role: Students
Xuyu Li
PhD Researcher
Xuyu is a second-year PhD student in the School of Computer Science and Statistics at Trinity College Dublin, where he is supervised by Dr. John Dingliana. His research primarily focuses on Extended Reality (XR) combined with Artificial Intelligence (AI) technologies.
Before joining the CRT-AI program, Xuyu earned a Master’s degree with Distinction from the City University of Hong Kong, where his research concentrated in the field of computer graphics. Outside of his academic work, Xuyu enjoys playing new video games and exploring their designs. He also enjoys spending time playing basketball and watching movies.
Supervisor: Dr. John Dingliana
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Daniel Sami Mitwalli
PhD Researcher
Daniel Sami Mitwalli is currently pursuing a Ph.D. at the University of Limerick, entering his first year of doctoral studies. Before this, he earned his degree in Applied Computer Science from the Technical University of Dortmund in Germany. His academic focus revolves around artificial intelligence and low-code, with a particular emphasis on graphical domain-specific languages and metamodeling.
Supervisor: Professor Tiziana Margaria
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Rahul Ponnusamy
PhD Researcher
Rahul Ponnusamy is a Ph.D. scholar in the Data Science Institute, School of Computer Science, at the University of Galway, starting in October 2023, under the supervision of Dr. Bharathi Raja Chakravarthi and the co-supervision of Prof. Paul Buitelaar. His doctoral research is funded by the SFI Centre for Research Training in Artificial Intelligence (CRT-AI). Rahul completed his Bachelor of Computer Application (B.C.A.) at Guru Nanak College (University of Madras), Chennai, Tamil Nadu, India in 2020. He graduated with an M.Sc. in computer science, specialization in Machine Intelligence, at the Indian Institute of Information Technology and Management Kerala, India in 2022. He has seven months of experience in working as a Data Scientist at Techvantage Analytics, Kerala, India. He worked on a project called CDocz, an intelligent document processing. He joined Insight as Research Assistant in the Fidelity project, titled “Exploring Techniques to Detect and Mitigate Non-Inclusive Language Bias in Marketing Communications using a Dictionary-Based Approach” and “Few Shot Learning for Detecting Inclusive Languages comments”, with the Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics, University of Galway, during the period from February 2023 to September 2023. Natural language processing, deep learning, text categorization, code-mix, under-resourced language, bias, cross-cultural, multimodal, large language models (LLMs), and other related topics are the main focus of his research. Prior to beginning his Ph.D., he worked on research projects that included the identification of homophobia and transphobia, offensive language, emotion, hope speech, non-inclusive language, and abusive language.
Supervisors: Dr. Bharathi Raja Chakravarthi and Prof. Paul Buitelaar
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Prasanna Kumar Kumaresan
PhD Researcher
supervision of Dr. Bharathi Raja Chakravarthi and the co-supervision of Prof. Paul Buitelaar. His doctoral research is funded by the SFI Centre for Research Training in Artificial Intelligence (CRT-AI) and the College of Science and Engineering at the University of Galway, Ireland. He holds a Bachelor’s degree in Computer Application (BCA) from Guru Nanak College, Tamil Nadu, India, and a Master’s degree in Computer Science with a specialization in Machine Intelligence from the Indian Institute of Information Technology and Management-Kerala (IIITMK), India. His research interests primarily revolve around natural language processing, including text classification using machine learning, deep learning, and Large Language Models (LLMs). He is particularly focused on addressing hate speech against LGBTQ+ in social media comments, especially for under-resourced languages. Before starting his Ph.D., he was involved as a Research Assistant in the Fidelity project with the Unit for Linguistic Data at the Insight SFI Research
Centre for Data Analytics, University of Galway, during the period from February 2023 to September 2023.
PUBLICATIONS
Homophobia and transphobia detection for low-resourced languages in social media comments
Kumaresan, P.K., Ponnusamy, R., Priyadharshini, R., Buitelaar, P. and
Chakravarthi, B.R., 2023. Homophobia and transphobia detection for
low-resourced languages in social media comments. Natural Language
Processing Journal, 5, p.100041.
