Nima Dokoohaki is a data scientist and he is currently affiliated with Accenture Nordics Applied Intelligence. In addition, he maintains collaboration with a research group at Software and Computer Systems department of Royal Institute of Technology (KTH) as an external advisor. His research interests include trust and privacy, applied machine learning, social computing and recommendation systems. He received his Ph.D. in information and communications technology (ICT) in 2013. The main theme of his research was how to understand and leverage the notion of Social Trust so online service providers can deliver more transparent and privacy preserving analytical services to their end users. His research has been backed by European projects funded from EU Framework Programme 7 and Horizon 2020 framework programs, as well as distinguished public funding organizations including Swedish Research Council and Vinnova. In 2014, he received a distinguished fellowship from the a European Research Consortium for Informatics and Mathematics (ERCIM). He has published over 30 peer-reviewed articles. In addition to two best paper awards, he has been interviewed for his visible research and his lecture has been broadcasted on Swedish public television. An ACM professional member, he is a certified reviewer for prestigious Knowledge and Information Systems (KAIS) as well as occasional reviewer for recognized international venues and journals.
Co-Edited Book together with Nitin Agarwall and Sepril Tokdemir
Emerging Research Challenges And Opportunities in Computational Social Network Analysis and Mining,
Published as part of Lecture Notes in Social Networks (LNSN) by Springer Nature, 2018.
Shatha Jaradat, Nima Dokoohaki, Kim Hammar, Ummal Wara, Mihhail Matskin
Dynamic CNN Models For Fashion Recommendation in Instagram
To appear in proceedings of The 11th IEEE International Conference on Social Computing and Networking (SocialCom 2018), 11-13 Dec. 2018, Melbourne, Australia .
Kim Hammar, Shatha Jaradat, Nima Dokoohaki, Mihhail Matskin
Deep Text Mining of Instagram Data Without Strong Supervision
To appear in proceedings of 2018 IEEE/WIC/ACM International Conference on Web Intelligence., Santiago Chile, 2018.
Shatha Jaradat, Nima Dokoohaki, Mihhail Matskin, Elena Ferrari
Learning What to Share in Online Social Networks using Deep Reinforcement Learning
In Machine Learning Techniques for Online Social Networks. Lecture Notes in Social Networks., Springer, 2018.