Dr. Seydibeyoglu is currently a visiting professor at University of Main. He introduce the state of art research, technology and applications of Nanocellulose, and discussed potential implications on future sustainable development plans and goals worldwide.
Future is bright with these disruptive, environmentally friendly and circular material practices. They can be also cheap at a competitive level while their use and functional properties need to meet the industry standards such as use of nanocellulose in car parts, etc.
We would like to thank Dr. Seydibeyoglu for his excellent seminar and sharing his time with us again.
Dr. Celikbilek is currently working at T-Mobile as Business Intelligence Manager. His seminar was focused on Data Science and Business Intelligence Applications in E-commerce and Tech Industry.
Dr. Celikbilek shared his recent projects that focused on application of machine learning, dashboarding, and data viz techniques on various e-commerce problems including prediction of sales, shipment time, and vendor clustering and classification from clothing, communication, and supply chain / logistics industries. Some of the key takeaways are:
Business understanding is far more important than having knowledge and skillset of business analytics and data science.
His suggested set of tools include python, SQL, tableau and PowerBI in addition to solid MS Excel knowledge and skills for working on large scale business analytics and intelligence projects.
As companies get bigger, the problems become more complex and required datasets, their volume, variety, veracity and value become more and more important and increase.
Business analytics tools, methods, knowledge and skills become more indispensable assets for new graduates to have and keep building up on as the industries get connected to each other globally more in depth.
We would like to thank Can for his excellent seminar and sharing his time with us again.
Dr. Gedik gave a research talk, which is an extension of our former research assistant Lu Bai’s thesis project on 11/24/2021 at the 2021 DSI Annual Meeting. The presentation was entitled “What It Takes to Win or Lose A Soccer Game? A Machine Learning Approach to Understand the Impact of Game and Team Statistics” and presentation can be accessed at this link.
In this research, we focused on building machine learning models to predict soccer game outcomes in five major soccer leagues, and extract knowledge on what factors play biggest role in winning and losing a soccer game over a 5 season data.
We would like to thank Lu for her excellent thesis work again.