We start with a crash course in quantum mechanics, recalling the notions of quantum states, quantum observables in pure and mixed states, and how to measure entanglement. Then we cover independent and entangled states of system components and give some simple examples of bi- and tripartite entangled states of Bell and Greenberg-Haros-Zeilinger. The famous Einstein-Podolsky-Rosen paradox of quantum non-locality will be illustrated with the example of Bell states. Then we shall discuss the relation between entanglement and mixing, quantitative measures of bipartite entanglement, and difficulties arising when these measures are extended to the multipartite case. This will set the stage for exposition of our recent results with A. Mandilara, A. Smilga, and L. Viola on group-theoretic setting of the problem of multipartite entanglement, and how the Cartan decomposition can be employed to define a logarithm of a vector quantity and use it to classify such entanglements. As is often the case in physics, new physical situations require a new and somewhat non-customary mathematical language to express them; here, the language of this kind is provided by the ring of nilpotent polynomials, which will be introduced on a simplest example. The lecture will be concluded with our recent results obtained in collaboration with Grigori Kabatiansky and Aikaterini Mandilara on multipartite entanglement in open quantum systems, whose states are mixed because of openness. We shall extensively use geometric pictures to illustrate the problem and algorithms for its solution.

Existing commercial wireless systems rely on closed and inflexible hardware-based architectures both at the radio frontend and in the core network. These problems significantly delay the adoption and deployment of new standards, impose significant challenges in implementing new techniques to maximize the network capacity and according coverage, and prevent provisioning of truly-differentiated services able to adapt to growing and uneven and highly variable traffic patterns. For these reasons, the research objective of this talk is to propose a new software-defined architecture for 5G and beyond wireless systems, to develop essential enabling technologies to support and manage the proposed architecture, and to showcase its major benefits by designing novel software-defined traffic engineering solutions. In particular, SoftAir, a Wireless Software-Defined Network architecture is proposed and its core architectural principles are studied, including (i) the scalable design of software-defined radio access and (ii) core networks, as well as (iii) new techniques to provide network virtualization. It is demonstrated how this new SoftAir architecture can guarantee essential properties that are at the cornerstone of 5G cellular systems, including the programmability, the cooperativeness, the virtualizability, the visibility, and the openness.

Ian F. Akyildiz, received the B.S., M.S., and Ph.D. degrees in electrical and computer engineering from the University of Erlangen-Nurnberg, Germany, in 1978, 1981, and 1984, respectively. Currently, he is the Ken Byers Chair Professor in Telecommunications with the School of Electrical and Computer Engineering and the Director of the Broadband Wireless Networking Laboratory and Chair of the Telecommunication Group at Georgia Institute of Technology, Atlanta, GA, USA. Since 2007, Dr. Akyildiz is an Honorary Professor with the School of Electrical Engineering at Universitat Politecnica de Catalunya (UPC) in Barcelona, Catalunya, Spain, and founded the N3Cat (NaNoNetworking Center in Catalunya). Since September 2012, Dr. Akyildiz is a FiDiPro Professor (Finland Distinguished Professor Program (FiDiPro) supported by the Academy of Finland) at Tampere University of Technology. He is also the Consulting Chair Professor with King Abdulaziz University, in Jeddah, Saudi Arabia since 2011. He served as the ExtraOrdinary Professor with University of Pretoria, South Africa between 2007-2012. He is the Editor-in-Chief of Computer Networks (Elsevier), and the founding Editor-in-Chief of the Ad Hoc Networks (Elsevier), the Physical Communication (Elsevier), and the Nano Communication Networks (Elsevier). He is an IEEE Fellow (1995) and ACM Fellow (1996). He has received numerous prestigious awards from IEEE and ACM. He also received the 2011 TUBITAK Exclusive Award for outstanding contributions to the advancement of scholarship/research at international level. He also received the Humboldt Research Prize from the Alexander von Humboldt Foundation in Germany, November 2013. He graduated 38 PhD students of whom 28 became very successful Professors. He published more than 500 papers in first rate journals and conferences. His h-index is 90 and total number of citations is 71K+ due to Google Scholar as of May 2015. His current research interests are in 5G Cellular Systems, TeraHertz band communication, nanonetworks, software defined networking, and wireless underground sensor networks.

