About me

I'm an Applied Machine Learning Engineer with a passion for pushing the boundaries of AI, particularly in the realm of Natural Language Processing (NLP). My journey has led me to Google, where I've dedicated the last 5+ years to building and deploying innovative ML solutions that impact millions of users. From improving search quality and reducing harmful content on YouTube to optimizing Google's contact center platform using AI, my work has consistently focused on real-world applications and measurable results.

I'm driven by a desire to solve challenging problems and create solutions that are both impactful and scalable. My experience spans research, development, and productionization, allowing me to bring a comprehensive perspective to every project. I'm constantly seeking new challenges and opportunities to expand my skillset, and I believe that AI has the potential to transform the way we live and work.

What i'm doing

  • design icon

    Machine Learning & AI

    Develop high-quality algorithms to enhance product applications.

  • Web development icon

    Applied LLMs

    Bridge gap between state-of-the-art research and production.

  • mobile app icon

    Software Engineering

    Develop software to manage the lifecycle of ML & Data in production.

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    Lead

    Lead projects and guide engineers to amplify the impact of AI.

Daniel lewis
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Daniel lewis

Richard was hired to create a corporate identity. We were very pleased with the work done. She has a lot of experience and is very concerned about the needs of client. Lorem ipsum dolor sit amet, ullamcous cididt consectetur adipiscing elit, seds do et eiusmod tempor incididunt ut laborels dolore magnarels alia.

Education

  1. Texas A&M University

    College Station, TX, USA

    2017 — 2019

    Master of Computer Science, GPA: 4/4

    GPA: 4/4

  2. National Institute of Technology, Warangal

    Telangana, India

    2011 — 2015

    Bachelor in Electronics and Commmunications Engineering

    GPA: 9.05/10

    Rank: 2/126

Academic Awards

  1. Texas A&M ACPC

    2019

    Second prize in TAMU Spring 2019 Team Programming Contest

  2. Merit Scholarship

    2012-2014

    Awarded scholarship for 3 years during undergrad for consistently ranking among the top

  3. Hackathon Award

    Summer-2014

    Received best prototype award for building 'NFC Based Smart Library' co-facilitated by Intel & FICE Organizations.

  4. NMTC National Contest

    2008

    Secured an All India Rank of 9 at National Mathematics Talent Contest

Career

Work Experience

  1. Machine Learning Engineer, Cloud Research - 20% time

    May 2023 – Present Google - Sunnyvale, California

    Research techniques to improve state-of-the-art Google LLMs for Text to SQL solution in GCP.

  2. Machine Learning Engineer, Customer Conversations Platform

    Jan 2022 – Present Google - Sunnyvale, California

    Own the knowledge retrieval platform, ensuring it delivers tailored search and recommendation solutions for Google employees and agents providing support for internal and external customers. Spearheading a $$3M+ cost-saving taxonomy platform that streamlines onboarding, routes tickets in real-time, and provides continuous ML model retraining for support teams.

  3. Machine Learning Engineer, YouTube Comments

    Jan 2021 – Jan 2022 Google - Mountain View, California

    Improved the low quality comments detection solution and reduced the viewership of racially insensitive comments on YouTube very significantly i.e. by ~50%. Led the Civility Reminders initiative for Spanish, prompting adherence to YouTube community guidelines and delivered a remarkable 46% reduction of low-quality comments authorship.

  4. Machine Learning Engineer, Core Platform for Search

    June 2019 – Jan 2021 Google - Sunnyvale, California

    Led the development of a cutting-edge BERT-based multi-task model for structural and semantic understanding of web pages, surpassing state-of-the-art performance. Developed a production-ready platform specifically for web page understanding models, reducing deployment time by 67%.

  5. NLP Intern

    Jan 2019 – April 2019 Remote, TX

    Researched, developed and deployed end-to-end BERT based classifiers for deed type documents using Tensorflow.

  6. Open Source Contributor

    Oct 2018 – May 2019 AutoKeras / Texas A&M University, College Station

    Played a pivotal role in the development of AutoKeras, an open-source AutoML system with over 9,000+ stars on GitHub, as one of 6 initial contributors. Leveraged my expertise in AutoML and BERT to build autotunable text classifier and regressor modules for AutoKeras.

  7. SWE Intern

    May 2018 – Aug 2018 Google - Mountain View, California

    Developed the prototype for the first transactional distributed aggregation system at Google to migrate from an eventual consistent system.

  8. System Design Engineer

    June 2015 – July 2017 SanDisk - Bangalore, India

    Designed and implemented firmware algorithms for performance improvement in flash-based storage systems using C++. The algorithms helped in releasing the world’s fastest and largest 256GB µSD card in 2016.

Awards

  1. Received multiple spot bonuses for humongous impact in youtube comments and google support platform

    2020-2024

  2. Awarded with the highest (PLATINUM) award for contributions to the 256GB µSD card at SanDisk

    2016

Technical skills

  • C++
    90%
  • Python
    80%
  • Java
    60%
  • Tensorflow
    80%
  • Pytorch
    60%

Research

Patents

  1. Folding operations in memory systems with single address updates

    US Patent - 2019

  2. Meta-groups in non-volatile storage based on performance times

    US Patent - 2019

Publications

  1. PromptMind Team at EHRSQL-2024: Improving Reliability of SQL Generation using Ensemble LLMs

    ClinicalNLP - NAACL, 2024

  2. PromptMind Team at MEDIQA-CORR 2024: Improving Clinical Text Correction with Error Categorization and LLM Ensembles

    ClinicalNLP - NAACL, 2024

  3. Image Dehazing: Improved Techniques

    Deep Learning Through Sparse and Low-Rank Modeling, 2019

  4. Implementation of Toeplitz Hash based RC-4 in WSN

    SPICES, 2015

  5. FPGA implementation of RC-4T and WPA

    NCCSN, 2014

  6. Multi level secure LEACH protocol model using NS-3

    ICNSC, 2014

  7. FPGA implementation of IEEE-754 floating point Karatsuba multiplier

    ICCICCT, 2014

Awards

  1. Secured second position in the Clinical NLP competition: Reliable Text-to-SQL Modeling on Electronic Health Records

    2024

  2. Secured second position in the Clinical NLP competition: Medical Error Detection & Correction

    2024

  3. Received best paper award for FPGA implementation of IEEE-754 floating point Karatsuba multiplier

    2014