Publications

Bio-molecular control theory:

1. Corentin Briat*, Ankit Gupta* and Mustafa Khammash. Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks. Cell Systems, 2016, Vol. 2(1) (*co-first authors).

2. Stephanie Aoki*, Gabriele Lillacci*, Ankit Gupta*, Armin Baumschlager, David Schweingruber and Mustafa Khammash. A universal  biomolecular integral feedback controller for robust perfect adaptation. Nature, 2019  (*co-first authors).

3. Corentin Briat*, Ankit Gupta* and Mustafa Khammash. Antithetic proportional-integral feedback for reduced variance and improved control performance of stochastic reaction networks. Journal of the Royal Society Interface, 2018, Vol. 15 (143) (*co-first authors).

4. Daniele Cappelletti, Ankit Gupta and Mustafa Khammash. A hidden integral structure endows Absolute Concentration Robust systems with resilience to dynamical concentration disturbances. Journal of Royal Society Interface 2020, 17:20200437.

5. Ankit Gupta and Mustafa Khammash. Universal structural requirements for maximal robust perfect adaptation in biomolecular networks. Proceedings of the National Academy of Sciences, 2022 vol. 119, no. 43, p. e2207802119.

6. Daniele Cappelletti, Ankit Gupta and Mustafa Khammash. A Linear Constrained Integral Feedback for a Class of Reaction Systems with Absolute Concentration Robustness. IEEE Conference on Decision and Control (CDC), 2019.

7. Ankit Gupta, Corentin Briat and Mustafa Khammash. Variance reduction in stochastic gene expression under integral feedback control. IEEE Conference on Decision and Control (CDC), 2018.

8. Ankit Gupta and Mustafa Khammash. The Internal Model Principle for biomolecular control theory. IEEE Open Journal of Control Systems, 2023.
   
   

9. Yuji Hirono*, Ankit Gupta* and Mustafa Khammash*. Rethinking Robust Adaptation: Characterization of Structural Mechanisms for Biochemical Network Robustness through Topological Invariants. PRX Life, 2025, Vol. 3, No. 1 (*equal authors).

10. Maurice Filo*, Ankit Gupta* and Mustafa Khammash. Anti-windup Strategies for Biomolecular Control Systems Facilitated by Model Reduction Theory for Sequestration Networks. Science Advances, 2024, Vol. 10(34) (*co-first authors).

11. Armin M. Zand, Ankit Gupta and Mustafa Khammash. Cascaded Antithetic Integral Feedback Motifs for Enhanced Stability and Performance. IEEE Control Systems Letters, 2024, Vol. 8.

12. Ankit Gupta and Eduardo D. Sontag. Cumulative dose responses for adapting biological systems. Journal of the Royal Society Interface, 2025, Vol. 22 (229).

13. Ankit Gupta*, Yuji Hirono*  and Mustafa Khammash*. An Internal Model Principle for Biochemical Networks: Algebraic and topological characterization for maximal robustness, 2024 (*equal authors). IEEE Control Systems Magazine, 2026, Vol.46(1).

14. Armin Zand, Ankit Gupta and Mustafa Khammash. Control with Practical Guarantees of Stationary Variance in Stochastic Chemical Reaction Networks. IEEE Conference on Decision and Control (CDC), Rio de Janeiro, Brazil, 2025.

Stability Analysis for Stochastic Reaction Networks:

1. Ankit Gupta*, Corentin Briat* and Mustafa Khammash. A scalable computational framework for establishing long-term behavior of stochastic reaction networks. PLOS Computational Biology, 2014, Vol. 10(6) (*co-first authors).

2. Ankit Gupta and Mustafa Khammash. Computational identification of irreducible state-spaces for stochastic reaction networks. SIAM Journal on Applied Dynamical Systems, 2018, Vol. 17 (2).

