Ahbaz Memon

I increased resource utilization by 25%, reduced project timelines by 30%, and automated the hiring process, resulting in significant cost savings and improved efficiency for Applus+ IDIADA.

Developed a Django based dynamic website with AI/ML prediction models, real-time data analytics, and visualization tools for Applus+ IDIADA, reducing manual effort by 40-50% and providing valuable skills for future endeavors.

As a part-time tutor at Diamond Home Tuitions, taught 11th and 12th-grade maths and physics, with a focus on the ICSE board curriculum, developing lesson plans and assessing student progress, helping students achieve their academic goals.

Journal Paper at Inderscience Publishers (IEL) in the International Journal of Computational Intelligence Studies · Oct 1, 2021, https://www.inderscienceonline.com/doi/abs/10.1504/IJCISTUDIES.2022.126906

Springer · Sep 1, 2022, https://link.springer.com/chapter/10.1007/978-981-19-5224-1_59

2022 IEEE Students Conference on Engineering and Systems (SCES) · Jul 7, 2022, https://ieeexplore.ieee.org/abstract/document/9887751/

Book Chapter in Technoarete Publishing · Dec 31, 2022, https://dx.doi.org/10.36647/MLAIDA/2022.12.B1.Ch006

IEEE Xplore 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS) · Dec 3, 2020, https://ieeexplore.ieee.org/abstract/document/9315862/

Patent 202121025562 · Issued Jun 12, 2021

Patent 202021009028 · Issued Mar 3, 2020

Led successful project to improve resource management efficiency by designing and implementing a web-based Resource Management Portal tool, built using various software tools and technologies including Django, resulting in a 25% increase in project efficiency.

Developed an AI module analyzing handwriting through Deep Learning, Computer Vision, NLP, and Psychology, including a personalized database, emotion recognition, and understanding of scribbled words, built with Python, NVIDIA, OpenCV, NLP, TensorFlow, and Neural Networks.

Developed AI system for hand gesture interpretation in defense sector, achieving high accuracy and published results in International Journal.

As Lead Data Scientist, I led a team in automating recruitment processes and designing 4 algorithms to rate a candidate's profile. We reduced the hiring time from weeks to 30 minutes and saved companies resources, achieving a more accurate assessment of candidate suitability.

Developed website with AI/ML prediction models, analytics built using Django and Python; automated report generation reducing manual effort by 40-50%; deployed to IDIADA Network.

In reality, Both licit and illicit, drug addiction is a complex disease, and quitting takes more than good intentions or a strong will. Rapid assessment surveys have facilitated the understanding of Changing patterns of use. Preliminary neurobiological research has focused on identifying individuals at high risk for alcohol dependence.

In recent decades, face recognition hypotheses and algorithms have gotten a lot of coverage. Unmanned and autonomous aircraft, video monitoring, suspect identification, building access control, and unmanned and autonomous vehicles are only a handful of the tangible developments gaining traction across sectors. Second, we'll go into the fundamentals of facial recognition and how to do it. Face image description using only a few face image features or the whole facial features is being established using local, holistic, and hybrid approaches.

🐄 A dairy farm management system (DFMS) is a vital tool for dairy farms to manage their operations effectively. One of the most critical aspects of a DFMS is a 🥛 Milk Production and Quality Monitoring System, which helps farmers monitor milk quality and quantity in real-time. This system can assist in reducing milk wastage and optimizing milk production. In this project, we propose the development of a comprehensive DFMS that includes a Milk Production and Quality Monitoring System, along with other features such as 🐮 animal health monitoring and 🌾 feed management. The system leverages IoT technologies to collect data on milk quality, quantity, and animal health, which can be used to make data-driven decisions. We also discuss the challenges associated with implementing such a system and provide recommendations for successful adoption.