Program: AWS Cloud Solutions Architect - In View
Program: Certificate in Data Science & Analytics
Position: Research Assistant
Program: Master of Chemical Engineering
Position: Data Analyst
Position: Process Integration Engineer
Position: Statistician
Program: Bachelor of Biosystems and Agricultural Engineering
A Python Flask app to explore the nature of human trafficking globally for the year 2018 using D3.js, Leaflet.js, Plotly.js, Amchart.js and AnyChart.js to create visualizations
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Analyzed United States Department of Agriculture Census data to explore how agricultural commodities prices in North Carolina have changed between 2012 to 2017 and what factors drive the change
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A webpage to display mars information scraped from various sources, using Splinter, BeautifulSoup and MongoDB database
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An interactive scatter plot, to explore the correlation between demographics and health risk factors in U.S. using D3.js
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An interactive dashboard to explore the Bacteria Biodiversity of microbes that colonize human navels, using Plotly.js to create visualizations
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Analysis of New York Citi's Bike Program which is responsible for overseeing the largest bike sharing program for 200,000+ data points in the United States through visualization in Tableau
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Employed Zillow's housing data to analyze United States’ housing market since the housing market collapsed in 2008 to identify how the market has or has not rebounded between then and 2019. Also developed a regression model to predict the future price.
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Visualizing the last seven days of US earthquake date using USGS GeoJSON and Leaflet to create the map
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Built a web app that detects objects by allowing users upload pictures, upload videos or take videos. The web app scrapes data pertaining to the detected objects from Walmart's website and allows users to filter and sort the data
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Evaluated the performance of using different GAN architectures such as FCN-RNN and C-RNN GANs to produce melodious musical frequencies
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Built an end to end machine learning pipeline to predict household prices in California using the Kaggle dataset. Some of the models used include: Random Forest, SVM, XGBoost. The XGboost model outperformed the others with a MSE of 51,009.51
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Designed a Resilient and Reliable AWS VPC application with public and private subnets, multi-availability zone, multi-region database, configured it in multiple geographically separate AWS regions and hosted it on an AWS S3 bucket
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Scraped Monster to determine the demand for general skills and technologies such as Python and R most relevant to data science [Extraction]. Performed various transformations using python and Regex [Transform]. Loaded the data to both a NOSQL and a MySQL database [Load]
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Built a model that correctly identifies weed types from a variety of weed and crop RGB images with CNNs using the V2 Plant Seedlings Dataset available on Kaggle. My aim was to maximize the accuracy and I achieved an accuracy of 81%
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Built a music recommendation system with collaborative filtering technique for implicit feedback dataset using the Alternating Least Square algorithm.
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Developed a model to predict bike rental count hourly or daily based on the environmental and seasonal variables using years 2011 and 2012 historical logs from Capital Bikeshare system, Washington D.C., USA. Applied GridsearchCV and RandomSearch with XGBoost to achieve a final RMSE of 59.304
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Simulated synthesis gas to dimethylether rection over a Cu-ZnO-Al2O3 Catalyst using the PSRK properties method on ASPEN. Also carried out process optimization, investment analysis and sensitivity analysis
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Designed a P.I feedback control system with the goal of maintaining the dissolved oxygen content at 50% of the air-based oxygen saturation concentration for fermentors in NC State University BTEC intermediate upstream suite
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Examined the electronic absorption spectrum of trans-diazobenzene by performing a geometry optimization in NCSU's HPC cluster. Used the CIS(D) method - a 2nd order perturbation method that uses CIS as its reference - and the 6-31G* basis set. Also compared the result to the values from Fliegl et al., J. Am. Chem. Soc. 125, 9821 (2003)
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Performed M.D simulation of water-methanol mixture to determine physical properties like self-diffusion coefficient, density and shear viscosity for a system consisting of 216 molecules of water and 216 molecules of methanol. Also compared the derived values to known experimentally derived values.
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