3. Ankit Gupta and Mustafa Khammash. Determining the long-term behavior of cell populations: A new procedure for detecting ergodicity in large stochastic reaction networks. 19th IFAC World Congress, Cape Town, South Africa, 2014.

4. Corentin Briat, Ankit Gupta, Iman Shames and Mustafa Khammash. Scalable tests for ergodicity analysis of large-scale interconnected stochastic reaction networks.  21st International Symposium on Mathematical Theory of Networks and Systems, Groningen, The Netherlands, 2014.

Sensitivity Analysis for Stochastic Reaction Networks:

1. Quentin Badolle, Ankit Gupta and Mustafa Khammash. Unbiased estimation of second-order parameter sensitivities for stochastic reaction networks. 2024. SIAM Journal on Scientific Computing, 2026, Vol. 48(1).

2.  Quentin Badolle, Ankit Gupta and Mustafa Khammash. The generator gradient estimator is an adjoint state method for stochastic differential equations, 2024.

3. Ankit Gupta, Muruhan Rathinam and Mustafa Khammash. Estimation of parameter sensitivities for stochastic reaction networks using tau-leap simulations. SIAM Journal on Numerical Analysis, 2018, Vol. 56 (2).

4. Ankit Gupta and Mustafa Khammash. An efficient and unbiased method for sensitivity analysis of stochastic reaction networks. Journal of the Royal Society Interface, 2014, Vol. 11. 

5. Ankit Gupta and Mustafa Khammash. Sensitivity analysis for stochastic chemical reaction networks with multiple time-scales. Electronic Journal of Probability, 2014, Vol. 19(59).

6. Patrik Dürrenberger, Ankit Gupta and Mustafa Khammash. A finite state projection method for steady-state sensitivity analysis of stochastic reaction networks. The Journal of Chemical Physics, 2019, Vol. 150(13).  

7. Ankit Gupta and Mustafa Khammash. Sensitivity analysis for multiscale stochastic reaction networks using hybrid approximations. Bulletin of Mathematical Biology. Special Issue: Gillespie and His Algorithms, 2018.

8. Ankit Gupta and Mustafa Khammash. Unbiased estimation of parameter sensitivities for stochastic chemical reaction networks. SIAM Journal on Scientific Computing, 2013 Vol. 35. 

Master Equation Solvers:

1. Quentin Badolle, Arthur Theuer, Zhou Fang, Ankit Gupta and Mustafa Khammash. Interpretable neural approximation of stochastic reaction dynamics with guaranteed reliability, 2025. 

2. Zhou Fang*, Ankit Gupta* and Mustafa Khammash. Advanced methods for gene network identification and noise decomposition from single-cell data. Nature Communications 2024, Vol. 15, No. 1  (*co-first authors).

3. Ankit Gupta, Christoph Schwab and Mustafa Khammash. DeepCME: A deep learning framework for computing solution statistics of the chemical master equation. PLOS Computational Biology, 2021, Vol. 17(12). 

4. Ankit Gupta, Jan Mikelson and Mustafa Khammash. A finite state projection algorithm for the stationary solution of the chemical master equation. The Journal of Chemical Physics, 2017, Vol. 147(15).

5. Benjamin Hepp, Ankit Gupta and Mustafa Khammash. Adaptive Hybrid Simulations for Multiscale Stochastic Reaction Networks. The Journal of Chemical Physics, 2015, Vol. 142(3).

6. Ankit Gupta and Mustafa Khammash. Padé SSA: A frequency domain method for estimating the dynamics of stochastic reaction networks. IEEE Conference on Decision and Control (CDC), Cancun, Mexico, 2022.

7. Ankit Gupta and Mustafa Khammash. Finding the steady-state solution of the chemical master equation. IEEE Conference on Control Technology and Applications, Hawaii, USA, 2017.

