Student Interview: Saad Waseem


Saad is a 2nd year student in the EDISS Programme. He was interviewed in May when still studying at Åbo Akademi University. This year Saad continued his studies at Mälardalen University.

In the interview Saad talks about the many opportunities within academia and industry that studying in the EDISS progamme has offered him. Saad also mentions the value of the Winter School, which gave him the opportunity to meet industrial partners from Spain. The internship period in Sweden Saad mentions as giving him yet another experience of working with machine-learning and data-science, something he would like to work with in his future career. 

Why did you choose to apply for the EDISS-program? 

Before starting my master’s studies, I was working in the software industry for a few years. I was   hoping to find a program that combined academic research and industrial experience, and so far, my experience with EDISS has been good as it combines all the subjects in a very subtle manner.

Now that you are here, how would you describe EDISS, what is it about and what have you learned so far? 

EDISS is awesome. It offers you many opportunities within academia and industry. Not only that, but there are also many different social events and student events that you get to participate in that gives you an opportunity to know different cultures and collect memories. 

What were your expectations and has the program met them? 

I was hoping for a program that combines academic research with industrial experience. I have found EDISS a perfect fit from that perspective as it combines the practical experience of data science and machine learning together with academic studies, so it has met my expectations. 

How has the financing worked for you? 

Well as an international student you always need funds to meet your day-to-day routines, to afford a reasonable accommodation and to travel around both for academic and non-academic reasons so yes, the EDISS grant has helped me in many ways. 

What do you think about studying in Finland, what has it been like? 

Studying in Finland is interesting. Everything is online and that gives us more flexibility in terms of time-management. We have many student associations here that we can join and get to know different cultures. We also have many social events that we can participate in and above all we also get student discounts at every outlet in Finland. 

What have you been doing outside of your studies in Finland? 

There are many things to do outside of studies, for example I’ve been participating in different social activities, sometimes I go to the gym and all the EDISS students are very participating and most often we also plan different excursions to have a bit of relaxing time that gives us a boost to get started with our upcoming studies. 

Thoughts about the Winter school, internship, and your upcoming exchange year? 

The Winter School experience was very exciting. We travelled to a whole new different country, not only that but to a different university, UIB in the Balearic Islands in Spain. That gave us a very exciting experience with all the academic and social activities that we did, and we got to meet industry partners from Spain, an amazing experience for us. 

The internship experience gives us hands-on experience with working with machine-learning and data-science. There are also many events where different companies come in and present their projects and we get a chance to work with them. Many of the companies come from the software industry and work particularly with data-science and machine-learning. 

Well about the upcoming exchange year, I hope that it is going to be more exciting than what we experienced during our first year. We all will be travelling to different countries and that will obviously give us experience from the academic and industrial structure they have there, and we’ll also get to know about their social values, so I feel excited about it. 

What are your future plans? 

I look forward to having an excelling career in data-science and machine-learning. 

Last updated on 5 December 2023