Michael Lash
- Assistant Professor
- Analytics, Information, Operations academic area
Contact Info
Lawrence
Personal Links
Education —
Research —
Research interests:
- Data Mining
- Machine Learning
- Decision Making with Machine Learning
- Reinforcement Learning
- Recommendation
- Outcome Optimization
- Graph Learning
- Causal Learning
- Predictive and Prescriptive Analytics
Teaching —
Teaching interests:
- Business Analytics
- Machine Learning
- Database Management
Selected Publications —
<div class="fp-publications fp-container"><div class="aca-article">Gupta, A., Lash, M., Nachimuthu, S. (2021). Optimal Sepsis Patient Treatment using Human-in-the-loop Artificial Intelligence. Expert Systems with Applications - Volume 169. <a href="https://doi.org/10.1016/J.ESWA.2020.114476">https://doi.org/10.1016/J.E… class="aca-article">Lash, M. (2020). Optimal Sepsis Patient Treatment using Human-in-the-loop Artificial Intelligence. Expert Systems with Applications.</div><div class="aca-article">Lash, M., Slater, J., Polgreen, P., Segre, A. (2019). 21 Million Opportunities: a 19 Facility Investigation of Factors Affecting Hand-Hygiene Compliance via Linear Predictive Models. Journal of Healthcare Informatics Research - Issue 4 | Volume 3. <a href="https://doi.org/10.1007/s41666-019-00048-1">https://doi.org/10.1007/s41… class="aca-article">Lash, M. (2019). 21 Million Opportunities: a 19 Facility Investigation of Factors Affecting Hand-Hygiene Compliance via Linear Predictive Models. Journal of Healthcare Informatics Research - Issue 4 | Volume 3. <a href="https://doi.org/10.1007/s41666-019-00048-1">https://doi.org/10.1007/s41… class="aca-article">Lash, M., Slater, J., Polgreen, P., Segre, A. (2019). 21 Million Opportunities: a 19 Facility Investigation of Factors Affecting Hand-Hygiene Compliance via Linear Predictive Models. Journal of Healthcare Informatics Research - Issue 4 | Volume 3. <a href="https://doi.org/10.1007/S41666-019-00048-1">https://doi.org/10.1007/S41… class="aca-article">Lash, M., Zhang, M., Zhou, X., Street, W., Lynch, C. (2018). Deriving enhanced geographical representations via similarity-based spectral analysis: predicting colorectal cancer survival curves in Iowa. International Journal of Data Mining and Bioinformatics - Issue 3 | Volume 21. <a href="https://doi.org/10.1504/ijdmb.2018.097677">https://doi.org/10.1504/ijdm… class="aca-article">Lash, M. (2018). Deriving enhanced geographical representations via similarity-based spectral analysis: predicting colorectal cancer survival curves in Iowa. International Journal of Data Mining and Bioinformatics - Issue 3 | Volume 21. <a href="https://doi.org/10.1504/ijdmb.2018.097677">https://doi.org/10.1504/ijdm… class="aca-article">Lash, M., Zhang, M., Zhou, X., Street, N., Lynch, C. (2018). Deriving enhanced geographical representations via similarity-based spectral analysis: predicting colorectal cancer survival curves in Iowa. International Journal of Data Mining and Bioinformatics - Issue 3 | Volume 21. <a href="https://doi.org/10.1504/IJDMB.2018.097677">https://doi.org/10.1504/IJDM… class="aca-article">Street, N., Lynch, C., Zhou, X., Zhang, M., Lash, M., Street, W. (2018). Deriving enhanced geographical representations via similarity-based spectral analysis: predicting colorectal cancer survival curves in Iowa. International Journal of Data Mining and Bioinformatics - Issue 3 | Volume 21. <a href="https://doi.org/10.1504/IJDMB.2018.10018956">https://doi.org/10.1504/IJ… class="aca-conf-proc">Lash, M., Sun, Y., Zhou, X., Lynch, C., Street, N. (2017). Learning rich geographical representations: Predicting colorectal cancer survival in the state of Iowa. