Dr. Ihsan Ullah did his Ph.D. in the University of Milan, specializing in designing lightweight deep neural network architectures with the pyramidal approach. He has more than nine years of research and development experience in applying Deep Learning to a variety of images, video, text, and time-series recognition problems while working with renowned labs in the US (Computational Vision and Geometry Lab at Stanford University), Europe (at CVPR Lab at the University of Naples Parthenope, Italy), and the Middle East (Visual Computing Lab in King Saud University, Saudi Arabia). Before joining the School of Computer Science in the University of Galway he was a Senior Research Data Scientist in CeADAR Ireland’s Centre for Applied AI in University College Dublin where he was the head of the Special Projects group and was actively involved in applying for various national and international fundings e.g., Horizon Europe, SFI, EI. Prior to that, he worked in Data Mining and Machine Learning Group of School of Computer Science in as the University of Galway a Senior Postdoc, Adjunct Lecturer, and Project Manager of the H2020 project ‘ROCSAFE’. He also worked as a Postdoc at INSIGHT Research Centre in the University of Galway and Research Engineer in Prosa Srl Italy. Currently, his main areas of research interest are in designing lightweight deep learning models in computer vision and Pattern Recognition, explainable AI, federated learning, and differential privacy. He was an invited member of the National Standards Authority of Ireland prestigious ‘Top Team” on setting the national Standards in AI, and he is a steering committee member of Oblivious.ai.
Research Focus and Applications
- Lecturer Above the Bar in Computer Science at the University of Galway
- Teaching Research in AI and Case Studies in Data Analytics to MSc Data Analytics and Artificial Intelligence
- Led Special Projects Group in CeADAR Irelands Centre for Applied AI @ UCD
- A machine learning researcher with extensive experience in applying Machine Learning sub-branch i.e. Deep Learning techniques to variety of image, video, text and time-series recognition problems.
- More than nine years of research and development experience in implementing and designing classification and regression models.
- Worked with renowned labs in US, Europe, and Middle East.
- Research interests: development & use of light weight neural networks for computer vision, text, and signal processing problems
- Managed H2020, SFI, and EI projects.
- Research contributions in Neural Networks (Pyramidal Neural Networks), Computer Vision (recognition of action, object, emotion, and dynamic scene, semantic segmentation, Synthetic data generation, etc.), Explainable AI (explaining deep learning models for images and tabular data) and Federated Learning
- Excellent publications in prominent research conferences & journals on cutting edge problems (30+ publications, 670 citations, H-Index: 11)
- Industry collaborations with Oblivious, UltanTechnologies, Unitek, Mortice, HealthyPlaceToWork, NVD, xWave, Pearson Milking technology, EnergyPro, Valeo, and IBM