Bala Krishna Kuthyaru

+1-850-***-**** ad3jdt@r.postjobfree.com https://www.linkedin.com/in/balakrishna-kuthyar-b87934170/ May 2024 graduate seeking full time SWE / SDE opportunities Experience

Deloitte Digital, Back end web developer Hybrid July 2020 Aug 2022

• Utilized SAP Commerce Cloud (Hybris), Spring MVC, and Core Java libraries to design and implement high performance REST APIs for an e commerce site using core Hybris functionalities, resulting in a 20% reduction in response time and improved overall website speed.

• Worked on data modeling, Backoffice customizations, and seamless integration with SAP Commerce WCMS and enhanced theproject’sefficiencyandfunctionality.This included successfully enabling localization for thewebsite,resulting in a 25% increase in user engagement from Spanish and English native users.

• Played a key role in modernizing customer touch points on the Australian website, contributing to a 15% boost in user retention and improved customer experience.

• Engaged in automation through creating JUnit test cases, they achieved a substantial 90% code coverage for the implemented classes.

• Written export scripts with Groovy and MySQL that reduced the time required for product data migration between environments by 40%, streamlining the testing process and increasing overall productivity.

• Coordinated several virtual well being sessions to uplift team morale amidst the pandemic, during which 75% of our work was conducted remotely from home.

• Received an Applause Award for the work done during the fourth quarter of 2021. Education

4.0/4.0 MS in Computer Science, Florida State University Florida, USA Aug 2022 May 2024 8.2/10 BTech in Computer Science, Jawaharlal Nehru Technological University Hyderabad Telangana, India Aug 2016 Sep 2020 Achievements: ACM ICPC Kolkata regionals participant, 2018 and 2019. Finalists in ”Hyderabad’s biggest coding contest”, 2019. Courses: Data Structures Data and Computer Communications Operating Systems Analysis Of Algorithms Machine Learning Con current, Parallel, and Distributed Programming Network Security Artificial Intelligence Database Management System Computer Networks Java Programming.

Skills

Programming Java, Python, C, C++, MySQL, Git, Scripting (Bash), LaTeX, MongoDB. Web Technologies HTML, CSS, Bootstrap, JavaScript (Node.js), JSP, XML, JSON. Tools / Frameworks Spring Web MVC, Spring Boot, JPA, Hibernate, JUnit, Jira(Agile), Splunk, Excel. Platforms Unix/Linux, Windows(Microsoft Suite), MacOS, SAP Commerce Suite Backoffice, SmartEdit, ImpEx, AWS. Certifications The Web Developer BootCamp by Udemy(2023), AWS Certified Cloud Practitioner Foundational(2022). Soft Skills Logical Reasoning, Attention To Detail, Time Management, Problem solving, Documentation. Projects

ROFCON Oct 2023 Nov 2023

Network Emulator, Academic Project

• Designed and implemented a Java based back end system that achieved a 40% increase in successful packet transmission to end points via routers and bridges, leveraging OOP principles. Co written four key classes, optimized socket programmingwithmulti threading, and orchestrated critical data structures for ARP.

• EngineeredacomprehensiveMACandportmappingframeworkwithintheBridgeclass,resulting ina35%improvement in system robustness. Conducted umpteen rounds of rigorous tests using the JUnit framework to validate the functionality.

• Technologies used: Java (Socket Programming (TCP/IP), Multi threading, I/O operations). Implemented multiple test cases using the JUnit Framework, resulting in a 50% increase in code reliability. Executed the system successfully in the Linux terminal. YelpCamp Website May 2023 July 2023

Review Website, Personal Project

• Developed and executed YelpCamp (a Yelp stylewebsiteforcampsites)that facilitated seamless user interactions, including log ins, posting reviews, comments, and editing previous submissions. Enhanced user engagement and experience through effective implementation.

• Designed and implemented a MongoDB infrastructure to efficiently store and manage data. Successfully handled substantial amounts of reviews and comments data, along with relevant information associated with users and campsites, contributing to the overall robustness of the system.

• Technologies used: Node.js, JOI, Cloudinary, Mapbox, Express, MongoDB, and Bootstrap. Passport.js was used to handle authenti cation.

Detection of Diabetic Retinopathy Nov 2019 June 2020 Image classification using Deep learning (Academic Project)

• Applied a deep learning model to predict the risk of a patient losing eyesight on a scale of 1–5, achieving an accuracy rate of 94.3% in risk assessment.

• The method is established upon a real time dataset of more than 4000 retinal images from individuals aged 35 and above. The images are pre processed by converting them into grayscale and are fed into the RESNET 50 CNN model, demonstrating 10.3% improvement in prediction accuracy compared to baseline models.

• Technologies used: Python libraries (NumPy, Seaborn, Matplotlib, Sklearn, Keras, TensorFlow).

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