Curriculum Vitae
Download a copy of my CV here
Education
PhD in Computer Science and Electronics Engineering,
Queen Marry University of London, United Kingdom
PhD Research Topic: AI-Based Cardiac Image Computing
Master of Science in Electronics and Information Engineering,
Jeonbuk National University, Jeonju, Republic of Korea
Master Research Topic: Applications of Computer Vision to Healthcare and Precision Agriculture
Bachelor of Science in Electrical and Electronics Engineering,
Bahria University Islamabad, Pakistan
Bachelor Research Topic: Deep learning-based Segmentation of Retinal Layers from OCT images
Magna Cum Laude Award For Outstanding Academic Achievements
Research Assistant
McDonald Institute for Archaeological Research, University of Cambridge, United Kingdom
I worked on facial emotion recognition in visual arts. The project’s goals include: Gathering a small training dataset of sculptures to analyze their emotions, using the existing facial emotion algorithms to assess the emotional potency of art, and coming up with unique ideas to improve the accuracy of multi-label classification problems.
Graduate Student Researcher
Core Research Institute of Intelligent Robots, Jeonbuk National University, Republic of Korea
I worked on different projects related to medical image processing and intelligent farming using state-of-the-art computer vision algorithms to solve the problems like classification, object detection, depth estimation, and segmentation for precision agriculture and healthcare. The goal of my research is to design efficient deep learning modules for real-time applications by reducing the parameterized complexity and inference time of the algorithms.
Internee
National Institue of Electronics
I worked on the project “Distance estimation between human and camera”. In the first part, a human was detected in live video and then found his distance from the camera using stereo vision techniques.
Publications
Sequential Segmentation of the Left Atrium and Atrial Scars Using a Multi-scale Weight Sharing Network and Boundary-based Processing Permalink
PMED-Net: Pyramid Based Multi-Scale Encoder-Decoder Network for Medical Image Segmentation Permalink
Khan. A,H. Kim and L. Chua. "PMED-Net: Pyramid Based Multi-Scale Encoder-Decoder Network for Medical Image Segmentation." IEEE Access , 2021(9). doi:10.1109/ACCESS.2021.3071754
DAM: Hierarchical Adaptive Feature Selection Using Convolution Encoder Decoder Network for Strawberry Segmentation Permalink
Ilyas, T.;. Khan. A, ; Umraiz, M.; H. Kim,, (2020). "DAM: Hierarchical Adaptive Feature Selection Using Convolution Encoder Decoder Network for Strawberry Segmentation ." Frontiers in Plant Science, 121(11). doi:10.3389/fpls.2021.591333
CED-Net: Crops and Weeds Segmentation for Smart Farming Using a Small Cascaded Encoder-Decoder Architecture Permalink
Khan. A,Ilyas, T.,Umraiz M., Manan Z., Kim H., "CED-Net: Crops and Weeds Segmentation for Smart Farming Using a Small Cascaded Encoder-Decoder Architecture." MDPI Electronics, , 2020(9). doi:10.3390/electronics9101602
SEEK: A Framework of Superpixel Learning with CNN Features for Unsupervised Segmentation Permalink
Ilyas, T.;. Khan. A, ; Umraiz, M.; H. Kim,, (2020). "SEEK: A Framework of Superpixel Learning with CNN Features for Unsupervised Segmentation." Physical Review NOT Letters, 121(11). doi:10.3390/electronics9030383
Skills
- Programming: MATLAB, Python (NumPy, SciPy, Matplotlib, Pandas, OpenCV, Tensorflow, Keras, PyTorch), C++, C, FPGA.
- Electronics: Arduino, Raspberry Pi, Analog & Digital Electronics.