About

Alec Hodgkinson is a seasoned deep learning engineer with over 6 years of relevant experience in the field. Currently working as a Software Engineer at Thumbtack, Alec has a passion for working on cool projects that allow him to touch every part of the technology stack nearly every day. Prior to his current role, Alec has worked as a Senior Machine Learning Engineer at Dawnlight and as a Machine Learning Engineer at Panasonic Beta. While at Panasonic Beta, Alec worked on the Home Action Genome project, where he collected a multi-view, multi-modal dataset composed of hierarchically structured activities set in the home. He also wrote sensor firmware for a Raspberry Pi based sensor kit, created a Flask-based front-end interface, and created a baseline model for the Home Action Genome dataset using PyTorch. Alec also helped organize the upcoming Compositionality and Multimodal Perception workshop (CAMP) at ECCV 2020. In addition to his work on the Home Action Genome project, Alec also worked on the DoorGym project, where he designed a novel vision pipeline to perform state estimation for a door opening robot using PyTorch and OpenCV. He also created an inference server that runs at over 60 FPS to communicate between the robot platform perception pipeline and control policy pipeline. Alec co-authored a paper that was accepted at the Deep Reinforcement Learning Workshop at NeurIPS 2019. Alec holds a Bachelor of Science (B.S.) degree in Mathematics, with a minor in Computer Science from Rensselaer Polytechnic Institute. Alec's tech stack includes expertise in Software Engineering, Machine Learning, Deep Learning, PyTorch, Reinforcement Learning, OpenCV, Flask, and Frontend development. Alec is a skilled rapid prototyper, implementing state-of-the-art models and writing technical reports.