About myself

I'm a perfectionist. There, I said it. As a life-long musician, perfectionism is an intrinsic part of my personality now - something that has overlapped into other facades of my life as well. Its a quality that goes hand-in-hand with patience, relentless obsessiveness, and sleepless nights; all in all, a perfect combination for a grad student!

I love data science - I have dabbled with data science projects in PySpark/Spark, Python, MATLAB, and R. My experience interning at Mad Street Den has given me a lot of exposure to writing MapReduce jobs in PySpark/Spark.

I also enjoy core backend development; I have coded quite extensively in Java, C++, and Python, and have experience building a large scale API in Scala as well. I've done a lot of web design over the years as well, and am comfortable working with Javascript/HTML/CSS. Check out some of my projects below!

Reach me at

Vikaasa Ramdas
3800 SW 34th Street, Apt EE 309
Gainesville, FL 32608 US

+1 (949) 505-9907
vikaasaramdas@gmail.com

Education

University of Florida, Gainesville

Master of Science in Computer Science graduating May 2017

Grade Point Average (GPA): 3.67
Courses taken: Analysis of Algorithms, Distributed Operating Systems, Data Mining, Human Computer Interaction, Pattern Recognition, Advanced Datastructures, Statistics, Bioinformatics, Computer Networks.
Organizations part of: UF Data Science and Informatics (UF-DSI), Association for Computing Machinery (ACM), Association of Computer Engineers (ACE)

Sri Venkateswara College of Engineering, Anna University, Chennai

Bachelor of Engineering in Electronics and Communication Engineering Aug 2011 to June 2015

Work

Mad Street Den

Data Science Intern April 2016 to September 2016

• Worked primarily on PySpark/Spark, and Python. Designed and implemented an end-to-end NLP project using PySpark, by first building a customized tagger for product descriptions using CRF and feeding this into separate word2vec models, and finally classifying the product based on style and occasion.
• Have also contributed to a map-reduced version of the k-medoids algorithm in PySpark, performed benchmarking tests on PySpark and implemented a unit test framework in PySpark.

Independent Research

Independent July 2014 to November 2014

Creation of Complex Percussion Patterns in Indian Classical Music Using Sparse Representation Learner
Proposed a method to generate complex melodic beat patterns using feature extraction, by mapping melodic patterns to vectors which are then given as input to the Sparse Representation Learner. (paper accepted at IEEE Spices 2015).

Skills

LANGUAGES
Python, PySpark, Spark, Scala, Java, C, C++, R, MATLAB, C#

WEB
JavaScript, HTML5, CSS

DATABASES
PostgreSQL, MySQL

TOOLS
InVision, Adobe Creative Suite, Git

LIBRARIES
STL Libraries, OpenCV, cvx-opt, scikit-learn (Python), pandas (Python), akka toolkit (Scala), spray toolkit (Scala), gensim (Python), NLTK (Python), textblob (Python)

Projects

Implemented a project that uses the Yelp Dataset to predict trends and future business attention, and identify potentially lucrative business locations for different business categories.

Designed a mobile/web application to onboard users to new cultures and mitigate culture shock through gamification.

Event Counter using Red Black Tree

Java Mar 2016

Implemented an Event Counter using a Red Black Tree in Java, which reads redirected input from a text file, executes different commands on the data, and prints the results.
The program was tested successfully with an input text file containing 100 million records.

Designed a prototype of a mobile news app called 'HappyFeed', based on user research.

Facebook REST API Simulator

Scala Dec 2015

Designed a client-server simulation model of the Facebook REST API supporting over 10000 users using spray-can and akka actor model and simulated features like profile, friend list, photos and albums.
Implemented end-to-end security using a combination of AES and RSA public key cryptography techniques.

IMDb movie analyzer tool

R, Python Dec 2015

Created a tool as the lead team member to predict genre of movies from a dataset extracted from IMDb containing 17000+ records. Performed text mining on the dataset to build new features.
Developed routines to perform classification, find association rules and cluster similar movies together.

Implementation of Gossip, Push-Sum Algorithms and Chord protocol

Scala Oct 2015

Implemented gossip, push-sum algorithms and chord protocol with an object access service.
Calculated and analyzed the convergence rate in different topologies for gossip and push-sum algorithms.

Bit-Coin Miner

Scala Sep 2015

Implemented Bit Coin Miner using akka actor model in Scala

Offline Multilingual Handwritten OCR using NMF and Sparse Representation Learner

MATLAB Mar 2015

Developed an application to perform OCR for three Indian languages (Tamil, Telugu, and Hindi), using NMF as the dimensionality reduction tool and Sparse Representation Learner as the classifier.
Created customized feature extraction techniques to map the character images from matrices to vectors.

Creation of Percussion Patterns in Indian Classical Music using Sparse Representation Learner

Research paper accepted at IEEE Spices 2015 Nov 2014

Proposed a method to generate complex melodic beat patterns using feature extraction, by mapping melodic patterns to vectors which are then given as input to the Sparse Representation Learner.

Behaviour Profile Assessment tool

VBA July 2014

Developed a tool to perform Behaviour Profile Assessment for a large number of subjects and to analyze the data collected in detail, using the DISC model of four factors, subsequently printing the results as a report.

Publications

Sudarshan Babu and Vikaasa Ramdas, "Ensembling Sparse Representation Classifiers through Layers of Support Vector Machines", to be published in the proceedings of the 15th IEEE International Conference of Machine Learning and Applications (ICMLA), Anaheim, USA 2016.

Workshops

PySpark Workshop, Vellore Institute of Technology (hosted)

Hosted a PySpark Workshop in Vellore Institute of Technology (VIT), on August 13th 2016.
Built a project to classify speeches by presidential candidates Barack Obama and Mitt Romney using PySpark, to demonstrate to the students the different aspects of building an end-to-end NLP project. These included teaching the students data cleaning and munging routines as a series of map and reduce operations, extracting n-grams, building word vectors, and finally, implementing the pipeline for the machine learning algorithm.
Explained to the students PySpark concepts related to broadcast variables, accumulators, and writing UDFs for Spark Dataframes and map functions for RDDs.
Also gave a brief overview of setting up AWS EMR cluster for running PySpark jobs and defining the different user configurations for setting up the cluster.

        MUSIC

I'm an Indian Classical instrumentalist playing the electric mandolin for over 16 years, and am a disciple of the renowned Mandolin U. Shrinivas and his brother Mandolin U. Rajesh.

Do check out my YouTube channel and my website, www.mandolinramdas.com