PhD candidates in NorwAI

PhD candidates in NorwAI

Several PhD candidates are now involved in the research in NorwAI. Below, you can read more about the candidates funded though the center, but also about candidates that we are collaborating with and that are funded through other projects. 


PhD candidates funded through NorwAI

PhD candidates funded through NorwAI


Tanja Knaus

Tanja Knaus

 

 

Topic: The materialization of the human voice into affective data - data practices of AI cloud services using vocal emotion recognition systems

Started: April 2022

Main supervisor: Prof. Susanne Bauer, University of Oslo

NorwAI Work Package: SOC - AI in Society
 
About: I’m a PhD research fellow at TIK Centre for Technology, Innovation and Culture at the University of Oslo. I hold a BA in Information Design, a MA in Media and Interaction Design both from the University of Applied Sciences, FH Joanneum Graz and a second MA in Cultural Studies, from the Department of Media, Communication and Cultural Studies at the Goldsmiths University of London with a focus in digital feminist cultures, software studies and critical data studies and computing.

My research interests are in the areas of affect theory, critical data studies, software studies, interaction design, human-computer interaction, big data and digital labour. I’m particularly interested in the fusion of human and nonhuman agency within algorithmic systems and new trends in algorithmic awareness, and ethics concerning biased data practices.

My plan at NorwAI is to investigate the sociotechnical implications of automation. I am especially interested in call centres that use vocal emotion recognition software. I will study the production of software and ‘data workers’ that collect, curate, and maintain data structures and algorithmic systems.


Nolwenn Bernard

Nolwenn Bernard

 

Topic: Study of fairness and transparency in conversational recommender systems

Started: February 2022

Main supervisor: Prof. Krisztian Balog, University of Stavanger

NorwAI Work Package: LAP - Language and Personalization
 
About: I am Nolwenn from France. Since my engineering degree in computer science, I have developed a strong interest in Natural Language Processing (NLP) and Information Retrieval (IR). My engineering internship lead to the publication of a conference article with collaborators on the topic of semantic similarity between scientific articles. Before starting the PhD, I worked 2 years as a R&D engineer for an academic publisher on projects related to these domains and social network. With NorwAI, I will focus on the notions of fairness and transparency in conversational information access systems. I am particularly interested in the notion of personal knowledge graphs to represent people, in how natural language explanations can be a tool to show fairness and build trust, and how information access systems can be evaluated with regards to fairness using simulation techniques.


Weronika Łajewska

Weronika Łajewska

Weronika Łajewska

Topic: Personalizing Conversational Informational Access

Started: February 2022

Main supervisor: Prof. Krisztian Balog, University of Stavanger

NorwAI Work Package: LAP - Language and Personalization
 
About: My name is Weronika Łajewska and I’m a PhD fellow at the University of Stavanger. I have a master’s degree in Artificial Intelligence from Warsaw University of Technology, and partially from Johannes Kepler University in Linz. My master thesis was focused on Named Entity Recognition and Disambiguation in the literature domain. My academic experience is related to the REFSA project, in which we were applying methods of Natural Language Processing and Machine Learning to automate the process of systematic literature reviews in the domain of food safety. In this project, I was mainly focused on knowledge-based systems using ontologies.

 

My PhD research concerns the personalization of conversational informational access search, with a special focus on transparency and explainability. I’m mostly interested in personalization in terms of the user’s context, background, knowledge, and cognitive abilities. The problem I want to investigate is how to explain to the user what is being personalized, why specific results are being presented and what is “not shown”.


Egil Rønningstad

Egil Rønningstad

Portrait Picture Egil Rønningstad

Topic: Norwegian Opinion summarization and Entity-level Sentiment Analysis

Started: October 2021

Main supervisor: Prof. Erik Velldal, University of Oslo

NorwAI Work Package: LAP - Language and Personalization
 
About: Enthusiast about Natural Language Processing for Low-Resource Languages like Norwegian. I recently got my Master's degree in Language Technology at UiO. My thesis was on Fine-Grained Sentiment Analysis with both monolingual and multilingual approaches. With my PhD work and involvement with NorwAI I hope to contribute towards aggregating textual sentiment towards individuals and organizations, so that we can better map opinion trends across publications and watch opinion developments over time.


David Baumgartner

David Baumgartner

Portrait David Baumgartner

Topic: Data analysis with noisy and low-quality data streams

Started: September 2021

Main supervisor: Prof. Heri Ramampiaro, NTNU

NorwAI Work Package: STREAM - AI for Streaming and Sensor-based Data

 

About: I am David from Austria, and this is my first time in Norway. I have a background in IT-Systems, Software Development, and Data Analytics/ML.

