publications

Journal Publications

  • Orrico, C. A., van Berkel, M., Bosman, T., Ceelen, L., Heemels, W.P.M.H., Koechl, F., Krishnamoorthy, D., 2025. Predictive density profile control with discrete pellets, applied to integrated simulations of ITER, Nuclear Fusion, Vol. 65(7), p. 076041. [pdf]
  • Krishnamoorthy, D., 2025. ECCBO: An Inherently Safe Bayesian Optimization with Embedded Constraint Control for Real-time Process Optimization, Journal of Process Control, Vol. 152, p. 103467. [pdf]
  • Krishnamoorthy, D., 2025. A General-Purpose Approach to Multi-Agent Bayesian Optimization Across Decomposition Methods, Optimization and Engineering, https://doi.org/10.1007/s11081-024-09953-w. [pdf]
  • Dirza, R., Varadarajan, H.P., Aas, V., Skogestad, S., Krishnamoorthy, D., 2025. A Comparative Study of Distributed Feedback Optimizing Control Architectures, IEEE Transactions on Control Systems Technology Vol. 33 ´(2), p. 613-628 [pdf]
  • Krishnamoorthy, D., 2023. An Improved Data Augmentation Scheme for Model Predictive Control Policy Approximation, IEEE Control System Letters, Vol. 7, p. 1867 - 1872. [pdf]
  • Orrico, C. A., van Berkel, M., Bosman, T., Heemels, W.P.M.H., Krishnamoorthy, D., 2023. Mixed-Integer MPC Strategies for Fueling and Density Control in Fusion Tokamaks, IEEE Control System Letters, Vol. 7, p. 1897 - 1902. (IEEE CSS TC-ES Outstanding Student Paper Prize) [pdf]
  • Bosman, T., Koechl, F., Ho, A., de Baar, M., Krishnamoorthy, D., van Berkel, M., 2023. Integrated model control simulations of the electron density profile and the implications of using multiple discrete pellet injectors for control, Nuclear Fusion, Vol. 63, p. 126047. [pdf]
  • Mdoe, Z., Krishnamoorthy, D., Jäschke, J. 2023. Stability Properties of the Adaptive Horizon Multi-Stage MPC. Journal of Process Control, Vol. 128, p. 103002. [pdf]
  • Krishnamoorthy, D. and Doyle III, F. J., 2022. Safe and Personalized Meal Bolus Calculator for Type-1 Diabetes using Bayesian Optimization. IEEE Transactions on Biomedical Engineering, Vol. 70(5), p. 1481 - 1492. [pdf][video]
  • Krishnamoorthy, D., 2022. A Sensitivity-based Data Augmentation for Model Predictive Controller Policy Approximation. IEEE Transactions on Automatic Control, Vol. 67(11), p. 6090 - 6097. [pdf][code]
  • Dirza, R., Matias, J., Skogestad, S., and Krishnamoorthy, D. 2022. Experimental validation of distributed feedback-based RTO, Control Engineering Practice Vol 126, p. 105253.[pdf]
  • Krishnamoorthy, D. and Doyle III, F. J., 2022. Model-free Real-time Optimization of Process Systems using Safe Bayesian Optimization. AIChE Journal, Vol. 69(4), p. e17993. [pdf]
  • Krishnamoorthy, D. and Doyle III, F. J., 2022. Safe Bayesian Optimization using Interior-Point Methods - Applied to Personalized Insulin Dose Guidance. IEEE Control System Letters Vol. 6, p. 2834 - 2839. [pdf][extended version]
  • Krishnamoorthy, D. and Skogestad, S., 2022. Real-Time Optimization as a Feedback Control Problem - A Review. Comput. & Chem. Eng. Vol. 161, pp. 107723. (Invited paper in connection to the Excellence in CAPE PhD thesis award) [pdf]
  • Krishnamoorthy, D., 2021. A Distributed Feedback-based Online Process Optimization Framework for Optimal Resource Sharing. J. Proc. Control, Vol 97, p.72-83. [pdf][Code]
  • Krishnamoorthy, D., Dimitri Boiroux, Tinna Björk Aradottir, Sarah Ellinor Engell and John Bagterp Jørgensen, 2021. A Model-free Approach to Automatic Dose Guidance in Long Acting Insulin Treatment of Type 2 Diabetes. IEEE Control System Letters, Vol. 5(6), p.2030 - 2035. [pdf][Code][slides][video]
  • Krishnamoorthy, D., Skogestad, S., 2020 Systematic design of active constraint switching using selectors. Comput. & Chem. Eng. Vol. 143, p. 107106. [pdf][Code][slides][video]
  • Krishnamoorthy, D., Biegler, L. and Jäschke, J., 2020 Adaptive Horizon Economic Nonlinear Model Predictive Control. J. Proc. Control, Vol 92, p.108-118. [pdf][slides]
  • Jahanshahi, E., Krishnamoorthy, D., Codas, A., Foss, B. and Skogestad, S., 2020. Plantwide control of an oil production network, Comput. & Chem. Eng. [pdf]
  • Krishnamoorthy, D., Fjalestad, K. and Skogestad, S., 2019. Optimal Control of offshore oil and gas production using simple feedback controllers, Control Engineering Practice Vol 91, 104107. [pdf] [Code]
  • Krishnamoorthy, D., and Skogestad, S., 2019. Online process optimization with changes in active constraint sets using simple feedback control structures, Ind. Eng. Chem. Res. Vol. 58, p.13555 - 13567. DOI: 10.1021/acs.iecr.9b00308 [pdf] [Code Example 1], [Code Example 2]
  • Straus, J., Krishnamoorthy, D. and Skogestad, S., 2019. Combining self-optimizing control and extremum seeking control - Applied to ammonia reactor case study, J. Proc. Control. Vol 78, pp.78-87.[pdf][slides]
  • Krishnamoorthy, D., Foss, B. and Skogestad, S., 2018. A Primal decomposition algorithm for distributed multistage scenario model predictive control. J. Proc. Control, Vol 81, pp 162-17* [pdf] [Code][slides]
  • Krishnamoorthy, D., Jahanshahi, E. and Skogestad, S., 2019. A feedback RTO strategy using Transient Measurements, Ind. Eng. Chem. Res. Vol 58 (1), p.207-216. [pdf]
  • Krishnamoorthy, D., Foss, B. and Skogestad, S., 2018. Steady-State Real-time Optimization using Transient Measurements. Comput. & Chem. Eng., Vol 115, p.34-45 [pdf]
  • Krishnamoorthy, D., Foss, B. Suwartadi, E., Jäschke, J. and Skogestad, S., 2018. Improving Scenario Decomposition for Multistage MPC using a Sensitivity-based Path-following Algorithm, IEEE Control System Letters, Vol 2(4), p.581-586 [pdf][slides]
  • Krishnamoorthy, D., Foss, B. and Skogestad, S., 2016. Real-Time Optimization under Uncertainty Applied to a Gas Lifted Well Network. Processes, 4(4), p.52 [pdf]

