TRUSTWORTHY AI
/TRANSPARENCY
/ROBUSTNESS
/SUSTAINABILITY
1-3 JULY 2020 _ MOSCOW _ SKOLTECH
We bring together scientists from various fields to address the problems of AI's trustworthiness in numerous AI application, ranging from engineering disciplines to medical diagnostics and legal issues. Progress requires a major step-change, along with the holistic approach.

The conference will be focused on AI trustworthiness in mathematical modelling (surrogate modelling and hybrid modelling), reinforcement learning, adversarial networks, sustainability of AI, including problems of transfer learning and data fusion, and AI's resilience. AI standardisation, verification, testing, ethical issues, and neuromorphic systems will be a part of the conference's general theme.
The emergent trends and global aspects of the AI need a strong foundation. Even a formulation of the trustworthiness of the AI problem requires rigorous scientific language and interdisciplinary expertise.
Maxim Fedorov
Professor, Skoltech Vice-President for Artificial Intelligence and Mathematical Modelling
major topics (sections)
Fundamental limitations of Data-driven AI (Adversarial Networks, AI cyber security, etc.)
Verification and approaches to correct AI errors
Data-driven modelling vs. Mathematical modelling
Problems and risks of AI in medicine, banking, jurisprudence
Emergent trends and fundamental problems of trustworthy AI (AI ethics, AI singularity, etc.)
Global aspects of AI
speakers & topics
conference schedule
Day 1

08:30 – 09:30
Registration

09:30 – 10:00

Opening

10:00 – 13:00
Session 1: Fundamental limitations of Data-driven AI (Adversarial Networks, AI cyber security, etc.)

13:00 – 14:30
Lunch

14:30 – 17:50
Session 2: Verification and approaches to correct AI errors

18:30 – 20:00
Poster Session
Day 2

10:00 – 12:50
Session 3: Data-driven modelling vs. Mathematical modelling

11:50 – 12:10
Coffee Break

12:50 – 14:30
Lunch

14:30 – 17:20
Session 4: Problems and risks of AI in medicine, banking, jurisprudence

18:30 – 20:00
Poster session
Day 3

10:00 – 11.40
Session 5: Emergent trends and fundamental problems of trustworthy AI (AI ethics, AI singularity)


