Publications

Zhang, H., Z. Jiang, S. Zhang, L. Tu, and D. Carlson. “Scale-free and unbiased transformer with tokenization for cell type annotation from single-cell RNA-seq data.” Pattern Recognition 168 (December 1, 2025). https://doi.org/10.1016/j.patcog.2025.111724.

Hickman, S. H. M., M. M. Kelp, P. T. Griffiths, K. Doerksen, K. Miyazaki, E. A. Pennington, G. Koren, et al. “Applications of Machine Learning and Artificial Intelligence in Tropospheric Ozone Research.” Geoscientific Model Development 18, no. 22 (November 20, 2025): 8777–8800. https://doi.org/10.5194/gmd-18-8777-2025.

Walder-Christensen, Kathryn K., Jack Goffinet, Alexandra L. Bey, Reah Syed, Jacob Benton, Stephen D. Mague, Elise Adamson, et al. “Sleep-Wake States Are Encoded across Emotion Regulation Regions of the Mouse Brain.” ENeuro 12, no. 11 (November 2025). https://doi.org/10.1523/ENEURO.0291-25.2025.

Li, Keyu, Charles Wood, Liz Nichols, Zachary D. Calhoun, Nrupen A. Bhavsar, and David Carlson. “Neighborhood Environmental and Contextual Factors Improve Prediction of Childhood Body Mass Index: An Application of Novel Graph Neural Networks.” AJE Adv, September 24, 2025. https://doi.org/10.1093/ajeadv/uuaf011.

Liu, Y., W. Shi, C. Fu, Z. Jiang, Z. Hua, and D. Carlson. “MOTTO: A Mixture-of-Experts Framework for Multi-Treatment, Multi-Outcome Treatment Effect Estimation.” In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2:1891–1902, 2025. https://doi.org/10.1145/3711896.3737056.

Zhou, Yanjie, Feng Zhou, Fengjun Xi, Yong Liu, Yun Peng, David E. Carlson, and Liyun Tu. “Efficient few-shot medical image segmentation via self-supervised variational autoencoder.” Medical Image Analysis 104 (August 2025): 103637. https://doi.org/10.1016/j.media.2025.103637.

Calhoun, Zachary, Mike Bergin, and David Carlson. “Big, noisy data: how scalable Gaussian processes can leverage personal weather stations to improve spatiotemporal coverage of urban climate networks,” May 21, 2025. https://doi.org/10.5194/icuc12-491.

Carlson, David E., Ricardo Chavarriaga, Yiling Liu, Fabien Lotte, and Bao-Liang Lu. “The NERVE-ML (neural engineering reproducibility and validity essentials for machine learning) checklist: ensuring machine learning advances neural engineering^{.” Journal of Neural Engineering 22, no. 2 (March 2025). https://doi.org/10.1088/1741-2552/adbfbd.}

Jain, V., A. Mukherjee, S. Banerjee, S. Madhwal, M. H. Bergin, P. Bhave, D. Carlson, et al. “A hybrid approach for integrating micro-satellite images and sensors network-based ground measurements using deep learning for high-resolution prediction of fine particulate matter (PM2.5) over an indian city, lucknow.” Atmospheric Environment 338 (December 1, 2024). https://doi.org/10.1016/j.atmosenv.2024.120798.

Carson, William E., Samantha Major, Harshitha Akkineni, Hannah Fung, Elias Peters, Kimberly L. H. Carpenter, Geraldine Dawson, and David E. Carlson. “Model selection to achieve reproducible associations between resting state EEG features and autism.” Sci Rep 14, no. 1 (October 25, 2024): 25301. https://doi.org/10.1038/s41598-024-76659-5.

Calhoun, Z. D., M. S. Black, M. Bergin, and D. Carlson. “Refining Citizen Climate Science: Addressing Preferential Sampling for Improved Estimates of Urban Heat.” Environmental Science and Technology Letters 11, no. 8 (August 13, 2024): 845–50. https://doi.org/10.1021/acs.estlett.4c00296.

Hughes, Dalton N., Michael Hunter Klein, Kathryn Katsue Walder-Christensen, Gwenaëlle E. Thomas, Yael Grossman, Diana Waters, Anna E. Matthews, et al. “A widespread electrical brain network encodes anxiety in health and depressive states.” BioRxiv, June 30, 2024. https://doi.org/10.1101/2024.06.26.600900.