Peer-reviewed Conference Publications

  • Herceg, D., Dell’Oro, M., Bertollo, R., Miura, F., de Klaver, P., Breschi, V., Krishnamoorthy, D., Salazar, M., 2025. A Scenario-based Model Predictive Control Scheme for Pandemic Response through Non-pharmaceutical Interventions, IEEE Conference on Control Technology and Applications (CCTA), San Diego, USA. [pdf]
  • Krishnamoorthy, D. and Doyle III, F., 2025. Personalized Meal Bolus Calculator for Type-1 Diabetes Accounting for Diurnal Effects. IFAC EDT, Valencia, Spain. [pdf]
  • Krishnamoorthy, D., 2024. ECCBO: An Inherently Safe Bayesian Optimization with Embedded Constraint Control for Real-Time Optimization. IFAC ADCHEM, Toronto, Canada (Keynote paper) [pdf]
  • Van der Horst, A., Meere, B., Krishnamoorthy, D., Bakker, S., van de Vrande, B., Stoutjesdijk, H., Alonso, M., Torta, E., 2024. A Bayesian optimization framework for the automatic tuning of MPC-based shared controllers. Proceedings of the 2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan. [pdf]
  • Krishnamoorthy, D., 2023. An Improved Data Augmentation Scheme for Model Predictive Control Policy Approximation, Proceedings of the 2023 IEEE Conference on Decision and Control, Singapore. [pdf]
  • Orrico, C. A., van Berkel, M., Bosman, T., Heemels, W.P.M.H., Krishnamoorthy, D., 2023. Mixed-Integer MPC Strategies for Fueling and Density Control in Fusion Tokamaks, Proceedings of the 2023 IEEE Conference on Decision and Control, Singapore. [pdf]
  • Chanfreut, P., Maestre, J.M., Krishnamoorthy, D. and Camacho, E.F., 2023. ALADIN-based Distributed Model Predictive Control with dynamic partitioning: An application to Solar Parabolic Trough Plants. Proceedings of the 2023 IEEE Conference on Decision and Control, Singapore. [pdf]
  • Krishnamoorthy, D. and Paulson, J., 2023. Multi-agent Black-box Optimization using a Bayesian Approach to Alternating Direction Method of Multipliers, IFAC World Congress, Yokohama, Japan (In-Press). [pdf][video]
  • Krishnamoorthy, D., 2023. On Tuning Parameterized Control Policies Online for Safety-Critical Systems – Applied to Biomedical Systems, IFAC World Congress, Yokohama, Japan (In-Press). [pdf][video]
  • Krishnamoorthy, D., 2023. Optimizing Surplus Heat Recovery using Fast Fourier Transform-based Extremum Seeking Control, IFAC World Congress, Yokohama, Japan (In-Press). [pdf][video]
  • Aas, V., Dirza, R., Krishnamoorthy, D., Skogestad, S., 2023. A comparative study of distributed feedback-optimizing control strategies, Computer-aided Chemical Engineering, (in-Press).
  • Krishnamoorthy, D. and Kungurtsev, V., 2022. A Sensitivity-assisted Alternating Directions Method of Multipliers for Distributed Optimization, Proceedings of the 2022 IEEE Conference on Decision and Control, Cancun, Mexico. [pdf][video]
  • Krishnamoorthy, D. and Doyle III, F. J., 2022. Safe Bayesian Optimization using Interior-Point Methods - Applied to Personalized Insulin Dose Guidance. Proceedings of the 2022 IEEE Conference on Decision and Control, Cancun, Mexico. [pdf]
  • Krishnamoorthy, D. and Doyle III, F. J., 2022. Personalized Dose Guidance using Safe Bayesian Optimization. NeurIPS 2022 Workshop on Learning from Time Series for Health, New Orleans, USA. (Spotlight paper)
  • Krishnamoorthy, D. and Doyle III, F. J., 2022. Personalized Dose Guidance using Safe Bayesian Optimization. 2022 Machine Learning for Health (ML4H), New Orleans, USA. [pdf][video]
