1. KUNAL LALWANI
LinkedIn: linkedin.com/in/kunal-lalwani E-mail: kunal4.lalwani@gmail.com
GitHub: github.com/kunal-lalwani/projects Phone: +1-619-576-6066
Website: kunal-lalwani.github.io
Actively Seeking Internship or Full-Time Employment as Data Scientist
Academics
Master of Science in Computational Science at San Diego State University, CA (GPA: 3.9/4) May 2019
Bachelor of Technology in Information Technology at Manipal University, India (GPA: 3.1/4) May 2017
Technical Skills
• Recommendation Based System • Data Visualization • Artificial Intelligence
• Machine Learning and Deep Learning • Parallel Programming • Data Mining and Analytics
Work Experience
Data Science Intern at Fōkcus, San Diego August 2018 – Present
Technology Stack: Python, Tensorflow, Scikit-learn, Pandas, Decision Trees, AdaBoosting, Support Vector Machine
• Embedded inside a dynamic startup culture for Planning, Storytelling, and Execution; ensure a healthy foundation of Startups
• Implemented Data Wrangling and Feature Engineering for a Score based Matching and Recommendation System; Performed
Statistical Analysis and developed a rules-based Decision Tree Predictive model to match 986 entrepreneurs with mentors
Deep Learning Intern at Smart Property, San Diego February 2018 – July 2018
Technology Stack: Python, Keras, Tensorflow, Scikit-learn, Pandas, CUDA, Convolutional Neural Networks, Git
• Provided a software-as-service that provides continuity and accuracy over the life and maintenance of property assets
• Exploited the distributed features of the cloud based services in the training model on Microsoft Azure with 21,564 images
taking less training with an accuracy close to state-of-the-art accuracy, 80%
Software Developer Intern at SAP Labs, India January 2017 – June 2017
Implemented business logic using Java Multithreaded Programming and Design Patterns, graphical user interface, and design
documents for various financial products. Also worked on Data Analysis and enhancements on change requests
Project JSync
Technology Stack: JAVA, Parallel Programming, Multi-threading, OpenMP, MPI
• Sped the file transfer process by 8 Times after developing a Platform Independent Version Control application
• Worked on socket programming, concurrency issues and application design, with focus on compressing/decompressing large
directories using parallel compression-streams and sending/receiving them serially over a socket stream.
Project Bug Tracking Dashboard
Technology Stack: Tableau, R, D3.js, Chart.js, SQL, Sybase Database
• Created and launched an analytic web page, which measured and increased the performance of the team by 200%
• Developed queries to access their quality tracking database and provide information that could help each team track their
weekly, quarterly, and yearly performance for all customers and highlight important/delayed bug-fixes
Software Developer Intern at Wipro Limited, India June 2016- August 2016
Technology Stack: Robotic Operating System(ROS), OpenCV, Python, C++, Neural Networks
• Developed object localization algorithms through convolutional neural networks for deployment of Autonomous Car
• Implemented a Selective Search and Sliding Window based approach to localization; Trained a CNN on ROS to place Bounding
Boxes over objects of interest with a classification accuracy of 92.86%
Research and Assistantship
• Thesis at Edwards Lab SDSU: Isolation of Metagenomes using Unsupervised Random Forest Clustering for Gene Analysis
• Researcher at Language Acquisition and Resource Center: Analysis of Technical papers by Natural Language Processing
• Teaching Assistant to prepare classwork activities for Machine Learning, Graph Theory and Mathematical Modelling course
Projects
• Airline Service, Good vs Bad!: Performed Sentimental Analysis for 6 major US airlines hence classified the customer reviews
• Popular Birth Names: Analyzed and Visualized the trends in births names from the SSA-US birth website’s 100 years data
• Best Airport to fly? Using the time delay, weather conditions and shortest distance to travel predicted the best airport in US
• Queens on Chessboard: Solved the N-Queen Artificial Intelligence problem using Constrained Optimization Techniques
• Winner of Qualcomm AI Hackathon’18 for American Sign Language Image Classification achieving accuracy of 100%
Languages : Python, Java, Julia, R, MATLAB, SQL, C, C++ Libraries : Numpy, OpenCV, Pandas, Scikit-Learn
BI Tools : Tableau, Crystal Reports, Excel Project Management : SVN, Git, Agile, SDLC, Jira
Database : MySQL, Oracle DB, SQL Server Parallel Computing : CUDA, MPI, OpenMP
Framework : Keras, Caffe, Tensorflow, Theano Big data Tools : Hadoop, Spark, AWS, Kafka, Cassandra
Personal Website
