Experience & Skills

• AI security and trust startup building authenticity, provenance, and real-time verification infrastructure for AI-generated media and enterprise interactions.
• Co-founded Aubric with Bhiksha Raj, who serves as President.

• Led architecture and development of Fortune Analytics — a generative AI business-intelligence platform built in partnership with Fortune Media analyzing 20+ years of Fortune 500 data.
• Recognized with the prestigious iF Design Award 2025 (User Interface) and filed European patent EP4660825A1 (LLM data visualization architecture).
• Spearheaded enterprise reasoning models and agentic architectures on Microsoft Foundry, presenting Accenture's reasoning-model framework at Microsoft Ignite 2025.
• Lead engineering teams delivering state-of-the-art agentic workflows, GraphRAG systems, and enterprise LLM integrations.

• Oversaw 14 researchers and engineers on Fortune Analytics.
• Delivered FALM (Fortune Analytics Language Model), a 7B model pretrained on 3T tokens with an in-house distributed training system, reaching 99.3% execution success on natural-language-to-chart generation.
• Played a critical role as Tech Lead on AI Refinery creation and the Accenture–NVIDIA partnership.

• Developed AI-driven drug discovery models for metabolic diseases.
• Leveraged tens of thousands of metabolomic data points to discover novel biological pathways and impactful therapeutics.

• Designed and deployed in-house verification platforms to simultaneously verify 52 compute subsystems delivered to silicon partners globally.
• Served as Project Lead for the first successful chip-to-chip subsystem verification on ARM architecture.
• Consecutively rated amongst the top 5% engineers globally within ARM for two years.
• Recipient of the ARM Bravo Award in 2016 & 2017 for uncovering critical RTL bugs and accelerating delivery throughput by 2x.

• Designed Low Power Interface protocols for AMBA 4 and ACE specifications across multi-cluster CPU arrangements.

Thesis: "Computational Audition with Imprecise Labels" (Advised by Prof. Bhiksha Raj & Prof. Rita Singh, CMU MLSP Group).

• Researched weakly-supervised sound event detection, learning from label noise, and multimodal video analysis.
• Published 60+ peer-reviewed papers across top venues including NeurIPS, ICLR, ICASSP, IJCAI, ACM ICMI, and IEEE/ACM TASLP.
• Recipient of CMU LTI Fellowship and Conference Travel Grants.

• Advised by Prof. Alexander Hauptmann on Deep Intermodal Video Analytics (DIVA) and acoustic gunshot analysis for public safety.
• Developed end-to-end activity localization and acoustic weapon categorization pipelines.

• Awarded the Gandhian Young Technological Innovation Award (GYTI 2017) at Rashtrapati Bhavan (top 39 of 2,915 entries nationwide).
• Recipient of two IEEE Student Enterprise Awards (Region 10) for Quadcopter and Wireless Sensor Network projects ($3,000 total funding).
• All India Rank 2151 in AIEEE 2011 and qualified IIT-JEE 2011 (Rank 6104).