Data Mining
Extracting structure and meaning from large, noisy, and heterogeneous datasets — the throughline of my work since 2012.
I have worked in data mining and machine learning since 2012, spanning business data analysis, social network analysis, and large-scale biological data mining. My interest lies in applying information technology across disciplines — biology, business, and social networks — to address the problems those fields actually face.

Research focus
Data Mining · Machine Learning · Data Analytics
About
Data mining, machine learning, and applied data analytics.
My research sits at the intersection of data mining, machine learning, and the disciplines that generate data faster than they can interpret it. Since 2012 I have built and applied analytical methods to business data, social network data, and large-scale biological datasets, with a consistent focus on results that hold up outside the lab.
Alongside academic work I have spent time in industry, developing gaming software at a commercial software firm. That experience shapes how I teach and supervise: computing is most valuable when it is grounded in a real problem, built to run, and explained clearly to the people who depend on it.
I welcome collaboration with researchers and organisations working on interdisciplinary data problems, and I supervise students interested in applied machine learning and data-driven research.
I like to connect and apply information technology to other disciplines — biology, business, and social networks — to address and support the demands they actually have.
Dr. Sarwar Kamal
Associate Professor, East West University
Research
The methods and application domains I work in, and the kinds of problems I supervise students on.
Extracting structure and meaning from large, noisy, and heterogeneous datasets — the throughline of my work since 2012.
Designing and evaluating learning methods that generalise beyond the dataset they were trained on.
Turning operational and commercial data into decisions, with attention to what an organisation can actually act on.
Studying structure, influence, and information flow across social networks at scale.
Applying computational methods to large biological datasets, where volume and complexity outpace manual analysis.
Connecting information technology to biology, business, and the social sciences to support the demands of each field.
Contact
For research collaboration, supervision enquiries, speaking invitations, or consultancy, please get in touch.