In the 2011 Open Networking Summit, a leading scientist in the Software Defined Networking (SDN) arena delivered a keynote with a bold title: “the Future of Networking, and the Past of Protocols”. The whole talk was about the importance of finding the “right” platform-independent abstractions so as to get rid of the “a new protocol per problem” era. While recognizing the paramount importance of the “centralized control side” of the SDN paradigm, we nevertheless believe that the today’s de facto reliance of scarcely expressive device-level programming interfaces might severely hinder any attempt to emerge with the above ultimate vision of platform agnostic programmable protocols. Backed up by recent promising results in two widely different networking fields (wireless and wired networks), we promote the usage of eXtended Finite State Machines (XFSM) as an extremely expressive and powerful abstraction to describe complex stateful behavior such as that mandated by protocol design, while retaining platform independency and portability across different network devices and nodes. We specifically discuss how such an XFSM abstraction permits to address portable protocol design in the wireless domain, and we discuss how such a very same (!) abstraction appears viable also as node-level behavioral forwarding specification for wired network switches (and, surprisingly, it appears also backward compatible with the therein state of the art forwarding abstractions such as OpenFlow). Is such recurrence of a same abstraction in widely different domains just a case, or it perhaps implies the possibility to foster a holistic approach to network programmability, irrespective of the networking domain?

Giuseppe Bianchi is Full Professor of Telecommunications at the School of Engineering of the University of Roma Tor Vergata, current chair of the relevant Bachelor/Master teaching programme in Internet Technology engineering, and former chair of the Telecommunications and Microelectronics PhD programme. His research activity, documented in about 180 peer-reviewed papers accounting for more than 9500 Google citations, spans several areas including wireless LANs, privacy and security, design and performance evaluation of broadband networks, network monitoring. His analytical models concerning the performance analysis of 802.11 WLAN networks are well known in the research community. He is editor for IEEE/ACM Trans. on Networking and Elsevier's Computer communication, and area editor for IEEE Trans. on Wireless Communications. He has (co-)chaired more than 10 international IEEE/ACM conferences/workshops, the latest one being IEEE Infocom 2014. He has been involved in more than 10 European funded project, with general and/or technical coordination roles for the projects FP6-DISCREET (privacy in smart environments), FP7-PRISM (privacy-preserving network monitoring), FP7-DEMONS (distributed network monitoring) and FP7-FLAVIA (programmable wireless systems).

Bacterial may be considered as a set of genes, an ordered sequence of genes, and a nucleotide sequence. This allows one to characterize various types of evolutionary events such as gene gains and losses, genome rearrangements, and homologous recombinations (exchange of genome fragments between closely related strains), respectively. Each direction yields mathematical problems that will be described in the lecture.

Dr. Gelfand received his Ph.D. in mathematics in 1993 from the Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, in Pushchino, and his D.Sc. in biology in 1998 from the Research Institute for the Genetics and Selection of Industrial Microorganisms in Moscow. Currently he is the Vice-Director for Science and the head of the Research and Training Center on Bioinformatics at the A.A.Kharkevich Institute for Information Transmission Problems, RAS, and a Professor at the Department of Bioengineering and Bioinformatics of the M.V.Lomonosov Moscow State University. His Howard Hughes Medical Institute-funded project focuses on "Comparative Genomics, Metabolic Reconstruction, and Analysis of Regulation in Bacterial Genomes." Gelfand's primary research areas include comparative genomics, metabolic reconstruction, analysis of regulation in bacterial genomes, and evolution of alternative splicing.

Understanding mechanisms that lead to aging and regulate lifespan is among the most challenging biological problems. Many complex human diseases are associated with aging, which is both the most significant risk factor and the process that drives the development of these diseases. It is clear that the aging process and the lifespan of species can be adjusted. For instance, mammals are characterized by >100-fold difference in lifespan. We employ this diversity in lifespan and the associated life-history traits to shed light on the mechanisms that regulate species lifespan. For this, we utilize methods of comparative genomics to examine the genomes of exceptionally long-lived species and carry out analyses across a panel of mammals and their organs at the levels of gene expression and metabolite concentrations. Aging and its causes remain difficult to define. Different theories posit that aging is caused by molecular damage, genetic programs, continued development, hyperfunction, antagonistic pleiotropy alleles, mutations, incomplete repair, etc. We suggest that these factors have the same conceptual basis and roughly synchronize their impact on fitness, but operate at different levels of biological organization. This model allows integration of aging concepts, provides insights into the origin of aging, and suggest how lifespan is influenced by genetic, environmental and stochastic processes.