  • Dirza, R., Rizwan, M., Skogestad, S. and Krishnamoorthy, D., 2022. Real-Time Optimal Resource Allocation Using Online Primal Decomposition, IFAC-PapersOnLine Vol. 55 (21), p.31-36. [pdf]
  • Bernardino, L.F., Krishnamoorthy, D. and Skogestad, S., 2022. Optimal Operation of Heat Exchanger Networks with Changing Active Constraint Regions, Computer Aided Chemical Engineering, Vol. 49, p.421-426.
  • Dirza, R., Krishnamoorthy, D. and Skogestad, S., 2022. Primal-dual Feedback-optimizing Control with Direct Constraint Control, Computer Aided Chemical Engineering, Vol. 49, 1153-1158. [pdf]
  • Bernardino, L.F.,Krishnamoorthy, D. and Skogestad, S., 2022. Comparison of Simple Feedback Control Structures for Constrained Optimal Operation. IFAC-PapersOnLine, Vol. 55 (7), p.883-888.[pdf]
  • Krishnamoorthy, D., Mesbah, A., Paulson, J., 2021. An Adaptive Correction Scheme for Offset-Free Asymptotic Performance in Deep Learning-based Economic MPC. IFAC ADCHEM 2021, In-Press. [pdf][slides][video]
  • Dirza, R., Skogestad,S., Krishnamoorthy, D., 2021. Optimal Resource Allocation using Distributed Feedback Real-time Optimization. IFAC ADCHEM 2021. (Keynote paper) [pdf][slides][keynote talk]
  • Krishnamoorthy, D., Dimitri Boiroux, Tinna Björk Aradottir, Sarah Ellinor Engell and John Bagterp Jørgensen, 2021 A Model-free Approach to Automatic Dose Guidance in Long Acting Insulin Treatment of Type 2 Diabetes. Proceedings of the 2021 American Control Conference, In-Press. [pdf][slides]
  • Mdoe, Z., Krishnamoorthy, D., and Jäschke,J., 2020. Adaptive Horizon Multistage Nonlinear Model Predictive Control. Proceedings of the 2021 American Control Conference, In-Press. [pdf]
  • Prakash, S., Krishnamoorthy, D., and Jäschke,J., Multi-scenario Design Optimization using ADMM of a Thermal Energy Storage system. Computer aided chemical engineering (ESCAPE 31), In-press. [pdf]
  • Krishnamoorthy, D.,Valli, C. and Skogestad, S., 2020. Real-time Optimal Resource Allocation in an Industrial Symbiotic Network using Transient Measurements. Proceedings of the 2020 American Control Conference ,p. 3541-3546, Denver. [pdf][slides][video]
  • Krishnamoorthy, D. and Skogestad, S., 2020. Linear Combination of Gradients as Optimal Controlled Variables, Computer aided chemical engineering, (In-press). [pdf][slides]
  • Krishnamoorthy, D., Jäschke, J. and Skogestad, S., 2019. Multistage Model Predictive Control with Online Scenario Tree Update using Recursive Bayesian Weighting, Proceedings of the 2019 European Control Conference, Naples, Italy [pdf][Slides]
  • Krishnamoorthy, D., Ryu, J. and Skogestad, S., 2019. Dynamic extremum seeking control applied to a gas lifted well network, IFAC DYCOPS-CAB, Florianopolis, Brazil [pdf]
  • Delou, P., Azevedo, J., Krishnamoorthy, D., de Souza Jr, M. and Secchi, A., 2019. Model Predictive Control with Recon_guration Strategy applied to an Electric Submersible Pump in a subsea environment, IFAC DYCOPS-CAB, Florianopolis, Brazil [pdf]
  • Thombre, M., Krishnamoorthy, D., and Jäschke, J., 2019. Data-driven Multistage Model Predictive Control of a Thermal Storage System with Time-Varying Uncertainty, IFAC DYCOPS-CAB, Florianopolis, Brazil [pdf]
  • Krishnamoorthy, D. Jahanshahi, E. and Skogestad, S., 2019. A feedback Real time optimization strategy applied to an evaporator process, PSE Asia, Bangkok, Thailand (In-Press)