11:40 –12:00
Coffee break

12:00 – 16:00
Session 6: Global aspects of AI


13:00 – 14:20
Lunch

15:00 – 15:20
Coffee break

16:00 – 17:00
Round table: Problems of Standardization


19:00 – ...
Cultural event
ATHINA KARATZOGIANNI
Dr Athina Karatzogianni is an Associate Professor in Media and Communication at the University of Leicester, UK. Her researchportfolio, on the impact of digitization on conflict, economics and security, reflects a commitment to research that is rigorous and innovative, with applied practice that is relevant and internationally influential.She has an extensive record of publications and citations in disciplinary, field-specific and cross-disciplinary research outlets, and has demonstrated sustained success in securing research income from Research Councils UK and the European Commission. Her most recent book is (2018) Platform Economics: Rhetoric and Reality the "Sharing Economy". Athina can be contacted at athina.k@gmail.com
EVGENY BURNAEV
Evgeny Burnaev obtained his M.Sc. Moscow Institute of Physics and Technology in 2006, and PhD from Institute for Information Transmission Problem in 2008. Currently, he is an Associate Professor in Skolkovo Institute of Science and Technology in Moscow, Russia. His research interests encompass Gaussian processes for multi-fidelity surrogate modelling and optimization, Deep Learning for 3D Data Analysis and manifold learning, on-line learning for prediction and anomaly detection. For his scientific achievements, Evgeny Burnaev was honored with the Moscow Government Prize for Young Scientists in the category for the Transmission, Storage, Processing and Protection of Information for leading the project "The development of methods for predictive analytics for processing industrial, biomedical and financial data'' in 2017.
IVAN TYUKIN
Info: TBD
ALEXANDER KULESHOV
Alexander Kuleshov is a specialist in the field of information technologies and mathematical modeling. In 2006, he was elected Director of the A.A. Kharkevich Institute for Information Transmission Problems (IITP) of the Russian Academy of Sciences. At IITP, he also served as the chairman of the Academic Council, Chairman of the Doctorate Dissertation Council, and Chair of Information Transmission and Processing. Throughout his academic career, he authored and co-authored 54 studies, including 4 monographs. In his speech for 100 days of presidentship, Dr. Kuleshov promised to lead Skoltech to the World Top 10 universities in 5 years which was achieved in advance.
DMITRY DYLOV
Dr. Dmitry V. Dylov is an Assistant Professor at the Center for Computational and Data-Intensive Science and Engineering at Skoltech. He earned his Ph.D. degree in Electrical Engineering at Princeton University (Princeton, NJ, USA) in 2010, and M.Sc. degree in Applied Physics and Mathematics at Moscow Institute of Physics and Technology (Moscow, Russia) in 2006. Dr. Dylov had been a Lead Scientist at GE Global Research Center (Niskayuna, NY, USA), where he had been leading various projects ranging from bioimaging and computational optics to medical image analytics. Dr. Dylov's innovation record includes IP contributions to GE Healthcare, frequent technical consulting to emerging start-ups, and the foundation of two spin-off companies with clinical validation in major hospitals in the USA (MSKCC, MGH, UCSF, Albany Med). Dr. Dylov has established a new theoretical and computational paradigm for treating noise in imaging systems, resulting in impactful publications in reputable journals, such as Physical Review Letters and Nature Photonics. His career record includes more than 50 peer-reviewed publications, 16 international patents, and more than 80 invited and contributed talks. Dr. Dylov has earned the McGraw Teaching Excellence certificate at Princeton and has been an instructor in the Edison Engineering Development Program at GE. He has served as an avid professional service volunteer, a scientific reviewer, and an advocate for the educational outreach within SPIE, OSA, APS, and IEEE societies.
NIKOLAY BRILLIANTOV
Prof. Nikolay Brilliantov has graduated Dept. of Physics of the Moscow State University, where he also received the PhD degree and the Doctor of Science degree. From 1995 he was working as a researcher in world-leading universities, including University of Toronto, Humboldt University of Berlin and University of Barcelona. From 2007 he is a Chair of Applied Mathematics at the Department of Mathematics of the University of Leicester (UK). From 2018 he took a position of full professor at Skoltech. He is a recognized expert in Statistical Mechanics and Kinetic Theory, an author of 3 monographs, published in Oxford University Press and Springer. He is also an author of more than 130 papers, including articles in Nature, Nature Comm., PNAS, Phys. Rev. Lett. and Rhys. Rev. X. In 2011-2016 he was on the Editorial Board of Phys. Rev. Lett., and from 2018 on the Editorial Board of Scientific Reports and Fluids. He is a distinguished referee for Europhys. Lett. and Phys. Rev. E. The results of his research had a multiple positive pressure coverage, including "New York Times", "Daily Mail", "Guardian", BBC, etc.
ALEXANDER BERNSTEIN
