Raymond Huffman

+1 (516) 695-0983 rhuffman@mit.edu http://huff.tech/ github@rhuffy

EDUCATION

Massachusetts Institute of Technology, Class of 2021 Manhasset High School, Class of 2017

B.S. in Computer Science (Course 6-3) GPA: 4.45/4.0 SAT: 2300

Gordon Engineering Leadership Program

Skills: Python, Java, C/C++, TypeScript, React, Julia, HTML, Angular, Git, AWS, Google Cloud Platform

WORK EXPERIENCE

Palantir Technologies Summer 2020

Incoming Software Engineering Intern.

Rentingway June 2019-present

Developing a mobile/web app in React and a Firebase back-end for a real estate technology startup. Implemented secure ACH payment processing and bank account authentication using Dwolla.

Lockheed Martin Advanced Technology Lab Summer 2019, Summer 2018

Implemented multiple features in a DoD machine learning platform. Programmed an interactive visualization tool used to display histories of model training, testing, and prediction generation.

Developed software for a distributed search optimization problem in Julia and JuMP. Applications include allocating sensor resources on a battlefield with limited information.

Citco Fund Services Summer 2017

Designed and implemented ETL procedures for a secure petabyte-scale data lake on AWS. Rewrote ETL scripts to prepare for automated trade reconciliation with SAP Machine Learning.

FSAE MIT Motorsports September 2017-present

Programmed embedded software for charging, regenerative braking, and a touch screen dashboard on an electric racecar. Software written in C and C++ for STM32 Arm-based microcontrollers.

MIT Global Teaching Labs – Italy January 2019

Taught computer science at an Italian technical high school. Material included programming in C, Java basics, Java GUI using Swing, relational databases and SQL.

Google CodeU Summer 2018

Participated in an invitation-only software engineering program, mentored by a Google engineer.

Wrote extensions for a chat-app using Google Cloud Platform AppEngine, Java, and JSP.

RESEARCH EXPERIENCE

Institute of Genetic Medicine, Johns Hopkins University Summer 2016

Finalist - Intel International Science and Engineering Fair

Developed a computational model that aggregates genetic data and identifies potential abnormalities. Used unsupervised machine learning to sort and classify suspect genetic regions.

Feinstein Institute for Medical Research Summer 2015

Published – 2^nd Author – Journal of Investigative Medicine, February 2016

Sequenced and analyzed genomes of breast cancer patients and isolated common mutated genes.

Manhasset High School 2016-2017

Finalist - Intel International Science and Engineering Fair

Developed a machine learning model using Keras to predict if gene mutations will be harmful.