Rinki Solanki

Data professional with 2.5+ years of industry experience in Data Analysis, Machine Learning, Python, SQL,
and Business Insights. Eager to transition into an Assistant Professor role, blending practical expertise with
academia to advance the field of Data Science. Dedicated to delivering engaging teaching, pioneering research,
and instilling a progressive approach to data science education.

Data professional with 2.5+ years of industry experience in Data Analysis, Machine Learning, Python, SQL,
and Business Insights. Eager to transition into an Assistant Professor role, blending practical expertise with
academia to advance the field of Data Science. Dedicated to delivering engaging teaching, pioneering research,
and instilling a progressive approach to data science education.

have worked on the fuzzy clustering domain by developing algorithms with the construction of novel similarity
measures implementing probabilistic theory in it. I have also extended proposed algorithms in kernel space
to deal with non-linear separable data. Moreover, I have studied the mathematical convergence of proposed
algorithms, which is one of the most essential properties of any algorithm. In addition, I have explored probabilistic
similarity measures on supplier selection and face identification problems.