Professor Andrzej Cichocki graduated from the Warsaw University of Technology, Poland, where he obtained his PhD and Doctor of Science degree (Habilitation) in Electrical Engineering and Computer Science. He received prestigious Alexander Humboldt and DFG Fellowships in Germany (University Erlangen-Nuernberg) in 1984-1994.
Currently he is working in the area of artificial intelligence for biomedical applications. Andrzej served as a Senior Team Leader and Head of the Laboratory for Advanced Brain Signal Processing at RIKEN Brain Science Institute, the leading research organization in Japan and also holds a position of Visiting Professor in universities in Poland, Japan, China and in the Systems Research Institute of the Polish Academy of Science.
Professor Cichocki is a holder of numerous patents and software developments and author of highly cited and well-known publications and 6 monographs in English (three of them translated into Chines). According to Google Scholar he has h-index 100 with more than 47,000 citations. Dr. Cichocki is a winner of numerous awards and prizes for his scientific achievements, awards for best conference presentations and best journal publications, e.g., the paper about tensors published in the IEEE Signal Processing Magazine (2015) and in Entropy about alpha-beta divergences (2014 and 2015). He is one of the most cited Polish scientist in area of AI, Computer Science and Engineering.
Under the guidance of Professor Cichocki the new Laboratory “Tensor Networks and Deep Learning for Applications in Data Mining” is established at SKOLTECH. It won the fifth competition for the Russian Federation Government grants for state support in 2017-2021 of scientific research conducted under the supervision of leading scientists at Russian universities and scientific organizations (“Megagrant”) with the total funding 90 million Rubles. The mission of the Laboratory is to perform cutting-edge opened research in the design and analysis of deep neural networks, tensor decomposition, tensor networks and multiway component analysis for biomedical applications and for improving quality of life. He is Fellow of IEEE from 2013.
His research focus on
1. AI, especially Deep Neural Networks, Unsupervised and Supervised Algorithms
2. Tensor Networks and Tensor Decomposition for Machine Learning and Big Data
3. EEG Brain Computer Interfaces, Human Computer Interactions and Human Cooperation
4. Signal/Image Processing and Machine Learning Algorithms
5. Portfolio Optimization and Time Series Analysis
6. Time Series Forecasting Using Deep Neural Networks and Machine Learning
7. Humanoid Robotics and Human Robot Interactions
Selected List of publications in 2016-2020 with the SKOLTECH affiliation
Peer-reviewed journal Publications (Web of Science)
Research Monographs (Books in English two of the translated into Chinese)
Recent presentations on international conferences:
Awarded IEEE Fellow in 2013.
Received doktorat honoris causae in Nicolaus Copernicus University (UMK), Torun, Poland in 2017.
The best paper award in 2019 in IEEE Signal Processing Magazine
for the paper “Tensor decompositions for signal processing applications: From two-way to multiway component analysis”, coauthored by A. Cichocki, D. Mandic, L De Lathauwer, A.H. Phan, Q. Zhao, C. Caiafa, G, Zhou.
The best paper award in Journal Entropy in 2015
for the paper “Generalized Alpha-Beta divergences and their application to robust non-negative matrix factorization” Entropy 2011, 13(1), 134–170; coauthored by A. Cichocki, S. Cruces and S. Amari doi:10.3390/e13010134 http://www.mdpi.com/1099-4300/17/2/882/htm
The Best paper award in Journal Entropy for 2014 for the paper coauthored by Andrzej Cichocki and Shun-ichi Amari,
“Families of Alpha- Beta- and Gamma- Divergences: Flexible and robust measures of similarities”
APNNA Best Paper Award for the paper coauthored by Yunjun Nam, Qibin Zhao, Andrzej Cichocki, and Seungjin Choi “A tongue-machine interface: Detection of tongue positions by glossokinetic potentials,” in Proceedings of the International Conference on Neural Information Processing (ICONIP-2010), Sydney, Australia, November 22-25, 2010.
Excellent ICONIP Paper Award 2016 for the paper couthored by Namgil Lee, Anh-Huy Phan, Fengyu Cong, Andrzej Cichocki. “Nonnegative tensor train decompositions for multi-domain feature extraction and clustering”
ФИО: Чихоцкий Анджей Станислав
Занимаемая должность (должности): Профессор
Преподаваемые дисциплины: –
Ученая степень: Ph.D в области электротехники и информатики – 1976; доктор наук в области электротехники и информатики – 1982, Варшавский политехнический университет
Ученое звание: нет
Наименование направления подготовки и/или специальности: Электротехника и информатика
Данные о повышении квалификации и/или профессиональной переподготовке: нет
Общий стаж работы: Более 44 лет
Стаж работы по специальности: 44 года