Vadim Gladyshev serves as a Professor of Medicine within the Genetics Division at the Brigham and Women’s Hospital of the Harvard Medical School. He received his bachelor's and master's of science degrees in biochemistry from Moscow State University as well as his Ph.D. in biochemistry. Vadim Gladyshev is the director of the Center for Redox Medicine, which is located in the Harvard Medical School New Research Building, and an Associate Member of the Broad Institute. Vadim has published more than 230 articles, edited three books, and chaired Gordon Research and a FASEB summer conferences.

The lecture will address the theoretical foundation and the practical implementation of technology to connect to the brain in order to obtain direct contact information. It will also address the construction of various schemes and algorithms for brain-computer interface, and the results of their testing. In the final part of the lecture will discuss possible options for the use of brain-computer interfaces in medicine and other areas of practical human activity.

Alexander Y. Kaplan, Sc.D., Professor, Head for Laboratory of neurophysiology and brain-computer interface at biological faculty of Moscow State University, an expert and organizer of activities in the field of diagnostics of functional states of the brain of the human operator, human-machine interaction and brain-computer interface, as well as in the development of new methods for analyzing biometric data, mostly - the data recording electrical potentials of the human brain. A.Ya.Kaplan's research works are supported by grants from various agencies and organizations, in particular, grants RHF, RFBR, Skolkovo Foundation, and others. Biomedical cluster of A.Kaplan’s work was awarded the Prize of the Russian Government in the field of science and technology for 2002. The results of his works published more than 150 peer-reviewed scientific publications in Russia and abroad, and are protected by 3 patents. Currently A.Ya.Kaplan is the key developers of effective brain-computer interface in the field of rehabilitation medicine and for the optimization of the human operator work.

Genetically, humans are very closely related to other primates: 99% of our genome is identical to that of chimpanzees and 98% - to the gorilla genome. Sill, in many cognitive aspects, humans are unique.
In our work, we use novel high-throughput technologies to obtain and analyze different types of big biodata from brains of humans, chimpanzees and other primate species. Our results provide some novel insights into the molecular mechanisms separating us from other species.

Philipp Khaitovich completed undergraduate studies in molecular biology at Moscow State University in 1995 and PhD in biochemistry at the University of Illinois at Chicago in 1999. From 2000 till 2006 Philipp worked as a postdoctoral researcher at the Max Planck Institute for Evolutionary Anthropology at the department of Evolutionary Genetics headed by Prof. Svante Pääbo. In September 2006, Philipp Khaitovich took a faculty position at the Institute for Computational Biology jointly established by the Chinese Academy of Sciences and the Max Planck Society in Shanghai China. In 2012 Philipp was promoted to the Institute Director position. He further received Full Professor position at ShanghaiTech University in Shanghai and became a fellow member of Max Planck Society. In 2013 Philipp received the Friendship medal – the highest award given to foreigners in China. In 2014 Philipp joined Skoltech University in Moscow, Russia, as a Full Professor.

In his landmark 1948 paper, Claude Shannon showed mathematically that it should be possible to transmit information reliably at a high rate even in a noisy system, as long as coding over arbitrarily long blocklengths is allowed. A perennial question in information theory is how relevant the asymptotic fundamental limits are when the communication system is forced to operate at a given fixed blocklength. The finite blocklength (delay) constraint is inherent to all communication scenarios. In fact, in many systems of current interest, such as real-time multimedia communication, delays are strictly constrained, while in packetized data communication, packets are frequently on the order of 1000 bits. Despite an obvious practical interest in the nonasymptotic fundamental limits, up until recently, such limits were widely believed to defy analysis. We show that the nonasymptotic fundamental limit of data compression can be closely approximated by a function of just two parameters of the source, namely, the rate-distortion function (Shannon’s asymptotic limit), and the rate-dispersion function, a new parameter of the source that characterizes the stochastic variability of the source at finite blocklength. We discuss a few common communication scenarios where the conventional engineering wisdoms derived from the classical asymptotic analysis fail. In those cases, the new nonasymptotic theory not only tells us what is achievable in principle at a given fixed blocklengh, but also establishes new design guidelines.

