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HEAD OF THE TEAM

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Phone: +91-1905-267261

Email: subhamoy@iitmandi.ac.in

DR. SUBHAMOY SEN

Associate Professor
School of Civil and Environmental 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.

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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

DRDO PROJECT

Digital Twin development employing Bayesian filters with sub- structured predictor models for aerospace structures applications. 

Ongoing

2

SJVNL

Study for the optimum height of lift for mass concreting in concrete dam structures.

Completed

3

AR&DB PROJECT

Development of damage detection technique for composite laminated structures under varying temperature. 

Completed

4

IMPRINT 2 DST

DST-Imprint 2- Water and Energy Efficient Reliable Irrigation System (WatEr-ERIS): Solar energy and Cloud-based decision support systems for an automated irrigation system. 

Completed

5

SEED GRANT, IIT MANDI

Robust health monitoring of steel bridges under varying environmental and traffic conditions: an application to Victoria bridge.

Completed

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

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

EWSHM 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

2018

2018

2018

2018


2017

2017


2015



2014



2014

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 Civil & Environmental Engineering,

IIT Mandi, Kamand, Himachal Pradesh 175001, India  teami4s.iitmandi@gmail.com 

Ph no: 0091-1905-267-261

AWARDS

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2009

GOVERNOR
GOLD MEDAL

awarded by Governor of West Bengal, India

2004
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DAAD
SCHOLARSHIP

awarded by Govt. of Germany

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MORE TO EXPLORE

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i4S

information and Statistics for
Stochastic Structural Systems

Location : i4s Laboratory (First Floor), A-14 Building, School of Civil & Environment Engineering, North Campus, IIT Mandi, Himachal Pradesh 175075, India

 

Email : teami4s.iitmandi@gmail.com

Phone01905 267 261

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