Projects

Glioblastoma (GBM) is the most common & aggressive brain tumor having dismal prognosis. Patients diagnosed with the disease have a median survival of about 15 months only. Current mode of therapy is limited to surgical removal of the tumor and routine chemo/radiotherapy. However, emergence of chemo/radio resistance, and tumor recurrence is common. There is a pressing need for devising novel, multimodal therapies. miRNA based therapies hold promise for cancer treatment owing to their multi-pathway targeting abilities. Our study focuses on two oncogenic miRNAs: namely, miR-196a and miR-210, both associated with GBM progression and aggressive phenotype. Our work (at IITD) on these two miRNAs show that both of these are hypoxia induced and function as oncogenic miRNAs by promoting cellular proliferation and migration and inhibit apoptosis and are also associated with poor patient survival. Although miRNA therapy sounds attractive, the major bottleneck is their delivery as in naked form they are susceptible to degradation by nucleases, clearance by the reticuloendothelial system etc. Dr. Popat's laboratory at UQ has recently prepared ultra-small silica nanoparticles which has potential to cross BBB and accumulate specifically in tumour microenvironment and deliver genetic molecules. By combining these two innovative technologies (micro RNA and nanoparticles) we will provide proof-of-feasibility and efficacy of new therapeutic strategies aimed at reversing the immune evasive capability of Glioblastoma. The work will involve synthesis and characterization of the nanoparticles, their ability to deliver anti-miRNAs to the cells will be checked along with its efficiency to inhibit levels of said miRNAs. Upon successful inhibition of the above miRNAs with co-delivery of anti-210 and anti-196a by the NPs to GBM cells, the effect on the different cancer hallmarks will be checked. After completing the cell-based studies, we would test the efficacy of this therapy in an orthotopic mouse model of GBM.

Renewable energy sources are intermittent sources of power and are highly dependent on weather and climatic conditions. Variations in power generation poses multiple operating constraints like requiring primary and spinning reserves, complicated power production planning, and balancing power etc. It also has commercial implications in terms of financial planning, cash flow and downtime scheduling etc. Forecasting of weather patterns can help plan long term and short term operations of wind turbines. State-of-the-art forecasts can also have a significant economic impact. ReNew Power owns and operates over 50 wind farms with installed capacity close to 3GW (as of January 2019). A reliable forecast system for each of the farms would add to robustness to financial planning at ReNew.

Air pollution is a major medical hazard, and among the world’s most populous countries, the largest increase in the number of pollution-related deaths was seen in India. Capturing of ultra-fine particles is the most challenging. High efficiency particulate air and ultra-low penetration air filters are used to collect fine air-borne particle of minimum size 0.3 and 0.1 μm respectively. Particles are trapped by sticking to a fiber through diffusion, interception, or impaction and sometimes by electrostatic attraction. To reach higher filtration efficiencies without increasing the pressure drop due to small pore size, electret filter media with electrostatically charged microfibers are often used which can even operate for large porosity. These filters generate an electrostatic field in their vicinity and act upon the incoming charged (Coulombic force) or uncharged particles (Polarization force). They are thermally stable and are insensitive to moisture and high temperatures, but efficiency gradually weakens with time. As mentioned by recent paper, filters with high efficiencies, low resistances and dimensional stability are highly desired. They suggested a hierarchical micro/nanofibrous filter for this purpose. The current project proposes to develop numerical model of fibrous filters for fine particle capture. Accompanying the simulations there will be experimental validation and finally an optimized air filter will be proposed. Lattice Boltzmann method for porous media will be used for simulation of filter material with appropriate consideration of boundary condition and forces: Coulomb force and Polarization force. Nonwoven fabrics will be prepared using polymer and employing melt blown technology. The diameter of the fibers will be determined by SEM and image analysis technique. The thickness, weight will also be noted. The process of charging will be carried out by a corona-charging apparatus. The numerically optimized fibrous filter media will be tested for their filtration efficiency and pressure drop using a filter test rig.

This work proposes the design of an optimal sliding mode control (SMC) for a nonlinear & coupled dynamics of spacecraft based on the Legendre pseudospectral method (PSM). In recent times, PSM, a numerical optimal control method, has become popular owing to its fast convergence and ease in handling of constraints, particularly in space applications. The pseudospectral method has been shown in the state of the art to perform well in solving a wide range of optimal control problems with varied performance indexes, stringent endpoint conditions along with path constraints. These advantages make the use of Legendre PSM based sliding mode controller a good choice for an Optimal-Robust controller. By the use of the proposed methodology, the objective function can be optimized, while satisfying the constraints on state & controls, which would be difficult using only SMC. The gains of the robust controller can further be tuned adaptively by involving adaptive control concepts to overcome the problem of overestimation and underestimation. The stability analysis of the proposed PSM based adaptive-robust scheme can be investigated through Lyanpunov stability analysis. Numerical simulations will be included to demonstrate the effectiveness of the proposed method. Spacecraft and other non-linear systems which has various applications in technologies of the future, can be considered for demonstrating the optimal-robust performance of the proposed strategy. On application of the proposed controller, the time-energy efficient performance of the spacecraft can be demonstrated while tackling external disturbances and uncertainties that it encounters.

