Andrew Siah

ML researcher with an emphasis on personalization and data‑efficient methods: Andrew is a co‑author on PersonalLLM (ICLR/ICLR‑workshop submissions and OpenReview entries), a public benchmark/dataset and method suite for tailoring LLMs to individual user preferences. His academic profiles list machine learning and physics as primary areas and include multiple co‑authored papers on personalization and data‑mixture/optimization topics. openreview+1

Operator / founder building practical AI for finance: Andrew co‑founded TabAI (product of New York AI Labs), which integrates agentic AI into Excel to accelerate FP&A and accounting workflows. TabAI positions itself as an enterprise/finance‑focused add‑in that connects QuickBooks/Xero/PDFs and uses agents to automate modeling, QA, and reporting — reflecting a focus on applied ML systems and productization for finance teams. tabai+1

Quantitative developer / practitioner in crypto and finance contexts: Public materials (conference/partner slides and a firm presentation) list Andrew in quantitative developer / quant roles (Abra) and other quant‑oriented engagements, indicating applied quantitative engineering experience alongside his academic ML work. dacfp+1