Degrees

Research grants

2022-2025 - Kavli Foundation (personal posdoctoral research grant) - Data-driven Control of Neural Dynamics as a Tool for Understanding Resilience to Environmental Temperature Change

Peer-reviewed Journal papers

R. Schmetterling, T. B. Burghi, and R. Sepulchre. ?Adaptive Conductance Control?. Accepted for publication at IFAC Annual Reviews in Control, December 2021. T. B. Burghi, M. Ivanova, H. Wang, E. Marder, and T. O?Leary. ?Rapid, interpretable, data-driven models of neural dynamics using Recurrent Mechanistic Models?. Proceedings of the National Academy of Sciences (PNAS). In print, accepted June 2025. Preprint available on
https://www.biorxiv.org/content/10.1101/2024.10.10.617633v2.

T. B. Burghi and R. Sepulchre, ? T. B. BurghiOnline estimation of biophysical neural networks, K. Schapiro, M. Ivanova, H. Wang, E. Marder, and T. O?Leary. ?Recurrent data-driven models quantitatively predict intracellular dynamics in a neural circuit?. Frontiers in Computational Neuroscience. In print, accepted July 2025. ?. Preprint; in review, IEEE Transactions on Automatic Control, November 2021.

C. Toschi, M. H. El-Sayed, T. B. Burghi, T. Sell, P. Moazen, L. Huang, U. Gether, T. W. Robbins, J. W. Dalley, ? T. B. Burghi and R. Sepulchre. ?Adaptive Observers for Biophysical Neuronal Circuits?. IEEE Transactions on Automatic Control 69.8 (2024), pp. 5020?5033.Dissociating reward sensitivity and negative urgency effects on impulsivity in the 5-choice serial reaction time task?. Under review, Brain and Neuroscience Advances, October 2021.

C. Grussler, T.B. Burghi, and S. Sojoudi, ? T. B. Burghi, J. G. Iossaqui, and J. F. Camino. ?A General Update Rule for Lyapunov-Based Adaptive Internally Hankel $k$-positive systemsControl of Mobile Robots with Wheel Slip?. International Journal of Adaptive Control and Signal Processing ?38.4 (2024), pp. 1172?1198.. Preprint; accepted for publication, SIAM Journal on Control and Optimization, March 2021.

T. B. Burghi, M. Schoukens, and R. Sepulchre. ? T. Anttonen, T. B. Burghi, L. Duvall, M. P. Fernandez, G. Gutierrez, C. M. F. Kermen, and A. Michaiel. Feedback identification of conductance-based models?Neurobiology and Changing Ecosystems: Mechanisms Underlying Responses to Human-Generated ?. Automatica 123, Article 109297Environmental Impacts?. Journal of Neuroscience 43 (45 Nov. 2023)., January 2021.

Conference papersC. Grussler, T. B. Burghi, and S. Sojoudi. ?Internally Hankel k-Positive Systems?. SIAM Journal on Control and Optimization 60.4 (2022), pp. 2373?2392. eprint: https://doi.org/10.1137/21M1404685.

T. B. Burghi, Timothy O'Leary, and R. Sepulchre. Schmetterling, ? T. B. Burghi, and R. Sepulchre. ?Adaptive conductance control?. Annual Reviews in Control 54 (2022), pp. 352?362. issn: 1367-5788. doi: https://doi.org/10.1016/j.arcontrol.2022.07.005.Distributed online estimation of biophysical neural networks?. Preprint; in review, 61st IEEE Conference on Decision and Control (CDC 2022).

J. G. Lee, T. B. Burghi, and R. Sepulchre. ?Induced contraction?. Under review, 61st IEEE Conference on Decision and Control (CDC). Mar. 2022. C. Toschi, M. H. Sayed, T. B. Burghi, T. Sell, P. Moazen, L. Huang, U. Gether, T. W. Robbins, and J. W. Dalley. ?Dissociating reward sensitivity and negative urgency effects on impulsivity in the five-choice serial reaction time task?. Brain and Neuroscience Advances 6 (2022), p. 23982128221102256.

J. G. Lee and T. B. Burghi. ?Funnel control by induced contraction?. Under review, 25th International Symposium on Mathematical Theory of Networks and Systems (MTNS). Feb. 2022. T. B. Burghi, M. Schoukens, and R. Sepulchre. ?Feedback identification of conductance-based models?. Automatica 123 (Jan. 2021), p. 109297. url: https://doi.org/10.1016/j.automatica.2020.109297.

T. B. Burghi, M. Schoukens, and R. Sepulchre. ? Peer-reviewed conference papersSystem identification of biophysical neuronal models?. 59th IEEE Conference on Decision and Control (CDC 2020) ? December 2020, Jeju Island, South Korea.

T. B. C. Grussler Burghi, M. Schoukens, and R. Sepulchre. ? Feedback for Nonlinear System IdentificationT. B. Burghi?. 18th European Control . ?On the monotonicity of frequency response gains?. In: Proceedings of the 62nd IEEE Conference (ECC 2019) ? June 2019, Naples, Italy. on Decision and Control (CDC). Singapore, Singapore, Dec. 2023, pp. 1686?1691.

