Maunil Vyas

Graduate Researcher at Arizona State University || Data Scientist at American Express || Seeking Full time Opportunities

I am Maunil Vyas, a graduate student in Computer Science at Arizona State University (ASU). I believe that for the foreseeable future, automation and Artificial Intelligence will be the biggest contributors to the betterment of society. Therefore, I work in the field of Machine Learning (ML) and Deep Learning . My primary area of interest lies in the applied and theoretical aspects of ML. Specifically, in the theoretical aspect, I desire to understand the learning mechanism of the human brain, so that I can build more powerful Neural Network models. On the other hand in the applied aspect, I wish to enable the AI-based technology on a day to day life, therefore, I work in the field of Computer Vision (CV) and Natural Language Processing (NLP) . Apart from ML, I mostly work on improving my Software Development skills to improve as a developer.

To fulfil my research interest I am currently working in two research labs at ASU.

Research areas (Deep Learning)
1) Zero-Shot Learning (Thesis work) : Recently Submitted my Novel generative model to ECCV 2020.
2) Privacy and Fairness in Machine Learning: Working on generating fair data representation using GANs to preserve fairness as well as data privacy. Work highlights

Currently I am also working at American Express as a part-time Data Scientist.

I will be graduating in May 2020 and seeking full-time opportunities, Specifically in Machine Learning and Data Science fields. I am also open to Software Development.

Please feel free to contact at +1-4403816682 or vyasmaunil33@gmail.com

Education

Italian Trulli

Master of Science in Computer Science

CGPA: 3.96

August 2018 - May 2020

Italian Trulli

Bachelor of Technology in Information and Communication Technology

CGPA: 3.71

August 2014 - May 2018

Experience

Italian Trulli

Data Scientist - Part Time

E-commerce customer retention system: Built a complete internal recommendation system that helps to see the performance of various ML models on daily basis using Kibana, Elastic Search, Pyspark and Hadoop. Dealing with the different aspects of the ML, related to data pipeline building, feature engineering, modelling and performance reporting everyday.

Tech : Python, Pyspark, Hadoop, Elastic Search

Aug 2019 - Cur

Italian Trulli CUbic, Center for Cognitive Ubiquitous Computing

Masters Thesis Student

Zero-Shot Learning for Visual Object Recognition: Developed a novel Generative model to perform Zero-Shot recognition for visual object recognition. Introduced a unique loss that helps to address the overfitting concern of the generative zero-shot model. The work is curently under review at European Conference on Computer Vision (ECCV) 2020 The proposed model leverages the semantic information in a form of either clean attributes or Wikipedia based text to perform the knowledge transfer.

Tech : Tensorflow, Pytorch, Python

June 2019 - Cur

Italian Trulli School of Electrical, Computer, and Energy Engineering

Graduate Researcher

Fair Data Generation: Developed Generative Adversarial Network-based systems to remove the inherent bias from the data set. Specifically, worked with the UCI Adult data set, Further details are discussed in (See my name in the acknowledgement section), Learning Generative Adversarial Representations under Fairness and Censoring Constraints

Tech : Tensorflow, Pytorch, Python

Jun 2019 - Feb 2020

Italian Trulli Speech and Hearing Science

Research Assistant

Data Collection Tools: Implemented web tools to help people label Audio (Speech) data online using Mechanical Turk and Amazon

Tech : Python Flask, Java script, HTML

Transcription Cleaning: Worked on Auto Encoders based models to denoise the transcript data

Tech : Pytorch, Python

Jan 2019 - Jun 2019

Italian Trulli School of Mathematics and Statistics

Instructional Aide

Worked as Instructional Aide for the courses MAT 142: College Mathematics and MAT 266: Calculus for Engineers II.

Oct 2019 - May 2020

Italian Trulli

Teaching Assistant

Being a teaching assistant in the course of Introduction to Computer Programming and Computer Networks, my primary responsibility was to support the professor to conduct the course smoothly. Mainly, I was accountable for taking recitation classes and doing the exam evaluation.

Aug 2017 - May 2018

Italian Trulli

Undergraduate Research Assistant, Program: GUJCOST, DST-UKIERI

ML Based Spectrum Sensing Scheme: I designed an ML-based spectrum sensing scheme for cognitive radio which significantly outperformed the conventional approaches, and published it in PIMRC 2017;

Tech : Python, Keras, MATLAB , USRPs, Disconn antenna

June 2016 - July 2017

Skills

Languages & Database
    Python, C++, C, Java, Shell, SQL, Java Script, Flask, PHP, HTML, CSS, LATEX
Machine Learning (ML):
    PyTorch, TensorFlow, Scikit-Learn, Keras, Jupyter, OpenCV, PDDL, CUDA
Computational Tool & Cloud
    MATLAB, Scilab, Tableau, R, AWS (EC2), Hadoop, Pyspark, Elastic Search
Operating Systems
  • Linux
  • Windows

