Parnika Damle

• Volunteered for open-source projects aimed at analyzing high-dimensional, high-volume datasets, and developing innovative data science solutions for them. • Performed data pre-processing, analysis, and visualization using Python and Tableau. • Experience in feature selection and predictive analytics.

• Subject matter expert (SME) in Discrete Maths and Graph Theory, Python programming, and Machine Learning (ML). • Coaching undergrads with application-oriented content delivery using innovative pedagogical approaches. Designing complex problem statements simulating real-world scenarios for hands-on lab sessions.

• SME in Statistical Analysis and Programming, ML, and Multivariate data analysis • Co-principal Investigator on a 'Grape Analysis Research' project aimed at early detection of disease in grape plants through deep learning.

• Developed novel approach for classification of multivariate data using graph-based features and ML classifiers. • Designed graph-based classifiers to enhance the performance of this approach. • Devised novel approaches for the detection of alcoholic vs controlled drinkers and brain activity recognition using multivariate time series data (biomedical EEG signals).

• Design and development of UI, task flows, and other business components for Oracle Time and Labour (OTL) project in Agile manner. • Bug fixing, Unit testing, Integration and deployment of application across environments.