i4S LAB
IIT MANDI
HEAD OF THE TEAM
DR. SUBHAMOY SEN
Associate Professor
School of Engineering
2017- Present
Dr. Sen is the head of Team I4S, IIT Mandi. Dr. Sen did his doctoral research in IIT Kharagpur, India and currently, is an Assistant Professor in IIT Mandi, HP, India. His research interest includes structural dynamics, vibration analysis, signal filtering and parameter estimation techniques.
Phone: +91-1905-267261
Email: subhamoy@iitmandi.ac.in
EDUCATION
Nov 2022 - Present
IIT Mandi, HP ,IN
May 2017 - Nov 2022
IIT Mandi, HP, IN
Nov 2016 - May 2017
INRIA , Rennes, FR
June 2016 -Aug 2016
IIT Bombay, IN
2011-2016
IIT Kharapur , IN
2010-2011 Technische Universitat, GER
2009-2011
IIT Kharapur, IN
2004-2008
BESU, WB ,IN
Associate Professor at School of Civil Engineering, Environmental Engineering ,IIT Mandi, HP, India
Assistant Professor at School of Engineering, IIT Mandi, HP
Post-doctoral fellow at I4S team, INRIA, Rennes, France, Team Leader- Dr Laurent Mevel
Post-doctoral Fellow at Indian Institute of Technology Bombay, SSR Civil Engg. Dept. Team Leader- Prof. Siddhartha Bhattacharya
Ph.D. from Indian Institute of Technology Kharagpur, Structural Engineering, SRRF Laboratory. Supervisor- Prof. Baidurya Bhattacharya
Masters thesis from Technische University at Darmstadt, Germany, IIT Kharagpur , IN ,Supervisor- Prof. Peter Hagedorn
Masters of Technology from Indian Institute of Technology Kharagpur, Specialized in Structural Engineering
Bachelor of Engineering from Indian Institute of Engineering science and Technology (Formerly BESU), Shibpur, Specialized Civil Engineering.
PROJECTS
1
DST-IMPRINT 2
2
DST-ECR
3
SEED-GRANT, IIT Mandi
4
ARDB GRANT-IN-AID
5
CHINESE STATE S&T GRANT
CONFERENCES
Damage detection in presence of varying temperature through residual error modelling approach with dual neural network
Damage detection in presence of varying temperature using two stage neural network
Correntropy based IPKF filter for parameter estimation in presence of non-stationary noise process
Estimation of time varying system parameters from ambient response using improved Particle-Kalman filter
Seismic induced damage detection through parallel estimation of force and parameter using improved interacting Particle-Kalman filter
Prediction of Flexural Buckling Strength of CFS Members with Local Geometric Imperfection using Stochastic Kriging
Adaptive nonlinear Kalman filtering technique for parameter identification: an application to Bouc-Wen model, Engineering Mechanics Institute (EMI) International Conference of ASCE on Mechanics for Civil Engineers against Natural Hazards
Identification of Bouc-Wen model parameters using Extended Kalman filter with adaptive process and measurement covariance matrices
Non-iterative eigenstructure assignment based finite element model updating of a Mindlin-Reissner plate in Duncan form of state space using ambient vibration response
Control theory based finite element model updating
EWSHW 2018
Manchester , UK
IMCE 2018
Pittsburg , PA ,USA
IFAC 2018
Poland
European Geosciences
Union
Vienna , Austria
IWSHM 2017
California, USA
ICOSSAR 2017
Vienna , Austria
ASCE 2015
Hong Kong, China
ICTACEM 2014
Kharagpur , India
ICTACEM 2014
Kharagpur , India
CAE 2013
IIT Madaras , India
2018
2018
2018
2018
2017
2017
2015
2014
2014
2013
PUBLICATIONS
2022
Damage detection in composite plates under varying temperature through residual error modelling approach with dual neural network
Sharma, S., Sen, S
2021
Sharma, S., Sen, S
2020
Robust filtering based health monitoring of tensegrity structures
Aswal, N., Sen, S. and Mevel L
2020
Input-robust strain based joint damage estimation by interacting Particle and Kalman filtering
Aswal, N., Sen, S. and Mevel, L
2020
Sen, S., Aswal, N., Zhang, Q, and Mevel, L
