Thiago Burghi
Background - Research - Publications
Position: Research Associate
Office Location: BN4-86
E-mail: tbb29 [at] cam.ac.uk
Principal Investigator: Dr Timothy O'Leary
Background
Degrees 2012: BSc Automation and Control Engineering (University of Campinas, Brazil) 2012: Diplôme d'Ingénieur (École Nationale Supérieure de Techniques Avancées, France) 2014: Msc Mechanical Engineering (University of Campinas, Brazil) 2020: PhD Feedback for neuronal system identification (University of Cambridge, UK) 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 ChangeResearch Interests
Neuronal systems; Deep learning; Adaptive control; Nonlinear system identification; Nonlinear systems analysis; Differential analysis.Publications
Peer-reviewed Journal papers 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 onhttps://www.biorxiv.org/content/10.1101/2024.10.10.617633v2. T. B. Burghi, 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. T. B. Burghi and R. Sepulchre. “Adaptive Observers for Biophysical Neuronal Circuits”. IEEE Transactions on Automatic Control 69.8 (2024), pp. 5020–5033. T. B. Burghi, J. G. Iossaqui, and J. F. Camino. “A General Update Rule for Lyapunov-Based Adaptive Control of Mobile Robots with Wheel Slip”. International Journal of Adaptive Control and Signal Processing 38.4 (2024), pp. 1172–1198. T. Anttonen, T. B. Burghi, L. Duvall, M. P. Fernandez, G. Gutierrez, C. M. F. Kermen, and A. Michaiel. “Neurobiology and Changing Ecosystems: Mechanisms Underlying Responses to Human-Generated Environmental Impacts”. Journal of Neuroscience 43 (45 Nov. 2023). C. 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. R. 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. 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. 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. Peer-reviewed conference papers C. Grussler and T. B. Burghi. “On the monotonicity of frequency response gains”. In: Proceedings of the 62nd IEEE Conference on Decision and Control (CDC). Singapore, Singapore, Dec. 2023, pp. 1686–1691. R. Schmetterling, T. B. Burghi, and R. Sepulchre. “Robust online estimation of biophysical neural circuits”. In: Proceedings of the 62nd IEEE Conference on Decision and Control (CDC). Singapore, Singapore, Dec. 2023, pp. 703–708. 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. 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. 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. 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. 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.