publications

Book

1. Optimization, Uncertainty and Machine Learning in Wind Energy Conversion Systems, Editor(s): Mitra, K., Everson, R., Fieldsend, J., Engineering Optimization: Methods and Applications (EOMA) series, Springer Nature Singapore Pte Ltd. 2025.  

Patents

2. A System And Method For Determining The Optimum Design Of The Hot Rolled Steel Products, Indian Patent No. 503430, granted on 25.01.2024, Inventor(s): Mohanty, I., Mitra, K., Malik, A., Mittal, P. and Bhagat, A. N.

3. A Biocompatible Head Plate for Semi batch Bioreactors, Indian Patent Application #: 202441035701, 2024, Inventor(s): Mahadevan, J., Giri, L. and Mitra, K.

4. Method And System For Steel Properties Prediction,Indian Patent Application #: 202431058136, Inventor(s): Mohanty, I., Roy, T. K., Tadepalli, A., Mitra, K.

5. Method to create compact, uniformly distributed and upgradable design of experiment for artificial intelligence based parsimonious model development to correlate coals, blends and coke properties under practical constraints, Indian Patent Application #: 202431058136, Inventor(s): Abhinav Kumar Soni, Srinivas Soumitri Miriyala, A. Suresh, Kishalay Mitra, Pratik Swarup Dash.

6. Development of a coal blend optimizer for the application of metallurgical coke making in steel industry, Indian Patent Application #: 202431058136, Inventor(s): A. Suresh, Aswitha Tadepalli, Abhinav Kumar Soni, Keerthi NagaSree Pujari, Kishalay Mitra, Rashmi Singh, Bidyut Das, Pratik Swarup Dash.

Book Chapters

7. Decoding the Challenge of Ammonia Combustion: A Hybrid Approach considering CFD & AI, In "Ammonia, Methanol, and Hydrogen as Emerging Fuels for De-Fossilized Transport Sector", Editors: Valera, H., Agarwal, A. K., Energy, Environment and Sustainability Series, 2025, Springer, Singapore. [Authors: Tadepalli, A., Mathew, R. S., Banerjee, R., Mitra, K.] 

8. Wind Behavior Modelling Towards Improvement of Sustainable Energy Generation: GANs vs Diffusion Models, In "Data-Driven Insights and Analytics for Measurable Sustainable Development Goals", Editors: Goswami, T., Roy, S. M., Senatore, S., 2025, Elsevier, United Kingdom. [Authors: Pujari, N. K., Mundra, S., Sharma, Y., Mitra, K.]  

9. Nonviral Platform for Expression of Recombinant Protein in Insect Cells. In "Baculovirus. Methods in Molecular Biology", Editors: Cox, M. M., Vol 2829, 2024, Humana, New York, NY. [Authors: Mahadevan, J., Mitra, K., Giri, L.]

10. Machine Learning Assisted Metaheuristic Based Optimization of Mixed Suspension Mixed Product Removal Process, In "Advanced Machine Learning with Evolutionary and Metaheuristic Techniques", Editors:  Jayaraman, V.K., Singh, K.P., Ojha, M., Siarry, P., Lecture Notes in Operations Research, 2024, Springer, Singapore. https://doi.org/10.1007/978-981-99-9718-3 [Authors: Ravi kiran, I., Nayak, S., and Mitra, K.]

11. Comparative Study of Automated Deep Learning Techniques for Wind Time Series Forecasting in “Statistical Modeling in Machine Learning”, Editors: Goswami, T. and Sinha, G. R., Elsevier, 2022, 327-356 [Authors: Pujari, N. K., Miriyala, S. S., and Mitra, K.]

12. Stochastic Optimization of Industrial Grinding Operation through Data-Driven Robust Optimization in “Statistical Modeling in Machine Learning”, Editors: Goswami, T. and Sinha, G. R., Elsevier, 2022, 249-267 [Authors: Pantula, P. D., Miriyala, S. S., and Mitra, K.]

13. Artificial Intelligence based Uncertainty Quantification technique for External flow CFD simulations in “Statistical Modeling in Machine Learning”, Editors: Goswami, T. and Sinha, G. R., Elsevier, 2022, 79-92 [Authors: Miriyala, S. S., Jadhav, P. D., Banerjee, R., and Mitra, K.]

14. Nonlinear System Identification of Environmental pollutants using Recurrent Neural Networks and Global Sensitivity Analysis in “Statistical Modeling in Machine Learning”, Editors: Goswami, T. and Sinha, G. R., Elsevier, 2022, 307-326 [Authors: Miriyala, S. S., Ravi kiran, I., and Mitra, K.]

15. Performance improvement in hot rolling process with novel Neural Architectural search in "Machine Learning in Industry", Editors: Dutta, S. and Davim, J. P., Springer, 2022 [Authors: Soumitri, M. S., Mohanti, I., and Mitra, K.]

16. Intuitionistic Fuzzy Approach Towards Evolutionary Robust Optimization of an Industrial Grinding Operation under Uncertainty in "Optimization in Industry", Editors: Dutta, S. and Davim, J. P., Springer, 2019 [Authors: Virivinti, N. and Mitra, K.]

17. Comparative Study of Multi / Many Objective Evolutionary Algorithms on Hot Rolling Application in "Optimization in Industry", Editors: Dutta, S. and Davim, J. P., Springer, 2019 [Authors: Mittal, P., Malik, A., Mohanty, I. and Mitra, K.]

18. Handling Optimization under Uncertainty using Intuitionistic Fuzzy Logic Based Expected Value Model in "Handbook of Research on Emergent Applications of Optimization Algorithms", Editors: Pandian Vasant, Sirma Zeynep Alparslan-Gok and Gerhard-Wilhelm Weber, IGI Global, 2018 [Authors: Virivinti, N. and Mitra, K.]

19. A Proposal for Parameter Free Surrogate Building Algorithm Using Artificial Neural Networks in "Handbook of Research on Emergent Applications of Optimization Algorithms", Editors: Pandian Vasant, Sirma Zeynep Alparslan-Gok and Gerhard-Wilhelm Weber, IGI Global, 2018 [Authors: Soumitri, M. S. and Mitra, K.]

20. Decomposition based multi-objective optimization of energy noise trade-off in a wind farm in "Handbook of Research on Emergent Applications of Optimization Algorithms", Editors: Pandian Vasant, Sirma Zeynep Alparslan-Gok and Gerhard-Wilhelm Weber, IGI Global, 2018 [Authors: Mittal, P. and Mitra, K.]

21. Efficient Optimization Formulation through Variable Reduction for Clustering Algorithms in "Handbook of Research on Emergent Applications of Optimization Algorithms", Editors: Pandian Vasant, Sirma Zeynep Alparslan-Gok and Gerhard-Wilhelm Weber, IGI Global, 2018 [Authors: Pantula, D. P., Soumitri, M. S. and Mitra, K.]

22. Chance Constrained Programming to Handle Uncertainty in Nonlinear Process Models in "Multi-Objective Optimization in Chemical Engineering: Developments and Applications", Editors: Gade Pandu Rangaiah and Adrián Bonilla-Petriciolet, John Wiley & Sons, 2013 [Author: Mitra, K.]

Journal papers

23. Tadepalli, A., Raju, C. S. D., Manekar, S., Mitra, K., Shee, D., Smart Optimization and Sensitivity Analysis of Lignin Depolymerization: Bayesian Learning Approach to Process and Catalyst Design, Environmental Chemical Engineering, accepted.

24. Tiwari, U., Ghaisas, N., and Mitra, K., Evaluating the combined effect of yaw misalignment and wind farm column misalignment on wake losses in finite wind farm arrays using large eddy simulations, Physics of Fluids, accepted. 

25. Roy, S., Pal, R. K., Mathew, R. S., Banerjee, R., Mitra, K., Banerjee, S., Reduction of detailed CH4/NH3/H2 combustion mechanism using ANN-based global sensitivity analysis, Fuel, 405, Part D, 2026, 136644, https://doi.org/10.1016/j.fuel.2025.136644.