Modified polymer surfaces are gaining huge significance in various fields with wide applications in the biomedical industry. The surface modification on polymers can be achieved by various methods like exuberant physical method, self-organization and self-assembly and chemical functionalization of the polymeric surface. Among all the methods self-organization and self-assembly at the molecular level inspired by the biological moieties like protein, DNA is considered as the forerunner because of its low cost and easily approachable techniques. Thin-film dewetting leading to the formation of self-assembled arrays of polymer droplets creates a modified surface over which the scaffolding can be carried out. This regular arrangement of polymer droplets is utilized as a template for self-arrangement of nanoparticles over this surface creating a surface with higher functionalities. The underlying dewetting stress, engineers the nanoparticles to self-assemble among themselves and form different morphologies adding an edge to the already modified surface. The biocompatible polymer blends can create a membrane-like porous surface which is mechanically strong and the addition of nanoparticles increases the surface functionalities and act as a bio-scaffold. Theoretical analysis will also be carried to understand the physics and the phenomenon of formation of the structures and morphologies. Successful TE approaches will be best achieved when the biomaterial scaffold has mechanical properties, surface chemistries, and structural mechanics that are compatible with that of bones and allow osteointegration and subsequent replacement by native tissues. In the proposed project, the biodegradable polymer will be used for making scaffolds using selective laser sintering (SLS) processes. SLS will be carried out to investigate the effects of processing parameters on the microstructure, mechanical properties, and geometrical accuracy of the scaffolds.

Preserved Ejection Fraction (pEF) is a condition in which the heart’s ability to pump blood throughout the body is reduced. It is characterised by a stiffening of the myocardium (cardiac tissue), leading to the heart not relaxing to its full size before contracting for the next heartbeat. This results in a reduction of the actual volume pumped by the heart and, consequently, pEF is present in approximately 50% of people who experience heart failure. The aim of this project is to determine the composite mechanical properties of myocardium that lead to pEF, and identify which component (e.g. titin) dominates these properties. An ongoing area of interest in the study of pEF is the exact way in which the properties of the myocardium change to increase the heart’s relaxation time. A better understanding of how much various tissue properties can change or which specific layers of tissue have the greatest effect on the relaxation could assist in directing treatments towards these problem areas, and focus research on the biological factors that create these changes or effect these areas. This research will be computational in nature. A coupled computational fluid-solid dynamics model will be used to create a digital twin of representative biological flow configurations. The lattice Boltzmann method will be used to model transient blood flow as a non-Newtonian Kuang-Luo fluid, while the finite element method will be used to represent the composite myocardium as a pseudoelastic, orthotropic material. A significant amount of research has been undertaken in computational haemodynamics, while more recent research has been conducted to experimentally determine the material properties of healthy myocardium. By modelling this coupled fluid-solid system, a better understanding of the exact material property changes that are associated with pEF can be achieved, as well as the possibility of exploring treatment methods.

Stress and sex-specificity in emotion disorder remains poorly understood. This PhD project plans to examine psychophysiological effects of stress (hormone and ERP response) cognitive [Iowa gambling task] and affect response in anxiety-depression.

Living around natural environments may have beneficial health effects. However, lack of evidence is a barrier to developing 'green' cities. Policy-makers in India and Australia want to reconcile the different dimensions of how changing the greenspace affects health and provides climate benefits.

This project focuses on the development of start-to-finish pipelines for biotherapeutics derived from functional genomics patient data.

There are multiple traditional geometric problems in computer vision such as camera pose estimation, 3D reconstruction depth estimation, and tracking for which strong mathematical models and efficient, robust algorithms have been known for decades. Recently with the popularity of deep learning, researchers have applied various deep neural networks models to almost all of these problems and demonstrated state of the art performance on the benchmark datasets. However, modern learning based techniques also have known shortcomings in terms of handling out of distribution situations and susceptibility to adversarial attacks. The objective of this project is to explore parametric deep neural networks, whereby a standard deep neural network is constrained to broadly follow the steps of a prescribed mathematical model with a scope for learning each of the individual step using the available data. The developed model should ideally have the flexibility of learning based techniques, and at the same time robustness and interpretability of conventional mathematical techniques.