T. B. R. Schmetterling, Burghi, J. Iossaqui, J. Camino, ?Stability analysis of perturbed nonlinear systems applied to the trajectory control of a wheeled mobile robot subject to lateral slip ?. Proceedings of the 17 ^thT. B. BurghiInternational Symposium on Dynamic Problems , and R. Sepulchre. ?Robust online estimation of Mechanics, Natal, Brazil, 2015. biophysical neural circuits?. In: Proceedings of the 62nd IEEE Conference on Decision and Control (CDC). Singapore, Singapore, Dec. 2023, pp. 703?708.

Conference posters T. B. Burghi , T. O?Leary, and R. Sepulchre. ?Distributed online estimation of biophysical neural networks?. In: Proceedings of the 61st IEEE Conference on Decision and Control (CDC). Cancun, Mexico, Dec. 2022, pp. 628?634.

T. B. Burghi, E. Morozova, S. Kedia, E. Marder, and T. O'Leary. "Learning a biophysical neural model during the time frame of an experiment." FENS Forum 2022 (Federation of European Neuroscience Societies). Feb. 2022. J. G. Lee, T. B. Burghi, and R. Sepulchre. ?Open-loop contraction design?. In: Proceedings of the 61st IEEE Conference on Decision and Control (CDC). Cancun, Mexico, Dec. 2022, pp. 7339?7345.

T. B. Burghi and Rodolphe Sepulchre. ?Identification of Excitable Neuronal Systems?. 27th Annual Computational Neuroscience Meeting (CNS*2018) ? July 2018, Seattle, WA, United States. J. G. Lee and T. B. Burghi. ?Funnel control by induced contraction?. In: 25th International Symposium on Mathematical Theory of Networks and Systems (MTNS). Bayreuth, Germany, Sept. 2022, pp. 248?253.

Talks T. B. Burghi, M. Schoukens, and R. Sepulchre. ?System identification of biophysical neuronal models?. In: 59th IEEE Conference on Decision and Control. Jeju Island, South Korea, Dec. 2020, pp. 6180?6185.

?Identification of Excitable Neuronal Systems?. 27th European Research Network on System Identification (ERNSI) Workshop ? September 2018, Cambridge, United Kingdom. T. B. Burghi, M. Schoukens, and R. Sepulchre. ?Feedback for nonlinear system identification?. In: 18th European Control Conference (ECC). Naples, Italy, June 2019, pp. 1344?1349.

T. B. Burghi, J. G. Iossaqui, and J. F. Camino. ?Stability analysis of perturbed nonlinear systems applied to the tracking control of a wheeled mobile robot under lateral slip?. In: XVII International Symposium on Dynamic Problems of Mechanics. Natal-RN, Brazil, Feb. 2015, pp. 22?27.

Peer-reviewed conference posters

T. B. Burghi, T. O?Leary, and R. Sepulchre. Neurons learn by predicting their synaptic inputs. Bernstein Computational Neuroscience Conference, Frankfurt am Main, Germany. Sept. 2024.

T. B. Burghi, E. Morozova, M. Ivanova, E. Marder, and T. O?Leary. Estimating mechanistic neuronal behaviour with artificial neural networks. Bernstein Computational Neuroscience Conference, Berlin, Germany. Sept. 2023.

E. Morozova, P. Newstein, T. B. Burghi, T. O?Leary, and E. Marder. Robustness of reciprocally inhibitory circuits to perturbation and neuromodulation. (Poster) Society for Neuroscience annual conference (SfN22), San Diego, USA. Nov. 2022.

T. B. Burghi, E. Morozova, S. Kedia, E. Marder, and T. O?Leary. Learning a biophysical neural model during the time frame of an experiment. FENS Forum 2022 (Federation of European Neuroscience Societies), Paris, France. Feb. 2022.

T. B. Burghi and R. Sepulchre. Identification of excitable neuronal systems. 27th Annual Computational Neuroscience (CNS) Meeting. Seattle, WA, United States, July 2018.

Invited talks

T. B. Burghi. Predicting bifurcations in biological neural circuits. Workshop on Leveraging bifurcations for control of intelligent and collective behaviors. Part of the IEEE Conference on Decision and Control (CDC) 2024, Milan, Italy. Dec. 2024.

T. B. Burghi. Estimation and closed-loop control of living neural circuits. Seminar at École de Mines de Paris, Centre Automatique et Syst`emes. Nov. 2024.

T. B. Burghi. Estimation and closed-loop control of living neural circuits. Seminar University of Oxford, Control Group, Department of Engineering Science. Nov. 2024.

T. B. Burghi. Estimation and closed-loop control of living neural circuits. Seminar at the Oxford Robotics Institute (ORI), University of Oxford. May 2025.

T. B. Burghi. Estimation and closed-loop control of living neural circuits. Seminar at Université de Lorraine, Centre de Recherche en Automatique de Nancy. Nov. 2023.

T. B. Burghi, E. Morozova, M. Ivanova, E. Marder, and T. O?Leary. Estimation and control of temperature-dependent neural dynamics. Workshop on Geometrically Guided Analysis and Design in Optimization and Control, Nanyang Technological University, Singapore. Dec. 2023.

T. B. Burghi, E. Morozova, M. Ivanova, E. Marder, and T. O?Leary. Tracking the effects of temperature perturbations in neuronal models: a data-driven approach. Society for Neuroscience annual conference (SfN23), Washington D.C., USA. Nov. 2023.

T. B. Burghi and R. Sepulchre. Identification of excitable neuronal systems. 27th European Research Network on System Identification (ERNSI) Workshop. Cambridge, UK, Sept. 2018.