Samruddhi Kamble

A highly motivated and academically distinguished fourth-year B.Tech student in Computer Science at Pune University, concurrently pursuing a Bachelor's in Data Science and Programming from IIT Madras. With a strong foundation in data analytics, machine learning, and statistical modeling, I bring hands-on research experience from prestigious international institutions, including CNRS LS2N Lab (France), Mitacs (Canada), Osaka University (Japan), and the 2041 Foundation (USA).

My interdisciplinary projects reflect a rare blend of technical depth and real-world impact—ranging from ecological AI using deep learning, to high-performance data mining, and climate analytics. Recognized for academic excellence and selected among top-tier global candidates for the Mitacs Globalink program, I excel in Python, R, Tableau, and advanced ML frameworks. I thrive in collaborative, research-driven environments, and am passionate about solving meaningful problems through data science and Artificial intelligence

• Selected as the youngest researcher from India for the 2041 Company project in New York.
• Secured a highly competitive Mitacs research internship in Canada
• Awarded as global researcher
• Mitacs GRI Scholar
• First-generation STEM student from a top-tier institution in India
• Successfully balanced dual-degree programs with high academic performance.

Vayu Astra, Top 10 in IBM Call for Code Global Competition, Developed an air quality index monitoring system using IBM IoT services.

• Mitacs Research Internship=Data Visualization and Visual Analytics, Developed advanced data visualization and visual analytics solutions to analyze large, complex datasets., Utilized Python, Tableau, and Power BI to create interactive dashboards and insightful visual representations., Conducted exploratory data analysis and statistical modeling to uncover trends and patterns., Applied machine learning algorithms to enhance data-driven decision-making processes., Leveraged Python libraries (Pandas, Matplotlib, Seaborn) to effectively communicate findings.
• Summer Project, University of Manitoba - Data Mining Lab, 06/01/24, 08/31/24, Conducted an in-depth literature review on state-of-the-art data mining techniques., Designed and implemented a novel Sorted Vertical Transaction Database (SVTDB) to enhance efficiency in frequent itemset generation., Developed an algorithm with a time complexity of O(nm
• Log(m)+3mn) that leverages support monotonicity and maximal support calculations., Conducted extensive experiments using real-world datasets demonstrating significant performance improvements., Collaborated with academic stakeholders to optimize implementations and extend algorithmic improvements.
• Research trainee, Osaka University, Japan, 08/01/21, 10/31/21, explored connections between algebraic geometry and geometric topology, studied the topological realization of WKB states in geometric quantization, contributed to the understanding of constructible sheaves in relation to Fukaya-Floer theory

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• Team member and youngest researcher from India, 2041 Company, New York, 09/01/21, 03/31/22, conducted exploratory data analysis using Python, developed predictive models for depletion trends, created visualizations to effectively communicate findings