About

Trisha Kanji is a highly skilled Software Engineer at Intuit, with a passion for Machine Learning and Data Science. She recently graduated from SUNY, Stony Brook with a Masters Degree in Computer Science, specializing in Data Science. Trisha has a diverse range of experience, having worked as a Graduate Teaching Assistant for Course CSE 214: Data Structures and Algorithms at Stony Brook University, and as a Builder at Mozilla Builders Spring Open Lab. At Mozilla Builders, Trisha developed an online platform for relief coordination by matching donation-related resources like food, clothing, etc. using relevant tweets. She implemented Naive Bayes Classifier for classification of tweets (Donation/Non-Donation, Donor/Requestor & Resource Type classification) and achieved an accuracy of approx. 80%, after parsing them using standard NLP techniques. Her website, https://help-for-all.herokuapp.com/, lists donation/request tweets location-wise, based on search. Trisha's education history includes a Bachelor of Engineering (B.E.) in Computer Science and Technology from the Indian Institute of Engineering Science and Technology (IIEST), Shibpur, and a Master of Science (MS) in Computer Science from Stony Brook University. Trisha's tech stack includes Software Engineering, Data Science, Machine Learning, Spring, Naive Bayes, NLP, and Search. She has 4.69 years of relevant experience and is continuously looking for opportunities to learn and grow in her field. With her passion for machine learning and data science, Trisha is a valuable asset to any team she works with.