Muddu Madakyaru

BE (Chemical), MTech(Chemical), PhD(Chemical Engineering and Process control)

Associate Professor, Department of Chemical Engineering, Manipal Institute of Technology, Manipal

https://orcid.org/0000-0002-2518-5190

Phone+91-820-2924316
Email muddu.m@manipal.edu
Websitehttps://manipal.edu/mit/department-faculty/faculty-list/muddu-madakyaru.html

Source: Scopus
Calculated based on no. of publications stored in Pure and citations from Scopus

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Personal profile

Research Interests

Chemical Engineering

Education/Academic qualification

Indian Institute of Technology, Bombay

15-07-2005 → 08-08-2010

Award Date: 08-08-2010

National Institute of Technology Karnataka

15-07-1996 → 15-08-1996

Award Date: 30-09-1998

RVCE

01-08-1991 → 30-07-1995

Award Date: 30-06-1995

External positions

16-01-2011 → 31-07-2014

16-07-2008 → 15-01-2011

16-07-2005 → 15-07-2008

22-09-1999 → 15-07-2005

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348 Citations
10 h-Index
17 Article
8 Conference contribution
2 Conference article
1 Chapter

Performance Evaluation of Independent Component Analysis-Based Fault Detection Using Measurements Corrupted with Noise
Kini, K. R. & Madakyaru, M., 2021, (Accepted/In press) In: Journal of Control, Automation and Electrical Systems.
Research output: Contribution to journal › Article › peer-review

Open Access
Improved anomaly detection based on integrated multi-scale principal component analysis using wavelets: An application to high dimensional processes
Ramakrishna Kini, K. & Madakyaru, M., 2020, In: IFAC-PapersOnLine. 53, 1, p. 398-403 6 p.
Research output: Contribution to journal › Conference article › peer-review

Open Access
1 Citation (Scopus)
Improved process monitoring strategy using Kantorovich distance-independent component analysis: An application to Tennessee Eastman process
Ramakrishna Kini, K. & Madakyaru, M., 2020, In: IEEE Access. 8, p. 205863-205877 15 p., 3037730.
Research output: Contribution to journal › Article › peer-review

Open Access
Monitoring multivariate process using improved independent component analysis-generalized likelihood ratio strategy
Ramakrishna Kini, K. & Madakyaru, M., 2020, In: IFAC-PapersOnLine. 53, 1, p. 392-397 6 p.
Research output: Contribution to journal › Conference article › peer-review

Open Access
1 Citation (Scopus)
Anomaly detection using multi-scale dynamic principal component analysis for Tenneesse Eastman Process
Kini, K. R. & Madakyaru, M., 14-05-2019, 2019 5th Indian Control Conference, ICC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 219-224 6 p. 8715552. (2019 5th Indian Control Conference, ICC 2019 - Proceedings).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
5 Citations (Scopus)

Research Interests

Education/Academic qualification

External positions

Performance Evaluation of Independent Component Analysis-Based Fault Detection Using Measurements Corrupted with Noise

Improved anomaly detection based on integrated multi-scale principal component analysis using wavelets: An application to high dimensional processes

Improved process monitoring strategy using Kantorovich distance-independent component analysis: An application to Tennessee Eastman process

Monitoring multivariate process using improved independent component analysis-generalized likelihood ratio strategy

Anomaly detection using multi-scale dynamic principal component analysis for Tenneesse Eastman Process