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 NUI 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 NUI Galway as a Senior Postdoc, Adjunct Lecturer, and Project Manager of the H2020 project ‘ROCSAFE’. He also worked as a Postdoc at INSIGHT Research Centre in NUI Galway and Research Engineer in Prosa Srl Italy. His research interests are mainly in computer vision and designing lightweight deep neural network architectures with the pyramidal approach. More specifically, he worked on recognition & segmentation problems in health, autonomous vehicles, & other application areas as well as understanding the deep AI models with explainable AI techniques. I am also interested to work on differential privacy and synthetic data generation. Specific research interests in semantic segmentation of aerial images, Aortic segmentation, medical report generation, object/pedestrian detection, multi-object tracking, fish species (Salmon) recognition/tracking/detection, explainable AI, federated learning, synthetic data generation, and signal processing (EEG, ECG, etc.).

I am a tenured Lecturer (Assistant Professor) in the School of Computer Science at NUI Galway. Previously, I held appointments as:

• Postdoctoral Researcher in the CIREGS lab at Cardiff University, UK, working with Dr. Meysam Qadrdan. This work was funded by the EPSRC.
• Postdoctoral Fellow at the Georgia Institute of Technology, USA within the ACES Research Group, directed by Prof. Santiago Grijalva, in collaboration with Sandia National Laboratories. My work was funded by Sandia National Laboratories and the National Science Foundation.

Before this, I completed my PhD in Computer Science at the National University of Ireland, Galway. My PhD research primarily consisted of developing methods to evolve neural networks and to apply these algorithms within the energy sector for tasks such as: wind generation forecasting, electricity generation dispatch, etc. This PhD dissertation was nominated for the 2018 European AI PhD Dissertation award.

My research broadly falls under the heading of machine learning, but explores multiple topics including: neural networks, evolutionary computing, reinforcement learning, multi-agent systems and swarm intelligence. I’m also interested in applications of machine learning methods to problems including: renewable energy, smart homes, infrastructure planning, smart grid, robotics and cloud computing.

I am currently a Lecturer in the National University of Ireland Galway and am responsible for the delivery of five modules each year which are attended by 400+ students, with subjects ranging from Software Engineering, to Web Programming and Reinforcement Learning. I have extensive experience in Machine Learning extending from my Masters right through to my PhD. Upon graduation in 2006, from a BSc in Computer Science, I was invited to join a research team as a research assistant for one year, researching business process analytics solutions. In 2009, I completed a MSc (research) where my thesis contribution was the research and development of machine learning techniques to accurately classify cardiac arrhythmias from 3 lead ECG communicated over a Zigbee wireless sensor network. In 2013, I received my Ph.D. in Computer Science from NUI Galway. My PhD research investigated the application of a subset of machine learning techniques known as reinforcement learning to automate resource allocations and scale applications in infrastructure as a service cloud computing environments. Upon completion of my PhD, I joined Schneider Electric as a research engineer on a globally distributed innovation team. In industry, I worked on projects which included data analytics, linked data (designing enterprise level data integration solutions, ontology design and mapping) and training machine learning classifiers for acoustic event classification (specifically detecting household alarm sounds in the presence of noise). Since returning to academia in 2015, I have authored or co-authored over 50 research articles, I hold 4 patents and have won a number of competitive funding awards. I am actively pursuing research in machine learning, cloud and distributed computing problems, cybersecurity and computer vision.