Advancing Data Science and Analytics in Business and Finance

The ICESCO Chair of Data Science and Analytics for Business, a collaboration between ICESCO and NUST, is dedicated to advancing data science in business and finance amidst the digital era's data surge.

Director of ICESCO Chair of Data Science and Analytics for Business

Prof Dr. Muhammad Moazam Fraz

Professor and Head of Department of AI and DS at School of Electrical Engineering and Computer Science, NUST.

Our Team

Dr. Fahad Ahmed Satti

Dr. Fahad Ahmed Satti

Assistant Professor, School of Electrical Engineering
and Computer Science, NUST
Saad Khan Al-Marwat Picture

Mr. Saad Al-Marwat

Business Expert
Head of Department of Finance
at National Business School, NUST
Dr. Nabeel Anwar

Dr. Nabeel Anwar

Focal Person
Head of Research at the School of
Mechanical & Manufacturing Engineering, NUST

Multidisciplinary Approach

To facilitate a comprehensive approach to data science and analytics education, the ICESCO Chair of Data Science and Analytics for Business will be co-hosted by two prominent NUST entities: the School of Electrical Engineering & Computer Science (SEECS) and the NUST Business School (NBS). This collaboration underscores the interdisciplinary nature of data science, where expertise from computer science and business converge to drive innovation and value creation.

Supported Projects

Initiative Academic Programs

What We Do
ICESCO and NUST's partnership aims to merge academic research with business and finance applications. By focusing on data science research and workforce development, this collaboration supports industries' growing reliance on data strategies, empowering organizations for strategic decision-making and optimal operations.

Research and

Initiate data science research to tackle local business challenges. By taking these solutions to market, we aim to drive technology-based resolutions, create new jobs, and generate novel business opportunities.

Foster Collaborative

Encourage synergies between academic, governmental, and industrial sectors. Such collaboration enriches applied research, bolsters industry, and informs policy-making.

Workforce Development in
AI & Data Science

Concentrate on training professionals in AI and Data Science, specifically tailored to business and finance. This not only fulfills local industry demands but also amplifies remittance inflow.

Resource Mobilization for
Data Science

Leverage both public and private resources to advance the research and application in the Data Science field, ensuring all stakeholders benefit.

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