Professor at the Practice Alexander Bernstein works at the Skoltech Center for Computational and Data-Intensive Science and Engineering since May 2016. He received a master degree in Math (1969) at the Department of Mechanics and Mathematics, Moscow State University, a PhD degree in Math (1973) from the Steklov Mathematical Institute of the USSR Academy of Sciences, and a Doctor of Sciences degree in Math (1987) from the Department of Computational Mathematics and Cybernetics, Moscow State University. In 1991, the USSR Higher Attestation Commission awarded Alexander with the academic rank of Professor in the field of Intelligent Technologies and Systems. Prof. Bernstein started his career at the Research Institute of Automatic Equipment in 1969, where he was developing mathematical models and algorithms for computer networks. Then he worked at the Software Engineering Center of the Russian Academy of Sciences (RAS), at the Institute for System Analysis RAS and at the Institute for Information Transmission Problems RAS doing theoretical and applied research in the field of Mathematical modeling, Mathematical and Applied statistics, Intelligent Data Analysis, and their applications. At the same time, he had part-time full professor positions at the Moscow State Institute of Radiotechnics, Electronics and Automation, the National Research University Higher School of Economics and the Moscow Institute of Physics and technology. His current research interests are in Mathematical modeling and Intelligent Data Analysis (including applied geometrical methods and Machine Learning) and their applications for the analysis of neuroimaging biomedical data. He has more than 150 scientific publications.
ALEXANDER BERNSTEIN
Professor at the Practice Alexander Bernstein works at the Skoltech Center for Computational and Data-Intensive Science and Engineering since May 2016. He received a master degree in Math (1969) at the Department of Mechanics and Mathematics, Moscow State University, a PhD degree in Math (1973) from the Steklov Mathematical Institute of the USSR Academy of Sciences, and a Doctor of Sciences degree in Math (1987) from the Department of Computational Mathematics and Cybernetics, Moscow State University. In 1991, the USSR Higher Attestation Commission awarded Alexander with the academic rank of Professor in the field of Intelligent Technologies and Systems. Prof. Bernstein started his career at the Research Institute of Automatic Equipment in 1969, where he was developing mathematical models and algorithms for computer networks. Then he worked at the Software Engineering Center of the Russian Academy of Sciences (RAS), at the Institute for System Analysis RAS and at the Institute for Information Transmission Problems RAS doing theoretical and applied research in the field of Mathematical modeling, Mathematical and Applied statistics, Intelligent Data Analysis, and their applications. At the same time, he had part-time full professor positions at the Moscow State Institute of Radiotechnics, Electronics and Automation, the National Research University Higher School of Economics and the Moscow Institute of Physics and technology. His current research interests are in Mathematical modeling and Intelligent Data Analysis (including applied geometrical methods and Machine Learning) and their applications for the analysis of neuroimaging biomedical data. He has more than 150 scientific publications.
MAXIM SHARAEV
Maxim Sharav obtained his MSc in Biochemical Physics, Dept. of Physics of Lomonosov Moscow State University, Moscow, Russia; Department of Biophysics in 2012 and became a PhD in Biochemical Physics at Dept of Physics of Lomonosov Moscow State University, Moscow, Russia; Department of Biophysics since 2016. His main research and scientific interests lie in the field of neuroimaging data analysis, mathematical modelling, neuroimaging methods development as well as the application of Artificial Intelligence (Machine Learning and Data Analysis) to scientific and medical problems in neuroscience, resting-state fMRI, multivariate pattern analysis in neuroimaging EEG, fMRI in attention, memory, cognition, biofeedback and brain-computer interface, statistical analysis/modelling (including Monte-Carlo simulation, nonparametric methods, resampling methods, Bayesian inference), optimization methods (including genetic algorithms, gradient methods, etc.). Maxim Sharaev has experience of working in IHNA RAS, Institute for Higher Nervous Activity and Neurophysiology as an Assistant and in NBICS, National Research Center "Kurchatov Institute" as a Researcher. Now he works in CDISE, Skolkovo Institute of Science and Technology as a Research scientist.
MAXIM FEDOROV
Prof. Maxim V. Fedorov is Skoltech's Vice President for Mathematical Modelling and AI (formerly — Director of Skoltech Center for Data Intensive Science and Engineering, Skoltech CDISE). He belongs to a wide range of international societies. He is known, inter alia, as an organizer of a large number of conferences and seminars, and as a multiple representative of the Russian Federation at conferences organized by UNESCO and other high-level institutions in the area of AI. Prof. Fedorov's educational activity experience is over ten years (2003-2016) of work at the leading research and education institutions of the Republic of Ireland, Germany and the United Kingdom (including Max Planck Society and Cambridge University). In 2012, he founded the Technology & Innovation Supercomputer Centre in Glasgow, which was led by him from 2012 to 2016. At the same time, Prof. Fedorov headed the independent scientific laboratory in the University of Strathclyde in Glasgow. As a research cluster leader, he also coordinated the activities of a number of the University's laboratories in several application areas of high-performance computing and information technologies for Big Data processing. Under Maxim Fedorov's personal guidance 10 PhD theses were successfully defended at University College Dublin (Ireland), the University of Duisburg-Essen (Germany) and the University of Strathclyde in Glasgow (UK).
SERGEY MOROZOV
Sergey P. Morozov, MD, MPH, PhD, Professor, Chief External Officer for Radiology and Instrumental Diagnostics, Moscow Health Care Department and RF Ministry of Health in the Central Federal District; Chief Executive Officer at the Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Moscow Health Care Department. Main focus of activity: development of teleradiology; promotion of artificial intelligence in diagnostics; development and implementation of screening programs; development of information technology in radiology; creation of radiology reference centers.

