Software engineer with hands-on knowledge of applying Machine Learning, Deep Learning, NLP to solve problems, implement Web apps and Automation Tools using Python. I have total 7 years of experience in developing Applications and more than 3 years in Machine Learning.
Summary
Work Experience
Qualcomm
Senior Engineer
March 2017 - Now
- Change Based Testing
- Trained a** Random Forest Classifier **to identify the Software Test cases that need to be executed based on the files and functions changed between two software builds. Model is able to find 90% of the regression issues using the predicted test cases.
- Duplicate Bug Detection
- Developed a** Word2Vec based Document Similarity Model** to identify the duplicate bug. Applied custom preprocessing to clean unstructured bug text data. Able to find 20-50% of duplicate Bugs.
- Coverage Based Testing
- Implemented Software Test Case Prioritization Algorithm to identify the Software Test cases that need to be executed based on the code changes between two software builds using Code Coverage .
- Developed a tool using libclang to capture Code Coverage on memory constrained build.
- Software Test Reporting Web Application
- Designed and developed Software Test Reporting Web Application using** Flask Framework**. Tool helps in tracking test coverage ,querying test case execution history and generating accurate reports.
- Applied Clustering to group the similar test cases.
- Deployed web and REST API applications on Ubuntu machines using Nginx and UWSGI.
Oracle
Application Developer
July 2015 - March 2017
- Reduced the load time of various invoice management and payment web pages by making performance fixes.
Education
Indian Institute of Technology, Kanpur
Electrical Engineering - M.Tech - Signal Processing, Communication and Networks
2013 - 2015
- CGPA - 9.25/10
Kakatiya Institute of Technology and Sciences, Warangal
ECE - B.Tech
2009 - 2013
- Percentile- 90.6/100
Skills
Programming and Tools
Python
Flask
GIT
SQL DB
Elasticsearch DB
C
JAVA
Docker
Data Science Skills
Tensorflow
Keras
Scikit-learn
NLTK
Pandas
Matplotlib
NumPy
CNN
RNN
LSTM
Regression
Classification
Ensemble Models
Data Preprocessing
Feature Engineering
Courses and Certificates
DeepLearning.AI Natural Language Processing Specialization.
coursera
Machine Learning A-Z™: Hands-On Python & R In Data Science
udemy
DeepLearning.AI TensorFlow Developer
Coursera
Publications
- R. Tripathi, B. Mohan and K. Rajawat, "Adaptive Low-Rank Matrix Completion," in IEEE Transactions on Signal Processing, vol. 65, no. 14, pp. 3603-3616, 15 July15, 2017, doi: 10.1109/TSP.2017.2695450. URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7903718&isnumber=7924436