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) - Pages 778-785. <a href="https://doi.org/10.1109/BIBM.2017.8217754">https://doi.org/10.1109/BIBM… class="aca-conf-proc">Lash, M., Lin, Q., Street, N., Robinson, J. (2017). A Budget-Constrained Inverse Classification Framework for Smooth Classifiers. IEEE International Conference on Data Mining Workshops (ICDMW) - Pages 1184-1193. <a href="https://doi.org/10.1109/ICDMW.2017.174">https://doi.org/10.1109/ICDMW.2… class="aca-conf-proc">Lash, M., Lin, Q., Street, W., Robinson, J. (2017). A Budget-Constrained Inverse Classification Framework for Smooth Classifiers. 2017 IEEE International Conference on Data Mining Workshops (ICDMW). <a href="https://doi.org/10.1109/icdmw.2017.174">https://doi.org/10.1109/icdmw.2… class="aca-conf-proc">Lash, M., Sun, Y., Zhou, X., Lynch, C., Street, W. (2017). Learning rich geographical representations: Predicting colorectal cancer survival in the state of Iowa. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). <a href="https://doi.org/10.1109/bibm.2017.8217754">https://doi.org/10.1109/bibm… class="aca-conf-proc">Lash, M., Slater, J., Polgreen, P., Segre, A. (2017). A Large-Scale Exploration of Factors Affecting Hand Hygiene Compliance Using Linear Predictive Models. IEEE International Conference on Healthcare Informatics (ICHI) - Pages 66-73. <a href="https://doi.org/10.1109/ICHI.2017.12">https://doi.org/10.1109/ICHI.2017… class="aca-conf-proc">Lash, M., Slater, J., Polgreen, P., Segre, A. (2017). A Large-Scale Exploration of Factors Affecting Hand Hygiene Compliance Using Linear Predictive Models. 2017 IEEE International Conference on Healthcare Informatics (ICHI). <a href="https://doi.org/10.1109/ichi.2017.12">https://doi.org/10.1109/ichi.2017… class="aca-conf-proc">Lash, M., Lin, Q., Street, W., Robinson, J., Ohlmann, J. (2017). Generalized Inverse Classification. Proceedings of the 2017 SIAM International Conference on Data Mining - Pages 162-170. <a href="https://doi.org/10.1137/1.9781611974973.19">https://doi.org/10.1137/1.9… class="aca-article">Gerke, A., Tang, F., Lash, M., Schappet, J., Phillips, E., Polgreen, P. (2017). A web-based registry for patients with sarcoidosis. Sarcoidosis vasculitis and diffuse lung diseases (SVDLD) - Issue 1 | Volume 34. <a href="https://doi.org/10.36141/svdld.v34i1.5129">https://doi.org/10.36141/svd… class="aca-article">Lash, M., Zhao, K. (2016). Early Predictions of Movie Success: The Who, What, and When of Profitability. Journal of Management Information Systems - Issue 3 | Volume 33. <a href="https://doi.org/10.1080/07421222.2016.1243969">https://doi.org/10.1080/… class="aca-article">Lash, M. (2016). Early Predictions of Movie Success: The Who, What, and When of Profitability. Journal of Management Information Systems - Issue 3 | Volume 33. <a href="https://doi.org/10.1080/07421222.2016.1243969">https://doi.org/10.1080/… class="aca-article">Lash, M., Zhao, K. (2016). Early Predictions of Movie Success: The Who, What, and When of Profitability. Journal of Management Information Systems - Issue 3 | Volume 33. <a href="https://doi.org/10.1080/07421222.2016.1243969">https://doi.org/10.1080/… class="aca-conf-proc">Lash, M., Fu, S., Wang, S., Zhao, K. (2015). Early Prediction of Movie Success — What, Who, and When. Social Computing, Behavioral-Cultural Modeling, and Prediction [Conference] - Volume 9021 | Pages 345-349. <a href="https://doi.org/10.1007/978-3-319-16268-3_41">https://doi.org/10.1007/9… class="aca-conf-proc">Lash, M., Fu, S., Wang, S., Zhao, K. (2015). Early Predictions of Movie Success: The Who, What, and When. Proceedings of the 2015 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP) - Pages 345-349. <a href="https://doi.org/10.1007/978-3-319-16268-3_41">https://doi.org/10.1007/9… class="aca-article">Gupta, A., Lash, M., Nachimuthu, S. Optimal Sepsis Patient Treatment using Human-in-the-loop Artificial Intelligence. Expert Systems with Applications.</div><div class="aca-conf-proc">Lash, M., Street, W. Personalized Cardiovascular Disease Risk Mitigation via Longitudinal Inverse Classification. Bioinformatics and Biomedicine Workshops (BIBMW), IEEE International Conference on.</div></div>