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Dr. Andrei Tchernykh

Dr. Andrei Tchernykh

Bio:

Prof. Andrei Tchernykh is engaged in an extensive research on grid and cloud research addressing resource optimization, both, theoretical and experimental, security, uncertainty, scheduling, multi-objective optimization, heuristics and meta-heuristics, adaptive resource allocation, energy-aware algorithms and Internet of Things (http://usuario.cicese.mx/~chernykh/).

He is holding a full professor position in computer science at CICESE Research Center, Ensenada, Baja California, Mexico. He is chairing the Parallel Computing Laboratory at CICESE, International Laboratory of Problem-Oriented Cloud Computing Environment at South Ural State University, Russia, and Leading Researcher at Institute for System Programming of the Russian Academy of Sciences.

He is Doctor in Computer Science from Institute of Precision Mechanics and Computer Engineering of the Russian Academy of Sciences. He gained industrial experience as supercomputer design team leader in Advance Technical Products Corp, and Supercomputer Design Department of Electro-Mechanical Enterprise, Russian leaders in HPC design and development.

Tchernykh leads a number of research projects and grants in different countries funded by CONACYT, NSF, ANII, Ochoa, INRIA, FNR, UC MEXUS, DAAD, LAFMI, UJF, INPG, REDII, FUMEC, etc. He has published about 200 papers, and served as a TPC member and general co-chair of more than 240 professional peer reviewed conferences. He has graduated 36 Ph.D. and M.S. students, and served as the External Examiner for Ph.D. programs in India, Malasia, Germany, Luxembourg. México, and France.

His scientific expertise is awarded by Level 2 in National System of Researchers (SNI), Mexico, Global Scholars Fellow at Tsinghua University (China), German Academic Exchange Service fellowship at University of Göttingen, Dortmund University, Severo Ochoa fellowship at Barcelona Supercomputing Center (Spain), etc. He is editorial board member of several journals, such as International Journal of Metaheuristics, Supercomputing Frontiers and Innovations, Computational Mathematics and Software Engineering, Proceedings of ISP RAS, etc. He also has served as a guest editor for several special issues including International Journal of Approximate Reasoning (Elsevier), ACM Springer Mobile Networks & Applications (MONET).

Resumen:

Intelligent data management in clouds: How to protect our data by adaptive security.

Managing information in many areas such as smart city, smart industry, smart medicine, etc. will be strongly associated with for the Internet of Things (IoT) and Industrial Internet of Things.

Despite many advantages of the fog-edge-cloud computing, they bring high risks of confidentiality, integrity, and availability associated with the loss of information, denial of access for a long time, information leakage, conspiracy, etc. One of the challenges is to design reliable secure systems that mitigate the uncertainty of the occurrence of technical failures, data security breaches, collusion, etc.

In this talk, we discuss methods and algorithms for supporting security expectations and requirements of cloud data storage under unknown risks that are difficult or impossible to anticipate and cannot be managed proactively. They are based on mechanisms of adjustable and adaptive security, reliability, and redundancy to cope with different user-provider preferences, workloads, system state, errors, and fog-edge-cloud properties, etc.

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