PhD, Biomedical engineering, Northwestern University, 2012 - 2019
MS, Biomedical Engineering, Northwestern University, 2012 - 2014
BS, Electrical Engineering, University of Illinois at Urbana Champaign, 2008 - 2011
Chowdhury, R.H. (2024). Reaching into the future. Elife, 13, e101739.eLife. doi: 10.7554/eLife.101739.
Dekleva, B.M., Chowdhury, R.H., Batista, A.P., Chase, S.M., Yu, B.M., Boninger, M.L., & Collinger, J.L. (2024). Motor cortex retains and reorients neural dynamics during motor imagery. Nat Hum Behav, 8(4), 729-742.Springer Nature. doi: 10.1038/s41562-023-01804-5.
Sadeghi, M., Sharif Razavian, R., Bazzi, S., Chowdhury, R.H., Batista, A.P., Loughlin, P.J., & Sternad, D. (2024). Inferring control objectives in a virtual balancing task in humans and monkeys. Elife, 12, rp88514.eLife. doi: 10.7554/eLife.88514.
Dekleva, B.M., Chowdhury, R.H., Batista, A.P., Chase, S.M., Yu, B.M., Boninger, M.L., & Collinger, J.L. (2023). Motor cortex retains and reorients neural dynamics during motor imagery. bioRxiv, 4(01-27), 2023.01.17.524394.Cold Spring Harbor Laboratory. doi: 10.1101/2023.01.17.524394.
Sadeghi, M., Razavian, R.S., Bazzi, S., Chowdhury, R., Batista, A., Loughlin, P., & Sternad, D. (2023). Inferring control objectives in a virtual balancing task in humans and monkeys. bioRxiv, 2023.05.02.539055.Cold Spring Harbor Laboratory. doi: 10.1101/2023.05.02.539055.
Feulner, B., Perich, M.G., Chowdhury, R.H., Miller, L.E., Gallego, J.A., & Clopath, C. (2022). Small, correlated changes in synaptic connectivity may facilitate rapid motor learning. Nat Commun, 13(1), 5163.Springer Nature. doi: 10.1038/s41467-022-32646-w.
Gallego-Carracedo, C., Perich, M.G., Chowdhury, R.H., Miller, L.E., & Gallego, J.Á. (2022). Local field potentials reflect cortical population dynamics in a region-specific and frequency-dependent manner. Elife, 11, e73155.eLife. doi: 10.7554/eLife.73155.
Keshtkaran, M.R., Sedler, A.R., Chowdhury, R.H., Tandon, R., Basrai, D., Nguyen, S.L., Sohn, H., Jazayeri, M., Miller, L.E., & Pandarinath, C. (2022). A large-scale neural network training framework for generalized estimation of single-trial population dynamics. Nat Methods, 19(12), 1572-1577.Springer Nature. doi: 10.1038/s41592-022-01675-0.
Feulner, B., Perich, M.G., Chowdhury, R.H., Miller, L.E., Gallego, J.Á., & Clopath, C. (2021). Small, correlated changes in synaptic connectivity may facilitate rapid motor learning. 2021.10.01.462728.Cold Spring Harbor Laboratory. doi: 10.1101/2021.10.01.462728.
Gallego-Carracedo, C., Perich, M.G., Chowdhury, R.H., Miller, L.E., & Gallego, J.A. (2021). Local field potentials reflect cortical population dynamics in a region-specific and frequency-dependent manner. 2021.05.31.446454.Cold Spring Harbor Laboratory. doi: 10.1101/2021.05.31.446454.
Keshtkaran, M.R., Sedler, A.R., Chowdhury, R.H., Tandon, R., Basrai, D., Nguyen, S.L., Sohn, H., Jazayeri, M., Miller, L.E., & Pandarinath, C. (2021). A large-scale neural network training framework for generalized estimation of single-trial population dynamics. 2021.01.13.426570.Cold Spring Harbor Laboratory. doi: 10.1101/2021.01.13.426570.
Versteeg, C., Chowdhury, R.H., & Miller, L.E. (2021). Cuneate nucleus: The somatosensory gateway to the brain. Curr Opin Physiol, 20, 206-215.Elsevier. doi: 10.1016/j.cophys.2021.02.004.
Chowdhury, R.H., Glaser, J.I., & Miller, L.E. (2020). Area 2 of primary somatosensory cortex encodes kinematics of the whole arm. Elife, 9, e48198.eLife. doi: 10.7554/eLife.48198.
