Source: http://www.bg.ic.ac.uk/research/g.stan/
Timestamp: 2019-04-18 22:47:05+00:00

Document:
My name is Guy-Bart STAN. I am a permanent academic member of staff in the Department of Bioengineering and the head of the Control Engineering Synthetic Biology group at Imperial College London (U.K.).
I am a Royal Academy of Engineering Chair in Emerging Technologies, Co-Director of the Imperial College Centre for Synthetic Biology, and Deputy Director of the EPSRC-funded Centre for Doctoral Training in BioDesign Engineering. I have been holding a EPSRC Engineering Fellowship for Growth in Synthetic Biology for the period January 2015 - February 2020.
I am also Co-Director of Research in Bioengineering, and a member of the Department of Bioengineering Research Committee and of the Equality and Departmental Culture Committee (EDCC).
I joined Imperial College in December 2009 as a Lecturer and got promoted to Reader in August 2014. From January 2006 until December 2009, I worked in the Control Group of the University of Cambridge (U.K.) as a Research Associate with support from EPSRC (EP/E02761X/1) for the period January 2007 - January 2010 and support from a European Commission FP6 Marie-Curie Intra-European Fellowship (EU FP6 IEF 025509 GASO) for the period January 2006 - January 2007. From January 2006 until December 2009, I was the weekly seminar organiser for the Cambridge University Control Group. From June to December 2005, I worked as Senior DSP Engineer at Philips Applied Technologies. I received my electrical engineering degree (with a speciality in electronics) in June 2000 and my Ph.D. degree (in Applied Sciences with a focus on Analysis and Control of Nonlinear Dynamical Systems) in March 2005, both from the University of Liège, Belgium. During my PhD, I mainly worked in the Nonlinear Systems and Control group at the Systems and Modeling research unit of the University of Liège and was supported by a PhD Research Fellowship from the F.N.R.S. (the Belgian National Fund for Scientific Research).
My webpage in the Department of Bioengineering of Imperial College London (U.K.).
My webpage in the Control Group of the University of Cambridge (U.K.).
For a quick overview of what the Control Engineering Synthetic Biology group is and examples of projects we are working on please have a look at this short introductory brochure.
Tools for engineering coordinated system behaviour in synthetic microbial consortia, N. Kylilis, Z. A. Tuza, G.-B. Stan, K. Polizzi, Nature Communications, July 2018, doi:10.1038/s41467-018-0504.
Computational Re-Design of Synthetic Genetic Oscillators for Independent Amplitude and Frequency Modulation, M. Tomazou, M. Barahona, K. Polizzi, G.-B. Stan, Cell Systems, Volume 6 (2018), n°4, pp. 508-520, doi:10.1016/j.cels.2018.03.013.
Burden-driven feedback control of gene expression, F. Ceroni, A. Boo, S. Furini, T. E. Gorochowski, O. Borkowski, Y. N. Ladak, A. R. Awan, C. Gilbert, G.-B. Stan, T. Ellis, Nature Methods, Volume 15 (2018), pp. 387-393, doi:10.1038/nmeth.4635. The paper made the cover of the May 2018 issue of Nature Methods.
Cell-free prediction of protein expression costs for growing cells, O. Borkowski, C. Bricio, M. Murgiano, B. Rothschild-Mancinelli, G.-B. Stan, T. Ellis, Nature Communications, Volume 9 (2018), doi:10.1038/s41467-018-03970-x.
The Interplay Between Feedback and Buffering in Homeostasis, E. Hancock, J. Ang, A. Papachristodoulou, G.-B. Stan, Cell Systems, Volume 5 (2017), n°5, pp. 498-508, doi:10.1016/j.cels.2017.09.013.
Identification of Nonlinear State-Space Systems from Heterogeneous Datasets, W. Pan, Y. Yuan, L. Ljung, J. Goncalves, G.-B. Stan, IEEE Transactions on Network Control Systems , Volume 5 (2017), n°2, pp. 737-747, doi:10.1109/TCNS.2017.2758966.
Quantifying cellular capacity identifies gene expression designs with reduced burden, F. Ceroni, R. Algar, G.-B. Stan, T. Ellis, Nature Methods, Volume 12 (2015), n°5, pp. 415–418, doi:10.1038/nmeth.3339. Preprint available here. The paper made the cover of the May 2015 issue of Nature Methods.
Simplified Mechanistic Models of Gene Regulation for Analysis and Design, E. Hancock, G.-B. Stan, J. Arpino, A. Papachristodoulou, Journal of the Royal Society Interface, Volume 12 (2015), n°108, doi:10.1098/rsif.2015.0312. A preprint is available here, while the supplementary information is available here.
Noise propagation in synthetic gene circuits for metabolic control, D. Oyarzun, J.-B. Lugagne, G.-B. Stan, ACS Synthetic Biology, Volume 4 (2015), n°2, pp. 116-125, doi:10.1021/sb400126a.
