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AI Researcher at J.P. Morgan Chase & Co.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Harvard University
S.M., Computational Science and Engineering
January 1, 2015 – January 1, 2016
The Chinese University of Hong Kong
International Summer School, Mandarin Chinese
January 1, 2012 – January 1, 2012
Amsterdam University College
B.S. (Hons), Computer Science, Economics
January 1, 2011 – January 1, 2014
J.P. Morgan
Senior AI Researcher
October 1, 2020 – October 1, 2021
Manhattan, New York, United States
Perceptive Automata
Senior Machine Learning Engineer
January 1, 2017 – January 1, 2020
Boston, Massachusetts, United States
Harvard University
Research Fellow
January 1, 2016 – January 1, 2017
Cambridge, Massachusetts, United States
Automated Anomaly Detection
December 1, 2015 – Present
This project attempts to provide a foundation to automate anomaly detection in surveillance video, utilizing contemporary methods of parallel computing. The focus of this project is to develop a detection algorithm that will run in real-time and provide decision support for an operator tasked with monitoring multiple camera feeds. To achieve this desired benchmark, the processing, detection, and decision algorithms were written in C and Python (leveraging the PyCUDA module) and run on a designated NVIDIA Jetson TK1.
Predicting NYTimes Comment Success
December 1, 2015 – Present
We have examined the relationship between comment success (i.e., the number of recommendations it receives by other users) as well as other features about the comments themselves. Specifically, we have built a model that can predict the success of a given comment. We envision this model as a complementary tool that could be used by the NYT moderators during their daily review of comments.
AUC Undergraduate Journal Open Submissions
December 1, 2011 – Present
Creating Amsterdam University College's first Open Submission Undergraduate Journal.
Cultural Fit Analysis
The candidate's background is heavily focused on academic research and machine learning, which is a significant pivot from the target role of an iOS Developer. While the projects demonstrate strong analytical and problem-solving skills, there is no direct evidence of interest or experience in mobile development, iOS ecosystem, or consumer-facing application development. This lack of direct alignment with the target role suggests a potential cultural fit challenge for a dedicated iOS development team.
Soft Skills & Operational Fit
The candidate's resume highlights experience as a Teaching Fellow and VP of External Relations, suggesting strong communication and leadership potential. However, specific operational fit for an iOS Developer role cannot be fully assessed without direct experience in agile methodologies, team collaboration on mobile projects, or problem-solving within a mobile development context.