Maxwell Alexander Xu

I work at the intersection of applied and theoretical machine learning for time-series data, with a strong application focus on mobile health sensors. My goal is to develop temporal machine learning methodologies to be used with modern wearable health technologies advancements (e.g. Amazon Halo, Apple Watch, etc.).

As a Georgia Tech Machine Learning PhD student, I work with Jim Rehg as my advisor. I am currently working on analyzing streams of mobile sensor data to develop personalized treatment approaches for chronic health conditions with funding from the NIH mHealth Center.

Prior to starting my PhD, I worked as a full-time Machine Learning Researcher within the cybersecurity division of Systems & Technology Research to discover vulnerabilities within speech processing programs. While an undergrad at Johns Hopkins, I helped found and lead a student venture, BioSwift, which aimed to develop medical devices for pediatric asthmatics.

My previous research experience includes bioinformatics work on the effect of the overexpression of the GABA genes on the prognosis of cancer. I was being advised by Soma Sengupta and Daniel Krummel, who are both currently based in the University of Cincinnati.

Research Highlights

Developed a representation learning method for histopathology images with deep clustering
Education

Aug 2020 —Aug. 2018Ph.D. in Machine Learning
PresentGeorgia Institute of Technology, Atlanta, GA
Advisor: Jim Rehg
Anticipated Graduation: Spring 2025

Aug 2016 —Dec 2019B.S. in Applied Mathematics and Statistics
Dec 2019B.S. in Biomedical Engineering
Johns Hopkins University, Baltimore, MD
Overall GPA: 3.84/4.00

Selected Awards

2020Georgia Tech Presidential Fellowship
Awarded for displaying exemplary levels of scholarship and innovation

2020Intuitive Surgical Best Project Award
For "MATHIAS: Modeling A Transferable Histopathological Image Analysis System"
Press Release: https://www.cs.jhu.edu/2020/01/28/deep-learning-course-prepares-students-for-success-in-ai-careers/

20191st Place in Fall 2019 Johns Hopkins FastForward U Spark Accelerator Competition
Press Release: https://ventures.jhu.edu/news/bioswift-aquatas-fast-forward-u-accelerator-demo-days/

20191st Place in 2019 ASAIOfyi Student Design Competition
Press Release: https://www.facebook.com/jhu.admissions/posts/congrats-to-team-bioswift-jhubme-hopkinsengineering/10156494724603946/

Selected Industry Experience

Jan 2020 —Systems & Technology Research, Boston, MA
Aug 2020Machine Learning Researcher, Cyber-Physical Systems
• Spearheaded machine learning initiatives within the cybersecurity vulnerability research
• Created a reinforcement learning method for greybox mutation-based fuzzer
• Developed a seq2seq VQ-VAE WaveRNN decoder for unsupervised representation learning of audio

May 2019 —Medtronic, North Haven, CT
Dec 2019AI/Data Science Engineer Contractor, Minimal Invasive Therapies Group
• Developed a tool to predict lung cancer recurrence from clinical big data using machine learning
• Created a computer vision blob detection tool
• Utilized survival analysis with Kaplan-Meier curve visualizations to identify cancer recurrence risk factors

Aug 2018 —BioSwift, Baltimore, MD
Dec 2019Former Chief Executive Officer and Co-Founder
• Designed device to augment dry powder inhalers for usage among pediatric asthmatics
• Secured over $10,000 in funding, from various business and design competitions as well as the Johns Hopkins Student Initiatives Fund
• Press Release: https://www.jhunewsletter.com/article/2019/11/fastforward-u-teams-innovate-with-new-and-old-technologies

Jan 2019 —Johns Hopkins University Department of Computer Science, Baltimore, MD
Jan 2020Teaching Assistant, Data Structures
• Collaborated with team of faculty during weekly meetings and actively contributed to course content
• Worked with students to enhance student understanding of content such as heaps, AVL trees, hashmaps

May 2018 —Centers for Disease Control and Prevention, Atlanta, GA
Aug 2018Biostatistics Intern, Outbreak Surveillance
• Spearheaded a new initiative to utilize whole genome multilocus sequence typing data for detecting disease clusters

Publications

Impact of Sequencing Radiation Therapy and Immune Checkpoint Inhibitors in the Treatment of Melanoma Brain Metastases
Daniel Pomeranz Krummel‡, Tahseen H. Nasti‡, Benjamin Izar†, Robert H. Press†, Maxwell Xu†, Lindsey Lowder, Laura Kallay, Manali Rupji, Havi Rosen, Jing Su, Walter Curran, Jeffrey Olson, Brent Weinberg, Matthew Schniederjan, Stewart Neill, David Lawson, Jeanne Kowalski, Mohammed Khan, Soma Sengupta
International Journal of Radiation Oncology, 2020
Project PDF ‡Co-first authors; †Co-second authors

