Abhay Goyal
Bio
I’m currently a Ph.D. student at Missouri University of Science and Technology (MS&T) under the guidance of Prof Sanjay K. Madria. I have completed my Master’s degree in Computer Science from Stony Brook University. My focus areas are Data Science, Data Analytics, Machine Learning, and Graph Neural Networks and their applications.
I have worked on numerous personal and academic projects relating to the different applications in the housing industry (AMES Housing), Fraud detection (IEEE Fraud Detection) and Sales Analysis (Retail Sales Analysis). These projects have given me an insight into how can ML and DL techniques be used to impact the betterment of the world we live in.
Education
| Degree | Major | University | Year | |
|---|---|---|---|---|
| Doctor of Philosophy (Ph.D.) | Graduate | Computer Science | Missouri University of Science and Technology | 2021-2025 |
| Master’s in Science (M.S) | Graduate | Computer Science | Stony Brook University | 2019-2021 |
| Bachelor of Technology (B.Tech) | Undergraduate | Computer Science | SRM Institute of Science and Technology | 2015-19 |
Contact
- Linkedin: /AbhayGoyal
- github: /AbhayGoyal
- Kaggle: /AbhayGoyal
- Wordpress : /AbhayGoyal
Relevant Coursework
Big Data and Cloud Computing, Mobile Computing, Human-Computer Interaction, Data Science Fundamentals, Probability and Statistics for Data Science, Visualization, Machine Learning, Databases
Tableau Work :- here
Past Experience
Interned at Pacific Northwest National Laboratory (PNNL) as a PhD Intern under Dr. Arnab Bhattacharya and Dr. Veronica Adetolda
Research under Dr. Sanjay K. Madria
Paper published
- MinerFinder: A GAE-LSTM method for predicting location of miners in underground mines
- A DTN-based Routing for Efficient Situational Awareness using Location Prediction Model in Underground Mine
- Demo : Miner-Finder: A System for Tracking Miners using GAE-LSTM and Contact Graph Framework in an Underground Mine
- App developed
Work in progress
- RL path navigation for miners in Underground mine
- PV prediction using CNFs.
- CGR GAE-LSTM based DTN routing algorithm
Personal Projects
- Retail Sales Analysis
- To perform descriptive analytics and models to increase sales.
- AMES Housing Project
- Analysed and understood the factors affecting house prices and made model to predict them.
- IEEE Fraud Detection
- Analysed and did in depth analysis of frauds, how do they occur and when
- Bank Marketing
- Analysed to predict(using Logistic Regression, Random Forest) what policies would people take based on features such as did, what they tak last time, salary, housing etc
- HR Analytics
- Did some basic visualizations do understand the satisfaction level of employees, used linear regression to predict it.
- Dashboard using D3.js
- To visualize and understand the adoption of DS and ML methods of organizations and individuals using the ML & DS Survey 2019 done by Kaggle.com