Gallego, J.A., Perich, M.G., Chowdhury, R.H., Solla, S.A., & Miller, L.E. (2020). Long-term stability of cortical population dynamics underlying consistent behavior. Nat Neurosci, 23(2), 260-270.Springer Nature. doi: 10.1038/s41593-019-0555-4.
Chowdhury, R.H., Glaser, J.I., & Miller, L.E. (2019). Area 2 of primary somatosensory cortex encodes kinematics of the whole arm. 643205.Cold Spring Harbor Laboratory. doi: 10.1101/643205.
Lucas, A., Tomlinson, T., Rohani, N., Chowdhury, R., Solla, S.A., Katsaggelos, A.K., & Miller, L.E. (2019). Neural Networks for Modeling Neural Spiking in S1 Cortex. Front Syst Neurosci, 13, 13.Frontiers. doi: 10.3389/fnsys.2019.00013.
Benjamin, A.S., Fernandes, H.L., Tomlinson, T., Ramkumar, P., VerSteeg, C., Chowdhury, R.H., Miller, L.E., & Kording, K.P. (2018). Modern Machine Learning as a Benchmark for Fitting Neural Responses. Front Comput Neurosci, 12, 56.Frontiers. doi: 10.3389/fncom.2018.00056.
Gallego, J.A., Perich, M.G., Chowdhury, R.H., Solla, S.A., & Miller, L.E. (2018). A stable, long-term cortical signature underlying consistent behavior. 447441.Cold Spring Harbor Laboratory. doi: 10.1101/447441.
Mazurek, K.A., Berger, M., Bollu, T., Chowdhury, R.H., Elangovan, N., Kuling, I.A., & Sohn, M.H. (2018). Highlights from the 28th Annual Meeting of the Society for the Neural Control of Movement. J Neurophysiol, 120(4), 1671-1679.American Physiological Society. doi: 10.1152/jn.00475.2018.
Benjamin, A.S., Fernandes, H.L., Tomlinson, T., Ramkumar, P., VerSteeg, C., Chowdhury, R., Miller, L., & Kording, K.P. (2017). Modern machine learning outperforms GLMs at predicting spikes. 111450.Cold Spring Harbor Laboratory. doi: 10.1101/111450.
Chowdhury, R.H., Tresch, M.C., & Miller, L.E. (2017). Musculoskeletal geometry accounts for apparent extrinsic representation of paw position in dorsal spinocerebellar tract. J Neurophysiol, 118(1), 234-242.American Physiological Society. doi: 10.1152/jn.00695.2016.
Glaser, J.I., Benjamin, A.S., Chowdhury, R.H., Perich, M.G., Miller, L.E., & Kording, K.P. (2017). Machine learning for neural decoding.
Suresh, A.K., Winberry, J.E., Versteeg, C., Chowdhury, R., Tomlinson, T., Rosenow, J.M., Miller, L.E., & Bensmaia, S.J. (2017). Methodological considerations for a chronic neural interface with the cuneate nucleus of macaques. J Neurophysiol, 118(6), 3271-3281.American Physiological Society. doi: 10.1152/jn.00436.2017.
Kim, D.H., Lu, N., Ma, R., Kim, Y.S., Kim, R.H., Wang, S., Wu, J., Won, S.M., Tao, H., Islam, A., Yu, K.J., Kim, T.I., Chowdhury, R., Ying, M., Xu, L., Li, M., Chung, H.J., Keum, H., McCormick, M., Liu, P., Zhang, Y.W., Omenetto, F.G., Huang, Y., Coleman, T., & Rogers, J.A. (2011). Epidermal electronics. Science, 333(6044), 838-843.American Association for the Advancement of Science (AAAS). doi: 10.1126/science.1206157.
Stoecker, W.V., Wronkiewiecz, M., Chowdhury, R., Stanley, R.J., Xu, J., Bangert, A., Shrestha, B., Calcara, D.A., Rabinovitz, H.S., Oliviero, M., Ahmed, F., Perry, L.A., & Drugge, R. (2011). Detection of granularity in dermoscopy images of malignant melanoma using color and texture features. Comput Med Imaging Graph, 35(2), 144-147.Elsevier. doi: 10.1016/j.compmedimag.2010.09.005.
Stoecker, W.V., Gupta, K., Shrestha, B., Wronkiewiecz, M., Chowdhury, R., Stanley, R.J., Xu, J., Moss, R.H., Celebi, M.E., Rabinovitz, H.S., Oliviero, M., Malters, J.M., & Kolm, I. (2009). Detection of basal cell carcinoma using color and histogram measures of semitranslucent areas. Skin Res Technol, 15(3), 283-287.Wiley. doi: 10.1111/j.1600-0846.2009.00354.x.