Machine Learning Information Technology

Karthik Reddy Kotla

Irvine, CA +1-480-***-**** ******@***.*** linkedin.com/in/karthikreddy1729 github.com/karthikreddy1729 EDUCATION

● University of California, Irvine Irvine, CA Sep 2023 - Dec 2024 Master of Computer Science, CGPA - 4.0/4.0

Coursework: Machine Learning and Data Mining, Artificial Intelligence, Operating Systems, Database Management System

● National Institute of Technology Karnataka, Surathkal Jul 2018 - May 2022 Bachelor of Technology - Information Technology, CGPA - 3.8/4.0 Coursework: Software Engineering, Data Structures, Analysis of Algorithms, Soft Computing, Data Warehousing TECHNICAL SKILLS

Programming/DBMS: Golang, Python, C, C++, Java, JavaScript, TypeScript, MySQL, MongoDB, DynamoDB, HTML5, CSS Frameworks/Libraries: Pytorch, Tensorflow, Keras, Pandas, Numpy, SciPy, Scikit-Learn, Matplotlib, Seaborn, OpenCV, NLTK, AWS, Lambda Stack, ECS, S3, GraphQL, Git, Docker, Kubernetes, Redis, Apache Spark, Agile, Azure, OpenCV.js Area of Interest: Data Science, Full-Stack Developer, Machine Learning, Deep Learning, Federated Learning, Artificial Intelligence, NLP, Computer Vision, Data Analytics, Data Analysis, Data Warehouse, Data Visualization PROFESSIONAL EXPERIENCE

Software Engineer Intern VirtuSense Technologies, United States Jun 2024 - Sep 2024

● Developing ProactiveStrides, an AI-enhanced mobile app for fall risk assessment using OpenCV.js with the MoveNet model for precise pose detection and React for frontend implementation, enhancing real-time mobility tracking for personalized patient care.

● Implementing secure, cloud-based access and comprehensive compliance practices, significantly improving documentation and patient data protection.

Student Software Developer SAP, United States Jan 2024 - May 2024

● Secured 2nd Place at UCI ICS Expo with SAP TradeGuard, a project enhancing fraud detection in trade promotions through advanced machine learning models, reducing detection time from a week to minutes.

● Developed TradeGuard’s core features: automated deal sheet verification, TensorFlow-based image manipulation detection, duplicate image identification using Redis, AI-generated image detection, and geolocation verification to ensure image-store congruence. Engineered both frontend and backend systems, enhancing the user interface. Application Developer Oracle, India Jun 2022 - Sep 2023

● Played a pivotal role in the development of Causal Analyzer, an innovative root cause localization tool tailored for cloud-native applications that expedite service recovery and remediation, effectively tackling critical challenges in microservices ecosystems. Employed the Knowledge-Graph service, a powerful data graph representation, to streamline the processing and analysis of existing application data, resulting in an impressive accuracy rate of 95%. Additionally, integrated graph neural networks and federated learning techniques to enhance predictive capabilities and optimize performance.

● Developed and fine-tuned Spring Boot-based REST APIs, achieving outstanding response times and reliability while collaborating with the CPQ team. Pioneered the integration of industry-leading security best practices, ensuring robust protection against potential threats.

● Proficiently crafted Swagger documentation to improve accessibility and understanding of each API feature. Executed thorough testing with JUnit, achieving 100% test coverage, to validate functionality for the developed APIs.

● Led and directed UI and REST automation initiatives within the team, primarily utilizing JavaScript and Selenium. Application Development Intern Oracle, India May 2021 - Jul 2021

● Developed and maintained APIs for the Titan project, delivering comprehensive statistics and insights. Orchestrated the collection of statistics by integrating with the Argo workflow, which posted data to a Redis stream.

● Implemented a robust data pipeline to persist this information into a Redis datastore for efficient storage and retrieval. Created the Stats API to seamlessly retrieve and present these vital statistics to end-users. Research Intern IIT Hyderabad, India Mar 2020 - May 2020

● Designed a project focused on driver attentiveness using advanced deep-learning techniques. Engineered a multi-faceted system encompassing Emotion recognition, Heart-attack detection, and Closed-eye prediction to ensure that the driver is alert while driving, achieving an accuracy of 97%.

PROJECTS

CancerCare AI HackTogether 2024, Microsoft Github

● Led the development of the Cancer Care Solution utilizing Microsoft Fabric tools such as Synapse Data Science, Data Warehouse, and Power BI, achieving an accuracy of 96%. Implemented an Azure OpenAI chatbot to enhance patient interaction.

● Enhanced dataset diversity and quality by applying data augmentation techniques, including CTGAN, to enrich the dataset. Managed database infrastructure utilizing Fabric’s Lakehouse architecture to ensure efficient data storage and retrieval within the Cancer Care Solution ecosystem.

Vehicle Re-identification Using Convolutional Neural Networks, Publication - ICADCML 2023 GitHub

● Developed a convolutional neural network (CNN) model integrated with vision-based techniques to accurately identify vehicles across multiple cameras without relying on number plates, achieving a noteworthy accuracy rate of 90%. Cloud-Based Event & Sentiment Detection of Geo-Tagged Twitter Data GitHub

● Implemented a project featuring a cloud-based system that extracts top local events and the sentiment of the crowd involved in the event with an accuracy of 97.5%.

● Architected a user-centric cloud-based system, prioritizing a seamless and intuitive end-user experience.

Contact this candidate