• Delivering new features in curve fitting to enhance customer workflows using curve fitting and statistical modeling.• Collaborating with cross-functional teams to design and implement high-quality, user-friendly software.• Working in an agile environment, adapting to changing requirements and delivering results efficiently.• Influence the long-term strategy of the Curve Fitting Toolbox by analyzing industry trends and customer requirements• Mentoring junior developers, fostering their growth and technical skills• Continous learning through MOOCs and Book Clubs on machine learning, statistics and software development

Led the development of Curve Fitter, the new user interface for curve fitting within MATLAB:• Collaborated with cross-functional teams to gather requirements and design an intuitive user interface.• Architected the software using proven design patterns to ensure a high-quality, scalable, and maintainable application.• Developed a comprehensive implementation plan and led the implementation to ensure timely delivery.• Provided technical guidance and mentorship to junior team members.

• Worked with the Statistics and Machine Learning team on developing a UI for Feature Selection in Classification and Regression Learner apps.• Worked with Computational Biology team on creating a prototype UI for simulating pharmacokinetic models.• Provided technical support to customers utilizing MATLAB and its toolboxes.

• Developed a model order reduction framework for stochastic differential equation representations of biomolecular systems with time-scale separation using control theoretic principles.• Analyzed and quantified the interplay between information transmission and signal noise in several gene regulatory and signal transduction network motifs that appear in the contexts of systems and synthetic biology.• Performed extensive numerical simulations using stochastic simulation algorithms for biomolecular systems to supplement the theoretical results obtained through above analyses. ••

• Course: Introduction to Numerical Simulations.• Designed and graded problem sets, held office hours and review sessions for a class of 60 students.

• Used optimal experimental design theory to evaluate and optimize pre-clinical oncology experimentalsetups for parameter identification of full and simplified TMDD models and a minimal PBPK modelfor mABs/ADCs to understand tissue distribution.• Developed a user interface based on the R programming language and Shiny package to identify the optimal experimental design for TMDD models.

• Collaborated in a multidisciplinary team taking part in a genetic engineering competition organized by MIT.• Analyzed a genetic engineering concept of using a bacterium to detect vibrio cholera in water and developed a mathematical model for the system.

• Trained to use the .Net programming language and Microsoft SharePoint for project management.• Served as an assistant to a number of project managers, preparing project proposals, taking minutesof the project meetings and performing other administrative duties.