Hello! I'm Keerti and this is about me
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I am a Software Development Engineer at Amazon Web Services. I graduated from the University of Southern California as Master of Science in Applied Data Science. I came to the US in Fall 2019 from India. I graduated with a B.Tech in Computer Engineering from Vishwakarma Institute of Technology Pune in May 2018 and worked as an Associate Data Scientist at Pivotchain Solutions Technologies Pvt. Ltd till June 2019 before coming to USC.
Keerti Bhogaraju
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Software Development Engineer
at Amazon Web Services
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Email:
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Address:
Seattle, WA
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Click here to download
my resume
WORK EXPERIENCE
June2020-August 2020
Data Scientist Internship
THE HERO LOOP
During Summer 2020, I joined the Hero Loop team to work on a digital app to locate volunteers for people who needed help in chores such as grocery pickup, dropping to the airport, etc. In order to prevent bad use of the application, I developed a machine learning model for detecting toxic messages and reporting of abuse. [Python, Nodejs]
May 2020-August 2020
Student Researcher
USC VITERBI SCHOOL OF ENGINEERING, CSSE
Working on modifying code2vec and code2seq models for improving representation learning on source code. Learned how to read and summarize a technical research paper. Implemented code2vec, code2seq in Tensorflow 2.x.
July 202- Present
Software Development Engineer
AMAZON.COM
Currently, I am a Software Development Engineer at the Vendor negotiations management team in the Automated Profitability Management Org.
July 2018-June 2019
Associate Data Scientist
PIVOTCHAIN SOLUTIONS TECH. PVT. LTD., Pune, India
After my internship ended, I continued at Pivotchain as a full-time employee for a year.
July 2017-April 2018
Data Science Intern
PIVOTCHAIN SOLUTIONS TECH. PVT. LTD., Pune, India
During my final semester of undergrad, I did my first internship at a company named Pivotchain. It is a data science & analytics startup. I got an exposure on different industry domains in which machine learning and data analytics use cases are developed.
EDUCATION
August 2019-May 2021
Master's Degree
MS in Applied Data Science
UNIVERSITY OF SOUTHERN CALIFORNIA (USC), CA USA
I am pursuing MS in Applied Data Science at USC since Fall 2019. My coursework rigorously covers Foundation of Data Management, Machine Learning for Data Science, Foundations and Applications of Data Mining and Analysis of Algorithms. My current courses include Deep Learning and Data Visualization I submitted my first research paper to the National Communications Association, Annual Conference on obtaining a metric to measure cultural capital of the influencers in social media movements. I participated in the GRIDS USC DataFest competition as well as my first hackathon HackSC. My current GPA is 3.35/4.
August 2014- May 2018
Bachelor's Degree
B.Tech in Computer Engineering
VISHWAKARMA INSTITUTE OF TECHNOLOGY (VIT PUNE), INDIA
I completed my Bachelor of Technology from VIT Pune in May 2018. The curriculum spanned different courses which included basics of Computer Science and Engineering such as Operating Systems, Computer Networks, Database Management Systems, Data Structures, Design and Analysis of Algorithms as well as courses which were relevant to the latest trends in the industry such as Object Oriented Modelling and Designing, Software Engineering, Data Science, etc. During the first semester of the final year, I got an opportunity to do a full-time internship for 6 months at a startup. My overall GPA is 8.79/10.
RESEARCH PROJECTS
Yang, A., Bhogaraju, K., Choi, I. M., Mokhberian, N., & Alipourfard, N. (2020, November). Towards a Measurement Framework of Cultural Capital in Social Mediated Movements: A Computational Approach. Paper submitted to the 2020 National Communication Association Annual Conference, Activism and Social Justice Division. Indianapolis, IN.
SKILLS
Domain Experience
Finance, Retail, Security, Social Science
Programming Languages
Python, Java, C++, C, R
Databases
MySQL, HiveQL, Firebase, MongoDB, DynamoDB
Other Tools & Technologies
Hadoop Spark, AWS, MapReduce, Tableau, Docker, Kibana, Elasticsearch, PyCharm, Eclipse, Jupyter Notebook, Git, GitHub
Frontend
HTML, CSS, JavaScript, AJAX, JQuery, D3.js
Other Skills
Word, PowerPoint, Excel, Docs, Slides, Spreadsheets, Forms
Adobe Spark Video Maker, Prezi
Python Libraries
Machine Learning - NumPy, pandas, scikit-learn, SciPy, pyspark, pyhive
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Deep Learning - TensorFlow, Keras, OpenCV
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Visualisation - matplotlib, seaborn, plotly
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Other - Luigi, crontab, pyhive, reportlab, Flask, Anaconda
Operating Systems
Linux, Windows, WSL
Languages
English(daily use), Marathi, Hindi, Telugu (mother tongue)
TECHNICAL PROJECTS
Customer 360
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Generated an overall customer view using geolocation, digital wallet transactions leading to behavioral and other psychographic parameters, to create targeted strategies through customer segmentation
Detecting unattended luggage in public places
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Trained an end-to-end AI module for detecting unattended objects in public places and raises an alert in real-time, attaining test accuracy of 76%. Implemented model compression to execute it on CPUs in real-time and retained output within 2 seconds
Smart Traffic Analyzer
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Prototyped a front-end user interface in JavaScript, HTML, and D3.js for vehicle detection, tracking and automated analysis of vehicle traffic at road intersections captured through video feeds. Added graphical interface for visualizing the analysis in the form of pie charts, histograms and road maps
Tracking Coastal Changes at Catalina Island
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Performed visualization on 20 years of time-series temperature of Catalina Island to recognize patterns and seasonality trends in variations of ocean temperature. Won Best Poster Award at GRIDS USC Projects presentation among 20 other projects.
Measurement Framework of Cultural Capital in Social Mediated Movements
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Obtained a metric to measure cultural capital of influencers in social media movements using exploratory factor analysis in Python. Submitted as a research paper to the National Communication Association Annual Conference, 2020 as second author. Won the Best Interdisciplinary Data Science Team prize at GRIDS USC CKIDS DataFest 2020
Offline Handwritten Character recognition
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Programmed a framework for extracting handwritten fields of different cheque formats achieving an accuracy of 80%
Business rating Prediction on Yelp dataset
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Designed a hybrid recommendation system on predicting user rating on businesses. Improved the model by reducing the RMSE error rate from 0.23 to 0.18
Gross Merchandise Volume for Merchants of Digital Wallet App
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Produced comprehensive analysis report from sales statistics of 200 merchants associated with a digital wallet app. · Retrieved raw tables with 3 billion records from HDFS, queried using HiveQL and identified non-profitable merchants
Optical Character Recognition for government recognized documents
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·Built a framework for extracting biographic details such as name, unique citizen ID number, date of birth from images of government identification cards