Ioanna Miliou Senior Lecturer

Contact

Name and title: Ioanna MiliouSenior Lecturer

Mail: ioanna.miliou@dsv.su.se
Phone: +468161608

ORCID0000-0002-1357-1967 Länk till annan webbplats.

Workplace: Department of Computer and Systems Sciences Länk till annan webbplats.

Visiting address Nodhuset, Borgarfjordsgatan 12

Postal address Institutionen för data- och systemvetenskap164 25 Kista

Research group

Data Science Research Group

The Data Science Research Group focuses on core data science research, as well as on applications where data science can provide insights for decision making. We formulate novel data science problems and develop algorithmic methods and methodological workflows.

Links

About me

I am Ioanna Miliou, a Senior Lecturer in Data Science. I am a member of the Data Science Research Group at the Department of Computer and Systems Sciences (DSV) of Stockholm University. I hold a Ph.D. in Computer Science from the University of Pisa, Italy, and a diploma in Electrical and Computer Engineering from the National Technical University of Athens, Greece. 

  • Current course at Stockholm University:
    • FODS: Foundations of Data Science (Fall 2024-2025)
  • Past courses at Stockholm University:
    • DATM: Data Mining (Spring 2024-2025)
    • DSHI: Data Science for Health Informatics (Spring 2023-2024)
  • Supervisor at the graduate level in Data Science and Health Informatics

Research overview

My research interests lie in the fields of Data Science for Social Good, Nowcasting, and Forecasting, with the use of Big Data Analytics, Data Mining, and Machine Learning. Using Big Data deriving from everyday life as external proxies, it is possible to nowcast and forecast the evolution of phenomena whose study relies only on historical data or data that come with a significant lag. I work mainly on epidemics, healthcare, peace, and sentiment.  

 

PhD students

Current:

  • Franco Rugolon, Ph.D. student in Data Science (co-supervisor)
  • Lena Mondrejevski, Ph.D. student in Data Science (co-supervisor)

Graduated:

  • Maria Bampa, Ph.D. in Data Science (2024, co-supervisor)

Projects

A3S: AI-based Asthma App using Spirometer: a collaboration with Magnus Jansson Saikat Chatterjee Björn Nordlund

OrganoFeed: a collaboration with Thomas E. Winkler

Let's talk about non-verbal communication: a collaboration with Stephan Hau, Håkan Fischer, Lennart Högman, and Petri Laukka

Socioemotional perception and recognition in single individuals: a collaboration with Håkan Fischer and Petri Laukka


OrganoFeed

The OrganoFeed project intends to make lab-grown mini-organs – organoids – more reliable for research. Using AI and microfluidics, it fine-tunes the organoid environment in real time, reducing errors. This could improve drug testing and even help replace animal experiments.

A3S: AI-based Asthma App using Spirometer

The A3S project aims to create an AI-powered asthma app with a spirometer, using explainable AI to analyze patient data and guide decisions. It focuses on transparent, person-centered care to help people manage asthma and reduce health risks.

Patient and Public AI-assisted Interventions

With better descriptions of a patient’s state and history, more efficient recommendations can be provided. We explore how AI tools can be put to practical use in healthcare. We focus on complex and multimodal data and use cases such as COVID-19 public health interventions or patient phenotyping for adverse drug events, sepsis, or cancer.

Contact

Name and title: Ioanna MiliouSenior Lecturer

Mail: ioanna.miliou@dsv.su.se
Phone: +468161608

ORCID0000-0002-1357-1967 Länk till annan webbplats.

Workplace: Department of Computer and Systems Sciences Länk till annan webbplats.

Visiting address Nodhuset, Borgarfjordsgatan 12

Postal address Institutionen för data- och systemvetenskap164 25 Kista

Research group

Data Science Research Group

The Data Science Research Group focuses on core data science research, as well as on applications where data science can provide insights for decision making. We formulate novel data science problems and develop algorithmic methods and methodological workflows.

Links

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