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Science Intern Vellore

Arlington, TX
June 20, 2021

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Atharva Kulkarni

Dallas, Texas, United States 309-***-**** in/inflatonn/ SUMMARY

Dynamic and creative Computer Science Engineer aiming to leverage a proven knowledge of research and development skills as a Software Development Engineer. Eager to be associated with a growing organization that provides a scope to enhance skills as per the latest trends. EDUCATION

Masters of Science in Computer Science

University of Texas • Arlington, TX • 2021 • 3.67

Bachelor of Technology in Information Technology

Vellore Institute of Technology • Vellore, TN • 2019 • 3.14 SKILLS

Proficient: Python, SQL,Git,Amazon Web Services(AWS),TensorFlow,Docker,HTML5,CSS3,Agile,NumPy,Pandas,Keras,Linux,SAS Exposure: Java,JavaScript,JUnit MATLAB,Android Studio,Salesforce,Microsoft Azure,Golang,Django,Flask,Google Cloud(GCP) EXPERIENCE

Research Intern

• Designed(JavaScript), built and tested(Golang) Automated Speech Recognition(Cubic) and Text To Speech(Luna) services with 93% accuracy.

• Co-ordinated with a team to develop various customer faced (APIs) involving speech recognition for Spanish ministry of Justice using AWS with accuracy of 95%.

• Researched the field of auto subtitle generation and forecasted the final results with 98% accuracy. Data Science Intern

• Utilized Einstein analytics and Machine Learning to conduct exploratory and confirmatory data analysis and successfully injected twitter data with 90% sentiment analysis accuracy.

• Accomplished over 112+ badges, 3+mini projects, 13+ trails to obtain the prestigious ranger badge on Salesforce trailhead.

• Conducted research on various market practices to be involved in the marketing team for meetings with customers such as Tata motors, Fullerton and PWC to understand the business end and integrate demos with 100% customer satisfaction and effective team communication. PROJECTS

Credit Card Fraud Detection Using Neural Networks

University of Texas at Arlington • August 2020

• Designed and implemented Multilayer perceptron neural network with almost 96% accuracy for Credit Card fraud transaction detection.

• Compared the accuracies of algorithms like Random forest(94%),Support vector machine(93%),Logistic regression(95%),XGBoost(94%).

• Minimized the False negatives to 8 from a dataset of almost 200,000. Loan eligibility prediction using Decision Trees

University of Texas at Arlington • November 2019

• Formulated 3 different algorithms to predict loan eligibility(Decision trees, Kmeans, Logistic regression).

• Performed outlier scaling and under sampling on top 4 features for better accuracy with a small sample size.

• Derived that decision trees perform the best for the given dataset with an accuracy of 89%. Autonomous Car in GTA 5

Vellore Institute of Technology • August 2018

• Designed a game playing script with 8+ different controls with the help of Alexnets and TensorFlow in Python.

• Analyzed computer vision techniques to detect lanes, objects and people with 82% accuracy. Useful for for scaling to actual autonomous cars.

• Achieved 82% accuracy with small sample of training data and limited hardware capabilities. Real time Sentiment Analysis of Twitter Data using Keywords Salesforce • May 2018

• Utilized flume (bash) and streamed real time twitter data in Hadoop Distributed File System on the basis of a key word with accuracy of 100%.

• AFINN dictionary employed with the help of hive (SQL) for querying and analysis. Implemented K means for the final result with 90% accuracy.

• Architected the whole program with the best case accuracy levels of 93%. CERTIFICATIONS

Machine Learning

Stanford University • 2018

Learnt how to build, develop and deploy various Machine Learning models. Cobalt Speech & Language January 2019 - June 2019, Boston, MA Salesforce May 2018 -June 2018, Mumbai, MH

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