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 wearable health sensors. I am actively looking for internships for Summer 2024.
As a Georgia Tech Machine Learning PhD student, I work with Jim Rehg as my advisor and have recieved the NSF Graduate Research Fellowship and Georgia Tech Presidential Fellowship awards. I am also a part of the NIH mHealth Center.
My previous bioinformatics research was on understanding how the overexpression of the GABA genes affects cancer prognosis. I was advised by Soma Sengupta and Daniel Krummel at UNC Chapel Hill.
---- Recent News: Our REBAR paper has been accepted into ICLR 2024!! ----
---- Webpage Last Updated: 01/18/2024 ----
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
2022National Science Foundation Graduate Research Fellowship
Awarded for displaying exemplary levels of research skill and potential
Press Release: https://grad.gatech.edu/news/49-students-awarded-prestigious-national-science-foundation-graduate-research-fellowship
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/
Retrieval-Based Reconstruction For Time-series Contrastive Learning
Maxwell A. Xu, Alexander Moreno, Hui Wei, Benjamin M. Marlin, James M. Rehg
The Twelfth International Conference on Learning Representations (ICLR), 2024
Paper
PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation
Maxwell A. Xu, Alexander Moreno, Supriya Nagesh, V. Burak Aydemir, David W. Wetter, Santosh Kumar, James M. Rehg
Proceedings of the Neural Information Processing Systems (NeurIPS), 2022.
Paper
Project Page
Code
Discovering Novel Predictors of Minimally Verbal Outcomes in Autism through Computational Modeling
Maxwell A. Xu, James M. Rehg, Agata Rozga, Jena McDaniel, Paul Yoder, Linda R. Watson, Nancy Brady
INSAR Oral + Press Conference (~ 1% acceptance rate), 2022.
Paper
Press Release
Video
Efficient Learning and Decoding of the Continuous-Time Hidden Markov Model for Disease Progression Modeling
Yu-Ying Liu, Alexander Moreno†, Maxwell A. Xu†, Jena McDaniel, Nancy Brady, Agata Rozga, Fuxin Li, Le Song, James M. Rehg
arXiv, 2021.
Paper
Code
†Co-second authors
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.
Paper
‡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.
Paper
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
Paper
‡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
Paper
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
Paper
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
Paper
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
Paper
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.
Paper
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