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Experience

  1. 2023

    Apple Inc.Present

    Embedded Software Engineer · Cupertino, CA

    Jan 2023 - Present

    Performance optimization on next-gen Apple SoCs.

    • Built an embedded application that dynamically predicts latencies of critical hardware IP blocks in real time, detecting bandwidth starvation, surges, and idling for key workflows.
    • Resulted in a 15% caching improvement for key end-user use-cases. Eased various bandwidth bottlenecks by 20% through software pre-fetching algorithms and proposed HW design changes.
    • Designed a live on-device dashboard for concurrent performance metrics across hardware IPs.
    • Accelerated a custom data engineering platform, improving visualization speed by 500% and memory use by up to 4000% compared to Apache Spark leveraging distributed caching schemes and parallel data processing.
    • Led hardware bring-up for multiple IP blocks across SoCs as the primary SME.

  2. 2022

    Purdue University

    Student · West Lafayette, IN

    Aug 2018 - Dec 2022

    M.S. Computer Engineering - 2022
    B.S. Computer Engineering - 2021

    Teaching assistant roles

    • ECE 469 GTA, Operating Systems
    • ECE 368 GTA, Data Structures and Algorithms
    • ECE 264, Advanced C Programming
    • CS 159, C Programming

    Relevant courses

    • Applied Algorithms
    • Programming Parallel Machines
    • Embedded Systems
    • Computer Architecture

  3. 2021

    L3Harris Technologies

    Embedded Software Engineering Intern · Melbourne, FL

    May 2021 - Aug 2021

    Developed embedded software for real-time custom hardware.

    • Developed embedded solutions on an ARM controller for upcoming product releases, optimizing features for product performance.
    • Integrated custom FPGA hardware with embedded software.
    • Produced design reviews and conducted code reviews.
    • Further technical details are confidential under US Title 18.

  4. 2020

    AT&T

    Software Engineering Intern · Seattle, WA

    May 2020 - Aug 2020

    Improved search platform with user prediction analysis and NLP-based topic identification.

    • Worked on AMP, an internal metadata search engine for applications, reports, and data.
    • Used predictive analysis and machine-learning models to classify users into personas and improve search-result relevancy.
    • Developed an NLP model to identify abstract topics from searches, improving user experience and search efficiency.

  5. 2019

    CME Group

    Software Engineering Intern · Chicago, IL

    May 2019 - Aug 2019

    Built fault-tolerance and automation for distributed order-entry systems.

    • Developed a wrapper and fault tolerance across Market Segment Gateway instances with fault-tolerance daemons in the GLOBEX Order Entry division.
    • Implemented dynamic state synchronization across client systems, order-entry systems, and the matching engine, improving the team's SDLC by over 30%.
    • Developed programs to reduce regression-report runtime on AWS EC2.
    • Placed third in the 2019 CME CodeUp for an efficient derivatives-market trading algorithm.