Reza is an expert in Artificial Intelligence (AI) and Machine Learning (ML) with a research focus on AI in Education and AI for Health. He is currently a Lecturer (Education) in Data Analytics and Machine Learning at the School of Electronics, Electrical Engineering and Computer Science (EEECS) at Queen's University Belfast, UK.

A Fellow of the Higher Education Academy (FHEA), Reza holds a PhD in Machine Learning from Newcastle University, UK. He also earned an MSc in Artificial Intelligence and Robotics from the Iran University of Science and Technology (IUST) and a BEng (Hons.) in Computer Engineering from Iran Azad University.

With extensive experience in both academia and the software industry, Reza has significantly contributed to various biomarker and subgroup discovery projects as well as numerous machine learning initiatives. His notable projects include:

• Contributed to establishing a novel assay and developed a molecular classification method based on a minimal DNA methylation signature suitable for routine diagnostic purposes, published in Nature Scientific Reports: View Publication
• Conducted biostatistical analysis of an infant Medulloblastoma cohort focusing on high-risk factors, published in Neuropathology and Applied Neurobiology: View Publication.
• Developed a NanoString classifier based on RNA-Seq data in collaboration with Institut Curie in Paris.
• Established an analysis pipeline for Whole Genome/Exome Sequencing (WGES) data of diagnostic and relapsed Medulloblastoma using the Genome Analysis Toolkit (GATK).
• Integrated high-dimensional biological cohorts using tensor decomposition techniques.
• Developed a web-based immune-based classification software for solid tumors.

Previous Positions and Education

• May 2019 – Present: Lecturer (Education) in Data Analytics and Machine Learning at EEECS, Queen's University Belfast, UK.
• June 2017 – April 2019: Postdoctoral Research Fellow at the Stratified Medicine Group (SMG), Centre for Cancer Research and Cell Biology, Queen's University Belfast, UK.
• January 2014 – May 2017: Postdoctoral Research Associate at the Northern Institute for Cancer Research, Newcastle University, UK.
• August 2013 – December 2013: Software Developer at Prophet Technology Ltd, Gateshead, UK.
• April 2009 – July 2013: PhD in Machine Learning (Image Processing/Computer Vision) at Newcastle University, UK.
• September 2006 – January 2009: Founder/CEO and Software Team Leader at Modern Enterprise Technology Corporation (METech), Iran.
• September 2001 – April 2009: Academic Lecturer at Iran Azad University, Iran.
• September 1998 – January 2001: MSc in Artificial Intelligence and Robotics at Iran University of Science and Technology, Iran.

For a comprehensive list of Reza's publications, please refer to his full publication page. His project content and code repositories are available on his GitHub profile

1. Application of AI and machine learning in education for improving student learning experience  
2. Leveraging cutting-edge AI techniques and synthetic biology to identify and design tumour-specific enhancer networks, aiming to transform cancer diagnostics and therapeutics. By uncovering and engineering DNA sequences that regulate gene expression, we aim to develop precise therapeutic approaches that target tumour cells while minimizing impact on healthy tissues.
3. High-throughput genomic analysis, integrating complex and multi-scale biological datasets
4. Developing AI-based methods and applying them to clinically annotated omics data accross multiple cancer subtypes
5. Developing commercial and clinically applicable AI-based software 
6. All statistical pattern recognition techniques, but not limited to, unsupervised, semi-supervised and supervised learning
7. High-dimensional data processing and mining in Illumina 450K/EPIC DNA Methylation and RNA-Seq (NGS data)
8. Mass-Spec DNA methylation and NanoString mRNA gene expression processing
9. Developing bioinformatics tools, pipelines and software for the analysis of genetic and epigenetic features of cancer-associated diseases in large cohorts 

MSc/PhD Supervision

I am seeking new talented MSc/PhD students with strong background in mathematics, machine learning and software development to join an existing research/development project. Please send your CV and a statement of research interests to my email.  

Data Analysis and Visualisation (CSC3062)

AI for Health (ECS8055)

Machine Learning (DSA8021)

Principles and Practices of Machine Learning (CSC7073)