Dennis Li has a strong background in quantitative research and engineering, with experience in machine learning and software development. Dennis is currently working as a Quantitative Researcher at Citadel Securities since March 2021. Prior to that, they were a Quantitative Research Engineer at Citadel from August 2020 to March 2021.
Dennis also has research experience as a Research Assistant at the Machine Learning Department at CMU from November 2019 to June 2020, where they worked on distributed low rank approximation and published a paper at ICML 2021. Dennis also conducted research on transformer-based deep learning models for modeling complex valued time series as a Research Assistant at the Machine Learning Department at CMU from November 2018 to May 2019. Their work on this topic was published at NeurIPS 2019 Workshop and ICASSP 2020.
Additionally, Dennis has gained practical industry experience through internships. Dennis worked as a Software Engineer Intern at Citadel Securities from June 2019 to August 2019 and as a Machine Learning Engineer Intern at Apple from May 2018 to August 2018.
Dennis has also held positions as a Machine Learning Engineer at CARNEGIE SPEECH, LLC from October 2017 to April 2018, and as a Visiting Undergraduate Research Intern at Harvard University from May 2017 to August 2017. Dennis also served as an Undergraduate Senator at Carnegie Mellon University from August 2018 to April 2019.
In addition to their industry and research experiences, Dennis has also served as a Teaching Assistant for Functional Programming at the Computer Science Department, Carnegie Mellon in the spring of 2017. Overall, Dennis has a diverse skill set and a strong foundation in both industry and academic settings.
Dennis Li completed their high school education at Ravenscroft School from 2014 to 2016. Dennis then went on to pursue a Bachelor's degree at Carnegie Mellon University, specializing in Computer Science with a minor in Machine Learning, from 2016 to 2019. Following their undergraduate studies, Dennis continued their education at Carnegie Mellon University, where they obtained a Master's degree in Machine Learning from 2019 to 2020. Additionally, they acquired several certifications, such as "Introduction to Linux" from edX in June 2017, "Using Python for Research" from edX in June 2017, and "Web Development" from Udacity in June 2017. Other certifications include "Introduction to Big Data with Apache Spark" from edX in July 2015, "Advanced Introductory Classical Mechanics" from edX in June 2015, "Computation Structures - Part 1: Digital Circuits" from edX in May 2015, "Introduction to Chemistry: Structures and Solutions" from Coursera in December 2014, "Introduction to Computational Thinking and Data Science" from edX in December 2014, "Introduction to Chemistry: Reactions and Ratios" from Coursera in October 2014, "Introduction to Computing with Java" from edX in September 2014, "Principles of Economics" from Stanford Continuing Studies in September 2014, "Microeconomics Principles" from Coursera in August 2014, and "Introduction to Computer Science and Programming Using Python" from edX in April 2014. Notably, they also completed the "Big Data and Social Physics" certification from edX, but the specific months and years of completion are not available.
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