Malini Anbazhagan

A recent graduate with Data Science & Analytical skills looking a Full-time position Portfolio: https://malini-ai.github.io/Portfolio.github.io/ adjdfg@r.postjobfree.com www.linkedin.com/in/malini-anbazhagan-410472135 https://github.com/Malini-AI WORK EXPERIENCE

University at Buffalo, Buffalo, NY Mar. 2020 - present Research Assistant

Developed modules to identify morphed facial images based on generated image scores

Researched on various IQA methods and Similarity methods to differentiate the facial images University at Buffalo, Buffalo, NY Jun. 2019 - Aug. 2019 Graduate Research Assistant

Developed functions to enable localized position detection for Roomba robot using floor texture recognition

Analyzed floor images to generate input parameters such as scale, blur values and features to be extracted JHP School, Gujarat, India Oct. 2017 - Apr. 2018

Teaching Intern

Taught Lego Robotics to students from grade 3 to 10 and trained them for WRO 2018 EDUCATION

University at Buffalo, Buffalo, NY

Aug. 2018 - Jun. 2020

Master of Science (MS) in Computer Science

GPA: 3.1/4.0

Marwadi University (GTU), Gujarat, India

Jun. 2013 - Apr. 2017

Bachelor of Engineering (BE) in Computer Engineering GPA: 8.9/10

SKILLS

Programming Languages: Python, C/C++, Java, CSS, HTML, HTML 5, R Data analytics tools and Libraries: Pandas, matplotlib, Anaconda, Tableau, NumPy, Scikit-learn, OpenCV, MATLAB, NLTK, TensorFlow, Hadoop, Spark, SAS

Database: My SQL, Microsoft Access

Tools: Adobe ( InDesign, Spark, Analytics, Captivate, photoshop), IBM analytics Expertise: Machine Learning, Data Mining, Data Analytics, Robotics, Image Processing, Research, Algorithm Development, A/B testing

PYTHON PROJECTS

Dimensionality Reduction and Association Analysis

Implemented PCA to reduce dimensionality of gene data for improved prediction confidence

Applied Apriori algorithm to generate association rules applicable to any generic datasets Data Classification and Cluster Analysis in Bioinformatics

Identified gene clusters with similar expression profiles using several classification and clustering algorithms viz. K-Nearest Neighbour, Decision Tree, Naïve Bayes and k-means, Density based

Identified the most efficient application for each of the 7 implemented algorithms Big Data Processing with Hadoop and PySpark

Implemented simple Map-Reduce programs to calculate word count, N-grams & Inverted Index on multiple files, relational join between two tables and KNN classification

Applied ML models in pyspark and processed the data using TF-IDF, countVector and word2vec Miscellaneous Projects

Text analysis and Text Mining using nltk and nlp packages

Speech Recognition, Movie Genre prediction, Live Weather Data Scrapping

Face and Emotion Recognition modules using PYPI and CNN

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