Victoria Kostina is an Assistant Professor of Electrical Engineering in California Institute of Technology. She earned her master's in 2006 from the University of Ottawa and her undergraduate degree in applied mathematics and physics in 2004 from the Moscow Institute of Physics and Technology. Victoria Kostina worked as a postdoctoral researcher with Prof. Sergio Verdú in Princeton University, where she completed her PhD and a postdoctoral position in electrical engineering. Her research interests lie in information theory, theory of random processes, coding, and wireless communications. She is particularly interested in fundamental limits of delay-sensitive communications.

The Internet of Things (IoT) has become an important R&D topic in the last years, where things refer to interconnected machines and objects with embedded computing and connectivity capabilities employed for direct integration between the physical world and computer-based systems. While R&D continue for general IoT devices, there are many application domains where very tiny, concealable, and non-intrusive Things are needed. The properties of recently studied nanomaterials, have inspired the concept of Internet of NanoThings (IoNT), based on the interconnection of nanoscale devices. Despite being theoretically an enabler for many applications, the artificial nature of IoNT devices can be detrimental where the deployment of NanoThings could result in unwanted effects on health or pollution. The novel paradigm of the Internet of Bio-Nano Things (IoBNT) has been recently introduced and stems from synthetic biology and nanotechnology tools that allow the engineering of biological embedded computing devices. Based on biological cells and their functionalities in the biochemical domain, Bio-NanoThings promise to enable applications such as intra-body sensing and actuation networks, and environmental control of toxic agents and pollution. The IoBNT stands as a paradigm-shifting concept for communication and network engineering, where novel challenges are faced to develop efficient and safe techniques for the exchange of information, interaction, and networking within the biochemical domain, while enabling an interface to the electrical domain of the Internet. In this talk we will reveal the concept of IoBNT, its peculiarities, and review the enabling technologies and challenges. We will investigate molecular communications and its applicability for IoBNT. The talk will be concluded with analysis of challenges for bio-cyber interfaces, the set of processes necessary to translate information from the biochemical domain of Bio-NanoThing networks to the Internet cyber-domain, which is based on electrical circuits and electromagnetic communications, and vice versa.

Y. Koucheryavy is a full professor and lab director in the Department of Electronics and Communications Engineering at the Tampere University of Technology (TUT), Finland. He received his Ph.D. degree (2004) from the TUT. He is the author of numerous publications in the field of advanced wired and wireless networking and communications. His current research interests include various aspects of heterogeneous wireless communication networks and systems, the Internet of Things and its standardisation, and nano communications. He is an associate technical editor of IEEE Communications Magazine and an editor of IEEE Communications Surveys and Tutorials.

Decoding algorithms suitable for arbitrary linear block codes are considered. Lower bounds on the complexity Maximum Likelihood (ML) decoding for almost all linear codes will be derived. Relationships between ML decoding problem and some other combinatorial problems with applications to communication and cryptography will be established and discussed.

Professor Eugene A. Krouk has graduated from Leningrad Institute of Aviation Instrumentation in 1973. He receive Ph.D. degree in 1978 and Doctor of Science degree in 1999. He receive the academic status of Associate Professor in 1990 and status of Professor in 2004. From 1974 till now he works in Saint-Petersburg State University of Aerospace Instrumentation. In 2001 the Systems Security Department was developed with active participation of Krouk E.A., and he became the head of this Department from the moment of its creation. In 2005 Krouk was elected as Dean of the Information Systems and Data Protection Faculty. From 2004 he is also the director of the Computer Security Institute. From 2007 he is ia Director of ICT Academy. In 2008 Krouk obtained the title Honoured Scientist of Russian Federation. Professor Krouk is an outstanding scientist in the field of theory and designing of infocommunication systems and technologies. His works in coding theory, cryptography, data communication theory is known both in Russia and abroad. He is an author of more than 120 printed works and 5 books.

