Ankit is currently working at Accenture as part of the Center for Advanced AI as LLM Architecture Associate Director. There, he previously led core development in the Accenture AI Refinery platform, architecting enterprise foundation model customization, agentic workflows, and reasoning systems, and is now focused on Physical AI (see his latest work, "Physical AI: The Next Frontier in AI and Robotics to Build Truly Autonomous Machines"). He also led the development of Fortune Analytics — a generative-AI business-intelligence platform built in partnership with Fortune Media that answers natural-language questions across decades of Fortune 500 financial data and journalism. The platform won the iF Design Award 2025 (User Interface) and led to European patent EP4660825A1. In November 2025, he presented Accenture's reasoning-model work on Microsoft Foundry at Microsoft Ignite 2025.

He obtained his Ph.D. from the Language Technologies Institute (LTI) at Carnegie Mellon University's School of Computer Science. His doctoral thesis, "Computational Audition with Imprecise Labels", is available on KiltHub and his defense presentation is on YouTube. He was advised by Prof. Bhiksha Raj and Prof. Rita Singh as part of the CMU Machine Learning for Signal Processing (MLSP) Group.

Beyond his core research, Ankit has architected several award-winning applied AI platforms including FactGPT, Beam, CallExpress.AI, and Herbal Tea Generator across Stanford AI for Education, AGI House, Beta University (BetaHacks), and NYC AI GPT hackathons (see Projects and Honors & Gallery). He is a recipient of the Gandhian Young Technological Innovation Award 2017 presented at Rashtrapati Bhavan, New Delhi (selected top 39 across India out of 2,915 entries).

Prior to his Ph.D., Ankit worked as a Deep Learning Scientist at ReviveMed. ReviveMed performs AI-driven drug discovery to identify novel therapeutics for metabolic diseases, leveraging tens of thousands of untargeted metabolomic datapoints to discover novel biology and translate metabolomic profiles into impactful therapeutics.

Ankit is fascinated by the applications of Multimedia Analysis and its growing importance in today's world where more than 90 percent of data consumed is multimedia. To learn more about the field, he graduated with a Master's in Language Technologies (MLT) at Carnegie Mellon University's School of Computer Science. During the master's program, Ankit was advised by Prof. Alexander Hauptmann in the Language Technologies Institute. His research focused on machine learning and signal processing with an emphasis on audio and multimedia analysis. His work on deciphering guntype information using acoustic analysis of gunshot recordings for public safety and on Deep Intermodal Video Analytics (DIVA) to recognize complex activities in large-scale surveillance videos was widely recognized.

Previously, he worked as a Verification Engineer and Project Lead at ARM, a leading global semiconductor IP provider. He is deeply familiar with ARM protocols like AMBA, AXI, CPU specifications, ARM architecture, and low-power hardware design. At ARM, his role centered on architecting in-house verification tools for simultaneous verification of complex sub-systems. These tools significantly enhanced scalability, minimized rework across cross-functional teams, and accelerated deliverable throughput. He designed a system power controller deployed across multiple ARM processor lines. Due to consistent high performance, he was appointed Project Lead to deliver the first chip-to-chip subsystem verification on ARM's platform, which was executed to completion. Ankit was consecutively rated amongst the top 5% engineers globally within ARM for two years and received multiple corporate Bravo awards.

Prior to that, he graduated with a Bachelor of Technology (B.Tech) in Electronics and Communication Engineering (ECE) from the prestigious National Institute of Technology Karnataka (NITK), Surathkal, where he was an IEEE Student Enterprise Award recipient and ranked in the top 0.2% nationwide (AIEEE AIR 2,151; IIT-JEE AIR 6,104).