Summary
Overview
Work History
Education
Skills
Certification
StyleLens - Fashion Finder (AI/ML Capstone Project)
Facial Analysis- Group Emotions (DL Project)
Understanding Networks through Clustering (ML Project)
Timeline
Generic

Mounika Kakanuru

McKinney,TX

Summary

  • AI/ML Engineer with experience in designing, developing, and deploying machine learning and deep learning models. Using Python libraries like TensorFlow, PyTorch, and MLOps.
  • Java Developer with in-depth experience across the Software Development Life Cycle (SDLC), including user interaction, business analysis, development, implementation, integration, and testing, utilizing Java/J2EE technologies in cloud environments.
  • AI/ML Expertise: Experience with deep learning models such as VGG16, YOLOv8, and Vision Transformers in projects like StyleLens - Fashion Finder (an AI-based fashion retrieval system) and Emotion Recognition (using facial expression analysis with YOLO and Deepface).
  • Enterprise Application Development: Skilled in designing RESTful APIs with OpenAPI 3.0, using Spring REST API, and integrating API testing tools like Postman.
  • Microservices and Distributed Systems: Proficient in building and deploying microservices-based applications using Spring technologies and cloud platforms like AWS and Pivotal Cloud Foundry.
  • Message Queue & Streaming: Experienced in producing and consuming Kafka messages with Avro schema, ensuring seamless communication in distributed systems.
  • CI/CD & DevOps: Adept at setting up continuous integration and deployment pipelines using Jenkins, and leveraging containerization with Docker and Kubernetes.
  • Cloud & Infrastructure: Proficient with AWS services (EC2, S3, IAM, Lambda), and deploying applications in cloud environments.
  • Data Science & Machine Learning: Applied machine learning techniques in fashion image retrieval systems and facial emotion detection models, incorporating algorithms for image similarity search, triplet loss, and performance metrics (Precision, Recall, mAP, and NDCG).
  • Automation and Testing: Expertise in test automation for APIs using Cucumber and Karate frameworks, along with comprehensive unit testing using JUnit and Mockito in CI pipelines.
  • Database & SQL: Strong knowledge of databases like Oracle, MySQL, and proficient in database programming using JDBC and SQL.
  • Agile Development: Experienced in Agile software development, with a focus on Scrum methodologies.
  • Cloud-native Development: Knowledge in using various cloud services, such as AWS EC2, S3, and IAM, for deploying and managing applications.
  • Strong Team Player: Adept at collaborating with cross-functional teams, with strong communication, and presentation skills.

Overview

5
5
years of professional experience
1
1
Certification

Work History

Technology Lead

Infosys Ltd.
Richardson, TX
04.2024 - Current
  • Led cross-functional teams to successfully deliver complex technology projects within agreed timeframes and budgets.
  • Collaborated with stakeholders to define technical requirements, ensuring alignment with business objectives.
  • Increased team productivity through effective collaboration, clear communication, and regular progress updates.
  • Designed documentation protocols and standard operating practices to unify technology management efforts across company.
  • Consulted with managers to determine and refine machine learning objectives.
  • Worked with large-scale datasets and feature engineering.
  • Designed machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
  • Developed ML algorithms to analyze huge volumes of historical data to make predictions.
  • Utilized data modeling and evaluation strategies to find patterns and predict unseen instances.
  • Optimized existing AI models for improved efficiency and accuracy, utilizing advanced optimization methods.
  • Implemented MLOps pipelines using AWS SageMaker and Kubeflow.

Technology Lead

DTCC
Coppell, TX
10.2022 - 03.2024
  • Participated in requirement gathering, planning, and design sessions through Agile methodology using Jira Agile Development Software.
  • Developed Camel routes using YAML DSL, and defined steps that are applied to a message as it travels from source to destination.
  • Developed multiple types of (source, sink, or action) Camel Components/Kamelets that can be used in any Camel routes by passing their required parameters.
  • Developed multiple source components to connect and get data using different databases (Snowflake, DB2, Oracle, SQL Server) or the HOPEX API.
  • Developed multiple types of Velocity templates to generate complex SQL queries for different data transformations (Type 1/Type 2).
  • Implemented the Velocity template in Kamelets to generate and execute the generated queries.
  • Designed and mapped the JSON configuration for data transformations.
  • Used Maven for the build framework, and Bitbucket for the continuous build system.
  • Used Jenkins for the CI/CD process.
  • Environment: Apache Camel, Java 8/J2EE, Spring Framework, Snowflake, DB2, Oracle SQL/PLSQL, Velocity template, AWS Cloud, IntelliJ IDEA, JSON, YAML, Jenkins, and Maven.

