Skip to content
All posts

Layke Blog | Meet our people – Lise Rückert and Henry Sjögren

Lise Rückert and Henry Sjögren are two bright engineering students with a strong passion for Machine Learning and Artificial Intelligence.

This spring, they will be writing their thesis along with Layke Analytics. They will be focusing on the techniques in the area of Natural Language Processes that Layke uses to integrate artificial intelligence into the hiring process.


Tell us about yourselves

Lise: “My name is Lise Rückert. I am 26 years old, originally from Dalarna, but currently living in Uppsala where I am studying my fifth and last year of a master’s program in Sociotechnical Systems Engineering. Before I can graduate in June, I’ll have to finish my master’s thesis, which is why I, together with Henry, am spending quite a lot of time here at Layke this spring”.

Henry: “My name is Henry Sjögren, 26 years old. Born and raised in Linköping I moved to Uppsala to take on the Master’s Programme in Sociotechnical Systems Engineering, where I’m currently doing my last semester. This spring I’m doing my master thesis on Layke, together with Lise, which so far has been very rewarding both in terms of fun and education”.


Tell us about your dissertation. What are you writing about? 

Henry: “Layke is involved with integrating AI in HR processes and one of their services involves matching résumés and job adverts, using techniques in the area of Natural Language Processing. They have given us the task to see if we can find ways to improve the existing model by looking into the possibility of deriving semantic meaning out of complete sentences instead of just words”.

Lise: “Since Layke is working with the automation of recruitment processes, my dissertation is very much along the lines of that. By using machine learning and artificial intelligence we want to examine if new, state-of-the-art methods within the area of Natural Language Processing will perform better than Layke’s existing model when it comes to comparing and matching electronic resumes and job adverts. If so, how much better is the performance and is it worth implementing?”


Lise Rückert
Lise Rückert

How did you choose your topic?

Lise: “I think that both Henry and I knew from the beginning when we first started looking for possible master theses, that we wanted to do something within machine learning. When we got in contact with Layke, they already had a very clear idea of what they wanted to examine and what they could offer topic-wise in relation to their company and business idea. Luckily, it mirrored what Henry and I were looking for very well!”.

Henry: “During my years in the engineering programme, machine learning piqued my interest from the start. Apart from that, I have always been interested in language and how one perceives it and makes sense of it. Therefore, when I got informed of the possibility to work with Layke on this project, I immediately felt it was something for me. When we began talking to the people at Layke, both me and Lise got a great view of the company, which has only gotten better since”.


Why are you interested in this topic?

Henry: “The idea of disassembling a language and trying to make a machine make sense of it really interests me. It raises such questions as what we ourselves take in when we read and listen. Combining this with machine learning is a perfect mix of some of my interests. The area of Natural Language Processing is constantly evolving and working with these techniques really makes me feel like I’m at the forefront of the tech business”.

Lise: “My interest in technology and machine learning comes from my education which is very IT-orientated. What you can do with various technologies and how it affects societies, as well as humans, is thrilling. The field of Natural Language Processing involves learning computers to understand and generate human language. I don’t know if further motivation for why this is an interesting topic really is needed. But apart from being a very central, and according to me, a cool area within machine learning today, Natural Language Processing has developed a lot during recent years and keeps doing so. That means that the techniques we are working with are very new, and the application domains are highly relevant.”


Lise Rückert and Henry Sjögren


How did you choose Layke?

Lise: “I first heard about Layke from a friend who works here, about a year ago. Already then, Layke sparked my interest. When Henry and I saw an advert about conducting a master's thesis at Layke back in October, we were very quick to apply. From the first meeting with Mikael Nelsson, a machine learning engineer at Layke, we had a very good feeling about Layke and felt that they could offer us a project that was right up our alley. And the rest is, as they say, history!”

Henry: “Lise and I had already begun discussing potential companies to do our master thesis on when we saw the advert from Layke. We immediately felt that this was something for us and, as soon as we got in contact with Mikael Nelson at Layke, who told us more about the company and the project, Lise and I looked at each other and said, ‘This is it!’.”


How is Layke Analytics helping you in writing your thesis? 

Henry: “We have all the assets we need at Layke. Everyone is keen on making sure that everything is going well. They have a clear understanding of what the university expects from our thesis and provide us with everything, from computing power to discussions about what our next step should be, as well as just being very welcoming”.

Lise: “Let’s just say that it would not be possible for me and Henry to conduct this thesis gracefully without the help of the Layke team. Not just when it comes to providing us with data, GPU power and critical knowledge about the topic itself and what technologies to use etc, but also by being a warm, fun and committed team”.


Henry Sjögren
Henry Sjögren


What are your overall expectations?

Lise: My overall expectations are to develop and learn a lot within the field of machine learning and, especially, Natural Language Processing. To wrap up my studies in a neat way by applying the knowledge and competencies I have gained on a real-life task, with a team of experts as help. And of course, to indulge me in Anna Rydin’s baked goods, one of the machine learning engineers working at Layke.

Henry: “In short, my expectations are experience and fun. I aim to learn as much as I can this spring, and it has already borne fruit. Finally, we can implement all the knowledge we have attained during our years at university in practice. Apart from that Lise and I are looking forward to hanging around at the office as soon as the railways allow us to”.

Lise Rückert and Henry Sjögren