26. Mahadevan, J., Mitra, K., Giri, L., An overview of virus-free protein expression in insect cells: A mode of rapid manufacturing platform for therapeutic protein and virus-like-particles, Biotechnology and Bioengineering, accepted, https://doi.org/10.1002/bit.28961.

27. Boruah, A., Pawar, D. S., Jain, R., Eregowda, T., Mitra, K., Chatterjee, P., Representative driving cycle-based framework to model indirect CO2 emissions from electric cars, Transportation Research Part D: Transport and Environment, 144, 2025, 104777.

28. Paul, G. P., Nagajyothi, V., Mitra, K., Metaheuristic Multi-Objective Optimization for Ring-Opening Branched Copolymerization of L-Lactide, Polymer Engineering Science, 65, 5, 2025, 2282-2294.

29. Paul, G. P., Nagajyothi, V., Mitra, K., Computational Approach for Copolymerization of Lactide with Lactone(5HDON) Inimer, Canadian Journal of Chemical Engineering, accepted,  https://doi.org/10.1002/cjce.25548 .

30. Ravi Kiran, I., Mitra, K., Robust Optimization of Cascaded MSMPR Crystallization Unit using Unsupervised Machine Learning, Canadian Journal of Chemical Engineering, 103, 3, 2025, 1112-1121.

31. Paul, G. P., Nagajyothi, V., Mitra, K., Integration of Neural Networks and First-Principle Model for Optimizing L-Lactide Branched Polymerization, Journal of Chemical Theory and Computation, 2024, 20, 24, 11058-11067.

32. Ravi Kiran, I., Mitra, K., Towards Faster Multi-Objective Surrogate Optimization using SVR: A Casting Case Study, Transactions of the Indian Institute of Metals, 2024, 77, 12, 4345-4354.

33. Panghal, R., Ghosh, S., Mitra, K., Yadav, P., Study of gravitational sedimentation of two flexible circular shaped particles using Immersed Boundary Method, Chinese Journal of Physics, 2024, 88, 647-669.

34. Ghosh, S., Yadav, P., Mitra, K., Panghal, R., Gravitational settling of two impermeable semi-torus particles, Chinese Journal of Physics, 2023, 86, 361–381.

35. Sharma, S., Mahadevan, J., Giri, L., Mitra, K., Identification of Optimal flow rate for Culture media, Cell Density and Oxygen towards maximization of Virus production in a fed-batch Baculovirus-Insect cell system, Biotechnology and Bioengineering, 2023, 120, 12, 3529-3542.

36. Dhyani V., George K., Gare S., Venkatesh K. V., Mitra K., and Giri L., A computational model to uncover the biophysical underpinnings of neural firing heterogeneity in dissociated hippocampal cultures, Hippocampus, 2023, 33, 11, 1208-1227.

37. Tadepalli, A., Pujari, K. N., Mitra, K., A Crystallization Case Study towards Optimization of Expensive to Evaluate Mathematical Models using Bayesian Approach, Materials and Manufacturing Processes, 2023, 38, 16, 2127-2134.

38. Manoj, A., Miriyala, S. S., Mitra, K., Multi-objective Optimization Through a Novel Bayesian Approach for Industrial Manufacturing of Polyvinyl Acetate, Materials and Manufacturing Processes, 2023, 38, 15, 1955-1963. 

39. Sharma, S., Sarkar, R., Giri, L., Mitra, K., Computational framework to understand the clinical stages of COVID-19 and visualization of time course for various treatment strategies, Biotechnology and Bioengineering, 2023, 120, 6, 1640-1656.

40. Sharma, S., Pujari, K. N., Giri, L., Mitra, K., Towards Performance Improvement of a Baculovirus-Insect Cell System Under Uncertain Environment: A Robust Multi-objective Dynamic Optimization Approach for Semi-batch suspension culture, Ind. Engg. Chem. Res., 2023, 62, 1, 111–125.

41. Pujari K, Miriyala, S. S. Mittal, P., Mitra, K., Better Wind forecasting using Evolutionary Neural Architecture Search driven Green Deep Learning, Expert Systems With Applications, 214, 2023, 119063.

42. Ravi Kiran, I., Naik, S., Mitra, K., Towards Faster Operational Optimization of Cascaded MSMPR Crystallizers using Multi-objective Support Vector Regression, Ind. Engg. Chem. Res. 2022, 61, 11518−11533. 

43. Krishnan, K. J., Mitra, K., A Modified Kohonen Map Algorithm for Clustering Time Series Data, Expert Systems With Applications, 2022, 201, 117249.

44. Soumitri M. S., Pujari, K. N., Naik, S., Mitra, K., Evolutionary Neural Architecture Search for Surrogate models to Enable Optimization of Industrial Continuous Crystallization Process, Powder Technology, 2022, 405, 117527.

45. Ravi Kiran, I., Mitra, K., Optimal Surrogate Building Using SVR for an Industrial Grinding Process, Materials and Manufacturing Processes, 2022, 37, 15, 1701-1707. 

46. Ravi Kiran, I., Soumitri M. S., Mitra, K., Deep Learning Based Dynamic Behaviour Modelling and Prediction of Particulate Matter in Air, Chemical Engineering Journal, 2021, 426, 131221. 

47. Gumte, K., Pantula, P. D., Soumitri M. S., Mitra, K., Data Driven Robust Optimization for Handling Uncertainty in Supply Chain Planning Models, Chemical Engineering Science, 2021, 246, 116889.

48. Kankanamge, D., Ubeysinghe, S., Tennakoon, M., Pantula, P. D., Mitra, K., Giri, L., Karunarathne, A., Dissociation of the G protein βγ from the Gq-PLCβ complex partially attenuates PIP2 hydrolysis, Journal of Biological Chemistry, 2021, 296, 100702.

49. Gumte, K., Pantula, P. D., Soumitri M. S., Mitra, K., Achieving Wealth from Bio-Waste in a Nationwide Supply Chain Setup under Uncertain Environment through Data Driven Robust Optimization Approach, Journal of Cleaner Production, 2021, 291, 125702.

50. Virivinti, N., Hazra, B., Mitra, K., Optimizing Grinding Operation with Correlated Uncertain Parameters, Materials and Manufacturing Processes, 2021, 36(6), 713-721.

51. Sharma, S., Pantula, P. D., Soumitri M. S., Mitra, K., A Novel Data-driven Sampling Strategy for Optimizing Industrial Grinding Operation under Uncertainty using Chance Constrained Programming, Powder Technology, 2021, 377, 913-923.

52. Singh, R., Sharma, S., Kareenhalli, V. V., Giri, L., Mitra, K., Experimental investigation into Indole production using Passaging of E. coli and B. subtilis along with unstructured modeling and parameter estimation using Dynamic Optimization: An Integrated Framework, Biochemical Engineering Journal, 2020, 163, 107743.

53. Ravi Kiran, I., Pantula, P. D., Soumitri M. S., Mitra, K., Data driven robust optimization of grinding process under uncertainty, Materials and Manufacturing Processes, 2020, 35, 1870-1876.

54. Mittal, P., Mitra, K., Micro-siting under practical constraints addressing the energy-noise-cost trade-off, Wind Energy, 2020, 23, 1905-1918.

55. Ravi Kiran, I., Soumitri M. S., Mitra, K., Recurrent Neural Networks based Modelling of Industrial Grinding Operation, Chemical Engineering Science, 219, 2020, 115585.

56. Pantula, P. D., Mitra, K., Towards Efficient Robust Optimization using Data based Optimal Segmentation of Uncertain Space, Reliability Engineering and System Safety, 197, 2020, 106821.

57. Pantula, P. D., Soumitri M. S., Mitra, K., An Evolutionary Neuro-Fuzzy C-means Clustering Technique, Engineering Applications of Artificial Intelligence, 89, 2020, 103435. 

58. Mittal, P., Mitra, K., In Search of Flexible and Robust Wind Farm Layouts Considering Wind State Uncertainty, Journal of Cleaner Production, 2020, 119195. 

59. Soumitri M. S., Mitra, K., Deep Learning based System Identification of Industrial Integrated Grinding Circuits, Powder Technology, 360, 2020, 921-936.

