• 👋 Hi, I’m @nmathgithub. I graduated with my PhD in mathematics with a focus on partial differential equations (PDEs).

• 👀 I’m currently interested in artificial intelligence, data science, visualization, mathematics, music, and cricket data!

• Specifically, these days I am playing around with the Python wrappers for GLVis and MFEM (finite element libraries). My goal is to be able to apply these visualizations to a system of nonlinear hyperbolic conservation laws.

• 🌱 I’m currently trying to further my understanding of deep learning, artificial neural networks, natural language processing, and computer vision by working on several personal projects.

• Main Project

Implemented a workflow by utilizing AWS cloud infrastructure tools to calculate DORA Metrics (DevOps Research and Assessments) and produce a dashboard in AWS Quicksight to help teams work more efficiently

To accomplish this task, we worked with AWS CDK (in Python) and automated a workflow. We first wrote a chain of three lambdas and connected them via a StepFunction to extract relevant data from Github pull requests and Azure project/pipeline APIs. In the process, we validated the data (by using the pydantic library) and wrote the data to an S3 bucket. A new file in the S3 bucket would trigger a data transfer into DynamoDB (which itself was created by using AWS Glue), which was finally used to produce a dashboard in AWS Quicksight.

• IT Code Jam (Hackathon)

Created a website as a demo for a Personalized Onboarding Experience in four days. This website was built using React.js & Node.js (hosted on AWS Amplify), which would take an individual's name & team as input and produce personalize webpages with relevant onboarding/installation information. As part of this project, we also made sure to implement several layers of security by using AWS Cognito.

Service Management & Automatation Team

Assisted the team in a company-wide release of ServiceNow, a service management tool from the beginning of the process to the Go-Live Phase and beyond. Specifically, I assisted in the discovery & documentation of ServiceNow Configuration Management Database (CMDB), wrote scripts for ServiceNow notifications, and debugged/tested issues with the interface

The second project was part of the "Battle of the Interns," where a group of IT interns proposed a solution and provided a demo to company executives. We created a digital dashboard to streamline prospecting in the bank. In the process, I utilized SQL to explore the data and build visualization in R & PowerBI.

Bank Data Warehouse & Salesforce Team

Helped eliminate techinical debt by doing regression testing for Salesforce (in Apex language). I provided value by increasing the test cases passed from 75% to 93%

As part of the "Battle of the Interns" project", we interviewed several teams across the bank and gauged which teams needed a streamlined service management system. We wrote a 30-page white paper and presented our findings to company executives. The next year, the company implemented ServiceNow, and I was called back to work with the Service Management team.

Alternative World Test Championship Points Table

I write articles & maintain a cricket blog/website at https://brokencricketdreams.com/. One of the aspects of the blog is to think about current problems in the sport and propose innovations that can make it better. Here is one such project.

Although the World Test Championship (WTC) is a good idea, it was not the greatest of systems at its inception. Over a course of a few articles, I exposed some of the shortcomings of the system, which lead me into thinking about an alternate system. A few months later, I put these ideas into action, created an algorithm that would make the WTC points table more balanced. and implemented it in R.

*My process of collecting and manipulating data, corresponding visualizations, and findings are documented here: Alternative World Test Championship Points Table

I want to combine my interests of deep learning, music, and cricket.

I have been playing the violin for about 14 years and have participated in high school & university orchestras, youth symphonies, church concerts, and musicals. In undergraduate, I minored in music and became interested in music theory and music history.

• Predicting Genre of Music Provided Training Sets
• Classify Music as 'Bach' or 'Non-Bach' provided music clips from the Baroque sets
• Predict a cricket team's likelihood of winning a World Cup or a league based on squad composition
• Implement a live scorecard on my website by reading official APIs (that refresh continuously) and formatting it in a presentable way

• Data Analysis

  • Python, Tensorflow, R, SQL, Jupyter Notebook, Java
  • Python Libraries: Keras, Tensorflow, Numpy, Pandas, Matplotlib

• AWS Services Used

  • Lambda, StepFunctions, S3, Glue, DynamoDB, QuickSight, Amplify, API Gateway, Cognito, Secrets Manager, SQS/SNS

• Information Technology

  • Apex, ServiceNow, Salesforce, Configuration Management Database (CMDB)
  • Development Lifecycle/Version Control: SCRUM/Agile, CI/CD (experience with Azure Pipelines), Github/Gitkraken

• Math Programming

  • Mathematica, Matlab, LaTex, XPP

• Web Development

  • React, Node.js, HTML, CSS
  • Visualization: PowerBI, D3, Tableau, Cognos, VTK, Paraview
  • Content Creation/Design: Canva, Audacity, Wordpress, Adobe Creative Cloud (Premier Pro);

• Microsoft

  • Word, Excel, Access, PowerPoint

1. Deep Learning Specialization by Andrew Ng in Coursera
   • Structuring Machine Learning Projects
   • Neural Networks and Deep Learning
   • Improving Deep Neural Networks: Hyperparameter Tuning, Regularization, and Optimization
   • Sequence Models
   • Convolution Neural Networks
2. DevOps Foundations (LinkedIn Learning)
3. Developing Serverless Solutions on AWS
4. Cloud (AWS): Build, Secure, Manage Serverless Applications at Scale on AWS
5. Fundamental Cloud Concepts for AWS
6. Introduction to Power BI Training

• Fundamental of Algorithms, Data Structures, Discrete Mathematics, Graph Theory, Visualization, Bioinformatics
• Statistical/Machine Learning, Numerical Optimization, Linear Algebra, Probability, Stochastic Modeling, Numerical Analysis

My area of research lies in hyperbolic partial differential equations (PDEs). The PDEs I deal with have applications in traffic flow & biology (specifically chemotaxis). I completed both my MS in Applied Mathematics & BS in mathematics with a minors in computer science and music from the University of Tulsa.

Publication Riemann Problem for a Non-Strictly Hyperbolic System in Chemotaxis

Conference Papers An Algorithm to Reverse the Generalized Factorials Process

A complete lists of my presentations and detailed research work is here.

Other mathematical interests: Complex Analysis, Number Theory, Topology

Here are some of my favorite books (resource textbooks and fun to read books both included)

1. An Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
2. Numerical Optimization by Jorge Nocedal and Stephen J. Wright
3. Hitting Against the Spin: How Cricket Really Works by Nathan Leamon & Ben Jones

Here are some YouTube channels & blogs I follow for data science.

• Code Basics
• TensorFlow, Specificially the NLP Zero to Hero Playlist
• Python Programmer
• Luke Barousse
• Ken Jee

Blog: Towards Data Science