Dr. Hassan Aqeel Khan is a Senior Lecturer in Applied AI and Robotics at Aston University Birmingham UK. His primary area of research is applications of Machine Learning and AI in Medical Imaging and Biomedical signal analysis. Hassan is currently leading a £200,000/-, EPSRC funded, grant related to the development of Explainable AI (XAI) solutions for neurological data using large language models (LLMs). Throughout his career, he has been involved in grants worth over £320,000/- as PI or CoI. His research projects have been funded by the EPSRC, German Academic Exchange Service (DAAD), Nokia Research Centre China, Deanship of Scientific Research at the University of Jeddah Saudi Arabia, and Higher Education Commission (HEC) Pakistan. Hassan’s recent research focuses on novel data annotation strategies for efficient labelling of large volumes of training data for computational pathology and neurology data. Hassan has a PhD in Electrical Engineering (2015) from Michigan State University, an MSc (with Distinction) in Signal Processing and Communication (2007) from the University of Edinburgh and BSc in Electrical Engineering (2003) from UET Taxila Pakistan.

Prof. Dr. Faisal Shafait has 15+ years of research and teaching experience in Artificial Intelligence and Machine Learning. He completed his PhD in Computer Engineering from TU Kaiserslautern, Germany in 2008 with the highest distinction. Currently, he is working as a Professor at NUST School of Electrical Engineering and Computer Science (SEECS) as well as Director of the Deep Learning Laboratory at National Center of Artificial Intelligence (NCAI), Islamabad. Dr. Faisal has made a significant international reputation in the field of Artificial Intelligence by earning more than 14,500 citations. He is the only Pakistani and Muslim scientist to receive the prestigious IAPR/ICDAR Young Investigator Award by the International Association of Pattern Recognition and is included in the list of the World’s Top 2% Scientists compiled by Stanford University. He was conferred the Pride of Performance award by the President of Pakistan in March 2024.

Dr. Moazzam Faraz is a Computing and AI leader at NUST credited with building high-impact programs and partnerships across academia and industry. With 20+ years of combined experience, he previously engineered enterprise software at Elixir Technologies (2003–2010), earned a PhD from Kingston University London, completed postdoctoral work at the University of Warwick, and joined NUST in 2014. He has served as Head of Software Engineering, founding Head of AI & Data Science, and acting Associate Dean, helping propel NUST’s Computer Science to QS #143 globally. His research applies computer vision, AI, and data science to national challenges in agriculture, healthcare, and urban sustainability, spanning precision agriculture, remote sensing, medical imaging, and visual surveillance. He has secured 20+ grants, authored two books, holds 10+ patents, launched two AI ventures, and supervised numerous MS/PhD theses. Honors include the Turing Institute’s Rutherford Fellowship, British Council UK Alumni Award, President’s and Rector’s Gold Medals; he is an IEEE Senior Member, SFHEA, ICESCO Chair of Data Science & Analytics, and listed among Stanford’s Top 2% Scientists.

Dr. Attya Bhatti is a tenured Professor at NUST’s Atta-ur-Rahman School of Applied Biosciences (ASAB), with a PhD in Human Molecular Genetics from Quaid-i-Azam University. Her research spans disease genomics and computational/experimental therapeutics—covering rheumatoid arthritis, type-2 diabetes, Alzheimer’s disease, and nanomedicine—and she has been recognized with awards including the PCST Productive Scientist Research Award. She has an extensive publication record across leading journals and books.

Dr Nosheen Abid is a Postdoctoral Researcher in the Department of Computer Science and Media Technology at Malmö University in Sweden. Her current research centres on the project “Human-robot collaborative learning for ultralight electric utility vehicles”, which integrates end-to-end imitation learning and interactive machine learning to advance autonomous, human-collaborative transport systems. She completed her PhD at Luleå University of Technology, where she developed an innovative Unsupervised Curriculum Learning (UCL) framework applied to Earth-observation imagery. Since 2016, her work has spanned multiple international AI domains including remote sensing, document & image understanding, and medical image analysis, blending academic research with real-world applications. With a multidisciplinary background across AI sub-fields, Dr Abid brings unique expertise at the intersection of deep learning, computer vision, and human-robot interaction.