Research by Topic

My research encompasses many topics, including causal inference, hypothesis testing, neuroscience, etc. You see my work by topic below, or you can browse by type or by year. A full list is also available on Google Scholar.

Causal Inference

• Batch Effects Are Causal Effects: Applications in Human Connectomics
  by Eric W. Bridgeford, Michael Powell, Gregory Kiar, Stephanie Noble, Jaewon Chung, Sambit Panda, Ross Lawrence, Ting Xu, Michael Milham, Brian Caffo, and Joshua T. Vogelstein
  in bioRxiv on August, 2023
• Learning Sources of Variability from High-Dimensional Observational Studies
  by Eric W. Bridgeford, Jaewon Chung, Brian Gilbert, Sambit Panda, Adam Li, Cencheng Shen, Alexandra Badea, Brian Caffo, and Joshua T. Vogelstein
  in arXiv on July, 2023

Hypothesis Testing

• Learning Sources of Variability from High-Dimensional Observational Studies
  by Eric W. Bridgeford, Jaewon Chung, Brian Gilbert, Sambit Panda, Adam Li, Cencheng Shen, Alexandra Badea, Brian Caffo, and Joshua T. Vogelstein
  in arXiv on July, 2023
• The Chi-Square Test of Distance Correlation
  by Cencheng Shen, Sambit Panda, and Joshua T. Vogelstein
  in Journal of Computational and Graphical Statistics on January, 2022
• hyppo: A Multivariate Hypothesis Testing Python Package
  by Sambit Panda, Satish Palaniappan, Junhao Xiong, Eric W. Bridgeford, Ronak Mehta, Cencheng Shen, and Joshua T. Vogelstein
  in arXiv on April, 2021
• Nonpar MANOVA via Independence Testing
  by Sambit Panda, Cencheng Shen, Ronan Perry, Jelle Zorn, Antoine Lutz, Carey E. Priebe, and Joshua T. Vogelstein
  in arXiv on April, 2021
• Learning Interpretable Characteristic Kernels via Decision Forests
  by Cencheng Shen, Sambit Panda, and Joshua T. Vogelstein
  in arXiv on September, 2020
• Multivariate Independence and K-Sample Testing
  by Sambit Panda
  in Johns Hopkins University on May, 2020

Neural Networks

• When Are Deep Networks Really Better than Decision Forests at Small Sample Sizes, and How?
  by Haoyin Xu, Kaleab A. Kinfu, Will LeVine, Sambit Panda, Jayanta Dey, Michael Ainsworth, Yu-Chung Peng, Madi Kusmanov, Florian Engert, Christopher M. White, Joshua T. Vogelstein, and Carey E. Priebe
  in arXiv on November, 2021

Neuroscience

• FiPhA: An Open-Source Platform for Fiber Photometry Analysis
  by Matthew F. Bridge, Leslie R. Wilson, Sambit Panda, Korey D. Stevanovic, Ayland C. Letsinger, Sandra McBride, and Jesse D. Cushman
  in bioRxiv on July, 2023
• Elucidating Relationships within Neurological Screening Batteries via Random Forest-Based Hypothesis Testing
  by Sambit Panda, Leslie R. Wilson, Jariatu Stallone, Dalisa Kendricks, Korey Stevanovic, and Jesse D. Cushman
  on July, 2023
• Selective and Mechanically Robust Sensors for Electrochemical Measurements of Real-Time Hydrogen Peroxide Dynamics in Vivo
  by Leslie R. Wilson, Sambit Panda, Andreas C. Schmidt, and Leslie A. Sombers
  in Analytical Chemistry on January, 2018

Random Forest

• Simplest Streaming Trees
  by Haoyin Xu, Jayanta Dey, Sambit Panda, and Joshua T. Vogelstein
  in arXiv on November, 2022
• When Are Deep Networks Really Better than Decision Forests at Small Sample Sizes, and How?
  by Haoyin Xu, Kaleab A. Kinfu, Will LeVine, Sambit Panda, Jayanta Dey, Michael Ainsworth, Yu-Chung Peng, Madi Kusmanov, Florian Engert, Christopher M. White, Joshua T. Vogelstein, and Carey E. Priebe
  in arXiv on November, 2021
• Learning Interpretable Characteristic Kernels via Decision Forests
  by Cencheng Shen, Sambit Panda, and Joshua T. Vogelstein
  in arXiv on September, 2020