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HTML, CSS, JS, Python, Matlab, Java, C, C++, MySQL, php, VB

Location:
Tempe, AZ
Posted:
March 09, 2018

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Resume:

SUMMARY

Computer Science graduate student with sundry certifications, with in-depth knowledge and strong fundamental concepts in data structures and object-oriented programming, actively seeking summer 2018 internship opportunities as a Software Engineer Intern.

ACADEMIC EDUCATION

Master’s in Computer Science Expected May ‘19

Arizona State University, Arizona, United States

Relevant courses- Statistical Machine Learning, Multimedia & Web Databases, Foundations of Algorithms, Software Process Management, Quality Management, Risk Management

Bachelor’s in Computer Engineering May ‘17

K. J. Somaiya Institute of Engineering and Information Technology, Maharashtra, India GPA: 3.6/4.0

Relevant courses- Artificial Intelligence, Big Data Analytics, Database management, Object oriented methodology, Data structures

TECHNICAL SKILLS

Tools- Flask, Hadoop MapReduce, Anaconda, phpMyAdmin, AutoCAD, Visual C++, Eclipse

Programming Languages- Python, Matlab, C, C++, VB, Java, PHP

Databases- MySQL, MongoDB, Redis

Design Languages- HTML, CSS, Bootstrap, JavaScript

Certifications- Artificial Intelligence- Knowledge Representation & Reasoning, Introduction to Machine Learning, Programming, Data Structures & Algorithms using Python, Python for Data Science, Introduction to Web Design and Development,

Web Development Foundations

PATENT

Fast and Secure In-Memory Database for Internet-of-Things (PSP-IP Complete Patent Application No. 201*********) April ‘17

The method includes- requesting data by calling HTTP API, reading entire data store in secondary storage in pages, predicting using the data frequency prediction module, analyzing the filter queries and requested data to determine a pattern for predicting that future data will be requested, wherein said pattern depends on the request frequency and vitality of the data and prediction score.

EXPERIENCE

Cyber-Socio Intelligent Systems (Graduate Services Assistant- Software Development) Feb ’18 - Current

Responsible for developing customized crawlers and parsers to scrape data from different websites using Tor browser for private access.

Crawler implementation using Selenium and Mechanize crawlers.

Parser implementation using Python, PyCharm, and Beautiful Soup to create parse trees and extract data.

Clifey Innovations (Intern Developer) July ‘15 - October ‘15

Performed vulnerability and networking scanning assessments.

Defended system against unauthorized access, modification and/or destruction.

Performed fraud detection based on user location data by Machine Learning algorithms.

PROJECTS UNDERTAKEN

Artificial Intelligence powered In-memory database (Python, Flask, MySQL, NoSQL, Redis, Waterfall) August ‘16-April ‘17

Designed regex to process user-friendly natural language queries and map to database-readable queries.

Implemented data requesting by HTTP API call with additional flexibility for query filtering, wherein the requested data is inserted into rings (primary memory) and the filter queries are analyzed to determine a pattern.

Developed linear regression model, apriori cluster model to learn trends of input query based on frequency of data call and pattern of called filter queries. This pattern analyses results in prediction of future data to be requested.

Ameliorated Anomaly Detection Algorithm (Python, Matlab, Agile) August ‘17 – December ‘17

Standardized and preprocessed data, utilized feature extraction strategies along with implementation of algorithms and analyzation of results.

Implemented anomaly detection techniques like k-nearest neighbor, one-class SVM and Eta one-class SVM on KDD dataset and Breast Cancer dataset.

Recommendation System (Python, Agile) August ‘17 – November ‘17

Demonstrated data rendering in a vector model and provided an insight about how well the features describe, discriminate or show similarity with the objects in a dataset.

Implemented various decomposition algorithms for grouping similar data and using page rank algorithm for quantifying relevancy of data for accurate recommendation.



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