Phylodynamics/Phylogenetics:

1. Ankit Gupta, Marc Manceau, Timothy Vaughan, Mustafa Khammash and Tanja Stadler. The probability distribution of the reconstructed phylogenetic tree with occurrence data. Journal of Theoretical Biology, Vol. 488, 2020. Post-​print (PDF, 525 KB) made available under the CC-​BY-NC-ND 4.0 licence. 

2. Marc Manceau, Ankit Gupta, Timothy Vaughan and Tanja Stadler. The ancestral population size conditioned on the reconstructed phylogenetic tree with occurrence data. Journal of Theoretical Biology, 2021, Vol. 509.

3. Jérémy Andréoletti, Antoine Zwaans, Rachel Warnock, Gabriel Aguirre-Fernández, Joëlle Barido-Sottani, Ankit Gupta, Tanja Stadler and Marc Manceau. The Occurrence Birth-Death Process for combined-evidence analysis in macroevolution and epidemiology. Systematic Biology, 2022.

Frequency-domain Analysis:

1.  Ankit Gupta and Mustafa Khammash. Frequency spectra and the color of cellular noise. Nature Communications 2022, Vol.13, No. 4305.

2. Ankit Gupta and Mustafa Khammash. Analytical computation of the power spectral density for unimolecular stochastic reaction networks. IFAC World Congress, Berlin, Germany, 2020.

Stochastic Filtering:

1. Zhou Fang, Ankit Gupta and Mustafa Khammash. Effective filtering approach for joint parameter-state estimation in SDEs via Rao-Blackwellization and modularization, 2025. Under Review. 

2. Zhou Fang, Ankit Gupta and Mustafa Khammash. Stochastic filtering for multiscale stochastic reaction networks based on hybrid approximations. Journal of Computational Physics, 2022, Vol. 467, No. 111441.

3. Zhou Fang, Ankit Gupta and Mustafa Khammash. Convergence of regularized particle filters for stochastic reaction networks. SIAM Journal on Numerical Analysis, 2023, Vol. 61, No. 2.

4. Elena D'Ambrosio, Zhou Fang, Ankit Gupta, Sant Kumar and Mustafa Khammash. Filtered finite state projection method for the analysis and estimation of stochastic biochemical reaction networks, 2022.  SIAM Journal on Applied Dynamical Systems, 2026, Vol. 25(1).

5. Zhou Fang*, Ankit Gupta* and Mustafa Khammash. Advanced methods for gene network identification and noise decomposition from single-cell data. Nature Communications 2024, Vol. 15, No. 1  (*co-first authors).

Role of noise in Systems Biology:

1. Ankit Gupta*, Benjamin Hepp* and Mustafa Khammash. Noise Induces the Population-Level Entrainment of Incoherent, Uncoupled Intracellular Oscillators. Cell Systems, 2016, Vol. 3(6) (*co-first authors).

2. Ankit Gupta, Andreas Milias-Argeitis and Mustafa Khammash. Dynamic disorder in simple enzymatic reactions induces stochastic amplification of substrate. Journal of the Royal Society Interface, 2017, Vol. 14(132). 

Measure-Valued processes and Cell Polarity:

1. Ankit Gupta. The Fleming-Viot limit of an interacting spatial population with fast density regulation. Electronic Journal of Probability, 2012 Vol.17.

2. Ankit Gupta. Stochastic model for cell polarity. Annals of Applied Probability, 2012 Vol.22.

Adaptive Dynamics:

1. Ankit Gupta, Viet Chi Tran and J.A.J Metz. A new proof for the convergence of an individual based model to the Trait substitution sequence. Acta Applicandae Mathematicae, 2014, Vol. 131. 

Miscellaneous:

1. Ankit Gupta, Patrik Dürrenberger and Mustafa Khammash. Quantification of loading effects in interconnections of stochastic reaction networks. Proceedings of the 18th European Control Conference (ECC), 2019.

2. Ankit Gupta and B. Sury. Decimal expansion of 1/p and subgroup sums, Integers, 2005 Vol 5(1), A19.