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About Me:
I’m a software developer based in the UK, currently crafting resilient backend systems at Barclays. With a strong foundation in computer science and a CGPA of 9.04 from MIT Manipal, I bring a mix of academic rigor and hands-on experience across enterprise and research projects.
I’ve built scalable Spring Boot APIs, deployed applications on Kubernetes and OpenShift, and orchestrated microservices using Camunda. My work spans from financial systems to machine learning research, and I’ve even led award-winning hackathon solutions in hardware-software integration.
- Skilled in Java, Python, Kafka, CI/CD, and Cloud-native development
- Experienced with tools like Jenkins, Helm, Docker, and RabbitMQ
- Passionate about problem-solving, automation, and building meaningful tech
Let’s build something great together.
Technical Skills:
Languages:
JavaPythonC++
PHPJavaScriptSQL
Shell Scripting
Frameworks & Libraries:
Spring BootCamundaLaravel
YOLOv5/YOLOv8ResNetOpenCV
Databases:
MySQLSnowflakeNoSQL
Cloud & DevOps:
AWSKubernetesOpenShift
DockerJenkinsHelm
Messaging & Integration:
KafkaRabbitMQIBM MQ
TCP Sockets
Tools & Methodologies:
GitLinuxAgile
MicroservicesOrchestration
Work Experience:
Developer | Barclays, Glasgow, UK
Aug 2023 – Present
- Built and integrated high-performance Spring Boot APIs for scalable backend systems
- Automated deployments using Jenkins and custom shell scripts on Kubernetes/OpenShift
- Led microservices orchestration using Camunda for streamlined workflows
- Designed messaging solutions using TCP sockets, IBM MQ, and RabbitMQ for financial systems
- Developed Python-based tools for automation and end-to-end system testing
Developer | Intecons Software Lab, Rajasthan, India
Dec 2022 – Aug 2023
- Led development of LeadPropeller, integrating U.S. government property data into Snowflake
- Created and optimized complex SQL queries for ETL pipelines
- Built and maintained full-stack applications using PHP and Laravel
- Integrated third-party APIs and developed internal CMS/CRM systems
President & Developer | Apple Developers' Group @ MIT, Manipal
Sep 2021 – Jul 2022
- Built an LoR automation system streamlining alumni requests and approvals
- Developed a centralized Placement Portal to manage job listings and student applications
- Provided technical mentorship to junior developers within the web subsystem
Research:
Plant Disease Detection using YOLOv8
Developed a deep learning-based diagnosis system for eggplant diseases using YOLOv8 for detection and ResNet-32 for classification.
PythonYOLOv8ResNet
View Details
Eggo – Counterfeit Egg Detection App
Built an Android app to detect discolored spots on eggs using YOLOv5. Achieved 94% accuracy and integrated the app with a PHP backend API.
AndroidPythonYOLOv5PHP
View Details
Colorium – Microfluidic Teaching Aid\
Created an Android app using OpenCV to detect color intensity on a thread-based microfluidic device for educational purposes.
AndroidJavaOpenCV
View Details
Education:
B.Tech in Information Technology
Manipal Institute of Technology, Manipal, Karnataka
Jul 2019 – Jun 2023
- CGPA: 9.04/10
- Strong foundation in Data Structures, Algorithms, and OOP
- Specialized in Machine Learning, Big Data, and Graph Analytics
- Hands-on with Distributed Systems, Databases, and Cloud Tech
High School
St. Anselm’s Pink City School, Jaipur, Rajasthan
Jun 2017 – May 2019
- Overall Percentage: 92%
- Best 4 Subjects (PCM + IP): 96%
- Core Subjects: Physics, Chemistry, Mathematics, Information Practices (Java)
Contact Information:
Email: ayushgoyalpro@gmail.com
Phone: +44 7407831142
LinkedIn: linkedin.com/in/devayushgoyal
GitHub: github.com/ayushgoyalpro
Feel free to reach out for collaboration opportunities or just to chat about technology!
Project: Plant Disease Detection using YOLOv8
Description:
A deep learning-based diagnosis system for eggplant leaf spot and fruit rot diseases using YOLOv8 for detection and ResNet-32 for classification. The model was deployed using cloud infrastructure for efficient processing and published in a reputable scientific journal.
Key Features:
- Used YOLOv8x for precise leaf detection
- Applied ResNet-32 for disease classification
- Integrated cloud-based tools for efficient computation
- Contributed findings to an international research journal
Technologies:
PythonYOLOv8ResNetMachine Learning
Research Paper: Read Paper
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Project: Eggo – Counterfeit Egg Detection App
Description:
An Android application designed to detect counterfeit country eggs by identifying discoloration using a mobile camera. It uses YOLOv5 for real-time object detection and integrates with a PHP backend API.
Key Features:
- Real-time detection using YOLOv5
- Achieved 94% accuracy in classification
- Backend integration using PHP API
- Mobile-friendly interface for on-the-go verification
Technologies:
AndroidYOLOv5PythonPHP
Research Paper: Read Paper
Back to Projects
Project: Colorium – Microfluidic Teaching Aid
Description:
A frugal innovation Android app using OpenCV to analyze color intensity from a thread-based microfluidic device. Developed to aid in visualizing cell disruption during biology education.
Key Features:
- Color detection for red, green, and blue intensities
- Built using OpenCV with a tailored algorithm
- Aimed at enhancing teaching tools in biology labs
- Works with smartphone cameras for accessibility
Technologies:
AndroidJavaOpenCV
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