Dataset for Identification of Homophobia and Transphobia for Telugu, Kannada, and Gujarati.
Prasanna Kumar Kumaresan, Rahul Ponnusamy, Dhruv Sharma, Paul Buitelaar,
and Bharathi Raja Chakravarthi. 2024. Dataset for Identification of Homophobia
and Transphobia for Telugu, Kannada, and Gujarati. In Proceedings of the 2024
Joint International Conference on Computational Linguistics, Language
Resources and Evaluation (LREC-COLING 2024), pages 4404–4411, Torino,
Italia. ELRA and ICCL.
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Dost Muhammad
PhD Researcher
Meet Mr. Dost Muhammad, a dynamic professional at the forefront of technological innovation, driven by a robust academic background and an unyielding passion for pushing the boundaries of technology. Armed with a BS (Hons) in Computer Science and a Master’s Degree in Artificial Intelligence, Mr. Muhammad is currently pursuing a Ph.D at the School of Computer Science, University of Galway, Ireland. His doctoral research delves into the intriguing realm of “Evaluating Explainable AI for Medical Image Processing: How Can the Interpretability Be Enhanced?” under the supervision of Dr. Malika Bendechache.
With a notable track record, Mr. Muhammad brings nearly seven years of valuable experience as a Lecturer in Computer Science, having contributed significantly to both government and semi-government universities. During this time, he supervised and mentored 27 undergraduate students, guiding them through the intricate landscape of Artificial Intelligence and fostering innovation in their final-year projects. Mr. Muhammad actively engaged in the organization of research conferences and symposiums, fostering a collaborative environment for both faculty and students.
Mr. Muhammad’s research interests are deeply rooted in Explainable Artificial Intelligence, coupled with the implementation of Machine Learning (ML) and Deep Learning (DL) techniques in interdisciplinary areas such as Health, Finance, Environment, and Disaster Management. His commitment to advancing knowledge is evident through various impact-factor publications in reputed journals, including a noteworthy book chapter.
Supervisor: Dr. Malika Bendechache
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Khanh-Tung Tran
PhD Researcher
Khanh-Tung Tran holds a B.S. degree in Computer Science from Ho Chi Minh University of Technology, Vietnam. With a background in academia and industry, he has enriched his skills and knowledge through research roles at WARA Media and Language (Sweden) and FPT Software (Vietnam). He has been working on large-scale research projects, under the guidance of Assoc. Prof. Johanna Björklund, Asst. Prof. Harry Nguyen, Dr. Xuan-Son Vu, and Dr. Duy Khuong Nguyen. His research interests include sound signal processing, spatio-temporal models, and multimodal machine learning.
Supervisor: Dr. Harry Nguyen
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Dung Minh Dao
PhD Researcher
Dung, also known as Robert is a first year PhD, working with Dr. Harry Nguyen (UCC).Dung holds a BSc in Computer Science from Hanoi University of Science and Technology, Vietnam. He also worked at AI Centre at FPT Software for two years.
His research work title Medical Training Analytics Framework with Enhanced Feedback using Reliable AI methods.
In his spare time, Dung enjoys reading, going to the gym and hanging out with his friends.
Teona Banu
PhD Researcher
Teona Banu is a first-year PhD student in Computer Science at Trinity College Dublin, supervised by Dr Carl Vogel. She completed her Master’s Degree in Data Science at TCD in 2023. Her research interests are Computational Linguistics, Cognitive Science, and Artificial Intelligence. She is currently researching the measurement of engagement in dialogues through the analysis of linguistic features and speakers’ personality traits.
She holds a Double Bachelor’s degree in Econometrics and Economics. During her undergraduate studies, she focused on operations research and policy evaluation. She studied the phenomenon of courier drainage in the meal delivery routing problem and the effects of wage transparency policies on the gender wage gap.
