Hamidreza (Hamid) Ahady Dolatsara is awarded his Ph.D. degree from Auburn University. He is a data scientist with research interests in health care analytics, finance, and transportation. Using data-driven studies, he employs and improves state-of-the-art, machine learning-based approaches to developing decision-support systems. As one example, he investigated the long-term financial well-being of companies and their association with the adoption of block-chain technology. Ahady Dolatsara is keen on exploring new ideas that will have a positive impact on society.
Hamidreza Ahady Dolatsara
Assistant Professor, School of Business
- About
- Scholarly and creative works
- Awards and grant
Degrees
- Ph.D. in Industrial & Systems Engineering, Auburn University, 2019
- M.S. in Information Systems Management, Auburn University, 2019
- M.Eng. in Industrial & Systems Engineering, Auburn University, 2015
- M.S. in Civil-Transportation Engineering, West Michigan University, 2014
- B.S. in Railroad Operation and Management Engineering, IUST, 2008
Affiliated Department
Scholarly and creative works
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Explaining predictive model performance: An experimental study of data preparation and model choice
Published in Big Data2023Vol. 11Issue #3 -
Success of Initial Coin Offerings (ICOs)
ICTIMESH 2023Dubai, EmiratesDecember2023 -
A DEA And Machine Learning Based Platform for Investigating Success of Initial Coin Offerings (ICOs)
Elsevier -
Cryptocurrency Fraud Detection
INFORMS Annual meetingIndianapolisOctober2022Sponsored by INFORMS -
Biased In Healthcare Analytics Ai Based Frameworks
INFORMS Annual MeetingIndianapolisOctober2022Sponsored by INFORMS -
An Analytical View On Applications Of Blockchain In Business
INFORMS Annual meetingIndianapolisOctober2022Sponsored by INFORMS -
An Interpretable Decision-Support Systems for Daily Cryptocurrency Trading
Published in Expert Systems With Applications2022Vol. 203 -
Evaluating the Effect of Newly Added Variables to Predictability of Heart Transplant Survival Outcome
Published in Business Analytics2022 -
Going Beyond Intent to Adopt Blockchain – An Analytics Approach to Understand Board Member and Financial Health Characteristics
Published in Annals of Operations Research2021 -
Predicting hotel reviews from sentiment: a multinomial classification
Published in Modeling in Management2021 -
An analytical approach for investigating long-term financial wellbeing of companies
Published in Business Venturing2021 -
Investigating Potential Bias And Discrimination In The Development Of A Typical AI Platform For Heart Transplantation
INFORMS ConferenceVirtualNov.2020 -
A two-stage machine learning framework to predict heart transplantation survival probabilities over time with a monotonic probability constraint
Published in Decision Support Systems2020Vol. 137 -
AHP Decision Making Algorithm for Development of HVDC and EHVAC in Developing Countries
Published in European Journal of Electrical Engineering and Computer Science2020Vol. 4Issue #3 -
Machine learning Clustering Algorithms Based on the DEA Optimization Approach for Banking System in Developing Countries
Published in European Journal of Engineering Research and Science2020Vol. 5Issue #6 -
A novel machine learning approach combined with optimization models for eco-efficiency evaluation
Published in Applied Sciences2020Vol. 10Issue #15 -
Optimized wavelet-based satellite image de-noising with multi-population differential evolution-assisted harris hawks optimization algorithm
Published in IEEE Access2020Vol. 8 -
Current Challenges in Development of a Survival Analysis Data Mining Study
INFORMS ConferenceSeattleOctober2019 -
Improving Non-monotonicity Issues in Predicting Survival Probability of Transplant Patients (INFORMS Conference presentation, Phoenix-USA, 2018)
INFORMS Conference2018 -
Analysis of Influential Range for Intersection Crashes
Published in Journal of the Eastern Asia Society for Transportation Studies2017Vol. 12
Awards and grants
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A Collaborative Research on House Market
Clark University – Faculty Development Fund
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Blockchain & Cryptocurrency Course
Clark University – Academic Innovation Fund
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Business Edge Technologies Lab
Clark University – Academic Innovation Fund award