The 2019 Syngenta Crop Challenge in Analytics judging panel includes experts with backgrounds in agriculture, education and technology. The committee will evaluate the entries on the use of predictive modeling to improve corn seed hybrid selection and decision-making.
Nicolas is an agronomist trained with a systems perspective. His graduate studies at the University of Illinois focused on studying soil-plant relationships with multivariate analysis and spatial statistics. After graduation, he worked for more than 10 years developing drought-tolerant traits and using geospatial datasets, analytics and crowdsourcing. As an assistant professor at the University of Illinois, his goal is to improve long-term profitability and stability of cropping systems by exploring applications of quantitative methods on big data.
Durai is the area coordinator and senior lecturer of data analytics at Olin Business School, Washington University in St. Louis. He received his doctorate in industrial engineering (data analytics concentration) from the University of Texas at Arlington. He performed his doctoral research in the Center on Stochastic Modeling, Optimization, and Statistics (COSMOS). He also has a master’s in industrial engineering from the University of Texas at Arlington and a bachelor’s in mechanical engineering from Bharathiar University, India. His research interests include business analytics, machine learning, optimization, simulation, and simulation-based optimization applied to diverse applications.
Along with his colleagues, he won the third prize of 2017 Syngenta Crop Challenge in Analytics. In addition, the paper he co-authored with his colleagues from the 2016 Syngenta Crop Challenge in Analytics won the 2017 INFORMS Data Mining Best Paper Award and 2018 Olin Award.
Greg is the head of novel algorithm advancement at Syngenta. In the 18 years he has been with the company, he has held a variety of roles in research and development that include platform and protocol development of high throughput systems, soybean trait development and leading global genetic projects in oilseeds. In his current position, he is responsible for leading the development of tools and methods focused on process improvement, optimization and improved decision making in Syngenta’s breeding programs.
Sina received his doctorate in industrial engineering from Wayne State University in 2017 and his bachelor’s and master’s degrees in industrial engineering from Sharif University of Technology, Tehran, Iran. He is currently an operations research analyst in Analytics, Data and Decision Sciences Organization at Turner Broadcasting System and working on predictive analytic problems in media and advertising.
Guiping is an associate professor in the department of Industrial and Manufacturing Systems Engineering at Iowa State University. Her areas of research interests are operations research and optimization with applications in big data analytics, bioinformatics, supply chain design and energy systems analysis.
Daniel is a scientist at the International Center for Tropical Agriculture (CIAT). He is agronomist by training and has been a pioneer of using artificial intelligence techniques for agricultural research in developing countries, he coordinates the Data-Driven Agronomy Community of Practice of the CGIAR Platform for Big Data in Agriculture. His work has received recognition from the World Bank Group (2015) and the United Nations (2014 and 2017). The team he leads at CIAT took the top prize at the Syngenta 2018 Crop Challenge in Analytics.
Alex is an assistant research professor at the Center for Computational Genetics and Genomics at Temple University. His research focuses on the evolution of complex traits in structured populations. He obtained a bachelor’s in mathematical biology from the University of Pennsylvania and a doctorate in theoretical population genetics from Harvard University.
Michael is senior data scientist at Fortune Brands GPG’s Supply Chain Center of Excellence and a lecturer in Northeastern University’s Master of Analytics and Master of Enterprise Intelligence program. Michael holds a master’s and doctorate in industrial engineering and operations research from the University of Massachusetts Amherst and a bachelor’s and master’s degree in business engineering from the Karlsruhe Institute of Technology. His research and expertise focuses on supply chain and operations connected with advanced analytics. Michael worked for and with companies like Volkswagen AG, Pratt & Whitney, McKesson, and Philips Research.
Lizhi is an associate professor in the Industrial and Manufacturing Systems Engineering Department at Iowa State University. He received his doctorate from the University of Pittsburgh. His research interests include optimization, machine learning, and their applications in transportation, energy, agriculture and manufacturing systems. His team won the third place in the 2018 Syngenta Crop Challenge in Analytics.