60. Soumitri M. S., Mitra, K.,Multi-Objective Optimization of Iron Ore Induration process using optimal neural networks, Materials and Manufacturing Processes, 35, 2020, 537-544. 

61. Lee, S.B., Mitra, K., Pratt III, F. D., Anderson, T. M., Ramadesigan, V., Chalamala, B. R., Subramanian, V. S., Open Data, Models, and Codes for Vanadium Redox Batch Cell Systems: A Systems Approach using Zero-Dimensional Models, ASME Journal of Electrochemical Energy Conversion and Storage, 17(1), 2019.

62. Pantula, P. D., Mitra, K., A Data-Driven Approach Towards Finding Closer Estimates of Optimal Solutions Under Uncertainty for an Energy Efficient Steel Casting Process, Energy, 189, 2019, 116253.

63. Mittal, P., Mohanty, I., Malik, A., and Mitra, K., Many-objective optimization of hot rolling of steel: A Hybrid Approach, Materials and Manufacturing Processes, 35, 2020, 668-676. 

64. Gumte, K., Mitra, K., Bio-Supply Chain Network Design to tackle ethanol deficiency in India: A mathematical framework, Journal of Cleaner Production, 234, 2019, 208-224.

65. Dawson-Elli, N., Kolluri, S. K., Mitra, K., Subramanian, V., On The Creation of a Chess-AI-Inspired Problem-Specific Optimizer for the Pseudo Two-Dimensional Battery Model Using Neural Networks, J Electro Chemical Society, 166, 2019, A1-A15.

66. Mittal, P., Mitra, K., Determining Layout of a Wind Farm With Optimal Number of Turbines: A Decomposition Based Approach, Journal of Cleaner Production, 202, 2018, 342-359.

67. Swain, S., Gupta, R. K., Ratnayake, K., Priyanka, P., Singh, R., Jana, S., Mitra, K., Karunarathne, A., Giri, L., Confocal imaging and k-means clustering of GABAB and mGluR mediated modulation of Ca2+ spiking in hippocampal neurons, ACS Chemical Neuroscience, 9 (12), 3094-3107.

68. Dawson-Elli, N., Lee, S. B., Pathak, M., Mitra, K., Subramanian, V., Data Science Approaches for Electrochemical Engineers - An Introduction through Surrogate Model Development for Lithium-Ion Batteries, J Electro Chemical Society, 165, 2018, A1-A15.

69. Singh, R., Miriyala, S. S., Giri, L., Mitra, K., Kareenhalli, V. V., Identification of Unstructured model for Subtilin production through Bacillus subtilis using Hybrid Genetic Algoritm, Process BioChemistry, 60, 2017, 1-12.

70. Soumitri M. S., Subramanian, V., Mitra, K., TRANSFORM-ANN for Online Optimization of Complex Industrial Processes: Casting process as Case study, European Journal of Operational Research, 264, 2018, 294-309.

71. Pantula, D. P., Soumitri M. S., Mitra, K., KERNEL: An enabler to build smart surrogates for online optimization and knowledge discovery, Materials and Manufacturing Processes, Genetic Algorithms special issue, 32, 2017, 1162-1171.

72. Gupta, R. K., Swain, S., Kankanamge, D., Pantula D. P., Singh, R., Mitra, K., Karunarathne, A., Giri, L., Comparison of calcium dynamics and specific features for G-protein coupled receptor targeting drugs using live cell imaging and automated analysis, SLAS DISCOVERY: Advancing Life Sciences R&D, 2017, 22, 848-858.

73. Mittal, P., Mitra, K., Kulkarni, K., Optimizing the number and locations of turbines in a wind farm addressing energy - noise trade-off:  A hybrid Approach, Energy Conversion and Management, 132C, 2017, 147-160 .

74. Virivinti, N., Mitra, K., Fuzzy Robust Optimization for Handling Feed Stream and Model Parameter Uncertainties during Comminution Process, Journal of the Taiwan Institute of Chemical Engineers, 70, 2017, 411-425. 

75. Virivinti, N., Mitra, K. (2016), A Comparative Study of Fuzzy Techniques to Handle Uncertainty: An Industrial Grinding Process, Chemical Engineering and Technology, 39, 1031-1039.

76. Soumitri M. S., Mittal, P., Majumdar, S., Mitra, K., Comparative Study of Surrogate Approaches while Optimizing Computationally Expensive Reaction Networks, Chemical Engineering Science, 140, 2016, 44-61.

77. Bhutani, U., Laha, A., Mitra, K., Majumdar, S., Sodium Alginate and Gelatin Hydrogels: Viscosity Effect on Hydrophobic Drug Release, Materials Letters, 164, 2016, 76-79. 

78. Mittal, P., Kulkarni, K., Mitra, K., A Novel Hybrid Optimization Methodology to Optimize the Total Number and Placement of Wind Turbines, Renewable Energy, 86, 2016, 133-147.

79. Laha, A., Bhutani, U., Mitra, K., Majumdar, S., Fast and Slow Release: Synthesis of Gelatin Casted-Film based Drug Delivery System, Special issue on Nano Materials, Materials and Manufacturing Processes, 31, 2016, 223-230.

80. Virivinti, N., Mitra, K., Intuitionistic Fuzzy Chance Constrained Programming for Handling Parametric Uncertainty: An Industrial Grinding Case Study, Industrial Engineering and Chemistry Research, 54 (24), 2015, 6291–6304.

81. Mogilicharla, A., Mitra, K., Majumdar S., Multi Objective Optimization of Long Chain Branched Propylene Polymerization, Polymer Engineering and Science, 55, 2015, 1067–1076.

82. Mogilicharla, A., Mittal, P., Majumdar S., Mitra, K., Kriging Surrogate based Multi-objective Optimization of Bulk Vinyl Acetate Polymerization with Branching, Materials and Manufacturing Processes, Genetic Algorithms special issue, 30, 2015, 394-402.

83. Mogilicharla, A., Mitra, K., Majumdar, S., Modeling of propylene polymerization with long chain branching, Chemical Engineering Journal, 246, 2014, 175-183.

84. Mogilicharla, A., Chugh, T., Majumdar S., Mitra, K., Multi-Objective Optimization of Bulk Vinyl Acetate Polymerization with Branching, Materials and Manufacturing Processes, 29, 2014, 210-217.

85. Virivinti, N., Mitra, K., Fuzzy Expected Value Analysis for an Industrial Grinding Process, Powder Technology, 268, 2014, 9-18.

86. Goel, H., Chandran, R. P., Mitra, K., Majumdar, S., Ray, P., Estimation of Interfacial Tension for Immiscible and Partially Miscible Liquid Systems by Dissipative Particle Dynamics, Chemical Physics Letters, 600, 2014, 62-67.

87. Mitra, K., Evolutionary Surrogate Optimization of an Industrial Sintering Process, Materials and Manufacturing Processes, 28, 2013, 768-775.

88. Mitra, K., Sensitivity Through Optimization Under Uncertainty Approach, Computer Methods in Materials Science, 13, 2013, 107-112.

89. Mitra, K., An uncertainty based formal approach towards parametric sensitivity: A case study on epoxy polymerization, Polymer Engineering and Science, 51, 2011, Page 1957 - 1968.

90. Mitra, K., Majumder, S., Successive approximate model based multi-objective optimization for an industrial straight grate iron ore induration process using evolutionary algorithm, Chemical Engineering Science, 66, 2011, 3471–3481.

91. Mitra, K., Handling Uncertainty in Kinetic Parameters in Optimal Operation of a Polymerization Reactor, Materials and Manufacturing Processes, 26, 2011, 446-454.

92. Mitra, K., Gudi, R. D., Patwardhan, S. C. and Sardar G., Resiliency Issues in Integration of Scheduling and Control, Industrial Engineering & Chemistry Research, Vol. 49, Page 222-235.

93. Mitra, K. (2010), Assessing Optimal Growth of Desired Species in Epoxy Polymerization under Uncertainty, Chemical Engineering Journal, 162, 201o, 322-330.

94. Mitra, K. and Ghosh, S., Unveiling Salient Operating Principles for Reducing Meniscus Level Fluctuations in an Industrial Thin Slab Caster Using Evolutionary Multi-Criteria Pareto Optimization, Materials and Manufacturing Processes, 24, 2009, 88-99.

