MOIN AMINNASERI

***** ****** **** *****, ******, CA 92617 H: 949-***-**** ac0jn0@r.postjobfree.com

http://www.ics.uci.edu/~maminnas/

Recently graduated Computer Scientist with deep expertise in database design, collecting datasets and solving machine learning problems. Proven ability to identify business needs and develop valuable solutions to drive accuracy and process efficiency. Seeking an opportunity to drive business effectiveness through making recommendations based on data findings. Dedicated and hard-working with a passion for Big Data. C++ and Python specialist

High proficiency in SQL

Advanced knowledge of statistical models

Data visualization with R and python

Extensive knowledge of machine learning

Hands-on experience with scikit-learn, pickle,

pandas, Tensorflow, and Keras

Knowledge of Hadoop ecosystem

Master of Science: Networked Systems, Winter 2017

University of California, Irvine - Irvine

Emphasis in Data Science, 3.8 GPA

Notable Courses Machine Learning, Network Security, Social Network Data Analysis, Natural Language Processing, Neural Networks and Deep learning, Middleware for Distributed Systems Bachelor of Science: Computer Engineering, 2015

Sharif University of Technology - Tehran, Iran

Research Assistant, 04/2016 to 01/2017

University of California Irvine – Irvine, California, United States Developed an Augmented Reality application in C# using Unity and deployed it on Microsoft Hololens. Illustratiing linear algebraic concepts and visualizing data in holograms PROFESSIONAL SUMMARY

SKILLS

EDUCATION

WORK HISTORY

Research Assistant, 10/2015 to 04/2016

University of California Irvine – Irvine, California, United States Built, tested and deployed scalable, highly available database of Plants on PostgreSQL. Automated polishing and importing initial data from .csv files using bash and python scripting. Conceptualized, planned and executed back-end of a crowdsourcing web application using Django framework to enrich the Plant database for future machine learning purposes. Neural Network Project, 01/2017 to 04/2017

Music Genre Detection with Deep Learning – Irvine

Interfaced with Spotify's RESTful API to gather dataset of MP3 files. Trained a novel approach of convolutional LSTM Neural Network paralleled on GPU Achieved competing accuracy according to literature review on genre detection Natural Language Processing, 01/2017 to 03/2017

Word Embedding – Irvine

Implemented a novel approach based on matrix factorization Resulting in more compact representation, time/complexity reduction, and improved accuracy in linguistic tasks of similarity and analogy.

Acquire Valued Shopper, 09/2014 to 02/2015

Kaggle – Irvine

Created effective model to predict repeated buyers, after they have bought products with promotional offers. Polished and extracted relevant data for training reducing 87% of the size Feature engineering by analysing and Investigating influential factors Trained model with quantile regression on Vowpal Wabbit and ranked among top 10% of the leader board Proven ability of mining hidden gems in data and targeting them for business profits