Rishi Venkat Sompalli

720-***-**** adgx01@r.postjobfree.com LinkedIn

SUMMARY

A data enthusiast with two years of experience in critical thinking, problem solving, leveraging statistical methodologies to build predictive models and visualization of large data that enable strategic decision making. Actively looking for full time opportunities. EDUCATION

Master’s in Computer Science, University of Colorado, Denver, USA CGPA 3.76/4 Aug 2018 – May 2020 Coursework: Machine Learning, Deep learning, Database systems, Operating systems, Algorithms, Software architecture, Cloud Computing.

Bachelor’s in Computer Science, Anna University, Chennai, India CGPA 3.6/4 Aug 2013 – June 2017 Coursework: Data structures, Design and analysis of algorithms, Software development, Object oriented analysis and design, DBMS. TECHNICAL SKILLS

Programming Languages: Python, C/C++, JavaScript, Angular, HTML, CSS, SQL, Flask, MongoDB, NodeJS, Java. IDE, Applications and Cloud: AWS, S3, Git, GitHub, CI/CD workflow, Tableau, Visual Studio Code, Jupyter Notebook, Google Colab, PyCharm CE, SSIS, Android Studio, SQL Server, SageMaker. Operating Systems/ SDLC methodologies: Windows, MacOS, Linux, Agile, Scrum. Data Science Libraries: NumPy, Pandas, SciPy, SciKit-Learn, Seaborn, Matplotlib, ggplot2, Plotly, Keras, TensorFlow. Data Science Algorithms: Linear Regression, Logistic Regression, ANN, SVM, Naïve Bayes, Random Forests, Decision Trees. PROFESSIONAL EXPERIENCE

Graduate Student Assistant, Auraria Library, Denver Aug 2019 – May 2020

• Tasked with requirement gathering, data pre-processing, feature engineering and application of algorithms to build a machine learning model in python to predict the usage of the magazines, journals, books used by the peers across the university.

• Transformed raw data into MySQL with ETL applications to prepare unruly data for machine learning.

• Developed SQL queries in SSMS, to filter the incoming books and store them under specific category. Used Excel to establish a live connection to follow the circulation of books in and around the library.

• Used Tableau as a visualization tool, to analyze the end of monthly circulation of performance sheets and periodicals for the library.

• Worked on an agile environment to strategize the KPI’s and identify the critical metrics to manage the progress of the active projects. Data Science Intern, GLF, Chennai Apr 2017 – Aug 2018

• Built statistical models in python using historical data to predict real estate prices in several economic markets and focused on analyzing the factors affecting the value of the properties.

• Used data mining techniques to develop prediction algorithms to classify similar properties together to develop sub-markets and each zip code was divided into submarkets.

• Performed data extraction, data cleaning and data wrangling by finding anomalies and outliers using python and Excel.

• Created and presented executive dashboards and scorecards to show the trends in the data using Tableau. Research Assistant, Velammal Medical College & Research Institute, Chennai Apr 2016 – Apr 2017

• Designed and developed the database application in the study “Search for Diabetes” using MS Access and MS SQL.

• Participated in requirement gathering sessions with scholars to distill technical requirements from business demands.

• Performed data extraction, data cleaning and data wrangling by finding anomalies and outliers to facilitate data governance.

• Enabled effective decision making by retrieving data from disparate data sources and compiling it into a usable business format.

• Created projection graphs and recruitment progress reports for principal investigator and project manager using Power BI.

• Analyzed health data to estimate the trends over time in diabetes by age, race/ethnicity, gender, diabetes type and other metrics.

• Regression analysis were conducted to identify the risk and opportunities of research participants using Python and MS Excel. ACADEMIC PROJECTS

Short Term Solar Forecasting using LSTM (Python, RNN, Keras, Matplotlib, Seaborn). Mar 2020 – May 2020

• Performed Data gathering, Data cleaning and Exploratory Data Analysis (EDA) to analyze the solar irradiance measurements.

• Implemented a LSTM model, a kind of Recurrent Neural Network (RNN) to predict the solar irradiance in the future based on local weather conditions and current solar irradiance with a test accuracy of 85%. Sentiment Analysis for Hotel Reviews (Natural Language Processing, Python, Naïve-Bayes, Pandas, Matplotlib). Jan 2020 – Mar 2020

• Implemented a bag-of-words model along with the Naïve Bayes Classifier for sentiment analysis of hotel reviews.

• Successfully classified the reviews into positive or negative with a test accuracy of 92%. Face Login Using Angular and NodeJS (Angular, NodeJS, MongoDB, Microsoft Face API). Feb 2019 – Apr 2019

• Implemented a face login for an Angular web application using Microsoft Face API.

• Availed Angular for frontend and NodeJS server for backend to communicate with Face API and stores data in a MongoDB. Analyzing Emotions in Videos Using Facial Expressions (Python, Flask, HTML, CSS, Keras, TensorFlow). Sept 2018 – Dec 2018

• Built a Convolution Neural Network (CNN) in Keras with TensorFlow backend from scratch to recognize facial expressions in videos using OpenCV and the model was represented as a JSON string after training and evaluation.

• Created a Flask application to serve predictions and designed an HTML template for the Flask application to recognize facial expressions in video and visualized the trends of emotions using Matplotlib.

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