Bilal Aamer

Solely pioneered a GenAI PoC for Forbes 500 clients, developing NLP solutions using cutting-edge LLMs (Deepseek R1) and contributing to AICS department initiatives for client-facing GenAI systems.

Led development of a GenAI PoC for BNY Mellon’s client onboarding platform, designing and implementing a multi-agent orchestration solution on an internal platform and collaborating with AI leadership.

Integrated state-of-the-art open-source LLMs into product workflows, authored technical documentation for the LLM-VM package, and collaborated on product roadmap and stakeholder alignment.

Curated and annotated client datasets and implemented a state-of-the-art model architecture that achieved an initial accuracy of 85% for research and client projects.

Activities and societies: Relevant coursework: AI, ML, Neural Networks & Deep Learning, Data Mining, DBMS, OOPS, OS, DSA, Speech Processing, Advanced DBMS, Advanced DSA; student projects included AutoPaLM (autonomous agent, reinforcement learning) and Locus 2.0 (full-stack app with GPT-3.5-turbo query bot).

Completed an Integrated Dual Degree (BTech + MTech) in Computer Science and Engineering with coursework in AI, ML, neural networks, deep learning, data mining, DBMS, operating systems, and advanced data structures.