  • Krishnamoorthy, D., Foss, B. Suwartadi, E., Jäschke, J. and Skogestad, S., 2018. Improving Scenario Decomposition for Multistage MPC using a Sensitivity-based Path-following Algorithm, 57th IEEE Conference on Decision and Control, Miami beach, Forida. [pdf]
  • Krishnamoorthy, D., Foss, B. and Skogestad, S., 2018. A distributed algorithm for scenariobased model predictive control using primal decomposition (in-press), IFAC ADCHEM, Shenyang, China - Keynote paper and IFAC Young Author Award finalist [pdf]
  • Krishnamoorthy, D., Thombre, M., Jäschke, J. and Skogestad, S., 2018. Data-driven scenario selection for multistage robust model predictive control (in-press), IFAC NMPC, Madison, Wisconsin. [pdf]
  • Krishnamoorthy, D., Jahanshahi, E. and Skogestad, S., 2018. Gas-lift Optimization by Controlling Marginal Gas-Oil Ratio using Transient Measurements, IFAC-PapersOnLine, 51(8), pp.19-24 (IFAC OOGP, Esbjerg, Denmark) - IFAC-ABB Best Student Paper Award. [pdf]
  • Suwartadi, E.,Krishnamoorthy, D. and Jäschke, J., 2018. Fast Economic Model Predictive Control for a Gas Lifted Well Network, IFAC-PapersOnLine, 51(8), pp.25-30 (IFAC OOGP, Esbjerg, Denmark).[pdf]
  • Backi, C. J., Krishnamoorthy, D. and Skogestad, S., 2018. Slug handling with a virtual harp-based on nonlinear predictive control for a gravity separator, IFAC-PapersOnLine, 51(8), pp.120-125 (IFAC OOGP, Esbjerg, Denmark).[pdf]
  • Krishnamoorthy, D., Aguiar, M. A. M., Foss, B. and Skogestad, S., 2018. A Distributed Optimization Strategy for Large scale Oil and Gas Production Systems (in-Press), IEEE CCTA, Copenhagen, Denmark.[pdf]
  • Backi, C. J., Krishnamoorthy, D., Verheyleweghen, A. and Skogestad, S., 2018.Combined nonlinear moving horizon estimation and model predictive control applied to a compressor for active surge control (in-Press), IEEE CCTA, Copenhagen, Denmark.[pdf]
  • Bonnowitz, H., Straus, J., Krishnamoorthy, D., and Skogestad, S., 2018. Control of the Steady-State Gradient of an Ammonia Reactor using Transient Measurements, Computer aided chemical engineering, Vol.43, p.1111-1116 (ESCAPE 28, Graz)[pdf]
  • Reyes-Lúa, A., Zotica, C., Das, T., Krishnamoorthy, D., and Skogestad, S., 2018. Changing between Active Constraint Regions for Optimal Operation: Classical Advanced Control versus Model Predictive Control, Computer aided chemical engineering, Vol.43, p.1015-1020 (ESCAPE 28, Graz) - Keynote paper presented by S. Skogestad.[pdf]
  • Krishnamoorthy, D., Foss, B. and Skogestad, S., 2017. Gaslift optimization under uncertainty. Computer Aided Chemical Engineering, vol.40, pg 1753-1758 (ESCAPE 27, Barcelona).[pdf]
  • Krishnamoorthy, D., Pavlov, A. and Li, Q., 2016. Robust Extremum Seeking Control with application to Gas Lifted Oil Wells. IFAC-PapersOnLine, 49(13), pp.205-210.[pdf]
  • Krishnamoorthy, D., Bergheim, E.M., Pavlov, A., Fredriksen, M. and Fjalestad, K., 2016. Modelling and Robustness Analysis of Model Predictive Control for Electrical Submersible Pump Lifted Heavy Oil Wells. IFAC-PapersOnLine, 49(7), pp.544-549 (IFAC DYCOPS, Trondheim, Norway). [pdf]
  • Pavlov, A., Krishnamoorthy, D., Fjalestad, K., Aske, E. and Fredriksen, M., 2014, October. Modelling and model predictive control of oil wells with electric submersible pumps. IEEE Conference on Control Applications (pp. 586-592). (Antibes, France)