During my master's study and afterward, I was part of a smaller research group at my graduation University. I worked on small to medium-sized projects cooperating with companies. The topics were time-series, 2D and 3D images, machine learning model optimization, and explainable artificial intelligence. My interests lie in data analysis and machine learning with a greater focus on white-box models and understandability.
With NorwAI, I am working on noisy and low-quality data streams as with sensor data.Further, the focus is on the aspects of anomaly detection, forecasting, and the possible impacts on humans in the case of air quality and mobility of mobiles. The topic will be challenging but has many possibilities and is interesting for time-series, climate change, and personal health.

You can find me in many places in my free time, starting with swimming, biking, hiking, running, berry picking, and more.
 


Bjørnar Vassøy

Bjørnar Vassøy

Topic: Fairness, Accountability, Transparency and Privacy in Personalization/Recommender systems

Started: August 2021

Main supervisor: Prof. Helge Langseth, NTNU

NorwAI Work Package:  LAP - Language and Personalization

About: My name is Bjørnar Vassøy, I am 28 years old and hail from Stavanger, Norway. I have a master's degree in computer science from NTNU and wrote my thesis on session-based recommendation. Along with my supervisors, I published a short paper based on the work done in the thesis. After completing my master's degree, I spent 3 years working as an IT-consultant in Trondheim. I mainly worked on legacy code, devops ++ in a hydro power optimization tool (non-ML stuff), but I was also involved in some smaller projects where I worked on maritime ETA estimations using clustering of historical position data, NLP for hierarchical classification and semi-supervised NLP classification. I am a "geek incarnate" in the sense that I spend most of my spare time playing computer games(both by myself and with friends), watching tv-series/movies or browsing the web :)

My main research interests are within the fields/domains of personalization and NLP. I am especially interested in current/modern machine learning issues/topics like fairness, accountability, transparency, privacy and explainability. I highly prefer researching problems I believe have a real-word application and utility, preferably using real world datasets.


Katarzyna Michalowska

Katarzyna Michalowska

Portrait Katarzyna Michalowska

Topic: Informed machine learning

Started: January 2021

Supervisors: Prof. Morten Hjort-Jensen, University of Oslo, PhD Signe Riemer-Sørensen, SINTEF Digital

NorwAI Work Package: HYB - Hybrid AI Analytics

About: Katarzyna is a PhD fellow at the University of Oslo and a researcher in the Artificial Intelligence and Analytics group in SINTEF Digital. Her research concerns informed machine learning, which is integrating physical laws and domain knowledge into machine learning models in order to make them more trustable, consistent with the physical world and robust against imperfect data. She will be working on hybrid AI analytics in the NorwAI project, modelling wind energy in collaboration with TrønderEnergi and DNV.
Katarzyna has a master's degree in artificial intelligence which she was awarded at Utrecht University in the Netherlands. She has been dedicated to the field of artificial intelligence since her bachelor studies, which she conducted in Poland and partially in Spain. Leading to her PhD, Katarzyna worked as a researcher at SINTEF for two years, which she joined already as an intern during her master's degree. She has been involved in projects from various domains, including the energy, maritime, and building and construction sectors, as well as developing and teaching machine learning courses. Her main interest lies in problems that can be solved with neither purely analytic, nor standard machine learning implementations, and which she addresses with hybrid and informed machine learning.


Nikolay Nikolov

Nikolay Nikolov

Portrait Nikolai Nikolov

Topic: Flexible Deployment of Big Data Pipelines on the Cloud/Edge/Fog Continuum 

Started: January 2021

Supervisors: Dr. Dumitru Roman (Senior Research Scientist at SINTEF Digital and Assoc. Professor at University of Oslo, Norway), Dr. Radu Prodan (Professor at University of Klagenfurt, Austria), Dr. Ahmet Soylu (Professor at OsloMet, Norway), Dr. Mihhail Matskin (Professor, Vice Department Head at KTH Royal Institute of Technology, Sweden)

NorwAI Work Package: DATA - Data and Platform for AI

About: Nikolay is a PhD fellow at the University of Oslo and a research scientist in the Smart Data group at SINTEF Digital. His research is focused around novel methods to support the lifecycle of Big Data pipelines processing, enabling their definition, model-based analysis and optimization, simulation, and deployment on top of decentralized heterogeneous infrastructures. In the context of the NorwAI project, he will be working on the topic of enabling the flexible deployment of Big Data pipelines for AI that will support the NorwAI data platform.


Nikolay has been doing applied research related to data management, data integration, data enrichment, big data, and the semantic web since 2014 as part of SINTEF Digital. During the recent years, he has been involved in research, implementation and technical coordination in the context of several national and international research projects in the area of data-driven innovation. Nikolay holds a joint Erasmus Mundus M.Sc. degree in
Service Engineering from Stuttgart University, University of Crete and Tilburg University. Nikolay's main interest and focus is on approaches for supporting the lifecycle of Big Data pipelines on the Computing Continuum.


