A graduate with an eclectic set of educational and employment experience. Originally studied Mechanical Engineering (with sustainability) for my bachelors. Followed by a MSc in an Applied Maths & Physics, and diploma data analysis & science.
Coupled with my graduate employment experience initially in the IT sector, follow by Biomed & Energy sector has given me interest in research in applying data science to real world problems. My extra-curricular interesting in regenerative medicine inspired me in this case, to my current Ph.D. -applying machine learning to tissue engineering.

Supervisors: Dr. Tanya Levingstone & Dr. Malika Bendechache

Dermot Sheridan is a second-year PhD student in the School of Computing , Dublin City University , where he is supervised by Prof. Mark Roantree l His research is in the field of application of machine learning for athlete monitoring and performance prediction in team sports which is a subfield of Artificial Intelligence that is concerned with tools and techniques to help investigate sports performance. Dermot holds an MSc. of Science, where his thesis was focused on Fatigue and Recovery in Gaelic Football. Prior to joining the CRT-AI funded PhD programme, Dermot worked as a sport scientist and performance coach with elite Gaelic football in Ireland. In his spare time Dermot enjoys being active and hanging out with friends.

Supervisor: Prof. Mark Roantree

I am Ph.D student at DCU Centre for Medical Engineering Research at School of Mechanical and Manufacturing Engineering DCU, where I am supervised by Dr. Tanya Levingstone, Dr. Suzanne Little and Prof. Nicholas Dunne. My research falls in the field of tissue engineering, which refers to the practice of combining scaffolds, cells, and biologically active molecules into functional tissues.

During my PhD I aim to develop a novel Artificial Intelligence algorithm to optimise printing parameters for different bioinks.

I hold a Bachelor’s in Engineering, I joined Future Neuro Center at RCSI Dublin as a Visiting Scientist, where I analysed EEG data and built an interface for signal processing and data visualization.
Before joining the CRT-AI funded PhD program, I worked as a research assistant in the same group at RCSI, where we developed a machine learning algorithm for the detection of spontaneous seizures in EEG in multiple experimental mouse models of epilepsy.

Supervisors: Dr. Tanya Levingstone, Dr. Suzanne Little and Prof. Nicholas Dunne.

Eric’s main interests include data, technology, science overall and machine learning, mainly in the model explanation. He has several years’ experience working with data engineering, processing and analysis, and leading a data and development team. Eric’s PhD research focuses on the explainable aspect of deep learning techniques applied to image classification to support experts verifying machine-made decisions where ML or DL techniques are utilised and where catching potential false positives is essential. Eric held the MSc in Information Systems from the Federal University of Rio de Janeiro – Brazil. The research developed a framework to identify bot messages characteristics on Twitter and explains the concepts humanly to ordinary users. The paper from this research was published at the FATES workshop in 2019, and other publications will be released. Before developing his interests in data science, he entered many side-tracks on his professional development path, which touched upon web technologies, software development and business intelligence.

Supervisors: Dr. Alessandra Mileo

My name is An, I am from Vietnam. My previous major was Mathematics, specialising in Analysis. At the moment, I am a first year PhD student at School of Computing, DCU. Regarding my research interests, I would like to apply Machine Learning, Deep Learning and also Mathematical aspects such as Statistics to the financial field. For instance, using Deep Learning to predict stock prices and forecast the crisis in the financial market. When I have free time, I like to relax by cooking or simply reading my favourite books.

Supervisors: Dr. Martin Crane