Technology Lead

DTCC
Coppell, TX
11.2021 - 10.2022
  • Participated in requirement gathering, planning, and design sessions through Agile methodology using Jira Agile Development Software.
  • Developed RESTful web services using Spring Boot and Java.
  • Used the OpenAPI specification to document the APIs and registered the APIs in the API gateway.
  • Used the AWS SDK to access AWS services.
  • Developed DB repositories using Spring and AWS SDK to access DynamoDB.
  • Used AWS SQS to publish and listen to the messages from SQS, and integrated with Spring message listeners.
  • Used AWS S3 to store business-required documents in its buckets.
  • Used AWS CloudWatch to monitor the application health and performance, and used CloudWatch logs to search the events with its log groups and log insights.
  • Used Kafka as a message broker to produce and consume messages from a Kafka topic.
  • Developed JPA entities to map with relational DB tables, and used them with Spring Data repositories to access the data.
  • Developed functional tests using Cucumber and integrated them into the CI/CD pipeline.
  • I used Postman to test the APIs.
  • Used JUnit and Mockito to write unit tests.
  • Used Maven for the build framework, and Bitbucket for the continuous build system.
  • Used Jenkins for the CI/CD process.
  • Environment: Java 8/J2EE, Spring Framework, DynamoDB, AWS RDS, AWS Cloud, AWS SQS, Kafka, IntelliJ IDEA, JSON, YAML, Jenkins, and Maven.

Java Developer - II

SEIC
Oaks, PA
07.2020 - 11.2021
  • Participated in requirement gathering, planning, and design sessions through Agile methodology using Jira Agile Development Software.
  • Developed RESTful web services using the Spring REST API and applied traceable logs to the APIs using log4j-over-slf4j.
  • Designing RESTful APIs using the OpenAPI Specification.
  • Created microservices using the Spring Boot framework.
  • Used Java 8 streams and lambda expressions.
  • Deployed Spring Boot-based microservices within Pivotal Cloud with a CI/CD pipeline.
  • Implemented the unit tests using JUnit and Mockito frameworks, and integrated them into the Jenkins pipeline.
  • Developed functional tests using Postman and integrated them into the CI/CD pipeline.
  • Consumed REST services into the application using Spring Rest Template.
  • Integrated Spring (Dependency Injection) among different layers of an application.
  • Developed a web layer using the Spring framework and managed the project in the MVC pattern.
  • Functional testing of the REST API using the Postman tool.
  • Developed a Kafka producer/consumer using the Spring Boot framework.
  • Developed REST payloads using Jackson annotations.
  • Used Swagger API for API documentation.
  • Used Spring Actuator to identify the health of services.
  • Used Maven for the build framework, and Bitbucket for the continuous build system.
  • Used Jenkins for the CI/CD process.
  • Environment: Java 8/J2EE, Core Java - multithreading, Spring Framework (Spring Integration, Spring MVC, Spring IOC, Spring Boot, Cloud, Spring Batch, Spring Data), Jenkins, Oracle SQL/PLSQL, Pivotal Cloud Foundry, Kafka, RESTful web services using microservices architecture, Docker, Agile, IntelliJ IDEA, JSON, XML.