Synthetic gene circuits for metabolic control: design trade-offs and constraints, D. Oyarzun, G.-B. Stan, Journal of the Royal Society Interface, Volume 10 (2013), n°78, doi:10.1098/rsif.2012.0671.
The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology, M. Galdzicki, K. Clancy, E. Oberortner, M. Pocock, J. Quinn, C. Rodriguez, N. Roehner, M. Wilson, L. Adam, J. C. Anderson, B. Bartley, J. Beal, D. Chandran, J. Chen, D. Densmore, D. Endy, R. Gruenberg, J. Hallinan, N. Hillson, J. Johnson, A. Kuchinsky, M. Lux, G. Misirli, J. Peccoud, H. Plahar, E. Sirin, G.-B. Stan, A. Villalobos, A. Wipat, J. H. Gennari, C. Myers, H. Sauro, Nature Biotechnology, Volume 32 (2014), n°6, pp. 545–550, doi:10.1038/nbt.2891.
Engineering and ethical perspectives in synthetic biology, J. Anderson, N. Strelkowa, G.-B. Stan, T. Douglas, J. Savulescu, M. Barahona, and A. Papachristodoulou, EMBO reports, Volume 13 (2012), n°7, pp. 584-590, doi:10.1038/embor.2012.81.
Essential information for synthetic DNA sequences, J. Peccoud, J. C. Anderson, D. Chandran, D. Densmore, M. Galdzicki, M. W. Lux, C. A. Rodriguez, G.-B. Stan, H. M. Sauro, Nature Biotechnology, Volume 22 (Jan 2011), n°1, p. 22, doi:10.1038/nbt.1753.
I am passionate about developing new concepts and methods and applying the produced results to real-life problems. Currently, my main research interests are: Nonlinear Dynamical Systems Analysis and Control, Synthetic Biology, Systems Biology.
I am currently interested in the modelling, analysis, design, control, and implementation of cellular systems (in particular biomolecular feedback systems and gene regulatory networks); and in applications of systems and control engineering methods to the problem of robustly and optimally controlling natural or synthetic biology systems, e.g., robust control of gene regulation networks or optimal drug cocktails scheduling for chronic-like diseases treatments (e.g. cancer and HIV).
For a visual timeline of my career you can follow this link on Vizualize.me.
For a citations report of my published papers you can follow this link on Google Scholar Citations or this link on ResearchGate.
Interested in working with us in design and control of synthetic biology systems at the Department of Bioengineering of Imperial College London? There are always positions available for outstanding prospective PhD students and postdoctoral staff.
Hereafter, you will find links which provide you with information about openings and how to apply. Please email us if you wish to join the Stan Group.
If you want to conduct your own research, which is aligned with the core research work in my group, I can sponsor you for an Imperial College Research Fellowship for 4 years. Imperial College's prestigious Research Fellowships financially supports the brightest and very best early career researchers from across the world, providing a level of commitment and support that is rare from a UK university.
PhD position 1: We are looking for a highly motivated and dynamic PhD student to work on an exciting project focused on Advancing bacterial 3D printing for the production of next-generation bio-materials. The project is part of the Leverhulme Centre for Cellular Bionics. The ideal candidate will have a background in (as many as possible of) the following areas: bacterial synthetic biology (e.g. E. coli), genetic engineering, optogenetics, metabolic engineering, biomolecular feedback design and implementation, modelling in biology, computational modelling. This project will be realised in collaboration with Dr John Heap and Dr Connor Myant. The student will be embedded in the Imperial College Centre for Synthetic Biology. Instructions to apply can be found here.
PhD position 2: We are looking for a highly motivated and dynamic PhD student to work on an exciting project focused on Developing a framework for population-level cellular modelling employing agent-scale resource constraints (project #5). The project is part of the EPSRC-funded Centre for Doctoral Training in Engineering Biology. The ideal candidate will have a background in (as many as possible of) the following areas: cellular and synthetic biology mathematical and computational modelling, biophysics, genetic engineering, biomolecular feedback design and implementation. This project will be realised in collaboration with Dr Tom Ellis. Instructions to apply can be found here. Deadline for applications: 23:00 GMT on Monday 22nd April 2019.
PhD position 3: We are looking for a highly motivated and dynamic PhD student to work on an exciting project focused on Engineering synthetic microbial consortia for next-generation biotechnology (project #4). The project is part of the EPSRC-funded Centre for Doctoral Training in Engineering Biology. The ideal candidate will have a background in (as many as possible of) the following areas: microbial synthetic biology, synthetic microbial consortia, metabolic engineering, computational modelling of biological systems, bioinformatics, biomolecular feedback design and implementation. This project will be realised in collaboration with Dr Rodrigo Ledesma-Amaro. Instructions to apply can be found here. Deadline for applications: 23:00 GMT on Monday 22nd April 2019.