It is well-known that 90% of the digital data in the world has been created in the last two years. New facilities to gather, store and process data caused new user requirements on the one hand, and new mathematical and computer science problems on the other hand. Today we need new methods and new algorithms that allow obtaining useful information from raw data. The keynote will provide the state-of-the-art analysis in this area.

Alexander Kuleshov is an academician of the Russian Academy of Sciences, a specialist in the field of information technologies and mathematical modeling, a director of the Institute for Information Transmission Problems. He is a member of the international publishing council of the journal "Problems of the theory and practice of control", chairman of the Scientific Council IITP, chairman of the doctoral dissertation council at IITP, a member of the Coordination Council on Innovation and Intellectual Property of Russian Academy of Sciences. Alexander Kuleshov is the author of 75 scientific works, including 6 monographs.

I. Introduction. The Additive Regression Model.
The talk introduces into statistical nonparametric models where several nonparametric components/functions have to be estimated. This class of models is very important in applications because the existence of several nonparametric components allows a very flexible and accurate modeling of complex data structure. On the other side, the use of low dimensional functions enables an efficient statistical estimation and circumvents the "curse of dimensionality". Statistical inference in these models requires an asymptotic distribution theory of the nonparametric estimators. Such a theory allows to construct pointwise and uniform confidence intervals for the nonparametric functions and for test procedures on hypothesis of these functions. The leading example of this talk is the additive nonparametric model where the observations are given as the sum of values of nonparametric functions plus noise. It will be shown that nonparametric estimators can be constructed by solving linear empirical integral equations. This formulation allows to develop a complete asymptotic theory including the discussion of optimality issues.
II. Nonlinear Models. A Continuous Version of the Chain Ladder Model from Insurance Mathematics
In this talk we consider more complex nonparametric models than in the first talk. Again we assume that the model contains several nonparametric components but now we allow that the nonparametric components enter into the model non-linearly. We illustrate this class of models by looking at a model coming from insurance mathematics. The chain-ladder technique is an among actuaries widespread standard method for the prediction of outstanding claims. The basic model is discrete and the use of the method is typically not underpinned by statistical theory. We consider continuous generalisations of the chain-ladder technique that allows a clear statistical formulation and asymptotic theory. This will be done for several specifications of the model. In this model estimators are given by non-linear empirical integral equations. The theory is illustrated by data examples.

Dr. Enno Mammen is the full professor in Department of Economics, University of Mannheim, Mannheim, Germany. He completed his PhD in University of Heidelber. Author of more than 70 papers in the field of mathematic statistics and remarkable studies in theoretical econometric. In 1989 Dr. Mammen obtained Heinz-Maier-Leibnitz Prize and got a full professor position. In 1992 he published his research “ When Does Bootstrap Work? Asymptotic Results and Simulations” importance of this paper in statistical analysis hardly can be underestimated.

Understanding how metabolic reactions, cell signaling, and developmental pathways translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS) statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular biology approach directly ties gene function to phenotype through gene regulatory networks (GRNs). Using natural variation in allele-specific expression, GWAS and GRN approaches can be merged into a single framework via structural equation modeling (SEM). This approach leverages the myriad of polymorphisms in natural populations to elucidate and quantitate the molecular pathways that underlie phenotypic variation. The SEM framework can be used to quantitate a GRN, evaluate its consistency across environments or sexes, identify the differences in GRNs between species, and compare health and disease states. Here, it will be illustrate with recent data combining the analyses of body weight, plus protein, sugar, and triglyceride content in a reference panel of natural D. melanogaster.

Sergey Nuzhdin combines expertise in Population Biology (Professor in Evolution and Ecology, UC Davis, 1997-2007) and in Molecular and Computational Biology (USC, 2007-present). He has published more than 100 papers in peer-review journals, including PLoS Biology, Science, Nature Genetics, and PNAS; has trained over a dozen of independent investigators; and is serving on several editorial boards, and on NIH panels.