95. Mitra, K., Majumder, S., Runkana, V., Multi-objective Pareto Optimization of Straight Grate Iron Ore Induration Process Using Evolutionary Algorithms, Materials and Manufacturing Processes, 24, 2009, 343-350.

96. Mitra, K., Gudi, R. D., Patwardhan, S. C. and Sardar G., Towards Resilient Supply Chains: Uncertainty Analysis using Fuzzy Mathematical Programming, Chemical Engineering Research and Design, 87, 2009, 967-981.

97. Mitra, K., Multiobjective Optimization of an Industrial Grinding Operation under Uncertainty, Chemical Engineering Science, 64, 2009, 5043-5056.

98. Mitra, K., Gudi, R. D., Patwardhan, S. C. and Sardar G., Mid term Supply Chain Planning Under Uncertainty: A Multi-objective Chance Constrained Programming Framework, Industrial Engineering & Chemistry Research, 47, 2008, 5501-5511.

99. Mitra, K., Genetic Algorithms in Polymeric Material Production, Design, Processing and Other Applications, International Materials Review, 53(5), 2008, 275-297.

100. Mitra, K., Majumdar, S., Multi Criteria Optimal Control of Poly Propylene Terepthalate Polymerization Reactor, Materials and Manufacturing Processes, 22, 2007, 532-540.

101. Mitra, K. and Ghivari M., Modeling of an Industrial Wet Grinding Operation using data-driven techniques, Computers and Chemical Engineering, 30(3), 2006, 508-520.

102. Mitra, K. and Majumdar, S., Selection of Catalyst for the Esterification Step of the PPT Polymerization Process, Macromolecular Theory and Simulations, 15, 2006, 497-506.

103. Majumdar, S., Mitra, K. and Sardar, G., Kinetic Analysis & Optimization for the Catalytic Esterification Step of PPT Polymerization, Macromolecular Theory and Simulations, 14, 2005, 49-59.

104. Nath, N. K. and Mitra, K., Mathematical Modeling and optimization of two--layer Sintering Process for sinter quality and fuel efficiency by Genetic Algorithm two-layer sintering of iron ore, Materials and Manufacturing Processes, Special issue on Genetic Algorithms in Ferrous Production Metallurgy, 20(3), 2005, 335-349.

105. Rane, T., Dewri, R., Ghosh, S., Mitra, K. and Chakraborty N., Modeling the Rrecrystallization Process using Inverse Cellular Automata and Genetic Algorithms: Studies using Differential Evolution, Journal of Phase Equilibria and Diffusion, 26(4), 2005, 311-321.

106. Majumdar, S., Mitra, K. and Raha, S., Optimized Species Growth in Epoxy Polymerization with Real Coded NSGA II, Polymer, 46(25), 2005, 11858-11869.

107. Mitra, K. and Ghosh, S., Multiobjective optimization of Spray Cooling in an Industrial Thin Slab Casting Machine using elitist Genetic Algorithm, Steel Grips 3(2), 2005, 111-119. [https://www.tib.eu/en/search/id/tema:TEMA20060203942/Multi-objective-optimisation-of-spray-cooling-in?cHash=5e263f41fcd083f52ad438a53f59c81e]

108. Mitra, K. and Nath, N. K., Multiobjective Pareto optimization of two-layer sintering process for different bed heights by genetic algorithm, Steel Grips 2(5), 2004, 358-363. [https://www.tib.eu/en/search/id/tema:TEMA20050302300/Multiobjective-Pareto-optimization-of-two-layer?cHash=1393fef5f9e2d95c5c1912462a1d1c0c]

109. Mitra, K. and Gopinath, R., Multiobjective Optimization of an Industrial Grinding Operation Using Elitist Nondominated Sorting Genetic Algorithm, Chemical Engineering Science, 59(2), 2004, 385-396.

110. Raha, S., Majumdar, S. and Mitra, K., Effect of Caustic Addition in Epoxy Polymerization Process: A Single and Multiobjective Evolutionary Approach, Macromolecular Theory and Simulations, 13, 2004, 152-161.

111. Ghosh, S., Mitra, K., Basu, B. and Jategaonkar, Y. A. (2004), Control of Meniscus Level Fluctuation by Optimization of Spray Cooling in an Industrial Thin Slab Casting Machine using Genetic Algorithm, Materials and Manufacturing Processes, 19(3), 2004, 549-562.

112. Majumdar, S. and Mitra, K., Modeling of a Reaction Network and its Optimization by Genetic Algorithm: A Novel Approach, Chemical Engineering Journal, 100(1-3), 2004, 109-118.

113. Sahay, S. and Mitra, K., Cost Model Based Optimization of Carburizing Operation, Surface Engineering, 24(4), 2004, 379-384.

114. Nath, N. K. and Mitra, K., Optimization of Suction Pressure for Iron Ore Sintering by Genetic Algorithm, Ironmaking & Steelmaking, 31(3), 2004, 199-206.

115. Deb, K., Mitra, K., Dewri, R. and Majumdar, S., Towards a Better Understanding of the Epoxy Polymerization Process Using Multi-objective Evolutionary Computation, Chemical Engineering Science, 59(20), 2004, 4261-4277.

116. Mitra, K., Majumdar, S. and Raha, S., Multiobjective optimization of a Epoxy Polymerization Process using the Elitist Genetic Algorithm, Industrial & Engineering Chemistry Research, 43(19), 2004, 6055-6063.

117. Mitra, K., Majumdar, S. and Raha, S., Multiobjective Dynamic Optimization of Epoxy Polymerization Process, Computer and Chemical Engineering, 28(12), 2004, 2583-2594.

118. Mitra, K., Deb K. and Gupta Santosh K., Multi Objective Optimization of Industrial Semibatch Nylon 6 reactor using Genetic Algorithms, Journal of Applied Polymer Science, 69, 1998, 69-87.

Conference papers

119. Pujari, N.K., Qin, A.K., Mitra, K.,  Multi-Task Optimisation-Based Yaw Control For Wind Farm Power Generation, IEEE Congress on Evolutionary Computation, Hangzhou, China, June 8 - 12, 2025.

120. Neelapala, S. D., Jana, S., Mitra, K., Giri, L., Gare, S., Dhyani, V., Biochemical Oscillations in HeLa Cells: Automated Time-Lapse Image Analysis and Two-Step Parameter Estimation,  47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Copenhagen, Denmark, July 14-17, 2025.

121. Rangavajhala, A., Tadepalli, A., Mitra, K., Accelerating the Multi-Objective Optimization of Crystallization Process using High Fidelity Population Balance Model Under NUMBA CUDA Environment, 2024 Tenth Indian Control Conference (ICC), Bhopal, India, December 9-11, 2024.

122. Masampally, V. S., Sharma, S., Giri, L., Mitra, K., Physics Informed Deep Operator Networks for Baculovirus-Insect Cell System, 2024 Tenth Indian Control Conference (ICC), Bhopal, India, December 9-11, 2024.

123. Tadepalli, A., Ravisha J., Mitra, K., Enhanced Crop Classification through Satellite-Image Processing, IEEE India Geoscience and Remote Sensing Symposium (IEEE InGARSS 2024), Goa, India, December 2-5, 2024.

124. Tadepalli, A., Mitra, K., Satellite Image based Crop Classification Using Convolutional Autoencoder, GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Melbourne, Australia, July 14 - 18, 2024, 615 - 618. doi: 10.1145/3638530.3654383.

125. Gangmei, G., Rolfe, B., Rana, S., Mitra, K., Bhattacharyya, S., Fourier Neural Operator for Predicting the Growth of Precipitates in a Binary Alloy, Materials Science Forum, 1154, pp 17-23. doi: 10.4028/p-296lHr.

126. Mahadevan, J., Bagoria, N., Neelapala, S. D., Dhyani, V., Mitra, K., Giri, L., Towards fluorescent-tag-Less Viral titration: Automated Estimation of cell-Size Distribution and Infection Level from phase-Contrast Microscopy Using Deep Learning and Transfer Learning, 46th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, Orlando, Florida, USA, July 15-19, 2024.