Information about the Imperial College PhD Scholarship scheme is available here. Additionally, information about all Scholarship Schemes (including a scholarships search tool) is available here. Furthermore, Ph.D. studentships in the Department of Bioengineering are advertised here. Information about the PhD programme in the Department of Bioengineering and how to apply can be found here. For general information on the tuition fees and cost of living in London, please read this link. For other sources of funding you can also look at here and here (BioEngineering funding) and here (fees and funding). Finally, there are also other PhD scholarship schemes such as for example the Crick PhD Programme.
For support of research-related travel expenses you can check this link.
If you are a highly motivated and dynamic postdoctoral researcher with experience in synthetic biology, biomathematics, biophysics, or modelling and control of biological systems and you are looking to join us, please email us with your CV. Information about competitive PostDoctoral Fellowships is available hereafter.
If you would like to apply for a PostDoctoral Fellowship to work in my group, this list of PostDoctoral Fellowships might be useful. We are also welcoming and supporting outstanding postdocs applying for a Marie Sklodowska-Curie Individual Fellowship. Please contact me if you are interested.
In addition to the above, we could also support applicants for a Rosetree Trust Young Enterprise Fellowship. Young Enterprise Fellowships are aimed specifically at recently qualified postdoctoral researchers primarily in the fields of engineering, physical sciences, maths and computer science, who wish to develop a long-term programme of biomedical research. The scheme is designed for researchers to develop a new and truly innovative idea (rather than extend their current research) to address an important unmet clinical problem using a novel and potentially transformative approach. The fellowship offers up to £60,000 per annum for three years available for salary and consumables costs. Further information about the scheme and how to apply can be found on the Rosetree Trust website. We can only support applicants whose interests align with those of our group. Deadline: 31 March 2019.
Also, Dr Nick Jones has compiled a list of fellowships that you might also want to consider.
Another list of independent PostDoc funding (in Biology) has been compiled by Dr Dieter Lucas.
The current list of group members is available at the people section of our group website.
For more information about the various students I have supervised see the Supervisory Experience section of my CV.
As part of our research, we regularly develop software tools. Most of these can be downloaded directly from my group website in the section Research Projects.
Synthetic Biology: a Primer (Revised Edition), G. Baldwin, T. Bayer, R. Dickinson, T. Ellis, P. Freemont, R. Kitney, K. Polizzi, N. Rose, G.-B. Stan, Imperial College Press, Oct. 2015, ISBN-10: 1783268794, ISBN-13: 978-1783268795.
A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and System Characterizations, Eds.: V. Kulkarni, G.-B. Stan, K. Raman, Springer, July 2014, ISBN: 978-94-017-9040-6 (Print), 978-94-017-9041-3 (Online). Click here for amazon.co.uk link.
A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems, Eds.: V. Kulkarni, G.-B. Stan, K. Raman, Springer, July 2014, ISBN: 978-94-017-9046-8 (Print), 978-94-017-9047-5 (Online). Click here for amazon.co.uk link.
The exit time finite state projection scheme: bounding exit distributions and occupation measures of continuous-time Markov chains, J. Kuntz, P. Thomas, G.-B. Stan, M. Barahona, SIAM Journal of Scientific Computing, Volume 41 (2019), n°2, pp. A748–A769, doi:10.1137/18M1168261.
Whole-cell biosensor with tuneable limit of detection enables low-cost agglutination assays for medical diagnostic applications, N. Kylilis, P. Riangrungroj, H.-E. Lai, V. Salema, L.A. Fernandez G.-B. Stan, P. Freemont, K. Polizzi, ACS Sensors , Volume 4 (2019), n°2, pp. 370-378, doi:10.1021/acssensors.8b01163.
Computational Re-Design of Synthetic Genetic Oscillators for Independent Amplitude and Frequency Modulation, M. Tomazou, M. Barahona, K. Polizzi G.-B. Stan, Cell Systems, Volume 6 (2018), n°4, pp. 508-520, doi:10.1016/j.cels.2018.03.013.
Investigating the consequences of asymmetric endoplasmic reticulum inheritance in Saccharomyces cerevisiae under stress using a combination of single cell measurements and mathematical modelling, F. Jonas, K. Royle, R. Aw, G.-B. Stan, K. Polizzi, Systems and Synthetic Biology, Volume 3 (2018), n°1, pp. 64-75, doi:10.1016/j.synbio.2018.01.001.
Synthetic Biology Open Language Visual (SBOL Visual) Version 2.0, R. S. Cox, C. Madsen, J. McLaughlin, T. Nguyen, N. Roehner, A. Wipat, B. Bartley, J. Beal, S. Bhatia, M. Bissell, K. Clancy, T. Gorochowski, R. Grunberg, A. Luna, C. Myers, N. Le Novere, M. Pocock, H. Sauro, J. T. Sexton, G.-B. Stan, J. J. Tabor, C. Voigt, Z. Zundel, K. Polizzi, Journal of Integrative Bioinformatics, Volume 15 (2018), n°1, doi:10.1515/jib-2017-0074.
