Vagan
Terziyan
Professor
in Distributed Systems, Dr. (Habil.) Tech. (Faculty
of Information Technology, University of
Jyväskylä),
Head of Collective
Intelligence research group (former Industrial
Ontologies Group)
Head of Artificial Intelligence (International Master
Program),
Head of COIN: Cognitive Computing and Collective
Intelligence (International Master
Program),
Former head of WISE: Web Intelligence and Service
Engineering (International
Master Program),
Former vice-head of
MoTeBu:
Mobile Technologies for Business (International
Master Program),
MC member in ICT COST Action
IC1302 (KEYSTONE:
Semantic Keyword-based Search on Structured Data Sources),
MC member in CA COST Action CA16116 (WearableRobots:
Wearable Robots for Augmentation, Assistance or Substitution of Human Motor
Functions),
Visiting Professor
of AI
Department, Kharkiv National University of
Radio Electronics
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CV
Publications Projects Research Group IOG Research
Group CI Lectured Courses
60th Anniversary lecture: “COIN: Bridging Human
and Machine Learning for the Needs of Collective Intelligence Development”.
International Master Program: Artificial
Intelligence” (welcome to apply!).
International Master Program: COIN: Cognitive Computing and Collective
Intelligence (is finishing),
International Master Program: WISE:
“Web Intelligence and Service Engineering”
(has finished);
International Master Program: MoTeBu: “Mobile Technologies and Business” (has
finished);
Vision on the Mission of
University Education in General and the eEducation in
particular;
Educational Policy, Quality Assurance and its
IT Support (TRUST: Semantic Portal for
Quality Assurance) related interests; Inauguration Lecture (Full
Professor);
Video Interview
with Vagan Terziyan Article about Vagan Terziyan
in “Helsingin Sanomat” (20.09.2003)
Profile of Vagan
Terziyan in Google Scholar Citations
Vagan
Terziyan Academic Genealogy
Vagan
Terziyan at public academic portals:
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Read
some interesting latest articles from Vagan Terziyan:
Terziyan,
V., Malyk, D., Golovianko,
M., & Branytskyi,
V. (2022). Hyper-Flexible Convolutional Neural Networks
Based on Generalized Lehmer and Power Means. Neural Networks, 155, 177-203. Elsevier. https://doi.org/10.1016/j.neunet.2022.08.017
Golovianko,
M., Gryshko, S., Terziyan, V., & Tuunanen, T. (2022). Responsible
Cognitive Digital Clones as Decision Makers: A Design Science Research Study. European Journal of
Information Systems. https://doi.org/10.1080/0960085X.2022.2073278
Terziyan,
V., & Kaikova, O. (2021). Neural Networks with Disabilities: An Introduction to Complementary
Artificial Intelligence. Neural Computation, 34(1), 255-290. MIT Press Direct. https://doi.org/10.1162/neco_a_01449
Branytskyi,
V., Golovianko, M., Gryshko, S., Malyk, D., Terziyan, V., & Tuunanen, T.
(2022). Digital
Clones and Digital Immunity: Adversarial Training Handles Both. International Journal
of Simulation and Process Modelling, 18(2), 124-139. Inderscience
Publishers. https://doi.org/10.1504/IJSPM.2022.10048910
Terziyan,
V. (2017). Social
Distance Metric: From Coordinates to Neighborhoods, International Journal of
Geographical Information Science, 31
(12), 2401-2426. Taylor & Francis. https://doi.org/10.1080/13658816.2017.1367796
. (Find Brief
Description of the Social Distance Metric here.)
Read also our pre-publication draft, where we
explore the potential of the “Ignorance Learning”, i.e., discovering the voids
within the data spaces and using them to improve the classification
performance: Terziyan, V., and Nikulin, A. (2019). Ignorance-Aware Approaches and
Algorithms for Prototype Selection in Machine Learning, arXiv: 1905.06054. Published later as: Terziyan, V., & Nikulin, A. (2021). Semantics of Voids within Data: Ignorance-Aware
Machine Learning. ISPRS International Journal of
Geo-Information,
10(4), 246. https://doi.org/10.3390/ijgi10040246
Some
hobbies of Vagan Terziyan:
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