Major achievements:
  • Development of techniques for coronary CT angiography, CT colonoscopy, knee MRI, CT arthrography, endorectal coil MRI of the pelvis, functional MRI of the brain;
  • Research on the accuracy of various chemotherapy response assessment systems using CT, PET-CT, and MRI.
Under the guidance of Sergey P. Morozov:
  • The Unified Radiological Information Service (ERIS) has been developed and introduced in Moscow;
  • The pilot projects Breast Cancer Screening Using Mammography and Low-Dose Computed Tomography of the Chest as a Screening Method to Diagnose Lung Cancer and Other Chest Diseases are being implemented.
ALEXEY NATEKIN
Info: TBD
DESMOND HIGHAM
Des Higham is Professor of Numerical Analysis at the University of Edinburgh. He works on the development, analysis and implementation of computational algorithms. He holds an EPSRC/RCUK Digital Economy Programme Established Career Fellowship (2015--2020) and is institutional lead on an EPSRC Mathemtical Sciences Programme Grant (2017--2021). He received the Germund Dahlquist Prize from the Society for Industrial and Applied Mathematics (SIAM) for his research contributions in stochastic computation. He was elected Fellow of the Royal Society of Edinburgh in 2006, and received a Royal Society Wolfson Research Merit Award in 2012. Higham is Editor-in-Chief of SIAM Review, a journal that is consistently ranked number one in applied mathematics, by citation index. Web-site: https://www.maths.ed.ac.uk/~dhigham/
CATHERINE HIGHAM
Catherine's current position as a senior member of Prof. Rod Murray-Smith's Inference, Dynamics and Interaction group involves applying state-of-the-art machine learning and statistical methods to inverse problems in image processing arising from recent advances in Quantum Optics. The research associate position is supported by the EPSRC UK Quantum Technology Programme under grant P/M01326X/1. After a graduating with a mathematics degree from Oxford, she worked for Novaction, a brand/marketing consultancy based in Paris, France, who sponsored me through a business MBA at City University, London. After moving to Scotland, she worked as a strategic analyst at Scottish Hydro-Electric. Following a career break, she independently prepared and submitted a research proposal to the Daphne Jackson Trust, and obtained a two-year Fellowship 2006-2008. This was followed by a Lord Kelvin/Adam Smith PhD scholarship from the University of Glasgow, 2008-2012. Catherine's PhD work took place in Professor Darren Monckton's lab, which has accumulated one of the most comprehensive datasets concerned with unstable human DNA mutations. Website: https://www.gla.ac.uk/schools/computing/staff/catherinehigham/
MOHAMMAD MOUSAVI
Mohammad got his bachelors and masters degree in Computer Engineering and Software Engineering, respectively in 1999 and 2001, from Sharif University of Technology, Iran. Subsequently, he obtained his Ph.D. in Computer Science from Eindhoven University of Technology, The Netherlands in 2005. Since then he held positions at Reykjavik University (postdoctoral researcher), Eindhoven University of Technology (assistant and associate professor), Delft University of Technology (guest faculty member), Halmstad University (professor of Computer Systems Engineering), and Chalmers / University of Gothenburg (guest professor of Software Engineering). He currently holds the chair of Data-Driven Software Engineering at the Department of Informatics, University of Leicester. He has had various leadership positions in his past appointments, such as managing educational programs, leading research teams, and leading research-centre-building initiatives. Mohammad's main research area is in model-based testing, particularly applied to software product lines and cyber-physical systems. He has been leading several research initiatives and industrial collaboration projects on healthcare and automotive systems their validation, verification, and certification. Web page: https://www2.le.ac.uk/departments/informatics/people/mohammad-mousavi
DANIL PROKHOROV