Identification of Nonlinear State-Space Systems from Heterogeneous Datasets, W. Pan, Y. Yuan, L. Ljung, J. Goncalves, G.-B. Stan, IEEE Transactions on Network Control Systems, Volume 5 (2017), n°2, pp. 737-747, doi:10.1109/TCNS.2017.2758966.
Constructing Synthetic Biology Workflows in the Cloud, G. Misirli, C. Madsen, I. Sainz de Murieta, M. Bultelle, K. Flanagan, M. Pocock, J. Hallinan, J. A. Mclaughlin, J. Clark-Casey, M. Lyne, G. Micklem G.-B. Stan, R. Kitney, A. Wipat, IET Engineering Biology, Volume 1 (2017), n°1, pp. 61-65, doi:10.1049/enb.2017.0001.
Intracellular delivery of biologic therapeutics by bacterial secretion systems, B. Walker, G.-B. Stan, K. Polizzi, Expert Reviews in Molecular Medicine, Volume 19 (2017), e6, doi:10.1017/erm.2017.7.
Bounding stationary averages of polynomial diffusions via semidefinite programming, J. Kuntz, M. Ottobre, G.-B. Stan, M. Barahona, SIAM Journal on Scientific Computing, Volume 38 (2016), n°6, pp. A3891–A3920, doi:10.1137/16M107801X.
Overloaded and stressed: whole-cell considerations for bacterial synthetic biology, O. Borkowski, F. Ceroni, G.-B. Stan, T. Ellis, Current Opinion in Microbiology, Volume 33 (2016), pp. 123-130, doi:10.1016/j.mib.2016.07.009.
A Sparse Bayesian Approach to the Identification of Nonlinear State-Space Systems, W. Pan, Y. Yuan, J. Gonçalves, G.-B. Stan, IEEE Transacations on Automatic Control, Volume 61 (2016), n°1, pp. 182-187, doi:10.1109/TAC.2015.2426291.
Shaping Pulses to Control Bistable Systems: Analysis, Computation and Counterexamples, A. Sootla, D. Oyarzun, D. Angeli, G.-B. Stan, Automatica, Volume 63 (2016), pp. 254-264, doi:10.1016/j.automatica.2015.10.037.
Biomolecular implementation of nonlinear system theoretic operators, M. Foo, R. Sawlekar, J. Kim, D. Bates, G.-B. Stan, V. Kulkarni, Proceedings of the 15th European Control Conference (ECC 2016), Aalborg, Denmark, June 29 - July 1, 2016.
Online Model Selection for Synthetic Gene Networks, W. Pan, F. Menolascina G.-B. Stan, Proceedings of the 55th IEEE Conference on Decision and Control (CDC 2016), Las Vegas, NV, USA, 12-14 December, 2016.
SBOL Visual: A Graphical Language for Genetic Designs, J. Y. Quinn, R. S. Cox III, A. Adler, J. Beal, S. Bhatia, Y. Cai, J. Chen, K. Clancy, M. Galdzicki, N. J. Hilson, N. Le Novere, A. J. Maheshwari, J. A. McLaughlin, C. J. Myers, U. P, M. Pocock, C. Rodriguez, L. Soldatova, G.-B. Stan, N. Swainston, A. Wipat, H. M. Sauro, PLoS Biology, 2015, doi:10.1371/journal.pbio.1002310.
A minimal realization technique for the dynamical structure function of a class of LTI systems, Y. Yuan, A. Rai, E. Yeung, G.-B. Stan, S. Warnick, J. Gonçalves, IEEE Transactions on Control of Network Systems, Volume 4 (2015), n°2, doi:10.1109/TCNS.2015.2498468.
GeneGuard: a Modular Plasmid System Designed for Biosafety, O. Wright, M. Dalmans, G.-B. Stan, T. Ellis, ACS Synthetic Biology, Volume 4 (2015), n°3, pp. 307-3016, doi:10.1021/sb500234s.
Online fault diagnosis for nonlinear power systems, W. Pan, Y. Yuan, H. Sandberg, J. Gonçalves, G.-B. Stan, Automatica, Volume 55 (2015), pp. 27-36, doi:10.1016/j.automatica.2015.02.032.
A forward-design approach to increase the production of poly-3-hydroxybutyrate in genetically engineered Escherichia coli, R. Kelwick, M. Kopniczky, I. Bower, W. Chi, M. H. W. Chin, S. Fan, J. Pilcher, J. Strutt, A. J. Webb, K. Jensen, G.-B. Stan, R. Kitney, P. Freemont, PLoS ONE, Volume 10, (2015), n°2, doi:10.1371/journal.pone.0117202.
The Moveable Feast of Predictive Reward Discounting in Humans, B. Schoenhense, L. Dickens, B. Caldas, G.-B. Stan, A. Faisal, Proceedings of the 2nd Multidisciplinary Conference on Reinforcement Learning and Decision Making (RDLM 2015), The University of Alberta, Edmonton, Alberta, Canada, 7-10 June, 2015.
