Muhammad Bin Islam
Senior Technical Leader Healthcare Technology Solutions Cloud Architecture Team Leadership at Confidential
Punjab, Pakistan
Summary
👤
Senior🎓
Top SchoolMuhammad Bin Islam is a senior technical leader and Java solutions architect with 9 years of experience building high-throughput, cloud-native systems for financial services and healthcare. He has led teams of up to 14 engineers to deliver HIPAA-compliant platforms and billion-scale architectures using Spring Boot microservices, PostgreSQL, Kafka/RabbitMQ, and AWS/Azure serverless patterns. His background spans real-time trading systems, market-data pipelines, and secure enterprise integrations including Hyperledger Fabric for private-market workflows. He combines hands-on optimization (1000+ daily transaction services, real-time media streaming with Kurento/Ffmpeg) with full DevOps automation and GitOps practices to achieve repeatable 100% deployment automation. Known for translating pre-sales requirements into practical solution architectures, he balances technical depth with team building and mentoring. Based in Punjab, Pakistan, he pairs an MPhil in Computer Science with a history of freelancing and event leadership, reflecting both entrepreneurial initiative and broad operational experience.
9 years of coding experience
6 years of employment as a software developer
Mphil, Computer Science, Mphil, Computer Science at University of the PunjabBachelor's degree, Computer Science, 3.05, Bachelor's degree, Computer Science, 3.05 at University of Engineering and Technology, Taxila
Stackoverflow
11reputation
453reached
2answers
1question
Github Skills (74)
opencv10
windows10
linux10
audio10
openframeworks10
computer-vision10
emscripten10
opengl10
android10
html9
python9
google-cloud9
cpp9
bootstrap9
ios9
Programming languages (6)
Github contributions (5)
SomiaImdad/Plant-Disease-Diagnostics-using-UAV-and-Android-APP
Sep 2018 - Aug 2019
Plant diseases causes many significant damages and losses in crops around the world. Some suitable measures on disease identification should be introduced to prevent damages and minimize losses. Early Detection of Disease helps in increasing the crop productivity as well as in minimizing expense. Technical approaches using machine learning and computer vision are actively researched to achieve intelligence farming by early detection on plant disease. The accuracy of object detection and recognition systems has been drastically improved by the recent development in Deep Neural Networks. By using these systems and implementation of computer vision and machine learning techniques, plant diseases can be detected. Here we have used transfer learning based approach to diagnose diseases of different plants using its images captured by camera devices either drone or smartphone. Our goal is to build a market oriented product for Plant Disease Detection, a smartphone app compatible with both smartphone camera and drone camera. The target group of the user is those who request a quick diagnosis on common leaf disease at any time of the day i.e. Farmers, agricultural industries, agricultural consultants and Government Agencies & Departments.
Contributions:6 commits, 6 pushes, 1 comment in 11 months
computer-visiondeep-neural-networksmachine-learningobject-detectiontransfer-learning
UsamaIslam/UsamaIslam
Dec 2022 - Sep 2023
Contributions:4 pushes, 1 branch in 8 months
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