***** ****** *****

Irvine CA ***** MOIN AMINNASERI

U.S. Citizen

949-***-****

ac0gkw@r.postjobfree.com

EDUCATION

Irvine, CA University of California, Irvine Fall 2015-Winter 2017

● Master of Science in Networked Systems, G raduated April 2017. GPA: 3.8/4.0 Notable graduate courses: Machine Learning, Network Security, Social Network Data Analysis, Natural Language Processing, Neural Networks and Deep learning, Middleware for Distributed Systems Tehran, Iran Sharif University of Technology Fall 2009-Fall 2014

● B.S.E. in Computer Software Engineering, Graduated Feb 2015. Notable courses: Data Structures, Design of Algorithms, Database Design, Web Design, Object Oriented Systems Design EMPLOYMENT

Research Assistant University of California, Irvine Spring 2016 – Winter 2017 Developing Augmented Reality applications in C# using Unity engine and deploying them on Microsoft Hololens. Demonstrating holographic visualizations of linear algebraic concepts, to familiarize students with tensors as a new approach in solving machine learning problems.

Research Assistant University of California, Irvine Fall 2015 – Spring 2016 Back-end implementation and database design and manipulation of the web application using Django framework and Postgresql database, deployed on a PaaS named Heroku. This application provides a crowdsourcing platform to gather an enriched database of plants for further machine learning and data analysis. Data Mining, Intern Avisa Corp. Fall 2014 – Spring 2015 Given one year of customers transactions, provided a classification model to predict repeated buyers of the products with promotional offers with approximately 60% accuracy. Notable tasks: polished raw data reducing its size by 87%, data visualization(Weka), feature engineering, generated suitable train and test files for V owpal Wabbit data mining tool. TECHNICAL EXPERIENCE

● Natural Language Processing ( 2017). Word embedding with a new matrix factorization method to reduce memory complexity on high-rank sparse matrices. Also hands-on experience in Sequence tagging (part of speech and named entity recognition), language modeling, machine translation, and semi-supervised text classification.

● Neural Networks and Deep Learning ( 2017). Music genre detection using a two layer Neural Network with convolutional LSTM, taking only soundtrack files as input. Implemented procedures to interact with Spotify’s RESTful API and acquired preview songs along with their metadata as our dataset. After extracting Mel Frequency Spectrogram of input files, fed them to the Neural Network. Trained the model on a 6GB GPU and achieved an accuracy of 62%

● Implementation of Machine Learning Algorithms ( 2016). Implement of detailed r andom forest (with accurate entropy) and s tochastic gradient descent (with customized changes on steps and batches) to gain better accuracy. Predicting whether there is rainfall at a certain location, based on (preprocessed) infrared satellite image information. Exploring the data and analyzing the bagged results came up with AUC score of 0.655 and ranked in top 50 on K aggle. ADDITIONAL EXPERIENCE

● Web Scraper ( 2012). I mplemented scrapers on specific shopping websites and spread information about updates, new offers, and new items on the pages via email. Python

● Network Security: ( 2015). Implemented a DDoS attack mitigation method on HTTP layer, mounted on victim server, simulated HTTP flood attacks. Processing IP, URL, TimeStamp with a fast enough algorithm to minimize the overhead, and filtering out the attackers, Python, Java, AsterixDB, XML SKILLS AND TECHNOLOGIES

● Python; C++; C#; R; Java; SQL; JavaScript; HTML5; CSS3; PHP; Hive (In order of expertise)

● Visual Studio; MySQL; PostgreSQL; AWS; Weka; AsterixDB; Django; Unity; Hadoop; iPython;