Full Stack Developer Sr

USAA
Plano, TX
11.2019 - 07.2020
  • Participated in requirement gathering, planning, and design sessions through Agile methodology using Jira Agile Development Software.
  • Developed a RESTful web service using the Spring REST API, and applied traceable logs to the APIs using log4j-over-slf4j.
  • Created microservices using Spring Boot and its annotations.
  • Used Java 8 streams and lambda expressions.
  • Deployed Spring Boot-based microservices in Docker-based OpenShift containers.
  • Implemented the unit tests using JUnit and Mockito frameworks, and integrated them into the GitLab pipeline.
  • Developed functional tests using Postman and integrated them into the CI/CD pipeline.
  • Consumed external web services into the application using the Spring API.
  • Consumed REST services into the application using Spring Rest Template
  • Integrated Spring (Dependency Injection) among different layers of an application
  • Developed web layer using Springs framework and to manage the project in MVC pattern
  • Functional testing the REST API using Postman tool
  • Developed Rest Payloads using Jackson annotations
  • Used Swagger API for API documentation
  • Used Spring Actuator to identify the health of services
  • Used Gradle for build framework and GitLab for continuous build system
  • Used GitLab for Version Control
  • Environment: Java 8/J2EE, Core Java- multithreading, Spring Framework (Spring Integration, Spring MVC, Spring IOC, Spring Boot, Cloud, Spring Batch, Spring Data), GitLab, Oracle SQL/PLSQL, Kafka, RESTful Web services using Micro services architecture, Docker, Agile, IntelliJ IDEA, JSON, XML

Full Stack Developer Sr

USAA
Plano, TX
11.2019 - 07.2020
  • Participated in requirement gathering, planning, and design sessions through Agile methodology using Jira Agile Development Software.
  • Worked closely with the Business/Users team in translating technical requirements into application code.
  • Developed a RESTful web service using the Spring REST API, and applied traceable logs to the APIs using log4j-over-slf4j.
  • Created microservices using Spring Boot and its annotations.
  • Created a multi-layer architecture for an API functionality flow, like controllers and services.
  • Used Java 8 streams and lambda expressions.
  • Deployed the application in Docker-based OpenShift containers.
  • Building CI/CD pipelines suitable for GitLab to deploy the apps into OpenShift containers.
  • Setting up and configuring the CIT box servers required for the deployment of the applications.
  • Develop APIs to emit events to Kafka topics using the Kafka API with Avro schema.
  • Develop consumers to consume events from Kafka topics, and create BPM processes and tasks.
  • I worked on the BPM Admin tool to configure the attribute mapping required for BPM processes and tasks.
  • Implemented the unit tests using JUnit and Mockito frameworks, and integrated them into the Jenkins pipeline.
  • Developed functional tests using Postman and integrated them into the CI/CD pipeline.
  • Consumed external web services into the application using the Spring API.
  • Consumed REST services into the application using Spring Rest Template
  • Integrated Spring (Dependency Injection) among different layers of an application
  • Developed a web layer using the Spring framework and managed the project in the MVC pattern.
  • Functional testing of the REST API using the Postman tool.
  • Developed REST payloads using Jackson annotations.
  • Used Swagger API for API documentation
  • Used Spring Actuator to identify the health of services
  • Used Gradle for the build framework and GitLab for the continuous build system.
  • Used GitLab for version control.
  • Used Slog4j for logging error/debug messages to send the logs to Kibana/Splunk.
  • Used Kibana to debug the issues with application logs.
  • Create queries to filter the logs, and configure email alerts for the critical issues.
  • Environment: Java 8, Spring, Spring MVC, IntelliJ, JBoss 7, Spring REST API, Spring Boot, Kafka, Avro, BPM Admin tool, Postman, Kibana, JUnit, Mockito, Gradle, GitLab, and JIRA.