Modulating Native GABAA Receptors in Medulloblastoma with Positive Allosteric Benzodiazepine-derivatives Induces Cell Death
Laura Kallay, Havva Keskin, Alexandra Ross, Manali Rupji, Olivia A Moody, Xin Wang, Guanguan Li, Taukir Ahmed, Farjana Rashid, Michael Rajesh Stephen, Kirsten A Cottrill, T Austin Nuckols, Maxwell Xu, Deborah E Martinson, Frank Tranghese, Yanxin Pei, James M Cook, Jeanne Kowalski, Michael D Taylor, Andrew Jenkins, Daniel A Pomeranz Krummel, Soma Sengupta
Journal of Neuro-Oncology, 2019
Project PDF

Conferences

EXTH-12. Radiation Enhances Melanoma Response to Immunotherapy and Synergizes with Benzodiazepines to Promote Anti-Tumor Activity
Daniel Pomeranz Krummel‡, Tahseen H. Nasti‡, Benjamin Izar†, Robert H. Press†, Maxwell Xu†, Lindsey Lowder, Laura Kallay, Manali Rupji, Havi Rosen, Jing Su, Walter Curran, Jeffrey Olson, Brent Weinberg, Matthew Schniederjan, Stewart Neill, David Lawson, Jeanne Kowalski, Mohammed Khan, Soma Sengupta
Neuro-Oncology 2020. Phoenix, Arizona
Project ‡Co-first authors; †Co-second authors

Abstract 247: Identification of the GABAA Receptor in Melanoma Brain Metastases Patient Tumors and Demonstration that It is a Viable Drug Target using Benzodiazepine-Derivatives
Milota Kaluzova, Tahseen Nasti, Hiao-Rong Chen, Lindsey Lowder, Robert Press, Havi Rosen, Manali Rupji, Laura Kallay, Rikesh Patel, Andre Burnham, Maxwell Xu, Alexandra Ross, Havva Keskin, Erin Connelly, Benjamin Izar, Cory Adamson, Jeffrey Olson, Jing Su, Walter Curran, Ragini Kudchadkar, Matthew Schniederjan, Stewart Neill, David Lawson, Michael Chan, Jeanne Kowalski, Mohammad Khan, Daniel Pomeranz Krummel, Soma Sengupta
AACR Annual Meeting 2019. Atlanta, GA
Project

Abstract 2623: Modulating Native GABAA Receptors in Medulloblastoma with Positive Allosteric Benzodiazepine-Derivatives Induces Cell Death
Laura Kallay, Havva Keskin, Alexandra Ross, Manali Rupji, Olivia A. Moody, Xin Wang, Guanguan Li, Taukir Ahmed, Farjana Rashid, Michael Rajesh Stephen, Kirsten A. Cottrill, Austin Nuckois, Maxwell Xu, Deborah E. Martinson, Frank Tranghese, Yanxin Pei, James M. Cook, Jeanne Kowalski, Michael D. Taylor, Andrew Jenkins, Daniel Pomeranz Krummel, Soma Sengupta
AACR Annual Meeting 2019. Atlanta, GA
Project

COMP-22: Large Scale Transcriptomic Analysis of Melanoma Brain Metastases
Jeanne Kowalski, Daniel Pomeranz Krummel, Manali Rupji, Bhakti Dwivedi, Havva Keskin, Laura Kallay, Maxwell Xu, Alexandra Ross, Robert Press, Havi Rosen, Erin Connelly, Rikesh Patel, Benjamin Izar, Cory Adamson, Jeffrey Olson, Jing Su, Ragini Kudchadkar, Matthew Schniederjan, Lindsey Lowder, Stewart Neill, Walter Curran, David Lawson, Michael Chan, Mohammad Khan, Soma Sengupta
Neuro-Oncology 2018. New Orleans, LA
Project

PDTM-45: Positive Modulation of Native GABAA Receptors in Medulloblastoma Cancer Cells with Benzodiazepines Induces Rapid Mitochondrial Fragmentation and TP53-Dependent, Cell Cycle-Independent Apoptosis
Laura Kallay, Havva Keskin, Alexandra Ross, Olivia Moody, Kirsten Cottrill, Austin Nuckols, Guanguan Li, Taukir Ahmed, Farjana Rashid, Michael Stephen, Maxwell Xu, Deborah Martinson, Tobey Macdonald, Jeanne Kowalski, Xin Wang, Michael Taylor, James Cook, Andrew Jenkins, Daniel Pomeranz Krummel, Soma Sengupta
Neuro-Oncology 2018. New Orleans, LA
Project

CD131: Large Scale Transcriptomic Analysis of Melanoma Brain Metastases
Jeanne Kowalski, Daniel Pomeranz Krummel, Manali Rupji, Bhakti Dwivedi, Havva Keskin, Laura Kallay, Maxwell Xu, Alexandra Ross, Robert Press, Havi Rosen, Erin Connelly, Rikesh Patel, Benjamin Izar, Cory Adamson, Jeffrey Olson, Jing Su, Ragini Kudchadkar, Matthew Schniederjan, Lindsey Lowder, Stewart Neill, Walter Curran, David Lawson, Michael Chan, Mohammad Khan, Soma Sengupta
Annals of Neurology 2018.
Project