Aug 2021 – Aug 2023 · 2 yrs · Lexington, Kentucky, United States

• Develops machine learning and statistical models for gaining analytical insights from digitally collected medical datasets to develop AI systems that assist clinicians.
• Statistical Analysis: Implemented correlation, p-value, F1 score, ROC AUC score, Intersection over Union(IOU) evaluations to analyze the performance of various statistical and machine learning algorithms. E.g. used F1 score and ROC AUC Score to find the best classifier model for predicting heart beat rhythm from ECG features.
• Machine Learning: Developed multiclass classification, image segmentation and image matching algorithms on various digitally collected medical image datasets. E.g. developed image segmentation algorithms for segmenting horse bones from CT scans, and image matching algorithms to match tumor regions in patient eye taken from two different cameras.
• Data Cleaning and Preprocessing: Performed data cleaning and preprocessing on medical image datasets for data augmentation, noise reduction and feature engineering. E.g analyzed the image channels in CT images, to determine the best channels that capture the contrasting features of the different horse bones.
• Data Visualization: Developed plots to demonstrate the results of experiments and machine learning algorithms. E.g. plotted an overlap of the ground truth image and the segmented images of horse bones, to visualize the quality of overlap between the images.

Aug 2019 – Dec 2019 · 4 mos

• Instructed ‘Introduction to Programming in Java’ to a class of 200 undergraduate students as the lead instructor for one semester.

Jan 2019 – Dec 2020 · 1 yr 11 mos

• Develops machine learning, deep learning and NLP models for fake news classification and learning better text representations.
• Machine Learning: Developed multiclass classification and generative deep learning models for Fake News Detection and privacy preserved text representations.
• Data Cleaning and Preprocessing: Tokenized, removed stopwords, punctuations and encoded text data to make it usable for machine learning models. E.g preprocessed the input title and article text for Fake news analysis.
• Statistical Analysis: Analyzed the performance of the models using various statistical measures such as F1 score, ROC AUC score. E.g reported the weighted accuracy and F1 score of the Fake news prediction model.
• Data Visualization: Created plots to understand the data distributions and importance of features for the task at hand. E.g plotted the histogram distribution of feature values for each class to find features with dissimilar distributions for the classes.

Jan 2018 – Dec 2020 · 2 yrs 11 mos · Tempe

• Spring 2018 - SER 334 - Operating Systems and Networking
• Fall 2018 - CSE 230 - Computer Architecture and Assembly Language Programming
• Spring 2019 - CSE 340 - Principles Of Programming Languages

Oct 2015 – Apr 2017 · 1 yr 6 mos · Bengaluru Area, India

• Developed, deployed and maintained web application software and databases for the Mobile device management product MaaS360.
• Databases: Created, modified and queried databases using SQL and integrated the results in the products. E.g executed SQL queries to get policy values for a customer id who are not admins.
• Product Development: Developed new modules and maintained existing modules for the admin page of the IBM MaaS360 product and added Watson chatbot capabilities.

Jul 2014 – Sep 2015 · 1 yr 2 mos · Hyderabad Area, India

• Developed, debugged and maintained the point of sales ordering website for Verizon Wireless.
• Databases: Developed SQL queries and backend code to integrate the results in the web application.
• Product Development: Developed new modules for the Verizon Point of Sales ordering system.