Education

Master of Computer Application - Computer Applications Development

Osmania University
Hyderabad, India
01-2009

Bachelor of Computer Application - Computer Applications Development

Vaagdhevi Degree College
Proddatur, India
08-2003

Skills

  • Java
  • Agile methodology
  • RESTful web services
  • Microservices architecture
  • API documentation
  • Continuous integration
  • Unit testing
  • Team collaboration
  • Problem solving
  • Effective communication
  • Technical leadership
  • API development
  • Machine learning
  • Application support
  • Python
  • Spring Boot
  • Apache Camel
  • JPA
  • AWS
  • Pivotal Cloud Foundry
  • Oracle
  • MySQL
  • Snowflake
  • MongoDB
  • Kafka
  • REST
  • OpenAPI 30
  • Jenkins
  • Docker
  • Maven
  • Bitbucket
  • Git
  • JUnit
  • Mockito
  • Cucumber
  • Postman
  • IntelliJ IDEA
  • Eclipse
  • Gradle
  • Kibana
  • Splunk
  • TensorFlow
  • PyTorch
  • ML/DL deployment
  • Fine-tuning LLMs
  • Semantic Search

Certification

  • AWS Certified Cloud Practitioner
  • Kafka Certification (Udemy)
  • Oracle Certified Associate – Java 7
  • AI/ML and MLOps Courses: Introduction to Artificial Intelligence, OpenAI GPT Models, Generative AI, Deep Learning for Developers, PyTorch for AI, Fine-Tuning Large Language Models, Prompt Engineering, AI First in Cybersecurity, Responsible AI by Design

StyleLens - Fashion Finder (AI/ML Capstone Project)

  • Developed a deep learning-powered fashion image retrieval system to help users find visually similar fashion items by uploading an image.
  • Deep Learning Model: Extracts feature embeddings from fashion images using pre-trained models like VGG16.
  • FAISS: Utilizes FAISS for fast nearest neighbor search to find similar items.
  • Web Application: Built with Streamlit for user interaction and deployed on AWS EC2 for scalability with GPU support for fast inference.
  • Data Acquisition & Preprocessing: Used the DeepFashion dataset and applied normalization, data augmentation, and preprocessing for model training.
  • Model Training: Employed triplet loss or contrastive loss to optimize image embeddings, ensuring accurate retrieval results.
  • Image Retrieval: Retrieves the most similar fashion images based on cosine similarity or Euclidean distance.
  • Evaluation Metrics: Evaluated the system's performance using precision at K, mean average precision (mAP), recall at K, and retrieval speed/latency

Facial Analysis- Group Emotions (DL Project)

  • Understanding Group Emotions through Individual Facial Analysis,
  • Built a facial emotion detection system using YOLOv8 and Deepface to recognize individual and group emotions in images.
  • YOLOv8 for Object Detection: Used for detecting facial features and analyzing emotional states such as happiness, sadness, anger, and surprise.
  • Deepface for Facial Attribute Analysis: Used Deepface to analyze facial expressions, age, gender, and emotional states in real-time.
  • Model Training: Labeled facial images using tools like Roboflow, then trained a YOLOv8 model to detect emotional states based on annotated data.
  • Evaluation: Generated visual outputs like confusion matrices, precision-recall curves, and F1 score curves for performance evaluation.
  • Inference: Analyzed facial images for emotion detection, providing a percentage breakdown of emotional states.

Understanding Networks through Clustering (ML Project)

  • Conducted in-depth analysis of Facebook's anonymized social network data, focusing on community detection, social circles, and ego networks.
  • Applied graph machine learning techniques for community detection using algorithms like Girvan-Newman and Node2Vec.
  • Explored the '6 degrees of separation' experiment by calculating the shortest path between random nodes in the Facebook dataset.
  • Conducted a social circle analysis, visualizing ego networks, and clustering nodes based on node embeddings from Node2Vec.
  • Implemented the Girvan-Newman algorithm and ratio cut methods to detect communities and assessed their overlap with predefined social circles.
  • Used machine learning for clustering (K-means) and prediction tasks based on the node embeddings.

Timeline

Technology Lead

Infosys Ltd.
04.2024 - Current

Technology Lead

DTCC
10.2022 - 03.2024

Technology Lead

DTCC
11.2021 - 10.2022

Java Developer - II

SEIC
07.2020 - 11.2021

Full Stack Developer Sr

USAA
11.2019 - 07.2020

Full Stack Developer Sr

USAA
11.2019 - 07.2020

Master of Computer Application - Computer Applications Development

Osmania University

Bachelor of Computer Application - Computer Applications Development

Vaagdhevi Degree College
Mounika Kakanuru