Junior Software Developer
Pacsquare Technologies
Total years of experience :2 years, 2 Months
Fintech, Trading Application, FIX Communication, QuickFix Implementation
Specialized in ASP.NET Web API development, I've mastered the art of creating dynamic web applications using React and Angular. Excited to apply my expertise in backend development to contribute to innovative projects.
As part of my job responsibilities, I work closely with developers and quality assurance (QA) personnel to resolve any production issues that may arise. This involves identifying and diagnosing issues that are impacting the performance or functionality of our systems, and working collaboratively with the relevant teams to implement fixes and ensure that the issues are fully resolved.
In addition to this, I also present weekly reports on production issues to the Vice President or Head of Information Technology. These reports provide updates on any ongoing issues, as well as any new issues that have arisen since the previous report. By providing regular updates on production issues, I help to ensure that senior management are fully informed about the performance of our systems and any issues that may be impacting the business.
Apart from these responsibilities, I am also responsible for performing daily tasks such as managing membership details. This includes tasks like updating membership details such as upgrade, downgrade, and renewal of memberships, sending medical devices and medical kit shipments and enrolling groups. These tasks require me to work closely with other departments such as customer service and finance, to ensure that all membership-related tasks are completed accurately and in a timely manner.
Overall, my job involves working collaboratively with other teams to resolve production issues, providing regular updates on these issues to senior management, and performing daily tasks related to managing membership details. This helps to ensure that our systems are operating smoothly, and that our customers have a seamless experience when managing their memberships.
As part of my job responsibilities, I worked on annotating meter images using a tool called Label Studio. This involves manually marking specific areas of the images that correspond to the meter reading, so that the algorithm can learn to detect them accurately.
Next, I learned the Python library NetworkX to perform network analysis.
After this, I am trained the YOLOv3 algorithm to detect the meter reading based on the annotated images. YOLOv3 is a deep learning algorithm that can be trained to detect objects within an image, and I am using it to accurately identify the meter readings within the annotated images.
Finally, I applied Tesseract and EasyOCR to extract information from the regions that have been detected by YOLOv3. Tesseract is an optical character recognition (OCR) engine that can recognize text within an image, while EasyOCR is a Python library that provides a simple interface for performing OCR tasks. By applying these tools, I can extract the meter readings from the images and use them for further analysis.
Overall, my job involves using a combination of annotation tools, network analysis, machine learning algorithms, and OCR engines to accurately detect and extract meter readings from images.
I worked on a project that involved developing a human behavior detection system using a combination of Convolutional Neural Network (CNN) and mmWave Radar sensor technology.
The goal of the project was to accurately detect human activities such as walking, sitting, and falling, which could be useful in a variety of applications such as security and healthcare. To achieve this, we used CNN to process data from the mmWave Radar sensor and analyze patterns in the signals generated by human activities.
I played a key role in the project, working on the feature extraction, development and training of the CNN model and analyzing the results to improve accuracy. It was an exciting and challenging project that allowed me to further develop my skills in machine learning.
Initially worked on an object detection model, where machine learning architecture of YOLOv3 and the Darknet framework were utilized for detecting objects from highway videos. Here, my work resulted in improving the object accuracy of the model. Also, I performed segmentation annotation on an image data using the CVAT tool.
My internship also included covering the theory of a significant amount of image processing operations. Using these, I also implemented a traffic sign identification routine using Python and OpenCV using the type of arrows found in those.
I also Learned Pytorch and OpenCV during my internship.
Arabic Language, Quranic Translation, Fiqh, Usool Ul Fiqh, Usool Ul Hadith, Usool Ul Tafseer, Hadith 6 books, Fiqh&Hadith, Seerah
During the early years of my graduation, I focused on web development and became proficient in PHP core and MERN. I enjoyed the challenge of developing web applications and was recognized for my skills when my class teacher requested that I teach Bootstrap to my peers. However, my curiosity led me to explore other fields, particularly Artificial Intelligence (AI) and Machine Learning (ML). I was drawn to the potential of these technologies to automate and optimize various processes, and I pursued these topics further in my studies. For my Final Year Project (FYP), I applied deep learning techniques to develop a model capable of detecting weeds among soybean crops. This project involved working with a dataset of over 15,000 images, and I utilized Flask and Android app development to create a functional end-to-end solution. Through my experiences in web development and AI/ML, I have gained a diverse set of skills and have been able to apply them in various contexts.