Data Science Research Assistant

Kalyani Khandait

Master’s in Data Science University of Delaware August 2024 - Present

Bachelors in Computer Engineering Savitrbai Phule Pune University, Maharshtra, India July 2023 EDUCATION

PROJECTS

Research Assistant, Dutta Lab, University of Delaware Department of Animal and Food Sciences, Supervisor: Dr. Aditya Dutta Conducted comparative microbiome and genomic analysis across 662+ clinical samples from 9 body sites, aiming to identify translational biomarkers relevant to human ovarian cancer. Identified 23+ microbial biomarkers, isolating 8 high-impact markers through differential abundance analysis, significantly associated with cancer onset and supporting early detection models. Applied alpha diversity metrics (Shannon, Simpson) and linear regression to uncover stage-specific microbial variations (p < 0.01), and used beta diversity methods (Bray-Curtis, PCoA) to reveal cancer-stage-specific clustering patterns. Validated inter-group microbial differences using PERMANOVA (p = 0.001) and db-RDA, identifying distinct early-stage microbial signatures and explaining up to 31.3% of total variance across body sites. Relevant Courses: Regression Analysis (statistics course), Mathematics in Data Science EXPERIENCE

CPU Performance Analysis Using Regression Techniques Analyzed and predicted CPU performance using the UCI CPU Performance dataset, applying multiple linear regression on 7+ hardware parameters (e.g., memory, cache, cycle time) to identify and model key performance drivers. Identified two key parameters (max and min main memory) significantly impacting CPU performance, with a strong positive correlation observed for Cache Cycle Ratio and a negative correlation for Machine Cycle Time. Resolved multicollinearity (e.g., VIF = 6.43 for CacheCycleRatio) using Box-Cox transformations and variable selection; final model via backward elimination with AIC achieved R = 0.970, Adj R = 0.969, p < 0.05, and VIF < 5, meeting all regression assumptions. Prediction of Basketball Game Winners Using Machine Learning Developed predictive models leveraging Random Forest, Ridge Classifier, and Logistic Regression, achieving 90% accuracy with Random Forest.

Processed and analyzed large datasets using advanced techniques like sequential feature selection and time-series split. Enhanced prediction by integrating rolling averages, game context, and performance metrics, providing actionable insights for sports analytics.

Virtual Intern, Certified by Amazon Web Services

AWS Cloud Foundation Course highlighted proficiency in Amazon EC2 instance hosting and connectivity with Amazon S3 object storage. Demonstrated adeptness in interacting with SQL and NoSQL databases on Amazon Redshift and DynamoDB. Used and worked with AWS VPC, CloudWatch, Auto Scaling, and AWS Lambda for serverless operations. AWS Cloud Architecting Certification Hands-on experience with building scalable cloud infrastructures using EC2, Lambda, and Elastic Load Balancing, S3, CloudFront, RDS, and Route 53 for efficient application management. Familiar with AWS Security Hub, cost optimization tools, and cloud performance monitoring. Crowdfunding For StartUp Ventures using Blockchain Technology Bachelor’s Final Year Project - Networking & Security Developed a high-performance, cross-platform mobile application for startup crowdfunding using Flutter, enabling campaigns to connect with investors, including the general public. Designed and deployed secure, scalable smart contracts with Solidity and Truffle, facilitating transparent transactions on the Ethereum blockchain.

Managed blockchain interactions through platform-sensitive tokens convertible to INR and ERC-20 tokens, Utilized MongoDB Cloud Atlas for efficient data management of campaign and transaction records. Waste Management Using Blockchain Technology –

LNNS, Springer.

Crowdfunding Using Blockchain for Startup Ventures – IJCA

Crowdfunding Using Blockchain for Startup Ventures – ICCUBEA, IEEE.

PUBLICATIONS

+1-302-***-**** *******.**********@*****.*** https://github.com/kalyani-10 https://www.linkedin.com/in/kalyani-khandait/ S K I L L S

Languages & libraries -

Python, SQL, Java, R, SAS, C++, PyTorch, Matplotlib, Scikit, Numpy, Pandas,, Sklearn, data analytics

Software Technologies

Amazon AWS, Microsoft Office, data Visualization - Power BI

Contact this candidate