Dr. Danil Prokhorov started his research career in Russia. He studied system engineering which included courses in math, physics, mechatronics and computer technologies, as well as aerospace and robotics. He received his M.S. with Honors in St. Petersburg, Russia, in 1992. After receiving Ph.D. in 1997, he joined the staff of Ford Scientific Research Laboratory, Dearborn, Michigan. While at Ford he pursued machine learning research focusing on neural networks with applications to system modeling, powertrain control, diagnostics and optimization. He has been involved in research and planning for various intelligent technologies, such as highly automated vehicles, AI and other futuristic systems at Toyota Tech Center (TTC), Ann Arbor, MI since 2005. Since 2011 he is in charge of future research department in Toyota Motor North America R & D. He has been serving as a panel expert for NSF, DOE, ARPA, Senior and Associate Editor of several scientific journals for over 20 years. He has been involved with several professional societies including IEEE Intelligent Transportation Systems (ITS) and IEEE Computational Intelligence (CI), as well as International Neural Network Society (INNS) as its former Board member, President and recently elected Fellow. He has authored lots of publications and patents. Having shown feasibility of autonomous driving and personal flying mobility, his department continues research of complex multi-disciplinary problems while exploring opportunities for the next big thing.
PAVEL OSINENKO
Pavel Osinenko studied control engineering at the Bauman Moscow State Technical University from 2003 through 2009. He started his postgraduate education in vehicle control systems at the same university. In 2011, Pavel moved to the Dresden University of Technology after receiving a Presidential Grant for studying abroad. He obtained a Ph.D. degree in 2014 after having successfully defended his dissertation on vehicle optimal control and identification. Pavel has work experience in the German private sector and at the Fraunhofer Institute for Transportation and Infrastructure Systems. In 2016, he made a transition to the Chemnitz University of Technology as a group leader and research coordinator. He was actively involved in project coordination, doctorate supervision, teaching, administration etc. Pavel's major focus of research has been on reinforcement learning, especially its safety, and computational aspects of dynamical systems. Currently, he addresses the connections between control theory and machine learning, and, in particular, the matters of meeting specified certificates on reinforcement learning methods in dynamical context.
event details
VENUE
The Conference will take place at the heart of Moscow's Skolkovo Innovation Center – Skoltech Institute of Science and Technology, rated globally as one of TOP-100 young universities (by Nature Index). Skoltech was created during 2011 in collaboration with the Massachusetts Institute of Technology (MIT). Central to the campus are its multi-story laboratories that accommodate lab space, work and teaching areas, as well as the associated offices, which include 12 laboratory buildings within the insitute.
MOSCOW
Moscow is the capital of Russia and one of the largest cities in Europe. A historic center with modern infrastructure easily reachable from all major cities of Russia by air or train travel. Located on the river Moskva, in the west of the country, Moscow's landmarks include the Red Square, the Bolshoi Theatre, the Gorky Park, VDNH and the Tretyakov gallery. As the conference will be held in online format in 2020, we will be pleased to present you a virtual tour.
INFRASTRUCTURE
Zoom will be used as the main tool for online communication: sections, discussions, networking. Google Drive will be used to store and exchange presentation files and topical charts. All registered participants, as well as speakers, will also get the access to special webpage with useful links to files, chats, conference rooms, and other event-related content.
application
Your Name and Surname
E-mail
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Anything else we should know?
organizers / contact
Maxim Fedorov
Chair, Skoltech Vice President for Mathematical Modelling and AI
Anna Zhdanova
Manager
Ekaterina Loginova
Manager
Ivan Khlebnikov
Fundraising
Organizers:
Skolkovo Institute of Science & TechnologyCenter for Computational and Data-Intensive Science and Engineering


Do not hesitate to drop by:

30с1 Bolshoi boulevard, Skolkovo, 121205, Russian Federation
For directions on how to reach us, please see here