Current Projects

A.   Optimization and Modelling of Microbial Fuel Cell

Summary – To fulfill the increasing demand of energy as well as to reduce carbon dioxide emissions, sustainable and clean energy systems are needed. Most of the countries including Trinidad and Tobago are looking for Carbon – Neutral ways to generate energy from waste and Microbial Fuel Cells (MFCs) seems to be one of the alternative. MFCs are living, galvanic electrochemical systems in which the anoxic activity of microorganisms on waste matter generates electrons and cations and hence electricity. We are doing experimental work on designing and optimizing MFC prototype for its applications towards clean and sustainable energy generation, wastewater treatment, oil spill remediation or some other bio-remediated activities. The inter – comparison of these systems based on models to be implemented using Matlab and COMSOL Multiphysics software packages is also being done.

According to the EMA, there has been 377 oils spills in Trinidad between 2015 and 2018. Consequently, petroleum substances and chemicals are contaminating sea water which cause alarm due to the toxicity and effects on the human population, wildlife and the environment. MFC is a non-invasive remediation technique that can repair the contaminated entities organically. Currently, the materials used for this technology are expensive, along with the energy production being minimal, which means the technology is not yet ready for commercialization. Our research will play significant role in understanding how this technology can be applicable to oil spills in Trinidad, considering the number of spills the island had in the recent years.

Output:

We have presented research work in International Conferences at Spain (March 28-30, 2012), USA (Oct. 3-5, 2012) and T&T (June 1-5, 2020).

We have published two international Journal (5 and 16) and two international conference papers (2 and 4) out of this work.

Over the years 16 undergraduate, 1 MSc and 1 MPhil students were involved in this research work.

Currently Mr. Vekash Khan is doing research on MFC for oil spill remediation as an MPhil student.

B.   Design of Devices and Techniques for Medical Applications

Summary - State of art machine learning techniques and artificial neural network can be used to develop better devices and techniques for various medical applications. I am working with my collaborators Prof. B. P. Patil and Dr. Harjit Pal Singh on following research projects:

Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neuropsychiatric disorders in adolescence and adult, but the origin of this disorder is still under research. We build a deep learning based hybrid 2D convolutional neural network–long short-term memory (CNN–LSTM) model which classify the ADHD individuals from typically developing individuals based on resting state functional magnetic resonance imaging (rs-fMRI) images.

In an effort to fulfil the urgent necessity which has emerged to fight against the COVID-19 pandemic, I am working with my collaborators on Artificial Intelligence-based tool for automatic detection of the COVID-19 disease. We have developed automated Covid-19 detection system, which uses indications from Computer Tomography (CT) images to train the new powered deep learning model- U-Net architecture. The U-Net architecture used for Chest CT image analysis has been found effective. Our proposed method can be used for primary screening of COVID-19 affected persons as an additional tool available to clinicians.

An electrocardiogram (ECG) signal is an important diagnostic tool for cardiologists to detect the abnormality. In continuous monitoring, an ambulatory huge amount of ECG data is involved. This leads to high storage requirements and transmission costs. Hence, to reduce the storage and transmission cost, there is a requirement for an efficient compression or coding technique. We are working on the Block Sparse Bayesian Learning (BSBL)-based multiscale compressed sensing (MCS) method for the compression of ECG signals. The main focus of this technique is to achieve a reconstructed signal with less error and more energy efficiency.

Output:

Three papers, one in Elsevier (2), one in Springer (3) and one in World scientific (1) journals, have been published recently. Going to present a conference paper in July (1).

C.   Thin Film Solar Cell and Gas Sensors

Summary - I, along with my Associate Professional Mr. Kevin Beepat, am working in collaboration with Dr. Mahajan and his team at the Guru Nanak Dev University, India to investigate optoelectronic properties of MXenes in the context of climate change and their possible involvement in the production of solar cells. The intention is for the team based in India to work on experimental research with their MXene samples while we, the West Indian team, perform simulations on their work using COMSOL Multiphysics software. I have also worked with Indian team on the development of low cost, efficient and reversible chemiresistive sensors which is one of the future challenges for the detection of harmful and toxic gases. Departmental impedance spectroscopy equipment was also utilized in this study.

Output:

Recently one paper has been published in Elsevier’s Journal (4).