Publications

Under review at European Conference on Computer Vision (ECCV) 2020 a novel Generative model to address the Zero-Shot Learning for object recognition. - First Author


Artificial Neural Network Based Hybrid Spectrum Sensing Scheme for Cognitive Radio

M. R Vyas , D. K Patel, M. López-Benítez

Proceedings of the 28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communication (PIMRC 2017), Montreal, Quebec, Canada, October 8-13, pp xxx-xxx. (13 Citations, as of March 2020)

IEEE Page

Selected Academic Projects


Fairness Model for Deep Learning

Graduate Course Project - EEE 598: Statistical Machine Learning

Developed a Generative Adversarial Model having a novel Alpha loss to address the fairness concerns in Deep Learning. Specifically, worked on UCI Adult dataset.

Tech : Python, TensorFlow

Aug 2019 - Dec 2019
Team size: 3

Hotel Recommendation system

Graduate Course Project - CSE 578: Data Visulization

Live Demo, Video

Created a web-based visualization system for Hotel Recommendation. I worked on the text mining part of the system. Implemented a sentiment visualization from user comments, developed a word cloud from the sentiments of the comment words. Designed a comment similarity system to find the top comments using the Natural language inference idea.

Tech : Python, NLTK, D3.Js, Javascript, HTML, CSS

Jan 2019 - May 2019
Team size: 5

Drone based surveillance

Graduate Course Project - CSE 591: Perception in Robotics

Video

computer vision application for the surveillance using Drone. The system guides the drone to follow a person, who matches the desired soft features such as color of the cloths. Used Mobile Net for person detection and ResNet for the color classification. The KCF tracker is utilised to track the individual in the video frame. Tech: Python, Pytorch, OpenCV

Tech : Python, Pytorch, OpenCV

Jan 2019 - May 2019
Team size: 4

Natural Language Inference (NLI)

Graduate Course Project - CSE 576: Topics/Natural Language Processing

Modified the attention model of the Decomposable Attention Model for Natural Language Inference Model.

Tech : Python, Pytorch

Aug 2018 - Jan 2019
Team size: 4

Face Recognition Using Reinforcement Learning

Graduate Course Project - CSE 571: Artificial Intelligence

Implemented a paper titled : Face recognition using reinforcement learning .

Tech : Python

Jan 2019 - May 2019
Team size: 2

Designed and Implemented various features of a Compiler for a language

Graduate Course Project - CSE 340: Principles of Programming Lang

Improved my C++ skills by implementing various features for a compiler. Using the basic language grammar, implemented a predictive recursive parsing for Syntax Check, a type checker for Semantic Check and singly link list for program execution.

Tech : C++

Aug 2018 - Dec 2019
Team size: 1

Developed a parallel weight learning mechanism for Neural Networks

B. Tech final year Thesis

Represented the weight learning problem of the Neural Network as a constraint satisfaction problem. Using augmented Lagrangian tried to solve the optimization problem. Successfully trained NN for two-class classification without gradient based back propagation. Python, Theoretical Machine Learning, Mathematical Optimization

Tech : Python, Theoretical Machine Learning, Mathematical Optimization

Sep 2017 - May 2018
Team size: 2

22 Shruti Synthesizer

A project, combines my hobby and engineering

A funded project, aimed to build a music synthesizer for Indian classical instrument Harmonium with a facility of 22 Shruti (“Notes”).

Tech : Python, Scilab, MATLAB, Music-Theory, C++

Aug 15 - May 2017
Team size: 3

GANs + PPCA

My first work with GANs

Generated artificial images using GANs. Worked on techniques to make the Generator network faster using Probabilistic Principal Component Analysis (PPCA).

Tech : Python, Tensorflow, MATLAB

Jan 17 - May 17
Team size: 5

Awards

  • Dean's list ASU, 2018, 2019
  • Stood 4th in Gujarat (State Level) and 24th in India (Country Level), IEEE Xtreme Coding Competition, 2016
  • Standalone – “22 Shruti Synthesizer” –funded by SEAS, Ahmedabad University
  • Received a yearly scholarship (Merit Based) of 10,000/ - INR from Indian Government to support my bachelor studies
  • 22 Shruti Synthesizer, selected for presentation Scilab & OpenFOAM Conference 2018 , Pune, India

Non-technical Interests

Apart from being an engineer, I enjoy most of my time being indoors. Playing my Piano and Guitar in front of a huge crowd is my lifelong dream. I also manage to sing well thus, my passion for music in playing and singing lead me in the world of music recording. I have a small recording studio. Check out my YouTube Channel

After music, I prefer to watch sports, spcifically Cricket. I am MSD Fan.

Last but not least, I enjoy spending time with my family.