Biography
Sanja Šćepanović is a research scientist at Bell Labs, Cambridge in the Social Dynamics group led by Daniele Quercia. She completed her PhD at Aalto University, Finland in the Data Mining group with Prof. Aristides Gionis. Her thesis titled Data Science for Sociotechnical Applications was co-supervised by Prof. Pan Hui, and Prof. Jukka K. Nurminen. She researches health through social networks and mobile sensing, and urban outcomes using remote sensing. She also holds a business and innovation doctoral degree from the EIT Digital Academy. During her PhD time, she visited CERN and TU Delft. She is an alumna of International Space University. Her industry experiences include a startup in Silicon Valley, and ICEYE – a startup in Finland building the world’s first microsatellite SAR radar constellation.
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- PhD, Computer Science, Aalto University, Finland, 2014-2018.
- Doctoral Degree in Innovation and Entrepreneurship Education, EIT Digital Academy, Belgium, 2014-2018.
- Space Studies Program, International Space University, at Florida Institute of Technology and NASA Kennedy Space Center, 06-08 2012.
- Masters of Science (double-degree), NordSecMob, Aalto University, Finland and University of Tartu, Estonia, Double-Degree, 2009-2011.
- Diploma in Theoretical and Applied Mathematics, University of Montenegro, 2003-2008.
- Šćepanović, Sanja, Aiello, Luca, Zhou, Ke, Joglekar, Sagar, and Quercia, Daniele. “Health Indices from Online Symptom Taxonomy.” Accepted for publication in Proceedings of the International AAAI Conference on Web and Social Media (ICWSM 2021).
- Šćepanović, Sanja, Antropov, Oleg, Laurila, Pekka, Rauste, Yrjö, Ignatenko, Vladimir, & Praks, Jaan. (2021). Wide-Area land cover mapping with sentinel-1 imagery using deep learning semantic segmentation models. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 10357-10374.
- Šćepanović, Sanja, Joglekar, Sagar, Law, Stephen, and Quercia, Daniele. “Jane Jacobs in the Sky: Predicting Urban Vitality with Open Satellite Data.” Accepted for publication in Proceedings of the ACM on Human-Computer Interaction (CSCW 2021).
- Šćepanović, Sanja, Enrique Martin-Lopez, Daniele Quercia, and Khan Baykaner. "Extracting medical entities from social media." In Proceedings of the ACM Conference on Health, Inference, and Learning (ACM-CHIL 2020) (pp. 170-181), April 2020.
- Bondareva, Erica, Constantinides, Marios, Eggleston, Michael S., Jabłoński, Irineusz, Mascolo, Cecilia, Radivojevic, Zoran, & Šćepanović, Sanja (2022, July). Stress Inference from Abdominal Sounds using Machine Learning. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 1985-1988). IEEE.
- So, Wonyoung, Bogucka, Edyta P., Šćepanović, Sanja, Joglekar, Sagar, Zhou, Ke, and Quercia, Daniele (2020). “Humane Visual AI: Telling the Stories Behind a Medical Condition.” IEEE Transactions on Visualization and Computer Graphics (InfoVIS 2020).
- Šćepanović, Sanja, Martijn Warnier, and Jukka K. Nurminen. “The role of context in residential energy interventions: A meta review.” Renewable and Sustainable Energy Reviews, Elsevier, Volume 77, 2017, Pages 1146-1168 (2017).
- Šćepanović, Sanja, Igor Mishkovski, Pan Hui, Jukka K. Nurminen, and Antti YläJääski. “Mobile phone call data as a regional socio-economic proxy indicator.” PloS One 10, no. 4 (2015).
- Šćepanović, Sanja, Igor Mishkovski, Bruno Gonçalves, Nguyen Trung Hieu, Pan Hui. “Semantic homophily in online communication: evidence from Twitter.” Online Social Networks and Media 2C (2017) pp. 1-18, Elsevier.
- Organizing Team: Track Lead for ACM-CHIL, Co-chair for Responsible AI4EO session at IGRASS
- PC/Reviewer: TheWebConf, ICWSM, CSCW, ISGT-Europe, SocInfo, TKDD, Remote Sensing of Environment
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