Data Scientist, Computer Vision Engineer, Image Processing

AMITESH KUMAR SAH

**** ******* ******, **. *****, Missouri 63139 • +1-929-***-**** • ******@***.***

EDUCATION

New York University, Tandon School of Engineering, New York Sept 2015-May 2017

Master of Science in Electrical Engineering (Computer Vision and Data Science), GPA: 3.47/4

National Institute of Technology, Warangal, India Aug 2011- May 2015

Bachelor of Technology in Electrical and Electronics Engineering, 8.08/10

TECHNICAL SKILLS

Software and Programming: Expertise in C++, Python (numpy, scipy, pandas, scikit-learn, matplotlib, OpenCV, scrapy), Matlab,Tensorflow(Deep Learning), Linux OS, git version, Shell Scripting

Big Data Platform: Apache Spark, Apache Hadoop (MapReduce), PySpark,

Mllib Exploratory and Reporting tools: MySQL, PostgreSQL, Tableau

Cloud Technology: Amazon Web Services, EC2 instances, S3, MapReduce(EMR), HPC Cluster, Azure

GRADUATE LEVEL COURSES

Machine Learning, Data Structures and Algorithms, Big Data, Probability and Stochastic Process, Computer Vision, Image and Video Processing, Advance Digital Signal Processing, Medical Imaging.

PROFESSIONAL EXPERIENCE

Strayos, Saint Louis, MO June 2017- October 2017

• Software Engineer - Defined and implemented technical roadmap on automation of GCP marker detection using Convolutional Neural Network in Tensorflow and python.

• Complete migration of Strayos app end to end from Amazon AWS to Microsoft Azure.

• Developed algorithm to create pointcloud, textured 3D model from UAV drone imagery in C++ NYU

Stern School of Business, Marketing Department, NY August 2016 –May 2017

• Research Assistant-Data Scientist– web scraping, collecting unstructured text data and image data from the web (e-commerce and social-media website), and used their posts and hash tags to perform an analysis related to sentiments about brands and products. Used scarpy, python.

Pixie Scientific, New York April 2016-August 2016

• Intern- Data Scientist and Image Processing – Improved the segmentation accuracy to 93% from 84% when tested in 40,000 pixie pads and successfully extracted features from the reagent.

• Used SVC – one vs all classifier for 5 classes and carried out lots of cross-validation in Python

PROJECTS

NYC Crime 2006-2016 Factbook (Big Data) Feb 2017 –April 2017

• Validated hypothesis such as finding top 3 best places to live how crime Rate is dependent on unemployment rate, poverty rate, Median income. Used Hadoop MapReduce, Tableau, Pyspark Object

Detection and Localization and Multi-Class Classification Sept 2016-Nov 2016

• Used Caltech 101 and 256 datasets, where total images were 8677 and 29780 resp.

• Performed Feature Extraction using SIFT, Clustering for CDG, training the classifier and discriminative for the object classification and Hierarchical Segmentation for object localization

Computer Vision and Image Processing Projects Jan 2016-May 2016

• Optical Flow, shape from shading, Baseline JPEG Image Compression

ACADEMIC SCHOLARSHIPS

• Compex Nepal Scholarship ( 2011- 2015) : 100% scholarship in Undergraduate.

• Merit Based NYU Scholarship (2015-2017) for graduate studies

Contact this candidate