Speaker Name: Prof. Jithin John Varghese, Assistant Professor, IIT Madras
Date: 23-09-2026 (Wednesday)
Time: 14:30
Venue: LC001
The Department of Chemical Engineering, is pleased to announce that Prof. Mahesh Tirumkudulu has been elected as a Fellow of the Indian National Academy of Engineering (INAE).The INAE Fellowship is a distinguished recognition of outstanding contributions to engineering and technology.
The Department warmly congratulates Prof. Mahesh Tirumkudulu on this prestigious recognition and wishes him continued success in his academic and research endeavours.
The research work of Prof. Jason Picardo and his student Dr. Swarnaditya Hazra on aerosol transport in mucus-lined airways has been selected for the Prof. R. Kumar Award for Innovative Modelling in Chemical Engineering 2026.
The Department of Chemical Engineering, IIT Bombay, announces the schedule and seating arrangements for the Mid Semester (Autumn 2026-27) Examination for Undergraduate (UG), Postgraduate (PG), and Dual Degree (DD) students.
The Department of Chemical Engineering, IIT Bombay, is pleased to announce the 64th Department Degree Award Function (DDAF) 2026, celebrating the successful completion of academic programmes by students receiving their Ph.D., Dual Degree, M.Tech., B.Tech., and BS degrees.
The Department Degree Award Function will be held on Sunday, 23 August 2026, at 9:45 a.m. at LA002, Lecture Hall Complex, IIT Bombay.
The Department of Chemical Engineering, IIT Bombay, is pleased to announce the 8th Department Degree Award Function under the 64th Convocation of IIT Bombay 2026, recognizing the outstanding academic achievements, research contributions, and excellence of its students.
The awards will be conferred upon the recipients during the Department Degree Award Function (DDAF) on 23 August 2026.
The Department warmly congratulates all the awardees and acknowledges their exceptional accomplishments.
Ph.D. Awards
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.