SUDIPTA SWARNAKAR

312-***-**** •ac4412@r.postjobfree.com• https://my-static-aininja-site-example.herokuapp.com/index.html https://www.linkedin.com/in/sudipta-swarnakar-125a8065 • https://github.com/sswarnakar ACADEMIC BACKGROUND

2016 -2018 Illinois Institute of Technology Chicago, USA Master of Science in Computer Science

2010 -2014 West Bengal University of Technology Kolkata, India Bachelor of Technology in Electronics & Communication Engineering WORK EXPERIENCE

2017-Present Fulcrum Global Technologies Chicago, USA Data Science Intern

Ø Built a predictive model which helps Law Firms to innovate Client’s Intake Process using Machine Learning. Ø Processed large scale time series data given by the LexisNexis and Westlaw and applied statistical modeling for features detection in order to train the final predictive model using Artificial Neural Network. Ø Worked on a recommender system model using machine learning which recommends highest profitable clients internally to the firms. Ø Our current research indicates that our model has the capability to innovate the way Law firms do business and will result in 20-30% increase in profit by predicting the risk matrix and Client's Indicator Score(CIS) which help to identify the potential clients. Ø Our work and techniques believed to be novel and unique so now it’s the subject of a pending patent application. 2014-2016 TATA Consultancy Services, Cisco System Mumbai, India Machine Learning Software Engineer

Ø Worked as Machine learning engineer to generate insights and improve business operation for Cisco System. Ø Built Recommender system for Cisco Commerce Workspace(CCW) users to recommend products which resulted in 10% increase in revenue. Ø Helped to pipeline massive data-streams in distributed computing environments such as Hadoop and Spark. Ø Worked with senior engineers to develop high-quality software that is robust and reliable. Ø Analyzed and resolved source code bugs in Cisco System e-commerce application(CCW) used globally by 10000+ customers due to which clients reported profit of $6 million postfix.

TECHNICAL SKILLS

Programming Languages Python, C++, JAVA, SQL, Unix/Linux Scripting Frameworks and Libraries R Studio, Tableau, Tensorflow, MySQL, Gitlab CI/CD, Numpy, Pandas, Docker, PostgresSQL, GraphQL,Elasticsearch, MongoDB Distributed and Parallel Computing AWS, Google Cloud, Chameleon, Azure, Hadoop, Spark, Hive, HBase, GPGPU Computing, CUDA PROJECTS

2017 lifeguard.IO: A Real Time Drowning Detection System, Harvard University Ø Built a software pipeline for drowning detection system using 3D Convolution Neural Network and Computer Vision. Ø Achieved 92% accuracy and 91% precision and recall on unknown test video footages. Ø Recognized as the grand prize winner at the Hack Harvard 2017 by Microsoft. 2017 Loomo Robo: A Life Companion, MIT

Ø Built a running companion for elderly people using Loomo Segway Robot provided by Singapore and MIT Alliance Research and Technology (SMART). Ø Trained the Loomo robot and integrated several features like voice input, real-time object detection using computer vision and Deep Learning. Ø Acknowledged as the grand prize winner at the MIT Hacking Medicine 2017. 2017 Crime Prediction in Chicago, Illinois Institute of Technology Ø Built a crime prediction engine with 92% accuracy using machine learning to get real time updates on crime rates in Chicago area. Ø The machine learning model was trained on collected dataset from data.gov. 2017 LIFE.TECH: A Real Time Arrhythmia Detector

Ø Built a real time Arrhythmia detector using machine learning and statistical modeling. Ø Collected heartbeat data using ES8266 sensor and pushed to AWS which had RDS instance running with MySQL. Ø The model was trained using Artificial Neural Network with an accuracy of 98% and a precision and recall of 96%. 2017 Visualization of Google’s Genomic Data using PCA and Apache Spark Ø Called Genomics API using gRPC and then preprocessed the petabytes of genomic data using Apache Spark for statistical modeling. Ø Applied Principal Component Analysis on the preprocessed data for clustering gene expression data. 2017 Prediction of Ride Duration for Taxi Trips in New York City, Kaggle Ø Analyzed NYC Yellow Cab trip recorded data and found correlation between variables. Ø Used K-Means algorithm to compute geo-cluster pick up and drop off. Ø Achieved 95% accuracy with XGBoost and Random Forest algorithms. 2017 Heal App: An Uber for people in need

Ø Built an IOS application which provides uber-service for caregivers to reach out to people who are in need during difficulties Ø Acknowledged as the grand prize winner at Hack Illinois 2017. 2017 Performance benchmarking for CPU, GPU, Memory and Disk in Large Scale Distributed System Ø Wrote several scripts to benchmark performance for each devices in parallel and multithreaded environment. Ø Later used all captured performance measurements and expenses to analyze private cloud vs public cloud system setup and cost for small to large scale data centers.

VOLUNTEER EXPERIENCE:

Association of Computing Machinery (ACM)

Our main goal is to create a culture of Education, Mentorship and Collaboration in-order to uniting students with the field of Computing. Knapp Entrepreneurship Center @ Illinois Tech

Served as a member of the Knapp Entrepreneurship Center which offers a wide variety of supportive services for startup and small businesses located Illinois.