127. Gumte, K., and Mitra, K., A Circular Economy Approach Toward Managing E-waste in Indian Smart City, in "Applications of Operational Research in Business and Industries", Editors: Gunasekaran, A., Sharma, J.K., Kar, S., Lecture Notes in Operations Research, 2023, Springer, Singapore. doi: 10.1007/978-981-19-8012-1_18.

128. Gumte, K., and Mitra, K., Is Bio-supply Chain a Feasibility in India? An Uncertainty-Based Study, in "Applications of Operational Research in Business and Industries", Editors: Gunasekaran, A., Sharma, J.K., Kar, S., Lecture Notes in Operations Research, 2023, Springer, Singapore. https://doi.org/10.1007/978-981-19-8012-1_17.

129. Masampally, V.S., Sharma, S., Giri, L., Mitra, K., Physics Informed Neural networks for Baculovirus-Insect Cell System, 2023 Ninth Indian Control Conference (ICC), Visakhapatnam, India, 2023, pp. 22-27, doi: 10.1109/ICC61519.2023.10442232.

130. Pujari, K. N., Miriyala, S. S., Mitra, K., A Generative Adversarial Networks based Modelling for Efficient Design of Wind Energy Conversion Systems, 2023 Ninth Indian Control Conference (ICC), Visakhapatnam, India, 2023, pp. 299-304, doi: 10.1109/ICC61519.2023.10442336.

131. Pujari, K. N., Mitra, K., Wind Farm Layout Optimization Under Uncertainty using Bayesian Approach, 2023 Ninth Indian Control Conference (ICC), Visakhapatnam, India, 2023, pp. 90-95, doi: 10.1109/ICC61519.2023.10442007.

132. Pujari, K. N., Miriyala, S. S., Mitra, K., Jensen-ANN: A Machine Learning adaptation of Jensen Wake Model, 22nd IFAC World Congress 2023, IFAC-PapersOnLine, 56, 2, 2023, 4651-4656.

133. Sehanobish, D., Dhyani, V., Gare, S., Saha, D., Mitra, K., Giri, L., Microstate analysis of GABA_B and mGluR Mediated Modulation of Calcium Spiking in Hippocampal Neurons, 11th International IEEE EMBS Conference on Neural Engineering (NER'23), Baltimore, Maryland, April 2023, pp. 1-4, doi: 10.1109/NER52421.2023.10123717.

134. Manoj, A., Miriyala, S. S., Mitra, K., Multi-objective Bayesian Optimization for Computationally Expensive Reaction Network Models," 2022 Eighth Indian Control Conference (ICC), Chennai, India, 2022, pp. 428-433, doi: 10.1109/ICC56513.2022.10093513.

135. Lakshmi S. C., Miriyala, S. S., Mitra, K., C., Statistical Inference and Analysis for Efficient Modeling of Environmental Pollution using Deep Neural Networks, 2022 Eighth Indian Control Conference (ICC), Chennai, India, 2022, pp. 385-390, doi: 10.1109/ICC56513.2022.10093411.

136. Sharma, S., Giri, L., Mitra, K., Multi-objective Optimization and control under Uncertainty for performance improvement of a Baculovirus Expression Vector System, 2022 Eighth Indian Control Conference (ICC), Chennai, India, 2022, pp. 416-421, doi: 10.1109/ICC56513.2022.10093623.

137. Pantula, D. P., Miriyala, S. S., Mitra, K., A Deep Unsupervised Learning Algorithm for Clustering of Wind Frequency Maps, 2022 Eighth Indian Control Conference (ICC), Chennai, India, 2022, pp. 361-366, doi: 10.1109/ICC56513.2022.10093581.

138. Ravi kiran I., Naik, S., Mitra, K., Machine Learning Based Multi-Objective Surrogate Optimization of MSMPR Process, 2022 Eighth Indian Control Conference (ICC), Chennai, India, 2022, pp. 176-181, doi: 10.1109/ICC56513.2022.10093453.

139. Ravi kiran I., Mitra, K., System Identification and Process Modelling of Dynamic Systems Using Machine Learning, 26th International Conference on System Theory, Control and Computing (ICSTCC), Sinaia, Romania, 2022, pp. 564-569, doi: 10.1109/ICSTCC55426.2022.9931831.

140. Ravi kiran I., Mitra, K., Artificial Intelligence Assisted Optimization Under Uncertainty for Robust Solutions, 26th International Conference on System Theory, Control and Computing (ICSTCC), Sinaia, Romania, 2022, pp. 458-463, doi: 10.1109/ICSTCC55426.2022.9931860.

141. Ravi kiran I., Mitra, K. Data-Based Time Series Modelling of Industrial Grinding Circuits. In: Das, S., Saha, S., Coello Coello, C.A., Bansal, J.C. (eds) Advances in Data-Driven Computing and Intelligent Systems. ADCIS 2022. Lecture Notes in Networks and Systems, vol 698. Springer, Singapore. https://doi.org/10.1007/978-981-99-3250-4_23.

142. Gare, S., Chel, S., Pantula, P. D., Saxena, A., Mitra, K., Sarkar, R., Giri, L., Analytics Pipeline for Visualization of Single Cell RNA Sequencing Data from Brochoaveolar Fluid in COVID-19 Patients: Assessment of Neuro-fuzzy C-means and HDBSCAN, 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022, pp. 1634-1637.

143. Ravi kiran I., Mitra, K, Machine Learning Based Surrogate Assisted Multi-Objective Optimization of Continuous Casting Process, 2021 Seventh Indian Control Conference (ICC), 2021, pp. 283-288.

144. Sharma, S, Pujari K, Miriyala, S. S. Giri, L., Mitra, K., Unstructured Modeling and RNN Surrogate Development for Optimizing Vaccine Production in Baculovirus Expression Vector System, 2021 Seventh Indian Control Conference (ICC), 2021, pp. 406-411.

145. Krishnan, K. J., Mitra, K. Clustering Time Series Sensor Data Using Modified Kohonen Maps, 2021 Seventh Indian Control Conference (ICC), 2021, pp. 129-134.

146. Pantula, D. P., Miriyala, S. S., Mitra, K., A Deep Unsupervised Learning Algorithm for Dynamic Data Clustering, 2021 Seventh Indian Control Conference (ICC), 2021, pp. 147-152.

147. Pujari, K., Srivastava, V., Miriyala, S. S., Mitra, K., Comparison of Deep Reinforcement Learning Techniques with Gradient Based Approach in Cooperative Control of Wind Farm, 2021 Seventh Indian Control Conference (ICC), 2021, pp. 400-405.

148. Sharma, S., Saxena, A., Chel, S., Mitra, K., Giri, L., Mathematical modeling of viral infection dynamics and immune response in SARS-CoV-2: A computational framework for testing drug efficacy, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021, pp. 4370-4373.

149. Ramamurthy, A., Pantula, P.D., Gharote, M., Mitra, K, Lodha, S., Multi-Objective Optimization for Virtual Machine Allocation in Computational Scientific Workflow under Uncertainty, 11th International Conference on Cloud Computing and Services Science (CLOSER), April 2021, 240-247. 

150. Miriyala, S. S. and Mitra, K., Optimal Control using Evolutionary Algorithms through Neural network based TRANSFORMation, 2020 IEEE Symposium Series on Computational Intelligence (IEEE SSCI), Canberra, Australia, December 1 - 4, 2020, 1379-1386.

151. Ravi kiran I., Miriyala, S. S., Kolluri, S. and Mitra, K., Nonlinear Model Predictive Control of Industrial Grinding Circuits using Machine Learning, 2020 IEEE Symposium Series on Computational Intelligence (IEEE SSCI), Canberra, Australia, December 1 - 4, 2020, 1921-1927.

152. Miriyala, S. S., Chowdhury, S., Keerthi, N. P. and Mitra, K., Optimally designed Variational Autoencoders for Efficient Wind Characteristics Modelling, 2020 IEEE Symposium Series on Computational Intelligence (IEEE SSCI), Canberra, Australia, December 1 - 4, 2020, 2869-2876.