Shaping Pulses to Control Bistable Biological Systems, A. Sootla, D. Oyarzun, D. Angeli, G.-B. Stan, Proceedings of the 2015 American Control Conference (ACC 2015), Palmer House Hilton, Chicago, IL, 1-3 July, 2015.
Identifying Biochemical Reaction Networks From Heterogeneous Datasets, W. Pan, Y. Yuan, L. Ljung, J. Gonçalves, G.-B. Stan, Proceedings of the 54th IEEE Conference on Decision and Control (CDC 2015), Osaka International Convention Center, Osaka, Japan, 15-18 December, 2015.
Model Reduction of Genetic-Metabolic Networks via Time Scale Separation, J. Kuntz, D. Oyarzun, G.-B. Stan, A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and System Characterizations, Eds.: V. Kulkarni, G.-B. Stan, K. Raman, Springer, July 2014, pp. 181-210, doi:10.1007/978-94-017-9041-3_7.
Analysis of Synchronizing Biochemical Networks via Incremental Dissipativity, A. Hamadeh, J. Gonçalves, G.-B. Stan, A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems, Eds.: V. Kulkarni, G.-B. Stan, K. Raman, Springer, July 2014, pp. 117-139, doi:10.1007/978-94-017-9047-5_5.
The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology, M. Galdzicki, K. Clancy, E. Oberortner, M. Pocock, J. Quinn, C. Rodriguez, N. Roehner, M. Wilson, L. Adam, J. C. Anderson, B. Bartley, J. Beal, D. Chandran, J. Chen, D. Densmore, D. Endy, R. Gruenberg, J. Hallinan, N. Hillson, J. Johnson, A. Kuchinsky, M. Lux, G. Misirli, J. Peccoud, H. Plahar, E. Sirin, G.-B. Stan, A. Villalobos, A. Wipat, J. H. Gennari, C. Myers, H. Sauro, Nature Biotechnology, Volume 32 (2014), pp. 545–550, doi:10.1038/nbt.2891.
Mathematical modeling of HIV dynamics after antiretroviral therapy initiation: A clinical research study, P. S. Rivadeneira, C. H. Moog, G.-B. Stan, C. Brunet, F. Raffi, V. Ferre, V. Costanza, M.-J. Mhawej, F. Biafore, D. A. Ouattara, D. Ernst, R. Fonteneau, X. Xia, AIDS Research and Human Retroviruses, Volume 30 (2014), n°9, pp. 831-834, doi:10.1089/AID.2013.0286.
Mathematical modeling of HIV dynamics after antiretroviral therapy initiation: A Review, P. S. Rivadeneira, C. H. Moog, G.-B. Stan, C. Brunet, F. Raffi, V. Ferre, V. Costanza, M.-J. Mhawej, F. Biafore, D. A. Ouattara, D. Ernst, R. Fonteneau, X. Xia, BioResearch Open Access, Volume 3 (2014), n°5, pp. 233-241, doi:10.1089/biores.2014.0024.
Modelling essential interactions between synthetic genes and their chassis cell, R. Algar, T. Ellis, G.-B. Stan, Proceedings of the 53rd IEEE Conference on Decision and Control (CDC 2014), J.W. Marriott Hotel, Los Angeles, CA, USA, 15-17 December, 2014.
Inference of Switched Biochemical Reaction Networks Using Sparse Bayesian Learning, W. Pan, Y. Yuan, A. Sootla, G.-B. Stan, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2014), Nancy, France, 15-19 September, 2014.
Distributed Reconstruction of Nonlinear Networks: An ADMM Approach, W. Pan, A. Sootla, G.-B. Stan, Proceedings of the 19th IFAC World Congress (IFAC 2014), Cape Town, South Africa, 24-29 August, 2014.
Toggling a Genetic Switch Using Reinforcement Learning, A. Sootla, N. Strelkowa, D. Ernst, M. Barahona, G.-B. Stan, Proceedings of the 9th French Meeting on Planning, Decision Making and Learning (JFPDA 2014), Liege, Belgium, 12-13 May, 2014.
Observability and coarse-graining of consensus dynamics through the External Equitable Partition, N. O'Clery, Y. Yuan, G.-B. Stan, M. Barahona, Physical Review E, Volume 88 (2013), n°4, doi:10.1103/PhysRevE.88.042805.
Tuning the Dials of Synthetic Biology: A Review, J. Arpino, E. Hancock, J. Anderson, M. Barahona, G.-B. Stan, A. Papachristodoulou, K. Polizzi, Microbiology, Special Issue on Synthetic Biology, Volume 159 (2013), pp. 1236-1253 doi:10.1099/mic.0.067975-0.
Building-in Biosafety for Synthetic Biology, O. Wright, G.-B. Stan, T. Ellis, Microbiology, Special Issue on Synthetic Biology, Volume 159 (2013), pp. 1221-1235, doi:10.1099/mic.0.066308-0.