Sui, C., Z. Jiang, G. Higueros, D. Carlson, and P. C. Hsu. “Designing electrodes and electrolytes for batteries by leveraging deep learning.” Nano Research Energy 3, no. 2 (June 1, 2024). https://doi.org/10.26599/NRE.2023.9120102.

Brandsen, Sam, Tara Chandrasekhar, Lauren Franz, Jordan Grapel, Geraldine Dawson, and David Carlson. “Prevalence of bias against neurodivergence-related terms in artificial intelligence language models.” Autism Res 17, no. 2 (February 2024): 234–48. https://doi.org/10.1002/aur.3094.

Walder-Christensen, Kathryn, Karim Abdelaal, Hunter Klein, Gwenaëlle E. Thomas, Neil M. Gallagher, Austin Talbot, Elise Adamson, et al. “Electome network factors: Capturing emotional brain networks related to health and disease.” Cell Rep Methods 4, no. 1 (January 22, 2024): 100691. https://doi.org/10.1016/j.crmeth.2023.100691.

Walder-Christensen, Kathryn, Jack Goffinet, Alexandra Bey, Reah Syed, Jacob Benton, Stephen Mague, Elise Adamson, et al. “Sleep-wake states are encoded across emotion-regulation regions of the mouse brain.” BioRxiv, 2024. https://doi.org/10.1101/2024.09.15.613104.

Isaev, Dmitry, Samantha Major, Kimberly L. H. Carpenter, Jordan Grapel, Zhuoqing Chang, Matias Di Martino, David Carlson, Geraldine Dawson, and Guillermo Sapiro. “Use of Computer Vision Analysis for Labeling Inattention Periods in Eeg Recordings With Visual Stimuli.” Research Square, 2024. https://doi.org/10.21203/rs.3.rs-4637470/v1.

Calhoun, Zachary D., Frank Willard, Chenhao Ge, Claudia Rodriguez, Mike Bergin, and David Carlson. “Estimating the effects of vegetation and increased albedo on the urban heat island effect with spatial causal inference.” Scientific Reports 14, no. 1 (January 2024): 540. https://doi.org/10.1038/s41598-023-50981-w.

Scott, S. R., P. E. Hailemariam, P. V. Bhave, M. H. Bergin, and D. E. Carlson. “Identifying Waste Burning Plumes Using High-Resolution Satellite Imagery and Machine Learning: A Case Study in the Maldives.” Environmental Science and Technology Letters 10, no. 8 (August 8, 2023): 642–48. https://doi.org/10.1021/acs.estlett.3c00225.

Talbot, Austin, David Dunson, Kafui Dzirasa, and David Carlson. “Estimating a brain network predictive of stress and genotype with supervised autoencoders.” J R Stat Soc Ser C Appl Stat 72, no. 4 (August 2023): 912–36. https://doi.org/10.1093/jrsssc/qlad035.

Sui, Chenxi, Ziyang Jiang, Genesis Higueros, David Carlson, and Po-Chun Hsu. “Designing electrodes and electrolytes for batteries by leveraging deep learning.” American Chemical Society (ACS), July 7, 2023. https://doi.org/10.26434/chemrxiv-2023-jvfqq.

Jiang, Ziyang, Zhuoran Hou, Yiling Liu, Yiman Ren, Keyu Li, and David Carlson. “Estimating Causal Effects using a Multi-task Deep Ensemble.” In Proceedings of Machine Learning Research, 202:15023–40, 2023. https://doi.org/10.48550/arxiv.2301.11351.

Block, Carina L., Oznur Eroglu, Stephen D. Mague, Caroline J. Smith, Alexis M. Ceasrine, Chaichontat Sriworarat, Cameron Blount, et al. “Prenatal environmental stressors impair postnatal microglia function and adult behavior in males.” Cell Rep 40, no. 5 (August 2, 2022): 111161. https://doi.org/10.1016/j.celrep.2022.111161.

Thornton, Luka Lila, David E. Carlson, and Mark R. Wiesner. “Predicting emerging chemical content in consumer products using machine learning.” The Science of the Total Environment 834 (August 2022): 154849. https://doi.org/10.1016/j.scitotenv.2022.154849.

Jiang, Z., T. Zheng, M. Bergin, and D. Carlson. “Improving spatial variation of ground-level PM2.5 prediction with contrastive learning from satellite imagery.” Science of Remote Sensing 5 (June 1, 2022). https://doi.org/10.1016/j.srs.2022.100052.