Supervisor: Professor Carl Vogel
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Thomas Keogh
PhD Researcher
Thomas Keogh is a first-year PhD researcher in the School of Computing at Dublin City University (DCU), where he is supervised by Prof. Mark Roantree. His research is the field of machine learning and deep learning as applied to medical data. He’s currently collaborating with the School of Chemical Sciences and is researching deep learning-based spectroscopic analysis of exosomes, using Surface Enhanced Raman Spectroscopy (SERS), for the purposes of disease diagnosis and staging.
Thomas holds a BSc (Hons) in Applied Physics from DCU and an MSc in Medical Physics from the National University of Ireland, Galway (NUIG). His MSc thesis focused on a form of internal radiotherapy known as brachytherapy and was titled “Statistical analysis of doses to target and Organs at Risk (OAR) during Low Dose Rate (LDR) permanent prostate treatment for monotherapy patient cohort”. In 2020 he was selected by the European Society for Radiation Oncology (ESTRO) to present a poster version of his MSc thesis at the 2021 World Congress of Brachytherapy. Following graduation from his MSc programme with first-class honours in December 2020, he commenced work as a Medical Physicist in Diagnostic Radiology and Nuclear Medicine at Tallaght University Hospital, where he worked for 2 years before commencing his PhD research.
Supervisor: Professor Mark Roantree
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Fiona Murphy
PhD Researcher
Fiona Murphy is a first-year PhD student at Trinity College Dublin, where she is supervised by Dr. Alessio Benavoli. Her research involves developing novel algorithms for multiple time-series extrinsic regression, with applications across various types of large-scale systems that utilize time-series data.
She received her B.S. in Computer Science and Applied Mathematics at Stony Brook University, where she completed an Honors thesis using online convex optimization and model predictive control to explore solutions to oversupply on the power grid. Additionally, she has previous research experience in large-scale data analysis and online program anomaly detection via machine learning.
Supervisor: Dr. Alessio Benavoli
Joseph Chai
PhD Researcher
I am a first-year PhD student in the SFI Centre for Research Training in Artificial Intelligence in University College Cork. I obtained my bachelor’s degree in computer science in University of Glasgow and worked as a research assistant in National University of Singapore prior to joining the CRT-AI funded PhD programme. My supervisor is Dr Harry Nguyen and my current research topic is Geographical Mapping and Sustainable Impact Assessment AI. In my spare time, I enjoy doing martial arts.
Supervisors: Dr. Harry Nguyen & Professor Barry O’Sullivan
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Oleksii Dovhaniuk
I am a Ukrainian citizen residing in Western Ukraine’s Chernivtsi city. I completed my education as a Computer Engineer at Yuriy Fedkovich Chernivtsi National University, where I also received a master’s degree in Engineering with a focus on IoT Technologies and Cyber-physical Systems. I spent a semester studying in Germany as an exchange student, and during my master’s degree, I studied in Austria. In between my studies, I participated in the Work and Travel program in the United States. Overall, my academic pursuits have been diverse, spanning multiple countries and areas of study, providing me with a well-rounded education and valuable life experiences.
Since my bachelor’s study, I have engaged in various scientific endeavors focused on advanced computing, such as attending the ECODAM and IEEE International Conference on Electronics and Information Technologies. In addition to this, I worked in an IT company as a 3D artist, creating visualizations for mobile video games. My varied interests have helped me acquire the ability to work in different roles effectively. During my research, I designed a genetic algorithm for producing reversible circuits, which are more energy-efficient and less prone to faults than traditional circuitry.
Presently, I am collaborating with Professor Sabin Tabirca to create a medical resource scheduling application specifically for operating theatres in surgical procedures. By merging my expertise in evolutionary computing for optimal solutions and deep learning prediction models, we are developing an automated and efficient scheduler suitable for implementation in hospitals. In my leisure time, I have a keen interest in learning Japanese and playing the piano. I enjoy listening to new audiobooks focused on self-help or science fiction, and I have a passion for movies with profound meaning.
Supervisors: Professor Sabin Tabirca & Professor Mark Corrigan (CoMH UCC)
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