PhD, Computer Science, Purdue University In progress
MS, Computer Science, Purdue University December 2021
BS, Computer Science, Purdue University May 2018
[Pr3] Maxwell J. Jacobson, Yexiang Xue
Hypothesis Network Planned Exploration for Rapid Meta-Reinforcement Learning Adaptation.
Arxiv preprint, November 2023.
[pdf]
[Pr2] Maxwell J. Jacobson, Yexiang Xue
Integrating Symbolic Reasoning into Neural Generative Models for Design Generation.
Arxiv preprint, October 2023.
[pdf]
[J1] Maxwell J. Jacobson, Mohammed El Masry, Daniella Chanci Arrubla, Maria Romeo Tricas, Surya C. Gnyawali, Xinyu Zhang, Gayle Gordillo, Yexiang Xue, Chandan K. Sen, Juan Wachs
Autonomous Multi-modality Burn Wound Characterization using Artificial Intelligence.
In Military Medicine, 188(Supplement_6), 674-681, 2023.
[pdf]
[Pr1] Maxwell J. Jacobson, Daniella Chanci Arrubla, Maria Romeo Tricas, Gayle Gordillo, Yexiang Xue, Chandan Sen, Juan Wachs
Human-centered XAI for Burn Depth Characterization.
Arxiv preprint, October 2022.
[pdf]
[C1] Maxwell J. Jacobson, Case Wright, Nan Jiang, Gustavo Rodriguez-Rivera, Yexiang Xue
Task Detection in Continual Learning via Familiarity Autoencoders.
In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2022.
[pdf]
[O1] Maxwell J. Jacobson, Daniella Chanci Arrubla, Maria Romeo Tricas, Mohammed El Masry, Surya Gnyawali, Gayle Gordillo, Yexiang Xue, Chandan Sen, Juan Wachs
Autonomous Multi-modality Burn Wound Characterization using Artificial Intelligence.
In Military Health System Research Symposium (MHSRS), 2022.
[pdf]
Key:
[J] Journal Articles
[C] Conference Papers
[O] Other Non-Archival Talks/Posters
[Pr] Preprints
CS390: Neural Image Processing Jan 2019 - 2022
This course is an introduction to neural networks studied through the lens of image processing. Lectures cover theoretical topics while labs apply these topics to a working ML system. Labs include neural nets from scratch, image classification and hyperparameter tuning, style transfer, image generation, and a final project of the student’s choice. My contribution to this class is as its founder. I created this course with the help of Gustavo Rodriguez-rivera and inspired by Fei-Fei Li and Andrej Karpathy’s course "CS231n: Convolutional Neural Networks for Visual Recognition".
CS252: Systems Programming Aug 2018 - 2021
This class covers the basics of systems programming including programming in a Unix environment and building large low-level projects such as a memory allocator, a shell, and a web server. My contribution is as a longtime TA. I help students, conduct lab lectures, and help organize the UTAs.
CS408: Software Testing Aug 2019 - Dec 2019
This course covers basic software testing concepts and procedures. I helped TA for this course for one semester. I helped manage several teams and gave extra guidance to a team building a reinforcement learning application.
First Tech Challenge Mentor Aug 2014 - present
Throughout each semester of college, I volunteered with Central Catholic High School as a robotics club mentor. Over this time I taught my students skills like programming, design, teamwork, leadership, CAD, and basic electronics. I also spent two years as an officer for Purdue First Programs — a club that supports FTC teams in the area.
President of Society of Creative Roleplaying 2019-2020
I held the role of president for the Society of Creative Roleplaying at Purdue. I managed the club and handled scheduling.
Application Development Intern Summer 2015, Summer 2016
I worked for The Jacobson Group during the summers of 2015 and 2016. I completed a number of IT tasks and created an android prototype application to manage employee time cards. I also helped to build the front-end of the website, mostly working with HTML5 and CSS to create a good looking user interface.
AMBUSH November 2021 - 2022
A DoD funded project for autonomous burn wound analysis. Website here.
Doric, Prognet Library Spring 2020
Doric is a lightweight tool for implementing and extending progressive neural networks. It is a free and open-source library built atop PyTorch.
Poachnet, IBM-Funded IoT Project 2016 - 2018
Poachnet was a project aimed at protecting oyster farms from poachers and equipment thieves. We created a solar-powered apparatus using cameras to monitor near-shore oyster farms. We also used custom circuitry and an Arduino to directly monitor oyster farming equipment. I contributed to design, testing, device side scripting, and server side development.