PhD candidates funded through other sources

PhD candidates funded through other sources


Anna Rodum Bjøru

Anna Rodum Bjøru

 

Topic: Explainable deep bayesian learning

Started: November 2021

Main supervisor: Helge Langseth, Professor, NTNU

Project: EXAIGON

About: Anna Rodum Bjøru is from Trondheim. Her first studies at NTNU were in mathematics back in 2013 before turning to data. For the phd, she is doing research concerning techniques for explainable AI using deep Bayesian methods, with a focus on causal interpretation of learned data representations.

Her master’s in computer science at NTNU was finished in September 2021. The thesis was titled "The importance of disentanglement when learning representations", and considers data representations that disentangle independent generative factors of the data as an approach to generalizable machine learning.

The master thesis came second in the Norwegian Open AI Lab's AI Master's Thesis Award in 2021. The field of disentangled representations has been suggested a promising avenue in search of robust and generalizable machine learning algorithms and increased data efficiency. 
 


Nils Barlaug

Nils Barlaug

 

Portrait Nils Barlaug

Topic: Machine learning and explainability for data integration

Started: August 2019

Main supervisor: Jon Atle Gulla, Professor, NTNU

Project: Industrial PhD, Cognite/NTNU

About: My name is Nils Barlaug. I grew up right outside Oslo and moved to Trondheim to take a master degree in computer science. Before starting my PhD I worked one year at Cognite, a new and fast-growing industrial SaaS company from Norway, on machine learning infrastructure and enabling customers to deploy code with ease. My main interests are machine learning, algorithms & data structures, and practical applications.

I'm doing an industrial PhD in collaboration with Cognite and NTNU. My topic is machine learning and explainability for data integration with focus on entity matching. As the industry digitalize a significant portion of the challenges they meet involves integrating existing data systems and sources. The same business critical entities (equipment, products, customers, etc.) resides in different systems, but without common identifiers. The problem I want to solve is how businesses can disambiguate these entities across system and sources at scale with ease while at the same time trust the result. This calls for techniques and methods from multiple fields such as machine learning, information retrieval, data management, databases, and natural language processing.


Hassan Abedi Firouzjaei

Hassan Abedi Firouzjaei

Topic: Querying and mining location-based social network data

Started: June 2019

Main supervisor: Kjetil Nørvåg, Professor, NTNU

Project: Trondheim Analytica, NTNU Digital Transformation Initiative


Ludvig Killingberg

Ludvig Killingberg

Portrait Ludvig Killingberg

Topic: Bayesian deep learning and reinforcement learning

Started: October 2019

Main supervisor: Helge Langseth, Professor, NTNU


Mateja Stojanovic

Mateja Stojanovic

Portrait Mateja Stojanovic

Topic: Recommender Systems for Enhancing Students' Learning in Higher Education

Started: December 2020

Main supervisor: Özlem Özgöbek, Professor, NTNU


Betül Bayrak

Betül Bayrak

 

Topic: Explainable Case-Based Reasoning

Started: January 2022

Main supervisor: Kerstin Bach, Professor, NTNU

Project: EXAIGON

About: Betül Bayrak is 26 years old and graduated with a Master’s degree in Computer Science from Çankaya University, Turkey. The title of her thesis is “Link Prediction in Knowledge Graphs with Numeric Triples Using Clustering”. While pursuing on her master’s degree, she worked as a teaching and research assistant at Gazi University. Furthermore, she worked as a Research Engineer at Huawei Turkey focusing on recommender systems. Her main interests are artificial intelligence and graph-based applications.


Shiva Shadrooh

Shiva Shadrooh

Topic: Anomaly detection in streaming graphs 

Started: February 2020

Main supervisor: Kjetil Nørvåg, Professor, NTNU

Project: Big data & machine learning (DNB)

 


Yujie Xing

Yujie Xing

Topic: Generative Conversational Agents

Started: January 2021

Main supervisor: Jon Atle Gulla, Professor, NTNU

Project: Big data & machine learning (DNB)


Tu My Doan

Tu My Doan

 

Topic: Political text mining

Started: January 2020

Main supervisor: Jon Atle Gulla, Professor, NTNU

Project: Trondheim Analytica, NTNU Digital Transformation Initiative


Yanzhe Bekkemoen

Yanzhe Bekkemoen

Portrait  Yanzhe Bekkemoen

Topic: Probabilistic approaches to explainable AI and reinforcement learning

Started: October 2019

Main supervisor: Helge Langseth, Professor, NTNU


Shweta Tiwari

Shweta Tiwari

Portrait Shweta Tiwari

Topic: Machine Learning Method for Outlier Detection in Energy Trading

Started: October 2017

Main supervisor: Heri Rampiaro, Professor, NTNU


Stella Maropaki

Stella Maropaki

Protrait Stella Maropaki

Topic: Database systems

Started: April 2016

Main supervisor: Kjetil Nørvåg, Professor, NTNU


More to come

More to come...


Vacancies