Patents

  • Krishnamoorthy, D., and Doyle III, F.J. 2022, System and Methods for Individualized Bolus Calculations. US serial no. 63/338,363.
  • Aske, E., Krishnamoorthy, D., Fjalestad, K., Pavlov, A. and Fredriksen, M. 2014, Well Control system (WO2015070913A1, CA2930653A1, US20160290077A1, GB2535090B - granted) [link]
  • Krishnamoorthy, D. and Fjalestad, K. 2017, Estimating flow rate at a pump (WO2017061873A1, CA3001234A1, GB2543048A,RU2737055C2 - granted) [link]

Theses

  • Krishnamoorthy, D., 2019. Novel Approaches to Online Process Optimization under Uncertainty, PhD Thesis, NTNU. [pdf] [slides]
  • Krishnamoorthy, D., 2012. Efficient Algorithm implementation of Model Predictive Control, MSc Thesis, Imperial College London. [pdf][slides]

Press, Media, and others

  • Article on Universitets Avisa (in Norwegian) interviewing me in connection to my PhD Excellence Award. [link]
  • Contribution to the Biography on Prof. Jens G. Balchen titled, Altid Rabiat by Gard Paulsen (In Norwegian) [link][link to book]
  • Report on Age-dependent Epidemiological model of COVID-19 to assist policy makers in Norway - Communicated to the Director-General of the Norwegian Institute of Public Health (NIPH) on 23 March 2020 (National Lockdown announed on 12 March 2020). [link]