Salih Tutun


Lecturer in Data Analytics

Salih Tutun

Salih Tutun


Salih Tutun is a faculty member in the Olin Business School at Washington University in St. Louis. His research focuses on deep learning, reinforcement learning and explainable AI for understanding how human behaviors and social interactions affect the business. His research, teaching, and work experience in academia and industry have given him numerous opportunities to utilize his skills to generate value and make an impact. For example, he has been four times Reid Teaching Awards winners (in 2021, 2022 and 2023 from Olin Business School). In his research, Networked Pattern Recognition (NEPAR) is ranked by National News Hits and has over 9 million clicks in two months. This research is mentioned by more than 40 global news organizations and is published on the front cover of Industrial and Systems Engineering at Work magazine. His research has also been recognized as a finalist at the IISE Cup competitions (for 2020 and 2021). With his MDScan research, he achieved first place, winning the Gold Award at the 2023 IISE Cup competition. In 2024, he was honored with the Olin Research Award for his outstanding contributions. His research paper is also a finalist (ongoing now) in the Best Paper Competition at the INFORMS 2024 Data Mining Award Competitions.

Area of Expertise


Decision Analysis, Information Technology, Management Science

Education


  • Ph D 2018, State University of New York (SUNY) at Binghamton
  • MS 2012, Erciyes University
  • BS 2010, Sakarya Universitesi

Academic/Professional Activities


  • Editor, Book, Elsevier
  • Reviewer, Grant Proposal, National Science Foundation: NSF

Awards/Honors


  • INFORMS Data Mining Best Paper Competition – Runner Up, Informs 2024, 2024
  • Olin Research Award, Washington University in St Louis, 2024
  • Reid Teaching Award - MSBA-Financial Technology, , Washington University in St Louis, 2023
  • IISE Cup Competition 2023 - Gold Award, IISE , 2023
  • Reid Teaching Award - MSBA - Finance–Quantitative, Olin Business School, Washington University in St Louis, 2022
  • Reid Teaching Award - MSBA-Financial Technology, , Olin Business School, Washington University in St Louis, 2022
  • Reid Teaching Award - MSBA-Financial Technology, Olin Business School, Washington University in St Louis, 2021
  • IISE Cup Competition 2021 - Finalist, Institute of Industrial and Systems Engineers, 2021
  • IISE Cup Competition 2020 - Finalist, Institute of Industrial and Systems Engineers, 2020

Teaching Interests


Deep Learning for Prediction of Business Outcomes, Deep Learning for Business Analytics, Deep Reinforcement Learning, R and Statistics, Intro to Python and Data Science, Data Analytics in Python, Managerial Statistics, Data Visualization

Research Interests


Professor Salih Tutun is an expert in information technology as focused on explainable AI, deep learning, and reinforcement learning to design the artifacts for solving complex business problems.

Personal Interests


Soccer, traveling, reading, billards, and strategy games

Selected Publications


  • "Explainable Artificial Intelligence for Mental Disorder Screening: A Computational Design Science Approach", Journal of Management Information Systems
  • "An AI-based Decision Support System for Predicting Mental Health Disorders", Information Systems Frontiers Journal, with Marina Johnson, Abdulaziz Ahmed, Sedat Irgil, Ilker Yesilkaya, Abdullah Albizri, Esma Nur Ucar, Tanalp Sengun, Antoine Harfouche
  • "Digital transformation to mitigate emergency situations: increasing opioid overdose survival rates through explainable artificial intelligence", Industrial Management & Data Systems, with Marina Johnson, Abdullah Albizri, Antoine Harfouche
  • "New framework that uses patterns and relations to understand terrorist behaviors", Expert Systems with Applications, 358-375, with Mohammad Khasawneh, Jun Zhuang, 2017
  • "A Responsible AI Framework for Mitigating the Ramifications of the Organ Donation Crisis", Information Systems Frontiers Journal, with Antoine Harfouche, Abdullah Albizri, Marina Johnson, Haiyue He
  • "A new hybrid approach for feature selection and support vector machine model selection based on self-adaptive cohort intelligence", Expert Systems with Applications, 118-131, with Mohammed Aladeemy, Mohammad Khasawneh, 2017
  • "A new forecasting framework for volatile behavior in net electricity consumption: A case study in Turkey", Energy, with Chun-An Chou, Erdal Caniyilmaz, 2015