Many stochastic problems can be reduced to deterministic ones with very high dimensionality, and storage and operations in such high dimensions are not possible due to the curse of dimensionality. The concept of tensor methods is to use algebraic approximation tools to reduced the dimensionality by utilizing data-sparse multidimensional arrays representations. We will cover some of basic concepts of numerical tensor methods (canonical format, Tucker format, Tensor-Train format) and show some perspective application for solving stochastic problems, including multidimensional integrals, numerical solution of stochastic partial differential equations and many more.

Central pattern generators (CPGs) are capable to produce rhythmic patterned outputs without any rhythmical inputs from outside. CPGs have been shown to underlay most rhythmic behaviors. We will discuss the role of endogenous properties of individual cells and intercellular connections in CPG function in different organisms (from nematodes and mollusks to mammals) in rhythmic behaviors of diverse period range (from milliseconds to hours).

Yuri V. Panchin, Ph.D., Dr.Sc., Head for Laboratory #12 IITP RAS- “Information processing on cellular and molecular level”. He is also working at Moscow State University A.N. Belozersky Institute Of Physico-Chemical Biology. He has published more than 100 papers in peer-review journals on neuroscience, developmental biology, molecular biology, physiology and bioinformatics.

In this talk, we explore applications of (i) online stochastic optimization and (ii) clustering techniques to the design of radio resource allocation algorithms in wireless systems. (i) We first present recent theoretical developments for structured multi-armed bandit problems, a class of online stochastic optimization problems, and show how these results can be applied to devise optimal radio resource algorithms (such as rate adaptation, and channel selection schemes) in systems where maintaining precise estimates of channel conditions between transmitters and receivers is impossible or too costly. (ii) We then provide a brief survey of recent clustering techniques, including non-parametric bayesian tools. We explain how to leverage these techniques to design efficient algorithms predicting the mobility or channel conditions of mobile users, that in turn may be exploited to enhance radio resource allocation schemes.

Alexandre Proutiere received the Graduated degree in Mathematiques from Ecole Normale Superieure, Engineering degree from Telecom Paris, Engineer from Corps des Mines and Ph. D. in Applied Mathematics from Ecole Polytechnique. From 2000 to 2006 he was the Research Engineer at France Telecom R&D. Dr. Proutiere was the Invited lecturer and researcher at the computer science department ENS Paris from 2004 to 2006. He worked as researcher at Microsoft Research (Cambridge) from 2007 to 2011. In 2009 he received the ACM Sigmetrics rising star award. He also won the ACM best papers awards at Sigmetrics 2004 and 2010, and Mobihoc 2009.

Fluid limit was invented for finding stability (ergodicity) conditions for stochastic processes describing queueing networks. It means that the service times of all the customers tend to zero while the queues tend to infinity. In the limit, instead of stochastic process describing the random trajectories of interacting customers which travel over the network one obtains much more transparent deterministic fluid dynamics. Finding the stability conditions for network amounts to finding the conditions for fluid devastation for corresponding fluid dynamics. The investigation of fluid limit of queueing networks leads to important and surprising results.
On the other hand, the fluid limit does not give us any information about the properties of stationary distributions of the queues of the network, it gives us the conditions of its existence only. In mean-field limit the increasing sequence of networks with tending to infinity number of uniformly interacting nodes is considered. The natural hypothesis described the staionary distribution of such limiting infinite network is so-called Poisson Hypothesis. The study of stochastic processes arising at simultaneously application of fluid and mean-field limit gives us new unexpected results.

Aleksandr Rybko, doctor of science in Math started his career in Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute). Completed his PhD in Mathematics, Institute of Electronic Engineering in January 1984. Leading Researcher at the IITP RAS since 1995. Author of more than 50 papers. Awarded with numerous grants and fellowships. His scientific interests lie in Theory of Probability, Random Processes, Mathematical Physics, Theory of Interacted Particle Systems, Queuing Networks, application of the Theory of Markov Processes with Local Interactions to Networks with a large number of queues, Asymptotical Properties of Queuing Networks.

