Shilpa Rao

Staff Data Scientist at Walmart Global Tech

Computer VisionDeep LearningImage ProcessingArtificial IntelligencePythonTensorFlow
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About

I'm Shilpa Rao, a Staff Data Scientist at Walmart Global Tech. My career has been defined by a deep dive into the world of Computer Vision and Deep Learning, moving from research roles at USC to leading complex data science projects in the retail space. I specialize in building end-to-end systems—from data labeling on AWS to deploying production-ready models that solve real-world problems. I am incredibly passionate about the application of AI in e-commerce and staying at the forefront of evolving technologies. Beyond the technical side, I am a strong advocate for diversity in STEM and frequently volunteer at tech conferences. I’m always looking to connect with fellow engineers and data scientists to discuss the latest in AI or how we can better support women in tech.

Networking

What I can offer

  • ›Expertise in building production-ready deep learning models
  • ›End-to-end data labeling system design
  • ›Insights into AI applications in the retail sector
  • ›Mentorship for women in STEM

Looking for

  • ›expanding my professional network
  • ›exploring mutual opportunities in data science and AI

Best fit for

Data scientistsResearch engineersDiversity in STEM advocatesTech conference organizers

Current Interests

Deep learning model portabilityAI in retail and e-commerceWomen in Tech initiativesRoboticsComputer vision applications

Background

Career

Progressed from Research Intern and Student Worker to Data Scientist, Senior Data Scientist, and currently Staff Data Scientist at Walmart Global Tech.

Education

Master’s Degree in Electrical Engineering from University of Southern California (2017 – 2018); Bachelor of Engineering in Electronics and Communication Engineering from Sir M Visvesvaraya Institute of Technology, Bangalore (2012 – 2016).

Achievements

  • ›Developed deep learning models for gender and cartoon detection with <2% true rejection rates.
  • ›Built an end-to-end system with parallel AWS cloud servers for clothes production data labeling.
  • ›Developed an internal web tool for analyzing 'try on' results and producing ratings.
  • ›Conducted domain adaptation analysis using RESNET-101 Transfer learning.

Opinions

  • Professionals must stay continually updated and apprised about technologies to contribute effectively.
  • Strong advocate for diversity in tech and supporting women in engineering.