Systematic Computation of Nonlinear Cellular and Molecular Dynamics with Low-Power CytoMimetic Circuits: A Simulation Study, K. Papadimitriou, G.-B. Stan, M. Drakakis, PLoS ONE, Volume 8 (2013), n°2, doi:10.1371/journal.pone.0053591.
Nonlinear Heat Transfer Processes in a Two-Phase Thermofluidic Oscillator, C. Markides, O. Adebayo, R. Solanki, G.-B. Stan, Applied Energy, Volume 104 (2013), pp. 958-977, doi:10.1016/j.apenergy.2012.11.056.
Real-time Fault Diagnosis for Large-Scale Nonlinear Power Networks, W. Pan, Y. Yuan, H. Sandberg, J. Gonçalves, G.-B. Stan, Proceedings of the 52nd IEEE Conference on Decision and Control (CDC 2013), Palazzo dei Congressi, Florence, Italy, 10-13 December, 2013.
On Periodic Reference Tracking Using Batch-Mode Reinforcement Learning with Application to Gene Regulatory Network Control, A. Sootla, N. Strelkowa, D. Ernst, M. Barahona, G.-B. Stan, Proceedings of the 52nd IEEE Conference on Decision and Control (CDC 2013), Palazzo dei Congressi, Florence, Italy, 10-13 December, 2013.
Control of protein concentrations in heterogeneous cell populations, A. Vignoni, D. Oyarzun, J. Pico, G.-B. Stan, Proceedings of the 12th European Control Conference (ECC 2013), ETH Zurich, Switzerland, 17-19 July, 2013.
Stochastic simulation of enzymatic reactions under transcriptional feedback regulation, J.-B. Lugagne, D. Oyarzun, G.-B. Stan, Proceedings of the 12th European Control Conference (ECC 2013), ETH Zurich, Switzerland, 17-19 July, 2013.
Global State Synchronization in Networks of Cyclic Feedback Systems, A. O. Hamadeh, G.-B. Stan, R. Sepulchre, and J. M. Gonçalves, IEEE Transacations on Automatic Control, Volume 57 (2012), n°2, pp. 478-483, doi:10.1109/TAC.2011.2164015.
Arterial Reservoir-Excess Pressure and Ventricular Work, K. H. Parker, J. Alastruey, G.-B. Stan, Medical & Biological Engineering & Computing Journal, Volume 50 (2012), n°4, pp. 419-424, doi:10.1007/s11517-012-0872-1, Supplementary material.
Design constraints in an operon circuit for engineered control of metabolic networks, D. Oyarzun, G.-B. Stan, Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), Maui, Hawaii, USA, 10-13 December, 2012.
Reconstruction of Arbitrary Biochemical Reaction Networks: A Compressive Sensing Approach, W. Pan, Y. Yuan, J. Gonçalves, G.-B. Stan, Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), Maui, Hawaii, USA, 10-13 December, 2012.
Dynamical Structure Function Identifiability Conditions Enabling Signal Structure Reconstruction, J. Adebayo, T. Southwick, V. Chetty, E. Yeung, Y. Yuan, J. Gonçalves, J. Grose, J. Prince, G.-B. Stan, S. Warnick, Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), Maui, Hawaii, USA, 10-13 December, 2012.
Design tradeoffs in a synthetic gene control circuit for metabolic networks, D. Oyarzun, G.-B. Stan, Proceedings of the 2012 American Control Conference (ACC 2012), Montreal, Canada, 27-29 June, 2012.
The circadian oscillator gene GIGANTEA mediates a long-term response of the Arabidopsis thaliana circadian clock to sucrose, N. Dalchau, S. J. Baek, H. M. Briggs, F. C. Robertson, A. N. Dodd, M. J. Gardner, M. A. Stancombe, M. J. Haydon, G.-B. Stan, J. M. Gonçalves, A. A. R. Webb, Proceedings of the National Academy of Sciences of the United States of America (PNAS), Volume 108 (2011), n°12, pp. 5104-5109, doi:10.1073/pnas.1015452108, Supplementary material.
Computational design approaches and tools for synthetic biology, J. MacDonald, C. Barnes, R. Kitney, P. Freemont, G.-B. Stan, Integrative Biology, Special Issue on Synthetic Biology, Volume 3 (2011), n°2, pp. 97-108, doi:10.1039/c0ib00077a. Top ten most accessed Integrative Biology articles in February, March, May, June, July, and August 2011. Second most highly 2013 cited Integrative Biology submission from the U.K.
Fast consensus via predictive pinning control, H.-T. Zhang, M. Z. Q. Chen, G.-B. Stan, IEEE Transaction on Circuits and Systems I, Volume 58 (2011), n°9, pp. 2247-2258, doi:10.1109/TCSI.2011.2123450.
Robust dynamical network structure reconstruction, Y. Yuan, G.-B. Stan, S. Warnick, J. M. Gonçalves, Automatica, Special Issue on Systems Biology, Volume 47 (2011), n°6, pp. 1230-1235, doi:10.1016/j.automatica.2011.03.008.
