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Sravan Patchala

Sravan Patchala

AI Product Manager, Engineer, and Stanford MBA Candidate

Stanford, California
github
Joined August 2025
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Network

7.2K connections
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IIT Bombay Alumni
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Qualcomm Leadership Product
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Research Academia
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Big Tech AI/ML
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Product Managers
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Qualcomm AI/ML Engineers
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IIT Bombay Professors

Summary

Sravan Patchala is a technically proficient engineer with a strong foundation in Electrical Engineering from IIT Bombay, demonstrated through diverse projects like designing a self-balancing bot (Cubli) and implementing a 16-bit computer system, alongside applying machine learning to wireless sensor networks. github+2
He possesses significant expertise in AI/ML and its commercial application, cultivated during his time at Qualcomm where he worked on cutting-edge AI models, chips, and played a key role in productizing research breakthroughs for the automotive sector, including autonomous driving technologies. github+3
As an MBA candidate at Stanford GSB, Sravan is strategically combining his engineering background with business acumen, driven by a clear aspiration to lead in the tech industry and improve lives through AI/ML, as highlighted by his active participation in GSB's Tech and AI clubs and his LOWkeynotes presentation. github+4
Sravan is committed to leveraging technology for global social impact, particularly in automotive safety in developing countries. His research and public speaking on the topic advocate for using diverse global data to enhance driver assistance systems and address disproportionately high fatality rates. youtube+1
He is a published researcher with several academic papers and patents, demonstrating his contributions to areas such as heterogeneous networks, multi-armed bandits, network interconnections, net neutrality, and machine learning acceleration techniques. google+2

Work

Education

Projects

Writing

Apparatuses and methods for processing single instruction for machine learning acceleration

January 1, 2024

A patent detailing methods and apparatuses for accelerating machine learning computations by efficiently processing single instructions.

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Folding cumulative summation operations using matrix operations for machine learning acceleration

January 1, 2024

A patent describing techniques for accelerating machine learning tasks by folding cumulative summation operations through the use of matrix operations.

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On the economics of network interconnections and its impact on net neutrality

January 1, 2021

Academic paper exploring the economic aspects of network interconnections and their implications for net neutrality principles.

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Distributed learning and optimal assignment in multiplayer heterogeneous networks

January 1, 2019

Academic paper discussing distributed learning and optimal assignment problems in networks with multiple players and varied characteristics.

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Multiplayer multi-armed bandits for optimal assignment in heterogeneous networks

January 1, 2019

Academic paper focusing on the application of multi-armed bandit problems in a multiplayer context for efficient assignment in heterogeneous networks.

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Hobbies

Passionate football (soccer) fan, specifically a supporter of Manchester United since the early 2000s. github