scalable, and grounded in real-world constraints.