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Teaching Staff


Afshin Ashofteh is a full-time University Professor and consultant.

He holds five university degrees, including 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, a Master's degree in Mathematical Statistics, and a Bachelor's degree in Statistics and Econometrics.

For professional certifications, he is certified by TÜV NORD Germany for both Risk Management and Internal Audit of the Information Security Management Systems (ISMS). During his professional life, he passed courses for CCNA (Cisco Certified Network Associate), Network Plus, Security Plus, Active Directory, Linux Shell Programming, ITIL v3, COBIT Framework, and SQL Server.

He has been a full-time university professor and consultant for over two decades and an integrated researcher at the Information Management Research and Development Center (MagIC). He serves some national and international institutions as a technical advisor/consultant, such as IMF, WHO, UN DESA, Central Banks, Banking Research Institute, and Statistics Portugal (INE).

His scientific interests have focused on Data Science in Finance and implementing Big Data and predictive models in Risk, Banking, Financial Economics, and Official Statistics. He published in top-tier journals, such as a new machine learning approach with Big Data at a top 10% journal in Artificial Intelligence and a new Layered Learning Time Series forecasting model (called DELMS) in a top 10% journal in Computer Science.

For conferences till 2023, he was Invited Speaker at seven conferences and Keynote Speaker at two others (six in Europe, one in Africa, one in South America, and one in Asia).

- Awards:

(1) the Scholastic Achievement Award in 2015 (Central Bank of Portugal), (2) the Best Research Award in 2019 (International Statistical Institute), (3) and the Best Teaching Award in 2023 (Nova University Lisbon, Universidad Autónoma de Madrid, and the University of Rome Tor Vergata).

- Projects:

2022 - now: 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).

2021: 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 organised by the education section of the International Statistical Institute (ISI) in ISLP. The winners received prizes at the 63rd World Statistics Congress of the ISI in the Netherlands.

2009 - 2011: 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). This project aimed to present a strategic plan for promoting data and statistical literacy worldwide and in all walks of life. It was directed by Professor Dr Jim Ridgway, University of Durham, and Professor Dr Milo Schield, Augsburg University, Minneapolis.

- Recent Invited Speaker & Keynote Speaker

2023 - Keynote speaker - Brazil - Conference on Machine Learning and Big Data for Economic Stability and Risk Management, Universidade Federal do Rio Grande do Norte.

2018 - Invited - Spain - Mining Big Data for Statistical Systems of Monetary and Financial Institutions. Invited to talk at CARMA2018.

2017 - Invited - Morocco - Invited to talk at ISI World Statistics Congress.

2016 - Invited - Switzerland - Financial Stability and Statistical Systems in Banking. Invited by UNCTAD & WTO.

More information:

Scientific Publications

Ashofteh, A., Lopes, J., & Campos, P. (2024)

Population Trajectories Survey Methodology: Improving Coverage Error by Clustering of Freguesias and Dwelling Segmentation using Census Data in Portugal. 211. Abstract from European Conference on Quality in Official Statistics, Lisboa, Portugal.

Lopes, J., & Ashofteh, A. (2024)

Using population census data to assist in sampling of survey on origins and discrimination. 37-38. Abstract from XXXI Jornadas de Classificação e Análise de Dados, Leiria, Portugal.

Nunes, C. E. R., & Ashofteh, A. (2024)

A Review of Big Data and Machine Learning Operations in Official Statistics: MLOps and Feature Store Adoption. In H. Shahriar, H. Ohsaki, M. Sharmin, D. Towey, AKM. J. A. Majumder, Y. Hori, J-J. Yang, M. Takemoto, N. Sakib, R. Banno, & S. I. Ahamed (Eds.), 2024 IEEE 48th  Annual Computers, Software, and Applications Conference: COMPSAC 2024 (pp. 711-718). (Proceedings of the IEEE Annual Computer Software and Applications Conference). Institute of Electrical and Electronics Engineers (IEEE).

Ashofteh, A. (2023)

Big Data for Credit Risk Analysis: Efficient Machine Learning Models Using PySpark. In J. Pilz, V. B. Melas, & A. Bathke (Eds.), Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications: Selected Contributions from SimStat 2019 and Invited Papers (pp. 245-265). (Contributions to Statistics). Springer, Cham.

Ashofteh, A. (2023)

Teaching Note—Data Science Training for Finance and Risk Analysis: A Pedagogical Approach with Integrating Online Platforms. In C. P. Kitsos, T. A. Oliveira, F. Pierri, & M. Restaino (Eds.), Statistical Modelling and Risk Analysis: Selected contributions from ICRA9, Perugia, Italy, May 25-27, 2022 (Vol. 430, pp. 17-25). (Springer Proceedings in Mathematics & Statistics). Springer Nature.

Ashofteh, A., & Campos, P. (2023)

A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment. In P. Brito, J. G. Dias, B. Lausen, A. Montanari, & R. Nugent (Eds.), Classification and Data Science in the Digital Age (pp. 53-61). (Studies in Classification, Data Analysis, and Knowledge Organization). Springer, Cham.

Bravo, J. M., & Ashofteh, A. (2023)

Ensemble Methods for Consumer Price Inflation Forecasting. In CAPSI 2023 Proceedings (pp. 317-336). Article 25 (Atas da Conferência da Associação Portuguesa de Sistemas de Informação). Associação Portuguesa de Sistemas de Informação.

Martins, M. N., & Ashofteh, A. (2023)

A Systematic Review on Robot-Advisors in Fintech. In CAPSI 2023 Proceedings (pp. 160-185). Article 15 (Atas da Conferência da Associação Portuguesa de Sistemas de Informação). Associação Portuguesa de Sistemas de Informação.

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.