2020
One-dimensional convolutional neural network-based damage detection in structural joints. J Civil Structure Health Monti
Sharma, S., Sen, S
2020
Uncertainty quantification using the particle filter for non-stationary hydrological frequency analysis. Journal of Hydrology 584 (2020): 124666
Sen, S, Jianxun H, and K. S. Kasi Viswanathan
2020
Stationary hydrological frequency analysis coupled with uncertainty assessment under nonstationary scenarios (Conditionally accepted in Journal of Hydrology)
Sahagun, C, Jianxun He, Kasiviswanathan KS, Sen S
2018
Estimation of non-stationary noise processes in a damaged system through Correntropy based IPKF filter, IFAC papers Online
Sen S., Crenerie, A., Cereu, F, Demoulin, J. and Mevel, L
2018
Detection of seismic induced damage through parallel estimation of force and parameter using improved interacting Particle-Kalman filter, Mechanical Systems and Signal Processing,
Sen S., Crenerie A., Cereu, F, Demoulin, J. and Mevel, L
2017
Non-Gaussian parameter estimation using generalized polynomial chaos expansion with extended Kalman filtering, Structural safety
Sen S. and Bhattacharya B
2016
Online structural damage identification technique using constrained dual extended Kalman filters, Structural Control and Health Monitoring
Sen S. and Bhattacharya B.
2016
Progressive damage identification using dual extended Kalman filter, vol–227(8): 2099–2109, Acta Mechanica, Springer
Sen S. and Bhattacharya B.
2016
A non-iterative structural damage identification methodology using eigenstructure assignment in state space, Structure and Infrastructure Engineering
Sen S. and Bhattacharya B.
2015
Non-iterative eigenstructure assignment technique for finite element model updating. Journal of Civil Structural Health Monitoring
Sen S. and Bhattacharya B.
RESEARCH
1
DOCTORAL THESIS
Control theory based structural health monitoring using measured vibration response
The study employs control theory based techniques in health assessment of civil infrastructure systems. Eigenstructure assignment techniques, Kalman filtering and its nonlinear variants have been applied in this endeavor to deal model and measurement uncertainties affecting the identification process. Since the cost of instrumenting the structure as well as cost of computation is the major concern with traditional health monitoring algorithms, our study attempts to develop algorithms which are economical (both due to reduced instrumentation requirement and computation time) as well as precise in estimation.
2
POSTDOCTORAL RESEARCH
Development of robust and noise adaptive particle filtering based algorithm for structural health monitoring
The study focuses on systems with correlated noise process undergoing change in environment of noise or force. The development targets introducing a particle filter based algorithm that can overcome the barriers. Developed algorithm considers correlation in noise processes which is eminent when Kalman like filtering techniques are employed for SHM purposes.
3
LABORATORY
Information and Statistics for Stochastic Structural Systems (i4S)
Information and Statistics for Stochastic Structural Systems (i4S)
website: https://www.i4siitmandi.com/
School of Engineering, IIT Mandi, Kamand, Himachal Pradesh 175001, India teami4s.iitmandi@gmail.com
Ph no: 0091-1905-267-261
2009
2004
DAAD SCHOLARSHIP
awarded by Govt. of Germany
GOVERNOR GOLD
MEDAL
awarded by Governor of West Bengal, India
AWARDS
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information and Statistics for
Stochastic Structural Systems
i4S
ADDRESS
i4s Laboratory (First Floor), A-14 Building, School of Civil & Environment Engineering, North Campus, IIT Mandi, Himachal Pradesh 175075, India
Phone: 01905 267 261