Ravali Kolli

Milpitas, CA 916-***-**** adbttx@r.postjobfree.com linkedin.com/in/ravali-kolli1996/ github.com/RavaliKolli SUMMARY

Highly motivated, process-oriented software developer launching a career in the field of Software Engineering to utilize computational and problem-solving abilities with 2+ years of experience in software design, analysis, development, and testing. EDUCATION

Master of Science, Computer Science, California State University, Sacramento, CA (GPA: 3.7) Aug 2017 - Dec 2019. Bachelor of Engineering, Information Science, Dayanand Sagar College of Engineering, India (GPA 3.8) Aug 2013 - June 2017. TECHNICAL SKILLS

Programming: Python, Java, C, C++

Databases: MySQL, PL/SQL, Oracle, MongoDB

Data Science Libraries: PyTorch, Tensorflow, Keras, Pandas, Numpy, Scipy, OpenCV, Scikit-learn Web Technologies: HTML5, CSS, JavaScript, REST API, Flask Bigdata Frameworks: Spark, Kafka, Hadoop

DevOps Tech Stack: Git, AWS, Selenium, Kubernetes, Docker Tools and OS: Tableau, Eclipse, Visual Studio, Windows, Linux WORK EXPERIENCE

Intel Corporation - Software Engineering Intern May 2019 – Dec 2019.

• Developed a fully automated continuous integration system of Synopsys Library Compiler per specifications using Python, MongoDB, TCL and Fossil for the verification tool in the team.

• Performance enhancement of the verification tool noticed by cutting down the total turnaround time around 9X (e.g. 122 h to 12 h).

• Developed a machine learning model to predict runtimes for the tool from historical data. Travis Credit Union – Data Analytics Intern May 2018 – August 2018.

• Formatted, cleaned, combined and filtered 1.5 million data records from Customers and Transaction Data.

• Created scripts in JavaScript and Python to facilitate customer’s data collection from multiple domains.

• Created profits and losses visualization dashboards over all the counties using Tableau.

• Created and updated new SQL scripts in the data warehouse for daily reporting across domains. CSU Sacramento – Secure Programming Clinician and Teaching Assistant September 2017 – April 2019.

• Did Code Review of 30 students for Secure Programming project for 3months and mentored them concepts and issues individually.

• As a teaching assistant for Operating systems, Algorithms & Data Structures, Computer networks explained complex concepts in a small group setting and graded assignments and examinations for four semesters. Software Developer – RJS Recruitment and Consulting May 2016 – July 2017.

• Developed a website for secure transfer of confidential data through cloud as the third-party provider to offer services for the users.

• Constantly monitored all data transfers, intrusion detections and troubleshooting the issues occurred in the application.

• Technologies and Tools Used: Java, JSP, MySQL, Html, CSS, JS, Tomcat, NetBeans. ACADEMIC & PERSONAL PROJECTS

Yelp Business Rating Prediction:

• Performed preprocessing of the yelp dataset and trained with machine learning, deep learning models to predict business rating.

• Obtained the highest accuracy of 98% in the Tensor flow Linear Regression model with hyperparameter tuning compared to Logistic Regression, Naive Bayes and SVM.

Automation Framework for AWS instances (Java, Selenium, AWS):

• Developed a framework to automate the process of creation and deletion of AWS instances, this framework minimized the time consumption to create multiple instances automatically Video Streaming with Super Resolution using NAS:

• Developed a lightweight Super Resolution model using Neural Architecture Search to deliver enhanced video quality independent of available bandwidth.

• PSNR, SSIM, QoE quality values increased by 6%, 7%, 4% compared to existing methods. Detection of White blood cells using YOLO (You Only Look Once):

• Implemented with YOLO using a custom deep architecture darknet-19, an original 19-layer network supplemented with 11 more layers for object detection to detect and classify white blood cells with high accuracy.

• YOLO model delivered a higher accuracy of 87% outperforming CNN accuracy of 83%.

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