I am a Big Data practitioner with experience in computer vision and machine learning
I live in New York City and am currently working as a Computer Vision Engineer at Arcules. I graduated from Duke University with degrees in Economics (B.S.) and International Comparative Studies (B.A.) and previously worked at J.P. Morgan as a data scientist & credit trading analyst as well as at Slang as a data scientist consultant.
I like working on computer vision and machine learning-related projects in my free time and am a web3 enthusiast.
Computer Vision Projects
Supervised ML Projects
Unsupervised ML Projects
Papers Published
January 2022
A Computer Vision-assisted Approach to Automated Real-Time Road Infrastructure Management
Proposed a supervised object detection approach leveraging You Only Look Once (“YOLO”) and the Faster R-CNN frameworks to detect and classify road distresses in real-time via a vehicle dashboard-mounted smartphone camera, producing 0.68 F1-score experimental results ranking in the top 5 of 121 teams that entered the IEEE Global Road Detection Challenge as of December 2021.
Skills
Computer Vision: Pytorch | Tensorflow | Keras | You Only Look Once (YOLO) | Faster R-CNN
Python: pandas | numpy | scikit-learn | scipy | nltk | statsmodels | scrapy | Selenium | Dash | Flask | matplotlib | seaborn
Supervised ML: Linear & Logistic Regression | Random Forests | Gradient Boosting | XGBoost | Support Vector Machines | Neural Nets
Unsupervised ML: K-Means | K-Medians | HDBSCAN | Principal Component Analysis
R: dplyr | ggplot2 | Shiny | caret
SQL: MySQL | Teradata SQL | HiveQL
Dashboarding: Tableau | Alteryx | Adobe Analytics
Other Frameworks: Apache Spark | Git | Docker | AWS | Jira | Agile
Experience
March 2022 – Present
Arcules
Computer Vision Engineer
Responsible for development and deployment of computer vision models enabling object detection and instance segmentation applications using Pytorch and Tensorflow
March 2021 – March 2022
J.P. Morgan Chase
Data Scientist
Led machine learning classification project predicting customer deposit outflow transactions to competitors in following 30 days with responsibilities encompassing model training, data engineering and deployment tasks
March 2020 – December 2020
NYC Data Science Academy
Data Scientist Fellow
Graduated immersive data science program focused on machine learning, big data, Python and R development, SQL, Tableau, Docker and Git/GitHub with hands-on project work.
September 2019 – March 2021
J.P. Morgan Chase
Credit Trading Analyst
Structured and traded illiquid credit products as part of the Distressed Credit Trading desk with responsibilities including developing and presenting financial valuation models in Excel and Python
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