Dr. Suman Dutta

Dr. Suman Dutta

Designation Head of Department
Faculty Type Regular
Qualification

Ph.D., M.Tech, B.E.  

The focus of my research is to classify EEG signals for developing multi-task brain computer interface (BCI) system. BCI systems are developed by employing pattern recognition of spontaneous EEG signals related to a small set of mental task. The task of  EEG pattern recognition involves featureextraction through signal processing techniques and classification through employing machine learning techniques. I have developed  a number of  new  approaches  for extracting  nonlinear features from the EEG signals employing advanced signal processing techniques, namely empirical mode decomposition and its multivariate versions, phase space reconstruction techniques, independent component analysis , principal  component analysis etc. 

Publications in SCI indexed journals 

  • Classificationof non-motor cognitive task in EEG based Brain-computer interface using phase space features in multivariate EMD domain. (BIOMEDICAL SIGNAL Processing and Control 39(2018), 378-389. Impact Factor: 2.39) 
  • Automated  classification of  non-motor   mental  task   in  electroencephalogram   based  brain-computer   interface   using   multivariate   autoregressive   model in  the  intrinsic  mode  function  domain.  (  Biomedical Signal Processing and Control 43 (2018),174-182,  Impact Factor: 2.39) 

  A novel application of multi-scale multivariate entropy as features for classifying non-motor mental tasks in EEG based BCI. Have ( This paper has been accepted for publication in IETE journal of Research, but currently under  production checklist).


Data Science Experience 

  • Machine learning (ML) problem: Classification of   non-motor EEG signals for developing   Brain-Computer Interface (BCI) based applications.

 

  • Algorithms :Multilayer perceptron , linear discriminant analysis, k-nearest neighbor , decision tree classifier, support vector machine ,random forest , convolutional  neural  network , recurrent neural  network .
  • Software tools:MATLAB/SIMULINK,  Python and Python based libraries such as Keras, Tensor Flow, Theano, Pytorch


Professional activities:

  • Have experience in R&D Activities  within the Department
  • Project coordinator and Seminar coordinator for under graduate students.
  • Class Counselor for final year students.
  • Advisor of Student‘s activities of ISTE Student’s Chapter within the Institute.


Industrial experience:

Organization

Designation 

Period 

M/S ABB-ABL LTD

Engineer, Technical Services

May 1994- April 2000

M/S Medhaj Techno Concepts Pvt Ltd

 General Manager ( Execution)
 June 2018-May2019

Membership in professional organizations :         

Life member of Indian Society of Technical Education (Membership No LM  36675)


Honors and awards: 

Awarded National Scholarships twice i.e.  After10th and after 12th


Subjects taught:

UG level 

Digital Signal Processing,

Digital System Design using VHDL,

Biomedical Instrumentation,

Intelligent Instrumentation,

Control Systems, Advanced Control Systems,

Computer  Applications  in Power  System

Power System Operation & Control,

Network Analysis &Synthesis,

Electro Magnetic Field theory,

High Voltage Engineering.


PG level 

Modeling and Analysis of Electrical Machines,

Extra High Voltage A.C Transmission System,

Electrical Transients in Power System,

Artificial Intelligence

Power  Quality

Research interests: 

Deep learning based analysis of  biomedical  signals and images for screening and detection of  diseases/disorders.

Application of  Soft Computing (Fuzzy Logic, Artificial Neural Network, Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Tabu  Search) techniques

EEG based BCI systems.

MEMS&NEMS

Robotics & Artificial Intelligence 

FACTS devices and Renewable Energy.

 Power Quality Management 

Smart  Grid 

Machine learning/Deep  learning  systems in Python

Data Science Experience 

  • Machine learning (ML) problem: Classification of   non-motor EEG signals for developing   Brain-Computer Interface (BCI) based applications. 
  • Algorithms :Multilayer perceptron , linear discriminant analysis, k-nearest neighbor , decision tree classifier, support vector machine ,random forest , convolutional  neural  network , recurrent neural  network .
  • Software tools:MATLAB/SIMULINK,  Python and Python based libraries such as Keras, Tensor Flow, Theano, Pytorch


Professional activities: 

  • Have experience in R&D Activities  within the Department
  • Project coordinator and Seminar coordinator for under graduate students.
  • Class Counselor for final year students.

 Advisor of Student‘s activities of ISTE Student’s Chapter within the Institute.