丁香园AV

G枚khan Cetin received his MSc from SIAT in 2018. During his studies, G枚khan was involved in an industry-academy collaboration with Lululemon and joined Seaspan as a Team Lead in Business Intelligence and Analytics following graduation. He is now a Business Intelligence Engineer at Amazon.

Why did you choose the School of Interactive Arts & Technology?

Coming from a Computer Science background, I have always had interest in linking my primary area of expertise with other domains to produce interdisciplinary output in less-explored areas.

When I found out about SIAT, the opportunities that were offered struck me right away with potential research ideas. Initially, I was excited about exploring the 鈥榟uman鈥� aspect of human-computer interaction more and linking it to my strong technical side to improve user鈥檚 experience in operating technological devices and analytical processes. As I researched and learned more, I further refined my desired research field and finalized on what I have completed during my studies.

What was your research focus at SIAT?

I joined professor Wolfgang Stuerzlinger鈥檚&苍产蝉辫; at SIAT. There I focused on visual analytics on large display systems. My research was to improve data visualization dashboards that outperform generic solutions in special environments, compare physical displays to virtual reality devices in analytical tasks, and to offer solutions to main challenges in visual analytics in highly immersive settings.

Alongside doing cool stuff with virtual reality headsets, the main part of my research required me to work on HUGE display systems during my spell at the lab. As a matter of fact, my everyday computer was a state-of-the-art machine that was operating multiple custom-made graphics cards which supported an array of seven 85鈥� monitors side by side, along with an auxiliary screen in the front. Imagine walking into your lab in the morning, turning your computer on and over 60 million pixels light up on a 2x8 meter wall in front of you: that was my MSc at 丁香园AV!

What is your current career?

My research at SIAT opened the gates of visual analytics and the science of data visualization for me. Leveraging my research knowledge, I had the opportunity to work with global restaurant chains and retail giants to explore their data, analyze trends, make predictions, and provide actionable business items to the upper management. During my MSc, I was involved in an industry-academy collaboration with Lululemon, where I analyzed timeseries data and built mindfulness models for the industry partner.

Following my graduation, I started at Seaspan Corporation, which is a large multinational that is active in many fields in the maritime industry. Part of Seaspan鈥檚 business is to own and operate over a hundred massive containerships which exceeds a cumulative count of 1-million containers across their global fleet. A collection of fleets consisting of vessels each carrying over 10,000 containers non-stop around the world generates business for the globe and generates data for me! Around a year after my joining, I became the Team Lead in Business Intelligence and Analytics at Seaspan.

Along with my associates, we built business intelligence platforms, reshaped data flows, created reporting pipelines and took part in transforming the company towards a more data-driven business. As the pioneer of the move, I built hundreds of dashboards, cross-platform datasets, and served around 250 employees with industry-leading reporting solutions in operations, finance, accounting, commercial, insurance and IT.

After these interesting opportunities, I recently joined Amazon as a Business Intelligence Engineer. I had gained precious experience at Seaspan in logistics and transportation fields and now it is time to utilize the knowledge in the highest level of complexity that has ever been built. I am excited to be a part of the team which delivers around 100 million packages in North America weekly. The amount of data is enormous and so is the variety of challenges and opportunities. Stay tuned!

How did your experience as a graduate student help shape your career path?

Before joining SIAT, I was a computer engineering graduate. Right now, the field I am working in is more of a continuation of my grad field than my undergrad field. I feel like my SIAT experience has refined my interests, helped me determine what I ultimately want to do and provided me the skills and expertise to apply in the career I wanted to pursue.

What are the most important skills that you acquired as a MSc student that helped shape your career success?

I had the opportunity to work closely with amazing people. I can highlight my thesis supervisors; professor Wolfgang Stuerzlinger and professor John Dill. I believe I have learned a lot from this. One memory I always will keep is the infinite loops of extensive editing we went through on my thesis and research papers. The more we did, the more I learned. Consequently, the way I talk, think or write; it definitely has been reconstructed. My experience was a unique opportunity to grow as a professional.

Beyond that, of course, I also acquired domain specific skills and expertise. I dove deep in my research and learned the finest details of large display systems. I can talk for hours on the size, resolution, shape, distance, arrangement of screens, and how they impact user鈥檚 experience in analytical processes. I have also learned a lot about data visualizations, visual analytics, and business intelligence, all of which constitutes the foundation of my current career. 

What was your most valuable graduate student experience while at SIAT?

I had access to novel devices and breakthrough technologies which gives me an advantage by being a few steps ahead in the game. I don鈥檛 think there are many researchers who owned a computer worth $100K and explored the untouched spots of that research field!

Do you have any advice that you would like to share with current students or recent graduates?

If you are in SIAT right now, you have access to a set of instruments that you can interact with and leverage to have a great future ahead. Combinations of research areas are unique, the backgrounds of people around are diverse, and the opportunities are endless.

Another thing that I find useful is to understand how to link academic experience with future careers after graduation. Instead of following random directions in an academic path and trying to combine it with whatever is compatible after; thinking about the ideal career first, working backwards and navigating the studies respectively gave desired results in my own case.