153. Miriyala, S. S., Banerjee, R. and Mitra, K., Uncertainty quantification using Auto-tuned Surrogates of CFD model Simulating Supersonic flow over tactical missile body, 2020 IEEE Symposium Series on Computational Intelligence (IEEE SSCI), Canberra, Australia, December 1 - 4, 2020, 2885-2892.

154. Pantula, P. D., Miriyala, S. S., Giri, L. and Mitra, K., Synchronicity Identification in Hippocampal Neurons using Artificial Neural Network based Fuzzy C-means Clustering, 2020 IEEE Symposium Series on Computational Intelligence (IEEE SSCI), Canberra, Australia, December 1 - 4, 2020, 1594-1600.

155. Keerthi, N. P., Miriyala, S. S. and Mitra, K., Auto-tuned Deep Recurrent Neural Networks for Application in Wind Energy Conversion Systems, 2020 IEEE Symposium Series on Computational Intelligence (IEEE SSCI), Canberra, Australia, December 1 - 4, 2020, 3065-3072.

156. Gumte, K., Mitra, K., Strategic biofuel supply chain network design and techno-economic-environmental analysis for an Indian scenario, 2020 Advances in Control & Optimization of Dynamical Systems, IFAC-PapersOnLine, 53 (1), 69-74.

157. Ravikiran, I., Soumitri, M. S., Mitra, K., Modelling of pollutants and particulate matter in air using auto-tuned deep recurrent networks, 2020 Advances in Control & Optimization of Dynamical Systems, IFAC-PapersOnLine 53 (1), 530-535. 

158. Keerthi N. P., Soumitri M. S., Mittal, P., Mitra, K., Optimal Long Short Term Memory Networks for long-term forecasting of real wind characteristics, 2020 Advances in Control & Optimization of Dynamical Systems, IFAC-PapersOnLine 53 (1), 648-653.

159. Gumte, K., Pantula, P. D., Soumitri, M. S., Mitra, K., Data Driven Robust Optimization for Supply Chain Planning Models, Sixth Indian Control Conference 2019, pp. 218-223.

160. Ravi kiran I., Soumitri, M. S., Mitra, K., Recurrent Neural Network Based Modelling of Industrial Grinding Time Series Data, Sixth Indian Control Conference 2019, pp. 1-6.

161. Singh, R., Sharma, S., Giri, L., Mitra, K., Dynamic Optimization for Optimal production of Indole in a mixed culture, Sixth Indian Control Conference 2019, pp. 256-261.

162. Mittal, P., Mitra, K., Robust Wind Farm Layout Optimization under Uncertainty, Sixth Indian Control Conference 2019, pp. 164-169.

163. Soumitri, M. S., Nagalla, S. H., Mitra, K., Comparative study of optimal Long Short Term Memory Networks (LSTMs) for one day ahead solar irradiance hourly forecast, Sixth Indian Control Conference 2019, pp. 238-243.

164. Pantula, P. D., Soumitri, M. S., Swain, S., Giri, L., Mitra, K., Automation of Synchronicity Identification in Hippocampal Neurons through Intelligent Data Clustering Approach, Sixth Indian Control Conference 2019, pp. 268-273.

165. Pantula, P. D., Mitra, K., An Evolutionary Machine Learning Approach Towards Less Conservative Robust Optimization, IEEE Congress on Evolutionary Computation, Wellington, New Zealand, June 10-13, 2019, 2990-2997.

166. Mittal, P., Mitra, K., Variable Grid Resolution based Evolutionary Multi-objective optimization towards Micro-siting, IEEE Congress on Evolutionary Computation, Wellington, New Zealand, June 10-13, 2019, 2787-2793. 

167. Upadhyay, V., Ravutla, S. R., Dhyani, V., George, K., Swain, S., Mitra, K., Giri, L., A model screening framework for the generation of Ca2+ oscillations in hippocampal neurons using differential evolution, 9th International IEEE EMBS Neural Engineering Conference, San Francisco, CA, USA, March 20-23, 2019.

168. Mittal, P, Malik, A., Mohanty, I., Mitra, K., A hybrid constrained many-objective optimization approach towards production of hot rolled micro alloyed steels, XXVI Conference on Computer Methods in Materials Technology, KomPlasTech 2019, Zakopane, Poland, Jan 13 - 16, 2019.

169. Mittal, P., Mitra, K., Determination of optimal layout of wind turbines inside a wind farm in presence of practical constraints, IEEE Indian Control Conference, IIT Delhi, January 9 - 11, 2019.

170. Pantula, P. D., Soumitri M. S., Mitra, K., In Pursue of Closer Estimates of Optimal Solutions Under Uncertainty, IEEE Indian Control Conference, IIT Delhi, January 9 - 11, 2019.

171. Pantula, P. D., Soumitri M. S., Mitra, K., A Novel ANN-Fuzzy Formulation Towards Evolution of Efficient Clustering Algorithm, IEEE Indian Control Conference, IIT Delhi, January 9 - 11, 2019.

172. Dawson-Elli, N., Mitra, K., Subramanian, V. R., What Can Electrochemistry Learn from Chess?, Meeting Abstracts, 2018.

173. Lee, S.B., Pratt, H. D., Anderson, T. M., Mitra, K., Chalamala, B. R., Subramanian, V. R., Estimation of Transport and Kinetic Parameters of Vanadium Redox Batteries Using Static Cells, ECS Transactions, 2018, 85, 43-64.

174. Swain, S., Pantula, P. D., Mitra, K., Giri, L., Confocal imaging of cytosolic Ca2+ and fuzzy clustering reveals the circuit topology details underlying synchronization in hippocampal neurons, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, July 17 - 21, 2018, Hawai.

175. Soumitri M. S., Pantula, P. D., Giri, L., Mitra, K., Smart Data Analytics approach to model Complex Biochemical Oscillations in Hippocampal Neurons, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, July 17 - 21, 2018, Hawai.

176. Mittal, P., Mitra, K., A novel space decomposed cost-energy trade-off algorithm to determine the optimal number and layout of wind turbines inside a wind farm, IEEE Indian Control Conference, IIT Kanpur, January 4 - 6, 2018, 143 - 148.

177. Soumitri M. S., Mitra, K., Multi-objective Optimal Control of biochemical processes using Genetic Algorithms through ANN assisted reformulation, IEEE Indian Control Conference, IIT Kanpur, January 4 - 6, 2018, 149 - 154.

178. Soumitri M. S., Jadhav, P., Banerjee, R. and Mitra, K., Surrogate based optimization of CFD model simulating the supersonic flow over missile body under uncertainty using Artificial Neural Networks, ASCHT, IIT Madras, December 10 - 13, 2017. 

179. Jadhav, P., Soumitri M. S., Mitra, K. and Banerjee, R., Uncertainty estimations in external flow using Computational Fluid Dynamics (CFD), ASCHT, IIT Madras, December 10 - 13, 2017.

180. Mittal, P., Mitra, K., Decomposition based multi-objective optimization to simultaneously determine the number and the optimum locations of wind turbines in a wind farm, IFAC 2017 World Congress, Toulouse, France, July 9-14, 2017.

181. Mittal, P., Mitra, K., Energy-Noise Trade-off to Optimize the Total Number and the Placement of Wind Turbines on Wind Farms: A Hybrid Approach, IEEE Indian Control Conference, IIT Guwahati, January 4 - 6, 2017, 129 - 136. 

182. Pantula, D. P., Soumitri M. S., Mitra, K., Simultaneous Knowledge Discovery and Development of Smart Neuro-Fuzzy Surrogates for Online Optimization of Computationally Expensive Models, IEEE Indian Control Conference, IIT Guwahati, January 4 - 6, 2017, 260 - 267.

183. Soumitri M. S., Mitra, K., Novel Sample Size Determination Methods for Parsimonious Training of Black Box Models, IEEE Indian Control Conference, IIT Guwahati, January 4 - 6, 2017, 39 - 46.

184. Soumitri M. S., Pantula, D. P., Majumdar, S., Mitra, K., Journey Towards Parameter Free Surrogate Modelling for Enabling Online Optimization & Control of Complex Models, IEEE Indian Control Conference, Hyderabad, January 4 - 6, 2016, pp. 214-221.