Network of passive oscillators, V. Kulkarni, M. Riedel, G.-B. Stan, Proceedings of the 49th Annual Allerton Conference on Communication, Control, and Computing, University of Illinois at Urbana-Champaign, Allerton Retreat Center, Monticello, Illinois, USA, 28-30 September, 2011.
Decentralised Minimal-time Consensus, Y. Yuan, G.-B. Stan, L. Shi, M. Barahona, J. Gonçalves, Proceedings of the 50th IEEE Conference on Decision and Control (CDC 2011), Orlando, Florida, USA, 12-15 December, 2011.
Correct biological timing in Arabidopsis requires multiple light signaling pathways, N. Dalchau, K. E. Hubbard, C. T. Hotta, F. C. Robertson, H. M. Briggs, G.-B. Stan, J. M. Gonçalves, A. A. R. Webb, Proceedings of the National Academy of Sciences of the United States of America (PNAS), Volume 107 (2010), n° 29, pp. 13171-13176, doi:10.1073/pnas.1001429107, Supplementary material.
Constructive Synchronization of Networked Feedback Systems, A. O. Hamadeh, G.-B. Stan, J. Gonçalves, Proceedings of the 49th IEEE Conference on Decision and Control (CDC 2010), Atlanta, Georgia, USA, 15-17 December, 2010.
Robust Dynamical Network Reconstruction, Y. Yuan, G.-B. Stan, S. Warnick, J. Gonçalves, Proceedings of the 49th IEEE Conference on Decision and Control (CDC 2010), Atlanta, Georgia, USA, 15-17 December, 2010.
Minimal-time output final value of unknown DT-LTI systems with application to the decentralised network consensus problem, Y. Yuan, G.-B. Stan, L. Shi, M. Barahona, J. Gonçalves, Proceedings of the 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010), University Congress Center, Budapest, Hungary, 5-9 July, 2010.
Robust dynamical network structure reconstruction with application to systems biology, Y. Yuan, G.-B. Stan, S. Warnick, J. Gonçalves, Proceedings of the 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010), University Congress Center, Budapest, Hungary, 5-9 July, 2010.
Decentralized final value theorem for discrete-time LTI systems with application to minimal-time distributed consensus, Y. Yuan, G.-B. Stan, L. Shi, J. Gonçalves, Proceedings of the 48th IEEE Conference on Decision and Control (CDC 2009), Shangai, China, 16-18 December, 2009.
Minimal dynamical structure realisations with application to network reconstruction from data, Y. Yuan, G.-B. Stan, Sean Warnick, J. Gonçalves, Proceedings of the 48th IEEE Conference on Decision and Control (CDC 2009), Shangai, China, 16-18 December, 2009.
Dynamical structure analysis of sparsity and minimality heuristics for reconstruction of biochemical networks, R. Howes, L. Eccleston, J. Gonçalves, G.-B. Stan, S. Warnick, Proceedings of the 47th IEEE Conference on Decision and Control (CDC 2008), Cancun, Mexico, 9-11 December, 2008.
Robust Synchronization in Networks of Cyclic Feedback Systems, A. O. Hamadeh, G.-B. Stan, J. Gonçalves, Proceedings of the 47th IEEE Conference on Decision and Control (CDC 2008), Cancun, Mexico, 9-11 December, 2008.
Global Asymptotic Stability of the Limit Cycle in Piecewise Linear versions of the Goodwin Oscillator, A. Salinas-Varela, G.-B. Stan, J. Gonçalves, Proceedings of the 17th IFAC World Congress (IFAC 2008), Seoul, Korea, 6-11 July, 2008.
The cross-entropy method for power system combinatorial optimization problems, D. Ernst, M. Glavic, G.-B. Stan, S. Mannor, L. Wehenkel, Proceedings of the 7th IEEE Power Engineering Society (PowerTech 2007), Lausanne, Switzerland, 1-5 July, 2007.
Output synchronization in networks of cyclic biochemical oscillators, G.-B. Stan, A. O. Hamadeh, J. Gonçalves, R. Sepulchre, Proceedings of the 26th American Control Conference (ACC 2007), Times Square, New York City, USA, July 11-13, 2007.
Clinical data based optimal STI strategies for HIV: a reinforcement learning approach, D. Ernst, G.-B. Stan, J. Gonçalves, L. Wehenkel, Proceedings of the 45th IEEE Conference on Decision and Control (CDC 2006), San Diego, CA, USA, December 13-15, 2006.
Clinical data based optimal STI strategies for HIV: a reinforcement learning approach, D. Ernst, G.-B. Stan, J. Gonçalves, L. Wehenkel, Proceedings of the 15th annual machine learning conference of Belgium and The Netherlands (BENELEARN 2006), Ghent, Belgium, May 11-12, 2006.
Global analysis and synthesis of oscillations: a dissipativity approach, G.-B. Stan, Ph.D. thesis, University of Liege, Belgium, March, 2005.
