Ni Ji

Animals and humans have the remarkable ability to actively seek out new information (exploration) and rapidly derive structured knowledge from experiences (active learning), which allows them to navigate complex environments, optimize resource use, and adapt to dynamic, uncertain situations. In contrast, despite rapid advances, today’s AI agents still rely on large amounts of labeled data and struggle with autonomously learning from experience. By incorporating brain-like mechanisms for exploration and active learning, AI agents may become more data-efficient and capable of faster generalization and adaptation in unfamiliar environments.

Our group thus aim to understand how the brain explores and acquires structured knowledge in both physical and cognitive environments, particularly under uncertain or novel contexts. We focus on uncovering behavioral and neural mechanisms that control intrinsic motivation or curiosity-driven behavior, and how these principles can be translated into AI systems capable of efficient learning with minimal data. Through both empirical studies and the development of biologically plausible computational models, we seek to uncover neuro-behavioral mechanisms that enable adaptive, data-efficient exploration and learning in the brain, with the ultimate goal of creating AI algorithms that mimic these capabilities in real-world applications.

2020    Women in Science Travel (WIST) Fund

2020   Computational and Systems Neuroscience (COSYNE) Meeting Travel Award

2017-2019    Charles A. King Trust Postdoctoral Fellowship

2016-2017    JFDP Postdoctoral Fellowship

2015    Marine Biological Laboratory Computational Image Analysis Course Travel Award

2007-2011    Singleton Fellowship

2010    Okinawa Institute of Science and Technology Travel Award

2007-2009    Berea College Graduate Study Grant

2003-2007    Berea College Full Scholarship

Publications (selected)

1.Chen, J.*, An, J., Liu, Y., Ji, N.# (2025). Brain Bandit: A Biologically Grounded Neural Network for Efficient Control of Exploration. ICLR 2025 (Oral, top 1%).

Prior to 2022:

2. Ji, N.*, Madan, G.K., Fabre, G.I., Dayan, A., Baker, C.M., Kramer, T.S., Nwabudike, I, Flavell, S.W.# (2021). A neural circuit for flexible control of persistent behavior states. eLife 2021;10:e62889.

3. Ji, N.*, Venkatachalam, V., Rodgers, H.D., Lim, M., Kawano, T., Clark, C.M., Alkema, M.J.#, Zhen, M.#, Samuel, A.D.T.# (2021). Corollary discharge promotes a sustained motor state in a neural circuit for navigation. eLife 2021;10:e68848.

4. Ji, N.* and Flavell S.W.# (2017) Hydra: Imaging nerve nets in action. Current Biology 27(8): R294-295.

5. Venkatachalam, V.*, Ji, N.*, Wang, X., Mitchell, J., Klein, M., Tabone, C., Clark, C. M., Greenwood, J.S.F., Chisholm, A., Srinivasan, J., Alkema, M.J., Zhen, M., Samuel, A.D.T. #(2016). Pan-neuronal imaging in roaming animals. PNAS 113(8): E1082-1088.

6. Ji, N.*, Middelkoop, T.C.*, Mentink, R.A., Betist, M.C., Tonegawa, S., Mooijman, D., Korswagen, H.C.#, van Oudenaarden, A.# (2013) Feedback control of gene expression variability in the Caenorhabditis elegans Wnt pathway. Cell 155(4):869-80.

7. Tan, R.Z.*, Ji, N., Mentink, R., Korswagen, H.C., van Oudenaarden, A.# (2013) Deconvolving the roles of Wnt ligands and receptors in sensing and amplification. Molecular Systems Biology 9:631.

8. Ji, N.* and van Oudenaarden, A.# (2012) Single molecule fluorescent in situ hybridization (smFISH) of C. elegans Worms and Embryos. WormBook, ed. The C. elegans Research Community, WormBook, doi/10.1895/wormbook.1.153.1, http://www.wormbook.org.

9. Scott, B.B.*, Gardner, T., Ji, N., Fee, M.S. Lois, C.# (2012) Wandering neuronal migration in the postnatal vertebrate forebrain. Journal of Neuroscience 32:1436-46.