185. Mittal, P., Kulkarni, K., Mitra, K., Multi-objective Optimization of Energy Generation and Noise Propagation: A Hybrid Approach, IEEE Indian Control Conference, Hyderabad, January 4 - 6, 2016, pp. 499-506.

186. Virivinti, N., Mitra, K., Intuitionistic Fuzzy Expected Value Model for Industrial Grinding Process, IEEE Indian Control Conference, Hyderabad, January 4 - 6, 2016, pp. 369-376.

187. Soumitri M. S., Majumdar, S., Mitra, K., Optimization Using ANN Surrogates with Optimal Topology and Sample Size, ADCHEM 2015, Whistler, British Columbia, Canada, June 7 - 10, 2015, pp. 1169-1174.

188. Mittal, P., Kulkarni, K., Mitra, K. A Novel and Efficient Hybrid Optimization Approach for Wind Farm Micro-Siting, ADCHEM 2015, Whistler, British Columbia, Canada, June 7 - 10, 2015, pp. 397-402.

189. Mogilicharla, A., Majumdar, S., Mitra, K. Modeling and Optimization of Propylene Polymerization with Branching, Proceedings of European Symposium on Computer Aided Process Engineering (ESCAPE 24), June 15 – 18, Computer Aided Chemical Engineering, Elsevier, 33, 1435-1440.

190. Mogilicharla, A., Majumdar, S., Mitra, K. Kinetic Analysis and Optimization of Long Chain Branched Propylene Polymerization System, IFAC World Congress 2014, Cape Town, South Africa, 24-29 August, 2014.

191. Virivinti, N., Mitra, K. Expected Value Analysis for an Industrial Grinding Process with Fuzzy Uncertain Parameters, Proceedings of European Symposium on Computer Aided process Engineering (ESCAPE 24), June 15 – 18, Computer Aided Chemical Engineering, Elsevier, 33, 1453-1458.

192. Mitra, K. (2013), Parametric Sensitivity Through Optimization Under Uncertainty Approach, Genetic Algorithms in Materials Design and Processing, 20th conference on Computer Methods in Materials Technology (KomPlasTech 2013), Zakopane, Poland, January 13 - 16.

193. Mitra, K. (2013), Surrogate Model Based Optimization for Computationally Expensive Models, International Conference on Advances in Chemical Engineering (ACE 2013), IIT Roorkee, India, February 22 - 24.

194. M., Anitha, Chugh, T., Mitra, K., Majumdar, S. (2013), Effect Of Live Radical Species In Controlled Branching Of Bulk Free Radical Polymerization System: A Multi Objective Evolutionary Approach, International Conference on Advances in Chemical Engineering (ACE 2013), IIT Roorkee, India, February 22 - 24.

195. M., Anitha, Majumdar, S., Mitra, K. (2012), Optimal Process Conditions for the Controlled Branching of Polymer: Multi-objective Evolutionary Approach, International Conference on Natural Polymers & Biomaterials (ICNP – 2012), Kottayam, India, 26-28 October.

196. Mitra, K. (2012), Optimizing an Industrial Grinding Operation under Uncertainty, Advances in Control and Optimization of Dynamical Systems (ACODS) – 2012, February 16 - 18, Indian Institute of Science, Bangalore, India.

197. Mitra, K. and Ghosh, S. (2008), Evolutionary Multi-Criteria Pareto Optimization for Optimal Control of an Industrial Thin Slab Caster, Workshop on Neural Network and Genetic Algorithm in Materials Science & Engineering (NGMS 2008), January 11 - 13, Howrah, India.

198. Mitra, K., Gudi, R. D., Patwardhan, S. C. and Sardar, G. (2008), Supply Chain Planning under Uncertainty: A Chance Constrained Programming Approach, IFAC World Congress 2008, July 6 – 11, 2008, Seoul, South Korea.

199. Mitra, K., Majumder, S. and Runkana, V. (2008), Multi-objective Pareto Optimization of An Industrial Straight Grate Iron Ore Induration Process Using Evolutionary Algorithms, WSC 2008 Online World Conference on Soft Computing in Industrial Applications, November 10 - 21.

200. Mitra, K., Gudi, R. D., Patwardhan, S. C. and Sardar, G. (2008), A Comparison of Uncertainty Analysis Approaches in Supply Chain Planning, WSC 2008 Online World Conference on Soft Computing in Industrial Applications, November 10 - 21.

201. Mitra, K., Gudi, R. D., Patwardhan, S. C. and Sardar G. (2008), Towards Resilient Supply Chains: Uncertainty Analysis using Fuzzy Mathematical Programming, Proceedings of European Symposium on Computer Aided Process Engineering (ESCAPE 18), June 1 – 4, Computer Aided Chemical Engineering, 25, 701-706.

202. Mitra, K. (2007), Solving Industrial Problems Using Evolutionary Multi-objective Optimization Framework, Advances in Computational Optimization and its Applications, Editors Kalyanmoy Deb et al., University Press, Hyderabad, India, pp 187-191.

203. Mitra, K. and Majumdar, S. (2006), Finding Better catalyst for Optimal Control of PPT Polymerization Reactor, Workshop on Neural Network and Genetic Algorithm in Materials Science & Engineering (NGMS 2006), January 11 - 13, Howrah, India. 

204. Mitra, K., Sardar G. and Gopinath, R. (2006), Cost Effective Intelligent Control and Optimization: Need of the time in Mineral Processing Industry, Proceedings on International Seminar on Mineral Processing Technology, MPT 2006, March 8 - 10, 2006, Chennai, India.

205. Korgaokar, S., Mitra, K. (2006), Scheduling Supply Vessels for an Industrial Oil Exploration Operation: A Multi-objective Evolutionary Approach, Proceedings on IEEE International Conference on Industrial Technology, Special Session on Modeling and Optimization of Industrially Relevant Systems, ICIT 2006, December 14 - 16, Mumbai, India, pp 3038-3043.

206. Mitra, K. and Majumdar, S. (2005) Evolutionary Algorithms for Optimal Control of PPT Polymerization Reactor, Invited Lecture on Optimal Control, Proceeding of International Federation of Automatic Control (IFAC 2005), July 4 – 8, Prague, Czech Republic.

207. Junnuri, V. S. S. R., Mitra, K. and Barve, J. (2005) Nonlinear Modeling and Simulation of Industrial Wet Grinding Process, Proceeding of International Federation of Automatic Control (IFAC 2005), July 4 – 8, Prague, Czech Republic.

208. Mitra, K. and Nath, N. K. (2005) Analysis of Two Layer Sintering Process for Different Bed Heights by Genetic Algorithm, Proceeding of International Federation of Automatic Control (IFAC 2005), July 4 – 8, Prague, Czech Republic.

209. Mitra, K. and Ghivari M. (2005), Modeling of Wet Grinding Operation using Artificial Intelligence Based Techniques, Proceeding of International Federation of Automatic Control (IFAC 2005), July 4 – 8, Prague, Czech Republic.

210. Mitra, K. and Majumdar, S. (2005) Selective Dynamic Growth of Polymer Species in Epoxy Polymerization, CHEMCON 2005, December 27 – 29, India.

211. Mitra, K. and Majumdar S. (2005), Applications of Multi-objective Evolutionary Algorithm in Optimal Control of Polymerization Processes, Proceeding of International Conference on Advanced Materials Design & Development (ICAMDD 2005), December 14 – 16, Goa, India.

212. Mitra, K. and Gopinath, R. (2004), Multi Objective Optimization of an Industrial Grinding Operation Using Genetic Algorithm, European Symposium on Computer-Aided Process Engineering - 14, Editors: Barbosa-Povoa A. and Matos H., Computer-Aided Chemical Engineering, Elsevier, vol. 18, May 12 - 16, 2004, Lisbon, Portugal, pp 715-720.

213. Deb, K., Mitra, K., Dewri, R. and Majumdar, S. (2004), Unveiling Optimal Operating Conditions for an Epoxy Polymerization Process Using Multi-Objective Evolutionary Computation, Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2004), Kalyanmoy Deb et al. (Eds.), LNCS 3103, June 26 - 30, Seattle, USA, pp 920-931.

