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John L

- Research Program Mentor

MS Master of Science


Machine Learning, Financial Statistics, Corporate Finance, Econometrics, Business Analytics, Statistics, Healthcare Analytics

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Data Science in Risk Management

Market drawbacks are inevitable, but do you know that their patterns are identifiable with statistics? This project will utilize a variety of probability measures, including extreme-value distributions and volatility models to optimize the allocation of stocks in your stock portfolio. The measures will be implemented in Python and R. Through this project, you will be able to: 1) Master the concepts of probability distributions 2) Obtain hands-on exposure to tasks of a Quant 3) Maximize your portfolio returns with minimal risks

Deploying Trading Algorithms with Machine Learning (ML)

This project focuses on employing investment decisions based on model output, particularly for equities and cryptocurrencies. Techniques involve using regression and classification designs to predict the market's price composition. Fundamental and technical data are used. The models will be implemented in Python. Through this project, you will be able to: 1) Develop the mathematical foundations for the ML models and implement them 2) Optimization algorithms for training the models on actual data. 3) Analyze the performance of the trading algorithms

Feature Engineering for Alzheimer's Disease

The occurrence and impact of alzheimer's disease vary widely in the population, and several medical and demographic factors may be insightful for their prediction. Uncovering such an association can be instrumental in predicting the onset of alzheimer's and proactively aiding patients that may be at a higher risk. Through this project, you will be able to: 1) Perform Exploratory Data Analysis (EDA) in a medical context 2) Assess and design statistical learning models for disease emergence 3) Automate diagnosis results that mimics those of a robo-advisor

Coding skills

Python, R, SQL, C++, Spark, Hadoop

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