I am a postdoc at Stanford Statistics and the Wu Tsai Neurosciences Institute, where I work with Scott Linderman. My work lies at the intersection of probabilistic machine learning and statistical neuroscience—developing interpretable machine learning approaches to understand behavior and neural dynamics. I obtained my PhD at Princeton, advised by Jonathan Pillow. Long time ago, I was an undergrad at the Indian Institute of Technology in Delhi, where I worked with Sumeet Agarwal. I have also spent two wonderful summers working in industry—at Meta Reality labs working on wrist-based neural interfaces, and another at MosaicML working on large language models.
Aside from research: I like to overdose on literary/historical fiction and occasionally put on my creative writing hat. I also like running, painting, and listening to Bollywood music.
EDucation
Ph.D. in Electrical and Computer Engineering.
2019-2024. Princeton University [Thesis]
B.Tech in Electrical Engineering.
2015-2019. IIT Delhi
Research
BAYESIAN ACTIVE LEARNING FOR DISCRETE LATENT VARIABLE MODELS
Aditi Jha, Zoe C. Ashwood, Jonathan W. Pillow. Neural Computation. Volume 36, Issue 3. March 2023.
Paper / Talk at COSYNE workshops 2022
EXTRACTING LOW-DIMENSIONAL PSYCHOLOGICAL REPRESENTATIONS FROM CONVOLUTIONAL NEURAL NETWORKS
Aditi Jha, Joshua C. Peterson, Thomas L. Griffiths. Cognitive Science. Volume 47, Issue 1. January, 2023.
DYNAMIC INVERSE REINFORCEMENT LEARNING FOR CHARACTERIZING ANIMAL BEHAVIOR
Zoe C. Ashwood*, Aditi Jha*, Jonathan W. Pillow. Advances in Neural Information Processing Systems (NeurIPS) 35 (2022) [Oral Presentation].
Paper / Code / COSYNE Talk
FACTOR-ANALYTIC INVERSE REGRESSION FOR HIGH-DIMENSIONAL, SMALL-SAMPLE DIMENSIONALITY REDUCTION
Aditi Jha*, Michael J. Morais*, Jonathan W. Pillow. Proceedings of the 38th International Conference on Machine Learning (ICML), PMLR 139 (2021).
Paper/ Code/ Summary Video at Cosyne’21/ Invited Talk at MLSE 2020
EXTRACTING LOW-DIMENSIONAL PSYCHOLOGICAL REPRESENTATIONS FROM CONVOLUTIONAL NEURAL NETWORKS
Aditi Jha, Joshua C. Peterson, Thomas L. Griffiths. Proceedings of the 42nd Annual Conference of the Cognitive Science Society (CogSci), 2020.
DO DEEP NEURAL NETWORKS MODEL NONLINEAR COMPOSITIONALITY IN THE NEURAL REPRESENTATION OF HUMAN-OBJECT INTERACTIONS?
Aditi Jha, Sumeet Agarwal. Proceedings of the 3rd Computational Cognitive Neuroscience Conference (CCN) Berlin, Germany. 2019
Misc
Pillow Lab’s blog/ PNI’s CompNeuro Journal Club / My current read
Lastly, if you love this show too, we can be best friends