Abdul Wahid

SFI Confirm Centre for Smart Manufacturing fully funded PhD Scholarship.

Full merit CBNU Scholarship.

GPA: 4/4

As a postdoctoral researcher, I am involved in developing ontologies and knowledge graphs using large language models (LLMs) to enhance virtual worlds. My work extends to investigating the legal, ethical, and governance models essential for the sustainable and responsible development of these virtual environments.

I overlook the development and co-creation of the Advanced Computer Aided Phytotherapy (aCAP) system, which represents a significant leap in applying AI to identify and develop plant-based therapeutics for the animal industry.

• Reinforced student learning of skills and materials through daily and weekly check-ins, informal assessments, and observations
• Monitor students for carrying out experiments and address the problems they face
• Created individual homework assignments for students based on their progress in specific sections
• Engage in critical reflection on practice as a basis for improving student knowledge
• Assisting the professor in marking the assignments and scheduling the exams
• Provided timely and frequent feedback to students, fostering an environment of open communication and interest in discovery.

• Build hybrid deep learning models for predictive maintenance in smart manufacturing.
• Investigated different state-of-the-art algorithms for estimating the remaining useful life of complex cyber-physical systems.
• Collaborated with industry for real-time data collection and analysis.
• Explored transformer networks for estimating the remaining usefulness of complex cyber-physical systems.
• Published my work in various international workshops, conferences, and journals in AI.

• Advocating for the interests and needs of PhD students
• Represent the concerns, opinions, and ideas of my fellow PhD students to the faculty, administration, and other relevant parties
• Responsible for planning and organizing academic, social, or professional events and activities for PhD students
• Offering, guidance, advice and support to other PhD students experiencing academic or personal difficulties
• Engaging in meetings and committees where decisions affecting PhD students are made
• Effectively communicating and disseminating important information to PhD students promptly and appropriately
• Encourage collaboration among PhD students, both within and across departments, and help to build a sense of community among them.

• I was a part of the cloud core network (CNN) team where my focus was on Digital Twin technology
• My research focused on modelling digital twin technology for cloud networks
• Investigated the strategies to overcome the limitations of current modelling languages
• AI-based code generation engines for modelling DT technology for telecommunication networks
• Produced thorough research reports on a range of digital twin technologies, assessing suitability for telecommunication networks.

• Developed a semantic segmentation model using Deep learning for an autonomous vehicle
• Analyzed data to spot patterns, trends and outliers and formulated solid conclusions
• Semantic labelling and instance segmentation using weakly supervised convolutional neural network
• Estimating the mass of the Pig from its 2D image using deep convolutional neural networks
• Image Denoising Method Based on Directional Total Variation Filtering
• Disease Detection in hyperspectral images of apples using Deep convolution Neural Network
• Deep learning-based simple end-to-end architecture capable of extracting contextual information from the images
• Pedestrian recognition and detection using transfer learning
• Korean celebrity face recognition system-based YOLO.

• Supported research projects, aiding academic progression and growth in line with demands
• Taught courses like:
• Digital Signal Processing
• Image Processing and Computer Vision
• Visual basics (VB.NET)

• I was a part of the Media Communication and Signal Processing Lab
• Modelled a system for Mobile Indoor localization using Kalman Filter and trilateration Technique
• Proposed an RSSI-based indoor localization model based on Adaptive Neural Fuzzy Inference System
• Designed a system for the simultaneous detection and segmentation of humans based on the mean Shift
• Algorithm (MSA)
• Interpreted data to offer potential explanations for trends, patterns and causal links
• Followed established methodologies and reporting processes in line with the scientific method.

• Remote server maintenance and real-time service
• Traffic monitoring for various base stations and voltage control
• Handshaking protocols and telecommunications control maintenance.