Purva Gawde

A photo of Purva Gawde.
CLTA Assistant Professor, Teaching Stream
Telephone number
647.601.4658
Building IC 484

After completing master's in computer science, I completed my PhD in computer science from Kent State University, Ohio, USA. During PhD, I taught and developed curriculums for various subjects. After that, I worked as a post-doctoral researcher and curriculum developer at Ryerson University before joining UTSC as a lecturer in Computer Science since Fall 2020.

Teaching and developing undergraduate and graduate level courses made me aware of the challenges faced by students and teachers.  This experience inspired me to start exploring the world of pedagogy in Computer Science.

 

Education

PhD Computer Science

Kent State University, Ohio, USA

 

Teaching Interests

Programming language concepts, Databases, Web applications, Health Informatics, Artificial Intelligence

Research Interests

CS Education,  Database application in health informatics, Artificial Intelligence, Machine Learning

Publications

1. P. R. Gawde, A. K. Bansal, and J. Nielson, "Applying Markov Model for Automated Classification of Supraventricular Dysrhythmia," International Conference on Health Informatics and Medical Systems (HIMS), Eds: H. R. Arabnia and L. Deligiannidid, Las Vegas, July 2015, pp. 10-16

2. P. R. Gawde, A. K. Bansal, and J. Nielson, “Integrating Markov model and morphology analysis for finer classification of Ventricular Arrhythmia in real time”, IEEE International conference on Biomedical and Health Informatics (BHI 2017), Orlando, Florida, USA, February 2017, pp. 409-412

3. Purva R. Gawde, Arvind K. Bansal, Jeffrey A. Nielson, “Bivariate Markov Model Based Analysis of ECG for Accurate Identification and Classification of Premature Heartbeats and Irregular Beat-Patterns”, IEEE Conference Intelligent Systems (IntelliSys) 2018, London, UK, 6-7 September 2018, pp. 850-859, 2018.

4. P. R. Gawde, A. K. Bansal, and J. A. Nielson, “Integrating Markov Model, Bivariate Gaussian Distribution and GPU based Parallelization for Accurate Real time Diagnosis of Arrhythmia Subclasses,” in 2018 IEEE Technically Sponsored Future Technologies Conference, FTC 2018, Vancouver, Canada, November 2018.