Apple

Machine Learning Engineer

Anheuser-Busch InBev

Data Scientist

Product Management Intern

Cornell University

Degree: Master of Engineering in Computer Science
Awards: Cornell Tech Merit Scholarship

Masters Student

ServiceNow

♦ Platform UX Engineering Team: Development and maintenance of platform features
♦ Developed feature to identify labels for attachments with object recognition and machine learning (Named Entity Recognition), enabling hits in search results for image and text uploads. Framework used: OpenNLP (Java)
♦ Winner, Mini Project Hackathon, ServiceNow 2018

Associate Software Engineer

Solar Energy Research Institute of Singapore

♦ Optimized parameters for solar cell manufacture using a shallow Convolutional Neural Network(CNN)
to increase module efficiency. Trained on TensorFlow, and deployed with TensorFlow Serving.
♦ Implemented transfer learning for Silicon sheets with varying wafer properties and predicted process parameters to match efficiencies across manufacturing recipes.
♦ Predicted solar cell performance across climates. Analyzed influence on performance from weather
conditions as a part of the TruePower Project with Random Forest Regression with accuracy above 0.94.
♦ Visually detected defects in solar modules with YOLO algorithm and CNNs.

Research Intern

National Centre for Biological Sciences

♦ Simulated the Stable Matching Problem in a biological population to converge on a fitness function for Pareto efficiency.
♦ Participant of Physics of Life, Monsoon School 2016

Summer Intern

Tata Consultancy Services

Intern

SENSEI Technologies

Graduated from Cornell Tech, New York - Master's in Computer Science, with experience as a data scientist and a software engineer.

Interested in industry applications of Machine Learning.
Please reach out at: aks298@cornell.edu

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