As we continue our series of interviews with the distinguished IT-lecturers of KIMEP University, we would like to introduce you another insightful conversation featuring Engin Mendi, the Assistant Professor from the Department of Information Systems of KIMEP University. Engin Mendi is originally from Konya, Türkiye. His primary research focuses lie within the domains of image and video processing, health informatics, and the development of mobile applications. With a robust academic background, he has an extensive publication record, boasting over 30 contributions to the field. This includes more than 10 peer-reviewed journal papers, a book chapter, and a multitude of conference papers, highlighting his significant contributions and expertise in these areas.
ZHANARTU: Dr. Mendi, could you please share about yourself, about your academic background?
– I have a PhD degree in Computer Science from University of Arkansas at Little Rock (UALR), 2 MS degrees: one in Applied Science from UALR and one in Computational Sciences from Technical University of Munich in Germany and BS in Civil Engineering from Middle East Technical University in Ankara, Türkiye.
ZHANARTU: What was your international expertise in the IT sphere before you joined BISB program?
– I was a Research Assistant at Technical University of Munich, University of Arkansas at Little Rock and Istanbul Kultur University; a software Engineer at IABG mbH and Max-Planck Institute for Plasma Physics in Germany and at Wright-Brothers Institute of US Air Force and lastly I was a faculty member at Konya Chamber of Commerce University in Türkiye.
ZHANARTU: What courses do you teach at KIMEP University now?
– Currently, I teach Big Data Management, Machine Learning, Human-Computer Interaction and various programming courses in Python, C, C++, Java and Android.
ZHANARTU: What topics are your BIS students most interested in and why?
– Machine Learning and Big Data are some key topics that often attract the interest of BIS students. These topics provide the skills and tools necessary to extract valuable insights from data and have transformative potential across various industries. Our students want to understand how to apply these technologies to automate tasks, analyze data, and improve decision-making.
ZHANARTU: Please tell us, what practical skills students should receive after completion of your courses?
– After completion of the course students should be able to code in popular industry languages such as Python, Java, C++, and understand the basics of software development and system architecture. Also, they should be able to inspect, clean, analyze and model data, and develop solutions based on trends and patterns in the data. They can learn how to design and evaluate user interfaces and experiences for different types of applications and devices and be able to apply mathematical and statistical methods to model and solve real-world problems using data by various machine learning algorithms and libraries. Another skill that students should receive is problem solving. They can apply logical and critical thinking skills to resolve complex and difficult situations involving information systems.
ZHANARTU: Can you please tell us about the highlights of the beginning of this academic year?
– KIMEP University has been planning new initiatives such as new programs and courses that reflect the latest trends and developments in various fields, such as AI, software engineering, block chain technology, cybersecurity, etc. Thus, this would be a thrilling highlight that we will be able to share about in details a bit later on.
ZHANARTU: What do you think are the perspectives of BIS program in the nearest future?
– The importance of BIS is likely to continue growing. As organizations rely more on data-driven decision-making, there will be a growing demand for professionals who can design, implement, and manage effective information systems. BIS graduates will need to have skills and knowledge in applying AI and related technologies to various business problems and opportunities. For example, BIS graduates can use natural language processing, computer vision, machine learning, and deep learning to generate insights, predictions, recommendations, and actions from data.
ZHANARTU: Dr. Engin Mendi, thank you very much for your time! Wishing you all the best in the following academic year!