Global Analysis of Limit Cycles in Networks of Oscillators, G.-B. Stan, R. Sepulchre, Proceedings of the 6th IFAC International Symposium on Nonlinear Control Systems (NOLCOS 2004), Stuttgart, Germany, September 1-3, 2004, pp. 1433-1438.
Dissipativity and Global Analysis of Limit Cycles in Networks of Oscillators, G.-B. Stan, R. Sepulchre, Proceedings of the 16th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2004), Leuven, Belgium, July 5-9, 2004.
Dissipativity characterization of a class of oscillators and networks of oscillators, G.-B. Stan, R. Sepulchre, Proceedings of the 42nd IEEE Conference on Decision and Control (CDC 2003), Maui, Hawaii, USA, December 9-12, 2003, pp. 4169-4173.
Determination of the Scattering Coefficient of Random Rough Diffusing Surfaces for Room Acoustics Applications, J.-J. Embrechts, D. Archambeau, G.-B. Stan, Acta-Acoustica Acoustica, Volume 87 (2001), n° 4 pp. 482-494.
Comparison of Algorithms for Biological Network Reconstruction from Data, Openwetware webpage of Nuri Purswani as part of her MSc project with me in 2010.
Global Analysis of Limit Cycles in the Chua System, Internal report, Cambridge University, UK, April 2006, available upon request.
Dissipativity and Global Analysis of Limit Cycles, Internal Report, Montefiore, Ulg, 2004, available upon request.
The lecture notes and exercises for the Matlab practicals of the MRes course in Systems and Synthetic Biology at Imperial College can be found in the following zip file. Also, you can download here some advice for starting MRes students.
Optimal control with full information (dynamic programming).
The Kalman filter and "LQG" control.
Optimal control with an "H-infinity" criterion.
State-space tools for robustness analysis.
Slides of the lecture Convergence d'une série de Fourier (in French), May 14, 2009.
Corresponding lecture notes: Convergence d'une série de Fourier (in French), May 14, 2009. A java applet showing the usefulness and applications of Fourier series is availabe on the Falstad website. This applet should be used in parallel with these lecture notes to illustrate the introduced concepts.
Seminars in the Department of Bioengineering at Imperial College London.
Seminars at the Cambridge University Control Group on talks.cam.
Imperial's 2016 iGEM team - Ecolibrium (Lead Supervisor with Dr Karen Polizzi).
Imperial's 2014 iGEM team - Aqualose (Supervisor on the modelling side of the project).
Imperial's 2013 iGEM team - Plasticity (Supervisor on the modelling side of the project).
Imperial's 2011 iGEM team - Auxin (Supervisor on the modelling side of the project).
Imperial's 2010 iGEM team - Parasight (Supervisor on the modelling side of the project).
The title of my Ph. D. thesis is Global analysis and synthesis of oscillations: a dissipativity approach.
Furthermore, based on these results, we also propose a limit cycle oscillations synthesis method based on the design of a nonlinear parametric proportional-integral controller aimed at the generation of limit cycle oscillations with large basins of attraction in stabilisable nonlinear systems.
You can download here a summary of my (Ph.D.) F.N.R.S. research project Research.pdf (in french).
The translated title of my master thesis is Creation of an autonomous impulse response measurement system for rooms and transducers with different methods - "Réalisation d'une chaine de mesure autonome de la réponse impulsionnelle de salle selon différentes méthodes" (the manuscript is in french).
In this thesis, we compare four of the most used impulse response measurement techniques: Maximum Length Sequence (MLS), Inverse Repeated Sequence (IRS), Time Stretched Pulses, and Logarithmic Sinesweep. These methods are generally used for the measurement of the impulse response of acoustical systems such as transducers, rooms, and binaural impulse responses. The choice of one of these methods depending on the measurement conditions is critical. Therefore an extensive comparison has been realised. This comparison has been done through the implementation and realisation of a complete, fast, reliable, and cheap measurement system. In particular, these different methods have been compared with respect to best achievable signal-to-noise ratio, ease of use, harmonic distortion rejection/measurement, and robustness to measurement conditions (temperature change, impulsive and white noise, etc.). It is shown that in the presence of non white noise, the MLS and IRS techniques are more appropriate. On the contrary, in quiet environments the Logarithmic Sinesweep method is the most accurate: it allows for a direct improvement of the signal-to-noise ratio of up to 30 dB over the other methods, which can be critical for audio virtual reality systems such as auralization systems. Indeed, capturing binaural room impulse responses for high-quality auralization purposes requires a signal-to-noise ratio of more than 90 dB which is unattainable with other measurement techniques due to inherent nonlinearities in the measurement system (especially the loudspeaker), but fairly easy to reach with logarithmic sinesweeps due to the possibility of completely rejecting (and measuring) harmonic distortions. As a consequence, the sinesweep method opens the way for the development of high-quality auralization and sound spatialisation systems, which constitute the basis for advanced audio virtual reality systems.

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