About me
A small introduction about myself
Arindum Roy
Grad Student from Atlanta, Georgia.
I was born in the city of Bhubaneswar, India. I have an inquisitive attitude and I like to question the various things that happen around me. My career objective is to use my knowledge of Computer Science, for the development of applications that tackle the plethora of real- world problems that we face as a global community.
In my free time, I like to quiz and debate. I have been to several national level quizzes and parliamentary debates across India, and have learnt a lot from my experiences.
Technical Skills
I have throughout the course of my undergraduate years, predominantly worked with implementing machine learning algorithms in Python. I have worked on numerous projects that involved the building and deployment of recommendation systems, and of late, I am involved in the scaling of machine learning algorithms for implementation on large datasets, using Python. Throughout the term of my coursework, I have also been involved in subjects like operating systems design and embedded systems. I am also adept at working with databases and have experience in PostGRESQL, MySQL and SQLite.
Work Experience
Aug,2018
University of New Brunswick, Canada
Mitacs Globalink Research Intern
I am worked under Professor Suprio Ray, on scalable machine learning algorithms in Python, and the use of Language Integrated Querying with large databases that may either be structured or unstructured. We undertook the added challenge of handling out-of-memory datasets and materialized an approach in which these changes could be applied to existing codebases as well, with minimum code rewriting.
July, 2017
Indian Institute of Technology, Kharagpur
Summer Research Intern
I worked under Professor Debasis Samanta on the Data Extraction process of Recommendation Systems and designed a Feature Extraction System in Python, that used a recursive web-based crawler to return candidate research papers from search results, and then used CRF method of pattern recognition to extract various features from these papers.
August, 2016
Battle of Minds
Senior Question Designer
I was in charge of designing quiz questions on various genres, for an app based quiz show, which was meant for people of all age groups. Through this experience I was able to get an insight into the cognitive levels of various age groups, while satisfying my hunger for knowledge at the same time.
Education
Present
Masters of Science in Computer Science
Georgia Institute of Technology, Atlanta
Subjects undertaken:
Grade Point Average:
June 2019
B.Tech. in Computer Science and Engineering
National Institute of Technology, Rourkela
Subjects undertaken: Algorithm Analysis and Design(CS 332), Data Structures and Algorithms(CS 102), Database Management Systems( CS 201), Principles of Programming Languages(CS213), Theory of Computation(CS331), Compiler Design(CS 431), Computer Organization and Architecture(CS242), Operating Systems Design(CS334), Microprocessors and Microcontrollers(CS341), Data Communication(CS321), Information Theory and Coding(CS430) Discrete Maths(CS211), Computer Graphics(CS335), Computer Aided Design(ME421).
Grade Point Average: 8.61/10
June, 2015
senior secondary education (science)
Mother's Public School, Bhubaneswar
Subjects undertaken: Physics, Chemistry, Maths, Computer Science, English.
Percentage: 95.8
April, 2013
secondary education
St. Joseph's High School, Bhubaneswar
Subjects undertaken: Physics, Chemistry, Maths, Computer Science, Biology, History and Civics, Geography, English, Odia(Secondary Language).
Percentage: 96.2
Projects
Check out my Github profile!
April, 2018
fake facts detection in social media
Product Development Laboratory (CS368)
An Android app was developed that can be used to determine whether a fact is true or fake. With a reputed data set, an aggregate of various classification algorithms were used to learn the distinction between fake facts and real facts, and this model was stored on a Raspberry Pi server which can be accessed via an android app so that for any article given to it as input it can classify it as either fake or real.
November, 2017
optional elective recommendation system
Product Development Laboratory (CS367)
It employs a combination of Content-based and Collaborative filtering to recommend various Optional Electives taught in our institute to students, based on their preferences and likes by collecting data from previous students and applying a learning algorithm on them.
July, 2017
text-based recommendation system
Summer Internship Project
A web based recursive crawler was designed using Python, that has a GUI which takes input, crawls Google Scholar to download relevant research papers, extracts meta-data from these papers using CRF method of pattern recognition, and finally recommends papers to users, based on a set of features( author name, number of citations, author credibility etc) using a machine learning based filtering approach.