Research Publications

Know more about the publications we hold across various departments

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Pilani Chemical Engineering

Peer Reviewed Journal Publications

Faculty: Dr. Smita Raghuvanshi

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Pilani Chemical Engineering

Books Content

Faculty: Dr. Smita Raghuvanshi

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Pilani Chemical Engineering

Khurshid, A., & Pani, A. K. (2024). An integrated approach combining randomized kernel PCA, Gaussian mixture modeling and ICA for fault detection in non-linear processes. Measurement Science and Technology, 35(7), 076208.

Faculty: Dr. Ajaya Kumar Pani

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Pilani Chemical Engineering

Khurshid, A., & Pani, A. K. (2023). Machine learning approaches for data-driven process monitoring of biological wastewater treatment plant: A review of research works on benchmark simulation model no. 1 (bsm1). Environmental Monitoring and Assessment, 195(8), 916.

Faculty: Dr. Ajaya Kumar Pani

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Pilani Chemical Engineering

Vijayan, S. V., Mohanta, H. K., Rout, B. K., & Pani, A. K. (2023). Adaptive soft sensor design using a regression neural network and bias update strategy for non-linear industrial processes. Measurement Science and Technology, 34(8), 085012.

Faculty: Dr. Ajaya Kumar Pani

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Pilani Chemical Engineering

Palla, G. L. P., & Pani, A. K. (2023). Independent component analysis application for fault detection in process industries: Literature review and an application case study for fault detection in multiphase flow systems. Measurement, 209, 112504.

Faculty: Dr. Ajaya Kumar Pani

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Pilani Chemical Engineering

Pani, A. K. (2022). Non-linear process monitoring using kernel principal component analysis: A review of the basic and modified techniques with industrial applications. Brazilian Journal of Chemical Engineering, 39(2), 327-344.

Faculty: Dr. Ajaya Kumar Pani

know more

Pilani Chemical Engineering

Arpitha, V., & Pani, A. K. (2022). Machine learning approaches for fault detection in semiconductor manufacturing process: A critical review of recent applications and future perspectives. Chemical and Biochemical Engineering Quarterly, 36(1), 1-16.

Faculty: Dr. Ajaya Kumar Pani

know more

Pilani Chemical Engineering

Venkatavijayan S., Mohanta, H. K., & Pani, A. K. (2022). Adaptive non-linear soft sensor for quality monitoring in refineries using Just-in-Time Learning—Generalized regression neural network approach. Applied Soft Computing, 119, 108546.

Faculty: Dr. Ajaya Kumar Pani

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Pilani Chemical Engineering

Venkatavijayan S., Mohanta, H. K., & Pani, A. K. (2021). Support vector regression modeling in recursive just-in-time learning framework for adaptive soft sensing of naphtha boiling point in crude distillation unit. Petroleum Science, 18(4), 1230-1239.

Faculty: Dr. Ajaya Kumar Pani

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Research and Innovation:
Publications

Advances in neurological research highlight breakthrough therapies

Know more about the publications we hold across various departments

Peer Reviewed Journal Publications

Books Content

Khurshid, A., & Pani, A. K. (2024). An integrated approach combining randomized kernel PCA, Gaussian mixture modeling and ICA for fault detection in non-linear processes. Measurement Science and Technology, 35(7), 076208.

Khurshid, A., & Pani, A. K. (2023). Machine learning approaches for data-driven process monitoring of biological wastewater treatment plant: A review of research works on benchmark simulation model no. 1 (bsm1). Environmental Monitoring and Assessment, 195(8), 916.

Vijayan, S. V., Mohanta, H. K., Rout, B. K., & Pani, A. K. (2023). Adaptive soft sensor design using a regression neural network and bias update strategy for non-linear industrial processes. Measurement Science and Technology, 34(8), 085012.

Palla, G. L. P., & Pani, A. K. (2023). Independent component analysis application for fault detection in process industries: Literature review and an application case study for fault detection in multiphase flow systems. Measurement, 209, 112504.

Pani, A. K. (2022). Non-linear process monitoring using kernel principal component analysis: A review of the basic and modified techniques with industrial applications. Brazilian Journal of Chemical Engineering, 39(2), 327-344.

Arpitha, V., & Pani, A. K. (2022). Machine learning approaches for fault detection in semiconductor manufacturing process: A critical review of recent applications and future perspectives. Chemical and Biochemical Engineering Quarterly, 36(1), 1-16.

Venkatavijayan S., Mohanta, H. K., & Pani, A. K. (2022). Adaptive non-linear soft sensor for quality monitoring in refineries using Just-in-Time Learning—Generalized regression neural network approach. Applied Soft Computing, 119, 108546.

Venkatavijayan S., Mohanta, H. K., & Pani, A. K. (2021). Support vector regression modeling in recursive just-in-time learning framework for adaptive soft sensing of naphtha boiling point in crude distillation unit. Petroleum Science, 18(4), 1230-1239.

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Integrated First Degree

Higher Degree

Doctoral Programmes

WILP

Dubai Campus

Give us your feedback

Upload Screenshot

Research and Innovation: Publications

Advances in neurological research highlight breakthrough therapies

Know more about the publications we hold across various departments

Peer Reviewed Journal Publications

Books Content

Khurshid, A., & Pani, A. K. (2024). An integrated approach combining randomized kernel PCA, Gaussian mixture modeling and ICA for fault detection in non-linear processes. Measurement Science and Technology, 35(7), 076208.

Khurshid, A., & Pani, A. K. (2023). Machine learning approaches for data-driven process monitoring of biological wastewater treatment plant: A review of research works on benchmark simulation model no. 1 (bsm1). Environmental Monitoring and Assessment, 195(8), 916.

Vijayan, S. V., Mohanta, H. K., Rout, B. K., & Pani, A. K. (2023). Adaptive soft sensor design using a regression neural network and bias update strategy for non-linear industrial processes. Measurement Science and Technology, 34(8), 085012.

Palla, G. L. P., & Pani, A. K. (2023). Independent component analysis application for fault detection in process industries: Literature review and an application case study for fault detection in multiphase flow systems. Measurement, 209, 112504.

Pani, A. K. (2022). Non-linear process monitoring using kernel principal component analysis: A review of the basic and modified techniques with industrial applications. Brazilian Journal of Chemical Engineering, 39(2), 327-344.

Arpitha, V., & Pani, A. K. (2022). Machine learning approaches for fault detection in semiconductor manufacturing process: A critical review of recent applications and future perspectives. Chemical and Biochemical Engineering Quarterly, 36(1), 1-16.

Venkatavijayan S., Mohanta, H. K., & Pani, A. K. (2022). Adaptive non-linear soft sensor for quality monitoring in refineries using Just-in-Time Learning—Generalized regression neural network approach. Applied Soft Computing, 119, 108546.

Venkatavijayan S., Mohanta, H. K., & Pani, A. K. (2021). Support vector regression modeling in recursive just-in-time learning framework for adaptive soft sensing of naphtha boiling point in crude distillation unit. Petroleum Science, 18(4), 1230-1239.

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Research and Innovation:
Publications