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Afshin Ashofteh is an invited Professor Auxiliar at the NOVA Information Management School (Nova University of Lisbon), a research fellow of the department of Methodology and Information Systems at the Statistics Portugal (INE), an integrated researcher of the Information Management Research and Development Center (MagIC), and a member of two Technical Advisory Groups (TAG) in the World Health Organization (WHO), and the United Nations Department of Economic and Social Affairs (UN DESA).

He holds a Ph.D. in Information Management specializing in Statistics and Econometrics, an MBA in Finance, a Post-graduate degree in Statistical Systems specializing in Central Banks, and a Master`s and a BSc degree in Mathematical Statistics. He is certified by TÜV NORD for Risk Management and Internal Audit of Information Security Management System (ISMS). His professional path includes the experience of teaching and applying Data Science, Econometrics, and Statistics to problems in financial risks, actuaries, and official statistics. His scientific interests have focused on Data Science, Big Data, and predictive models. His recent work about a new machine learning approach for credit scoring with Big Data and its PySpark code was the winner of the first prize of the International Conference of Risk Analysis in Austria and was published in Expert Systems with Application journal (a top 5% journal in artificial intelligence).

- International Projects:

(1) Strategic Planning: One of the eight members of the strategic planning group of the International Data & Statistical Literacy Project. This project was initiated by the education section of the International Statistical Institute (ISI). The goal of this project was to present a strategic plan for promoting data and statistical literacy across the world and in all walks of life. This project was directed by Professor Dr. Jim Ridgway, University of Durham, and Professor Dr. Milo Schield, Augsburg University, Minneapolis. (Referenced by his permission:
(2) Jury Member of an International Competition: Honored to be joined by Ana Serradó Bayés, Delia North, James R. Nicholson, Anushka Karkelanova, and Matt Parry as the judging panel for the International Statistical Literacy Poster Competition of 2020-2021. This international competition was organized by the education section of the International Statistical Institute (ISI) in ISLP. The winners received their prizes at the 63rd World Statistics Congress of the ISI in the Netherlands.
(3) Member of Two Technical Advisory Groups: Member of two Technical Advisory Groups in the World Health Organization (WHO), and the United Nations Department of Economic and Social Affairs (UN DESA).

- Invited Speaker

2022 - Portugal - Data Collection Methods and Computer-Assisted Interviews. Invited to talk for master students of Faculdade de Economia, Universidade de Porto.
2019 - Portugal - Data Science and Open Banking. Invited to talk for new master's students of Nova IMS.
2018 - Spain - Mining Big Data for Statistical Systems of Monetary and Financial Institutions. Invited to talk at CARMA2018.
2018 - Portugal - New Technologies and Information Management for Central Banking. Invited to talk at Nova School of Business and Economics.
2017 - Morocco - The Challenges of Improving Financial Data and Statistical Literacy. Invited to talk at ISI World Statistics Congress.
2016 - Switzerland - Financial Stability and Statistical Systems in Banking. Invited by UNCTAD & WTO.

Publicações Cientificas

Ashofteh, A., Bravo, J. M., & Ayuso, M. (2022)

An Ensemble Learning Strategy for Panel Time Series Forecasting of Excess Mortality During the COVID-19 Pandemic. Applied Soft Computing, 128(October), 1-17. [109422].,

Ashofteh, A., & Bravo, J. M. (2021)

A Conservative Approach for Online Credit Scoring. Expert Systems with Applications, 114835. [Advanced online publication on 10 March 2021].

Ashofteh, A., & Bravo, J. M. (2021)

Data Science Training for Official Statistics: a New Scientific Paradigm of Information and Knowledge Development in National Statistical Systems. Statistical Journal of the IAOS, 37(3), 771 – 789.

Ashofteh, A., & Bravo, J. M. (2021)

Life Table Forecasting in COVID-19 Times: An Ensemble Learning Approach. In 2021 16th  Iberian Conference on Information Systems and Technologies (CISTI) (pp. 1-6). IEEE.

Ashofteh, A., & Bravo, J. M. (2020)

A study on the quality of novel coronavirus (COVID-19) official datasets. Statistical Journal of the IAOS, 36(2), 291-301.

Ashofteh, A., & Bravo, J. M. (2019)

A non-parametric-based computationally efficient approach for credit scoring using non-traditional data. In K. Moder, & B. Spange (Eds.), 8th  International Conference on Risk Analysis and Design of Experiments: book of abstratcts (pp. 9). University of Natural Resources and Life Sciences, Vienna, Austria, April 23rd  to 26th  , 2019.

Ashofteh, Afshin and Bravo, Jorge M., "A Non-Parametric-Based Computationally Efficient Approach for Credit Scoring" (2019)

CAPSI 2019 Proceedings. 4. Proceedings of the 19th  Portuguese Association of Information Systems Conference: digital disruption: living between data science, IoT and ... people. Association for Information Systems. Link:

Ashofteh, A. (2018)

Mining Big Data in statistical systems of the monetary financial institutions (MFIs). Congress UPV. 2nd  International Conference on Advanced Research Methods and Analytics (CARMA 2018) (Abstratcts). Editorial Universitat Politècnica de València . ISBN: 978-84-9048-689-4 (print version). DOI:

Ashofteh A. (2016)

Modern Monetary and Financial Management Information Systems. GAPnashr. ISBN 978-600-7197-29-5.

Ashofteh A. (2013)

Application of Stochastic Process Models in Security systems of E-Banking. In Proceeding of the International Conference on Electronic Banking and Payment Systems, Monetary Research Institute, September 2013. Pages 39-57.

Ashofteh A. (2010)

Data Literacy in Economy. 110 pages. Center of Statistical Society and Mathematics House of Isfahan. ISBN 978-600-04-4712-0.

Ashofteh A. (2005)

Statistical Methods and a Nonparametric Reliability Measure for Computer Intrusion Detection. In Conference Abstracts. Final Version. International Conference on the FUTURE OF STATISTICAL THEORY,PRACTICE AND EDUCATION. December 29, 2004 – January 1, 2005. Indian School of Business, Hyderabad, India.