Muhammad Abdul Basit Dalian University of Technology, China
As an accomplished Algorithm Engineer, he has embarked on a dynamic career in the ever-evolving realm of Artificial Intelligence. With a focus on image processing, stereo vision, and satellite imagery, he has showcased his expertise in cutting-edge technologies such as YOLO, Unet, ResNet, VGG, and RasterVision. His professional journey has been marked by significant contributions to groundbreaking research and development projects, resulting in numerous impactful publications that have greatly benefited both clients and employers. His academic background, complemented by bachelor’s and master’s programs, laid a robust foundation in speech signal processing, automatic speaker verification, anti-spoofing, and voice biometrics. This educational background has proven instrumental in supporting his achievements in AI, particularly in specialized areas such as audio and image processing, and satellite imagery analytics.
🎓Education:
He pursued his academic journey with a Master’s in Computer Science at Dalian University of Technology in Dalian, China, from 2019 to 2022. Prior to this, he completed his Bachelor’s in Computer Science at COMSATS University in Islamabad, Pakistan, spanning the years 2015 to 2019. His educational foundation includes Higher Secondary School Certificate (HSSC) in Engineering, attained at Fazaia Degree College in Kamra, Pakistan, from 2013 to 2015. Before entering higher education, he accomplished his Secondary School Certificate (SSC) or Matriculation at Fazaia Degree School in Kamra, Pakistan, from 2011 to 2013. These academic endeavors reflect his dedication to computer science and engineering, spanning various institutions and regions.
🌐 Profile Links:
Experience:
He worked as an Algorithm Engineer with a specialized focus on audio processing and image processing, contributing his expertise to cutting-edge projects. His primary concentration was on image processing, involving tasks such as image segmentation, object detection, and recognition using satellite imagery. In this capacity, he developed and implemented algorithms for image segmentation, utilizing popular techniques such as YOLO, RasterVision, UNet, ResNet, and VGG. Additionally, he proficiently leveraged deep learning frameworks, including TensorFlow, to train and deploy neural network models for image analysis and computer vision tasks. To optimize the performance of deep learning algorithms, he utilized CUDA technology for accelerated computations on GPUs, showcasing his commitment to achieving high efficiency in his work.
Publications:
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SDI: A tool for speech differentiation in user identification Published By : 2022
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MA-CNN: Multi-augmented data classification using 2D-CNN with kaiming initialization for environmental sound classification Published By : 2022
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A New Fractional-Order Stability Analysis of Sir Model for the Transmission of Buruli Disease : A Biomedical Application Cited By : 5, Published By : 2022
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Investigation of single bubble behavior under rolling motions using multiphase MPS method on GPU Cited By : 3, Published By : 2021
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4E (energy, exergy, economic and environmental) analysis of the novel design of wet cooling tower Cited By : 3, Published By : 2020
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Numerical study of laminar flow and friction characteristics in narrow channels under rolling conditions using MPS method Cited By : 6, Published By : 2019
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Numerical study of bubble rising in quiescent liquid under rolling motion conditions using MPS – MAFL method Cited By : 5, Published By : 2019
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A three-dimensional CFD and experimental study to optimize naturally air-cooled electronic equipment enclosure: Effects of inlet height, heat source position, and buoyancy on mean rise in temperature Cited By : 4, Published By : 2018