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Featured News

CSML Alumni Profile: Sid Gupta uses data science to analyze the financial markets
Aug. 10, 2022
Author
Written by Sharon Adarlo

For his master’s degree thesis, which also fulfilled requirements in the CSML graduate certificate, Sid Gupta compared the use of various machine learning methods to estimate probable volatility and prices for vanilla options, a type of financial derivative. In addition to neural networks, Gupta used decision tree-based ensemble models such as gradient boosted trees and random forests to estimate volatility. He used the S&P 500 option price data from 2016 to 2018 to train and test his models.

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Latest News

CSML Alumni Profile: Sid Gupta uses data science to analyze the financial markets

For his master’s degree thesis, which also fulfilled requirements in the CSML graduate certificate, Sid Gupta compared the use of various machine learning methods to estimate probable volatility and prices for vanilla options, a type of financial derivative. In addition to neural networks, Gupta used decision tree-based ensemble models such as gradient boosted trees and random forests to estimate volatility. He used the S&P 500 option price data from 2016 to 2018 to train and test his models.

Jafar Howe: applying machine learning to analyze and detect different language accents

For his independent project for CSML, Jafar Howe decided to develop an English language accent classifier, basically a tool to accurately detect different English accents. Howe did this by converting speech samples into a time-frequency spectrogram, a visual representation of audio. 

Linear dynamical systems research by Yanxi Chen and H. Vincent Poor wins outstanding paper at machine learning conference

Research on linear dynamical systems by Yanxi Chen, a doctoral student in Princeton University’s Department of Electrical and Computer Engineering, and H. Vincent Poor, the Michael Henry Strater University Professor, won the outstanding paper award at this year’s International Conference on Machine Learning, which was held in Baltimore, Maryland from July 17 to 23.

Caio Costa: advancing computer vision into new horizons

Caio Costa tackled computer vision for his CSML independent project, specifically how computers may perceive objects that are partially occluded from view. He set out to put together a machine learning process that uses light bounced off a surface to determine an object’s shape, a technique known as non-line-of-sight (NLOS) imaging, a burgeoning area of study in the computer vision field.

Princeton University is actively monitoring the situation around coronavirus (COVID-19) and the evolving guidance from government and health authorities. The latest guidance for Princeton members and visitors is available on the University’s Emergency Management website

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Events for Academic Year 2022-2023
Mon, Aug 1, 2022

Events at the Center for Statistics and Machine Learning are currently being scheduled. Please check back here later this month for events.