214. Mitra, K., Sahasrabudhe, R., Gopinath, R. and Sistu, P. (2004), Genetic Algorithm Based Optimization Applied to an Industrial Grinding Operation, Proceedings of International Seminar on Mineral Processing Technology 2004, February 19 - 21, Bhubaneshwar, India, pp 122 - 129.

215. Nath, N. K. and Mitra, K. (2004) Two Layer Sintering Process Analysis and optimization for sinter quality and fuel efficiency by Genetic Algorithm, Proceeding of Conference on Energy Management in Steel Industry, September 22 – 23, Jamshedpur, India.

216. Mitra, K., Majumdar, S. and Deb, K. (2004) Multi-Objective Evolutionary Computation Used in Unveiling salient features of Epoxy Polymerization System, TCS Technical Architects’ Conference, October 27 – 30, Hyderabad, India.

217. Mitra, K. and Majumdar, S. (2004) Analysis of PPT Polymerization Process with Evolutionary Methods, CHEMCON 2004, December 27 – 30, Mumbai, India.

218. Mitra, K. and Majumdar, S., Constraints handling technique in a reaction network: A genetic algorithm based approach, Proceedings on International Symposium on Process System Engineering and Control, January 3 - 4, 2003, IIT, Bombay, India, pp 98 - 103.

219. Momaya, P., Mitra, K., Sistu, P. and Gopinath, R., Advanced Process Control of Ore Beneficiation in Mineral Processing Plant, Proceedings on International Symposium on Process System Engineering and Control, January 3 - 4, 2003, IIT, Bombay, India, pp 126 - 130.

220. Nath, N. K. and Mitra, K., Application of Genetic Algorithm Technique to Evaluate the Optimum Operating Condition for Iron Ore Sintering Process, Proceedings on Asia Steel International Conference, Vol 1, April 9 – 12, 2003, Tata Steel, Jamshedpur, India, pp 1.b.4.1 - 1.b.4.9.

221. Sahay, S., Mitra, K. and Malhotra, C., Cost Model Based Optimization of Heat Treatment Operations: A Case Study for Gas Carburization, 2nd International Conference on Thermal Process Modeling, March 31 – April 3, Nancy, France, pp 33.

222. Ghosh, S., Mitra, K., Jategaonkar, Y. and Basu, B., Optimization of Spray Cooling in Thin Slab Caster to Control Bulging and Meniscus Level fluctuation using Genetic Algorithm, Frontiers of Casting and Solidification technology (FOCAST), March 1 - 2, IIT Kharagur, India.

223. Momaya, P., Mitra, K., Sistu, P. and Gopinath, R., Plant-wide Advanced Process Controller and Optimizer for Hindustan Zinc Limited, Proceedings on International Seminar on Mineral Processing Technology, MPT 2003, February 6 - 8, 2003, Goa, India, pp 144 - 149.

224. Nath, N. K. and Mitra, K., Optimization of coke rate and sinter quality by genetic algorithm for two-layer sintering of iron ore, Modeling, Control and Optimization in Ferrous and Nonferrous Industry, Editors: F. Kongli, B. G. Thomas, K. Swamiphakdi, MS&T '03: Material Science and Technology Conference, IMS and ISS joint event, Chicago, IL, November 9 - 12, pp 109 - 124.

225. Raha, S., Mitra, K. and Majumdar, S., Effect of Intermediate Addition of Monomer and Caustic on Semibatch Epoxy Polymerization, Abstract Ref. No. CHM-162, CHEMCON 2003, December 19 – 22, Bhubaneshwar, India.

226. Mitra, K., Majumdar, S. and Raha, S., Optimum Caustic Addition Pattern in Epoxy Polymerization Using Evolutionary Multiobjective Approach, Abstract Ref. No. CHM-161, CHEMCON 2003, December 19 – 22, Bhubaneshwar, India.

227. Nath, N. K. and Mitra, K., Optimization of Two-layer Sintering process by Genetic Algorithm, NMD-ATM, November 14 – 16, 2003, Kolkata, India, pp 42 - 43.

Conference presentations

228. Sakshi Manekar, Rashi Verma, Kishalay Mitra, Debaprasad Shee, Reductive depolymerization of lignin using supported Ni-M (M=Pd, Ru and Rh) catalysts to produce aromatic chemicals, 24th National Symposium on Catalysis (CATSYMP-24), Catalysis Society of India, Thapar Institute of Engineering and Technology, Patiala, India, February 24-26, 2025.

229. Y. Upase, A. Chakraborty, S. Upadhyaya, M. Arulraj, K. Mitra, Utilizing Dynamic Meteorological Variables andStatic Topographic Variables to Enhance SatelliteRainfall Estimates through Deep Learning Algorithm, In IWM8, 8th International Workshop on Monsoon held at Indian Institute of Tropical Meteorology, Pune, India, March 17 - 21, 2025.

230. Gaijinliu Gangmei, Santu Rana, Bernard Rolfe, Kishalay Mitra, Saswata Bhattacharyya, Learning coupled Allen-Cahn and Cahn-Hilliard phase-field equations using Physics-informed neural operator(PINO), 4th Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE), Pennsylvania Convention Center, Philadelphia, Pennsylvania, USA, March 3, 2025.

231. Tadepalli, A., Anusha, M. R. S., Mitra, K., Leveraging Machine Learning for Optimization of Gas-ification Process across Diverse Feedstocks, 1st International and 7th National Conference on Multidisciplinary Design, Analysis and Optimization (iNCMDAO 2024), Bengaluru, India, December 16 - 18, 2024.

232. Supekar, K., Tadepalli, A., Banerjee, R., Mitra, K., Machine Learning based spray operating parameters prediction using convolutional neural networks, International Conference on Experimental Mechanics (ICEM 2024), IIT Madras, Chennai, October 20 – 23, 2024.

233. Upase, Y., Chakraborty, A., Posimsetti, H.V., Upadhyaya, S., Arulraj, M., Mitra, K., Topography Guided Bias Correction Framework to Improve Satellite-based Retrievals over Mountain Regions, 11th Workshop of International Precipitation Working Group (IPWG-11), 15 - 18 July, 2024, Tokyo Institute of Technology, Tokyo, Japan.   

234. Tiwari U.D., Ghaisas N., Mitra K., Wind direction and yaw misalignment effects in wind farms studied using LES and a Gaussian wake model, Computations of High-speed, Turbulent, and Complex Flows (CHTC), Hyderabad, June 2024.

235. Upase, Y., Chakraborty, A., Posimsetti, V., Upadhyaya, S., Arulraj, M., Mitra, K., Leveraging Static Topographic Variables to Improve Satellite Rainfall Estimates using Convolutional Neural Networks, International Workshop on StratosphereTroposphere Interactions and Prediction of Monsoon weather EXtremes (STIPMEX), IITM, Pune, June 2 - 7, 2024.

236. Tadepalli, A., Mathew, R. S., Banerjee, R., Mitra, K., Unveiling Flame Characteristics for Combustion Process of Ammonia Blends using Machine Learning, 19th International Conference on Numerical Combustion (ICNC 2024), Kyoto, Japan, May 7-10, 2024.

237. Mahadevan, J., Mitra, K., Giri, L., 2023. Fabrication of silicone-based microparticles for application in high-density cell culture, IIChE-Chemcon, Kolkata, December 2023.

238. Mahadevan, J., Mitra, K., Giri, L., 2023. Mitochondrial ROS quantification method for recombinant protein expression in insect cells, Chemference, Goa, December 2023.  

239. Tiwari, U.D., Ghaisas, N. S., Mitra, K., Studying the combined effect of yaw misalignment and wind flow direction on wind farm wake losses, 14th Asian Computational Fluid Dynamics Conference, Bangalore, Nov, 2023. 

240. Tiwari U.D., Ghaisas N., Mitra K., Studying the combined effects of yaw angle and wind direction in finite wind farm arrays using large eddy simulations, Wind Energy Science Conference (WESC), Glasgow, May, 2023.