We start with a simple introduction to the linear network coding and show that it requires subspace codes. Nearly optimal subspace codes can be constructed using Gabidulin codes in rank metric. We will show that interleaving or equivalently direct sum of these codes allows for both: to decrease an overhead in the transmitted packets and to increase the decoding radius. Then we show and compare two methods of efficient decoding these interleaved codes. First is a classical method based on a syndrome decoding. Second is an interpolation-based decoding algorithm, which can be used as a list decoder or as a probabilistic unique decoder that outputs a unique solution with high probability.

Vladimir Sidorenko.
Vladimir Sidorenko was born in Krasnoyarsk, Russia. He received the M.S. degree in electrical engineering in 1972 and the Ph.D. degree in mathematics in 1975 both from the Moscow Institute for Physics and Technology.
From 1975 to 1983 he was with Computer center of 4th Department of Russian Health Ministry, first as a senior engineer and then as the vise director of the Computer center. In 1983 he joined the Institute for Information Transmission Problems (IITP), Russian Academy of Sciences, Moscow, as a senior research fellow. From 2003 till 2014 he was a senior researcher of Institute of Communications Engineering, Ulm University, where he reserved In centi award for the best lecturing. From January 2015 he is a senior researcher at Institute for Communications Engineering of Technical University of Muenchen, Germany, on leave from IITP. As invited researcher he worked at University of Lund, Sweden, Technical University of Darmstsdt, Germany, University of Lancaster, UK, and University of Aveiro, Portugal. His research interests include coding theory, telecommunications, signal processing, cryptology, and applications. He has published more than 120 research papers in these fields.

Hannes Bartz.
Hannes Bartz received his Dipl.-Ing. degree in Electrical Engineering and Information Technology from Technische Universitaet Muenchen, Germany in 2010.
During his undergraduate studies he worked on implementation of error correction schemes for Wireless Sensor Networks and Network Coding. In 2011 he joined the Institute for Communications Engineering at TUM (Prof. Gerhard Kramer) where he is involved in research on efficient error-erasure correction coding strategies for network coding.
Since 2011, Hannes Bartz is the Program Manager of the MSCE Program (Master of Science in Communications Engineering) and responsible for its organization and management.

The paper offers a new method of selecting an active subset of features based on the idea of multiple testing. The procedure selects a smallest subset for which the hypothesis of «no information outside» is accepted. We prove some oracle bounds for this choice and show how the detection quality depends on the signal-to-noise ratio.

Vladimir Spokoiny is a full professor in Humbolt University in Berlin Head of the research group "Stochastic Algorithms and Nonparametric Statistics" of the Weierstrass Institute for Applied Analysis and Stochastics, professor in Moscow Institute of Physic and Technology. Graduated from Moscow Institute of Railway Engineering, Department of Technical Cybernetics, Moscow, Russia. Head of Laboratory of Structural Methods of Data Analysis in Predictive Modeling Moscow Institute of Physics and Technology. Author of a numerous articles in mathematical statistic.

In this lecture the history of our understanding of human molecular biology from the age of enlightenment till today will be presented. The early renaissance academics were multimodal scientists with knowledge in many areas. Following in their footsteps however, science became fragmented, with specialists working in their own areas. The genome project demonstrated the need for convergence of the work of many scientists of different areas of biology, physics, chemistry, and bioinformatics. In the last quarter century the golden age of neuroscience has arrived, progressing from the “decade of the brain” (1990-2000) to multiple international projects including “Enigma.” We have learned more about the thinking brain in the last 25 years than in all of human history. Researchers exploring the potential power of the human cerebrum, will foster new achievements in endeavors to understand the epigenetics of the brain and the interconnections of the human mind with computer science and robotics. This will lead to our ability to correct the deficiencies of the human body.

Dr. Vladimir Zelman graduated from the Novosibirsk Med Inst, Novosibirsk, Russia in 1959. Since 1961 head of neiroanaththesiology department in Neurology Institute RAMS in Moscow. Moved to USA in 1975. He works in Los Angeles, CA and specializes in Anesthesiology. Dr. Zelman is Professor and Clinical Chair of Anesthesiology, Professor of Neurology and Neurological Surgery with Keck Medical Center Of USC, LAC USC Medical Center and USC Norris Cancer Hospital. Member of USC Program in Neural, Informational and Behavioral Sciences. Professor and honorary member of Russian Academy of Medical Science.