Monoclonal antibodies are complex biological products, and glycosylation and other critical quality attributes (CQAs) can significantly influence their efficacy, stability, and pharmacokinetics. These attributes are sensitive to the metabolic state of the production cell and bioprocess conditions, making their prediction and control an important challenge in biomanufacturing. This project will develop mechanistic and data-driven models to predict mAb glycosylation and CQAs from cellular metabolism and process variables.

Therapeutic proteins exhibit complex structural heterogeneity arising from glycosylation, post-translational modifications, sequence variants, and product-related impurities. This project will develop computational methods for interpretation of high-resolution mass spectrometry data to characterize these critical quality attributes. The research will integrate machine learning, statistical analysis, and computational mass spectrometry to enable robust and scalable analytical workflows for biopharmaceutical development.

Therapeutic proteins exhibit complex structural heterogeneity arising from glycosylation, post-translational modifications, sequence variants, and product-related impurities. This project will develop computational methods for interpretation of high-resolution mass spectrometry data to characterize these critical quality attributes. The research will integrate machine learning, statistical analysis, and computational mass spectrometry to enable robust and scalable analytical workflows for biopharmaceutical development.

Chinese Hamster Ovary (CHO) cells are the dominant host for manufacturing monoclonal antibodies and other biotherapeutics. This project will integrate extracellular and intracellular metabolomics with genome-scale metabolic models to characterize cellular metabolism during bioprocessing. The objective is to identify metabolic bottlenecks, optimize media and feeding strategies, and develop predictive models for improving cell growth, productivity, and product quality.

The work involves synthesis, characterization and performance evaluation of catalyst for the production of sustainable aviation fuel (C8-C16 hydrocarbons) from renewable feedstock. Student is also expected to perform techno-economic and life cycle assessment. 

This project focuses on converting CO₂ into valuable fuels and chemicals using dry reforming of methane. You will work on developing coke-resistant catalysts and explore photothermal approaches to drive the reaction more efficiently. The work will involve catalyst synthesis, advanced characterization, flow reactor experiments, and reactor design/ optimization. 
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This project explores methane pyrolysis as a route to produce clean hydrogen, with solid carbon as a valuable co-product. You will work on developing advanced catalysts with high activity and resistance to deactivation, along with designing and operating reactors for high-temperature conversion. The project combines catalyst development, reaction kinetics, and reactor engineering, including studies on carbon formation and process optimization. It offers opportunities to work on both experiments and scale-up strategies for continuous, low-carbon hydrogen production.

Methane, a potent greenhouse gas, is often wasted through flaring. This project explores how it can be directly converted into more valuable fuels and chemicals using renewable electricity. You will work with non-thermal plasma and catalysis to enable methane conversion at low temperatures, addressing key challenges like energy efficiency and product selectivity. The project combines catalyst development, reactor design, and process modeling.

This work envisages integration of stability and estimation in context of PINNs.