| 1 |
Automatic real-time calibration, assessment, and maintenance of generic Raman models for online monitoring of cell culture processes
Tulsyan A, Wang T, Schorner G, Khodabandehlou H, Coufal M, Undey C
Biotechnology and Bioengineering, 117(2), 406, 2020 |
| 2 |
A machine-learning approach to calibrate generic Raman models for real-time monitoring of cell culture processes
Tulsyan A, Schorner G, Khodabandehlou H, Wan T, Coufal M, Undey C
Biotechnology and Bioengineering, 116(10), 2575, 2019 |
| 3 |
Univariate Model-Based Deadband Alarm Design for Nonlinear Processes
Tulsyan A, Gopaluni RB
Industrial & Engineering Chemistry Research, 58(26), 11295, 2019 |
| 4 |
Industrial batch process monitoring with limited data
Tulsyan A, Garvin C, Undey C
Journal of Process Control, 77, 114, 2019 |
| 5 |
Estimation and identification in batch processes with particle filters
Zhao ZG, Tulsyan A, Huang B, Liu F
Journal of Process Control, 81, 1, 2019 |
| 6 |
Design and assessment of delay timer alarm systems for nonlinear chemical processes
Tulsyan A, Alrowaie F, Gopaluni B
AIChE Journal, 64(1), 77, 2018 |
| 7 |
Advances in industrial biopharmaceutical batch process monitoring: Machine-learning methods for small data problems
Tulsyan A, Garvin C, Undey C
Biotechnology and Bioengineering, 115(8), 1915, 2018 |
| 8 |
Interval enclosures for reachable sets of chemical kinetic flow systems. Part 1: Sparse transformation
Tulsyan A, Barton PI
Chemical Engineering Science, 166, 334, 2017 |
| 9 |
Interval enclosures for reachable sets of chemical kinetic flow systems. Part 2: Direct-bounding method
Tulsyan A, Barton PI
Chemical Engineering Science, 166, 345, 2017 |
| 10 |
Interval enclosures for reachable sets of chemical kinetic flow systems. Part 3: Indirect-bounding method
Tulsyan A, Barton PI
Chemical Engineering Science, 166, 358, 2017 |
