Ljubisa Miskovic

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ljubisa.miskovic@epfl.ch +41 21 693 98 92 http://lcsb.epfl.ch

https://orcid.org/0000-0001-7333-8211

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EPFL SB ISIC LCSB
CH H4 595 (Bâtiment CH)
Station 6
1015 Lausanne

+41 21 693 98 92
+41 21 693 28 35
Local: CH H4 595
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+41 21 693 98 92
+41 21 693 28 35
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+41 21 693 28 35
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Biographie

Ljubisa Miskovic earned his Ph.D. degree in Automatic Control from the Swiss Federal Institute of Technology (EPFL) under the co-supervision of Dominique Bonvin and Alireza Karimi, in 2006. He pursued his postdoctoral studies at the Centre for Systems Engineering and Applied Mechanics, Universite Catholique de Louvain with Michel Gevers before moving to the laboratory of Vassily Hatzimanikatis at the EPFL. In 2010, he became a research scientist. His research interests include systems biology, metabolic engineering, synthetic biology, data-driven control design, system identification, stochastic processes and estimation theory.

Publications

Publications Infoscience

Main publications

The Dawn of High-throughput and Genome-scale Kinetic Modeling: Recent Advances and Future Directions

I. Toumpe; S. Choudhury; V. Hatzimanikatis; L. Miskovic

ACS SYNTHETIC BIOLOGY. 2025. DOI : 10.1021/acssynbio.4c00868.

Ljubisa Miskovic

Biographie

Publications

Publications Infoscience

Main publications

The Dawn of High-throughput and Genome-scale Kinetic Modeling: Recent Advances and Future Directions

Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states

Rational strain design with minimal phenotype perturbation

Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks

A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics

Constraint-based metabolic control analysis for rational strain engineering

Large-scale kinetic metabolic models of Pseudomonas putida KT2440 for consistent design of metabolic engineering strategies

Uncertainty reduction in biochemical kinetic models: Enforcing desired model properties

Control Theory Concepts for Modeling Uncertainty in Enzyme Kinetics of Biochemical Networks

Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations

Enzyme annotation for orphan and novel reactions using knowledge of substrate reactive sites

Discovery and Evaluation of Biosynthetic Pathways for the Production of Five Methyl Ethyl Ketone Precursors

A Design-Build-Test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models

Identification of metabolic engineering targets for the enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models

iSCHRUNK – In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks

Antihypertensive drugs metabolism: an update to pharmacokinetic profiles and computational approaches

Rites of passage: requirements and standards for building kinetic models of metabolic phenotypes

Towards kinetic modeling of genome-scale metabolic networks without sacrificing stoichiometric, thermodynamic and physiology constraints

Modeling of uncertainties in biochemical reactions

Closed-loop identication of MIMO systems: a new look at identifiability and experiment design

Production of biofuels and biochemicals: in need of an ORACLE

Identiﬁcation and the information matrix: how to get just sufﬁciently rich?

Closed-loop Identification of Multivariable Systems: With or Without Excitation of All References?

Iterative minimization of H2 control performance criteria

Correlation-Based Tuning of Decoupling Multivariable Controllers

Identification of multi-input systems: variance analysis and input design issues

Iterative Correlation-Based Controller Tuning

Control of an Active Suspension System as a Benchmark for Design and Optimization of Restricted Complexity Controllers

Correlation-Based Tuning of a Restricted-Complexity Controller for an Active Suspension System

Iterative Correlation-Based Controller Tuning: Application to a Magnetic Suspension System

Application of the minimum state error variance approach to nonlinear system control

Nonlinear system control using the MSEV approach

Enseignement & Phd

Doctorants

A dirigé les thèses EPFL de

Cours

Numerical methods

Chemical process control

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