Aleksander Madry is a Professor of Computer Science at MIT, leads the MIT Center for Deployable Machine Learning as well as is a faculty co-lead for the MIT AI Policy Forum. His research interests span algorithms, continuous optimization, and understanding machine learning from a robustness and deployability perspectives.
Aleksander's work has been recognized with a number of awards, including an NSF CAREER Award, an Alfred P. Sloan Research Fellowship, an ACM Doctoral Dissertation Award Honorable Mention, and Presburger Award. He received his PhD from MIT in 2011 and, prior to joining the MIT faculty, he spent time at Microsoft Research New England and on the faculty of EPFL.

Dr Hana Chockler is a Reader (Associate Professor) in the Department of Informatics at King's College London. Since February this year, Dr Chockler also has a role of a PI of Strategic research agenda at causaLens - a startup that leverages Causal AI to understand, explain, predict and shape the world.
Before joining King's College in 2013, Dr Chockler worked as a Research Staff Member at IBM Research Laboratory in Haifa, in the formal verification and in software testing groups. She earned her PhD degree in Computer Science from the Hebrew University of Jerusalem, researching sanity checks for formal verification. This direction motivated her interest in causal reasoning and its applications.
Dr Chockler's main research interests lie on the border between software engineering and causal reasoning. She is interested in formal verification of hardware and software, automatic generation of specifications, explanation of counterexamples, connections between concepts in AI and software engineering, and learning.

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.

Dr Bastiaan Quast is a data scientist and author of the popular machine learning library rnn, which implements recurrent neural network architectures in the R language, making these algorithms accessible to statisticians, as well as the author of the datasets GUI: datasets.load, and the author of the upcoming book: "Machine Learning Algorithms from Scratch in R" with Manning.

Deniz Susar is a Governance and Public Administration Officer, Digital Government Branch, Division for Public Institutions and Digital Government is a Governance and Public Administration Officer at the Division for Public Institutions and Digital Government of UNDESA. Deniz's main work areas include digital government and preparation of the biannual UNDESA flagship publication 'United Nations eGovernment Survey'. As part of his current role, he also supports the Internet Governance Forum (IGF). HIs main research areas include e-government, open government, citizen engagement, internet governance, AI, and other frontier technologies and open government data. Deniz holds a Master Degree on International Political Economy and Development from Fordham University, New York, United States and a Computer Engineering degree from the Bosphorus University of Istanbul, Turkey.

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.

Jaroslav is co-founder of the OTS Lab, the innovative transport consulting bureau. He tech-led the development of the first commercial multimodal agent-based transport model in Russia and the global transport model for FIFA World Cup 2018. Jaroslav professional interests include multi-agent model training, combating model's overfitting, evolutionary algorithms in transit optimization.

Alexey Neznanov received the master degree with honor in applied mathematics at Moscow Power Engineering Institute in 2002. After three years he defended PhD theses on structural analysis about effective distinction of fragments layout in graph models. He held positions of programmer, analyst, researcher, and educator. He designed and taught original courses "Design of Human-Computer Interaction", "Applied Graph Theory", "Distributed Systems", "Computer Architecture and System Programming", and other courses about effective algorithms and data management in MPEI, MIPT, and HSE. He is an author of textbook on introductory programming and more than 60 research papers. Alexey is a coauthor of free research software like Formal Concept Analysis Research Toolbox (FCART) and educational software like Peer Assessment System for Complex Artifacts (PASCA).
His main affiliation is National Research University Higher School of Economics (where he has been an associated professor at School of data analysis and artificial intelligence since 2008, and a senior researcher at International Laboratory for Intelligent Systems and Structural Analysis since 2013).
From 2012 till 2015 he held position as head of the analytical department at Dmitry Rogachev Federal Scientific and Clinical Centre of Pediatric Hematology, Oncology and Immunology. Alexey is a member of the IEEE.

MGIMO University, Digital Economy and Artificial Intelligence Department, researcher; Center for Global IT Cooperation, Head of Analytics. A member of the OECD Network of Experts on AI (ONE AI), expert in ISO/IEC JTC 1/SC 42 and the National TC164 "Artificial Intelligence", author of publications in the field of AI.

Alexey has expertise in numerical methods, statistics, and industrial applications of data analysis. He completed a Ph.D. in Math at IITP RAS in 2017. Alexey obtained a new result on the effectiveness of Bayesian procedures for Gaussian process regression and a first-ever theoretical justification for the selection of the design of experiments for variable fidelity models as well as minimax errors for Gaussian process regression.

He developed a pioneering industry-level tool for data fusion that solves a regression problem for the case of data with more than one fidelity. In 2018 he was awarded Moscow government award for young scientists "Development of predictive analytics methods for processing industrial, biomedical and economic data" joint with E. Burnaev and M. Panov. Now Alexey focuses his research on the development of new methods for Bayesian optimization and embeddings for weakly structured data. He also actively participates in industrial projects and teaching routines including joint projects with Sberbank and Gazprom Neft.

Andrey V. Neznamov has a scientific degree of candidate of legal sciences and acts as senior research fellow at the Institute of State and Law of the Russian Academy of Sciences. He is also Managing Director of the Centre for AI regulation of Sberbank (the Russian National Center of competences for artificial intelligence), where he deals with the regulation of artificial intelligence, robotics, big date, self-driving vehicles and emerging technologies. He acts a deputy head of the working group on regulation of robotics and AI technologies in the Russian Parliament, and also the member Coordinating Council for Youth Affairs in the Scientific and Educational Spheres of the Council under the President of the Russian Federation for Science and Education.
Andrey is the co-chair of the CAHAI-COG of Council of Europe and acts as an expert for AI regulation in different international bodies. He is the coauthor of the Russian AI strategy and the Concept of AI and robotics regulation upon 2024.
Andrey has over 70 publications on the regulation of artificial intelligence in Russia and abroad.

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).

Aleksandr Rubashevskii is a Skoltech Ph.D. student in the Reinforcement Learning (RL) field under the supervision of Prof. Pavel Osinenko. He graduated from a Skoltech-HSE joint Master's program Math of Machine Learning. His current research interests are connected with RL formal guarantees of safety and stability. Overall, his main goal is to develop a symbiosis of theoretical and experimental methods so that RL can be fully utilized in industrial applications, namely as the intersection of classical control theory and reinforcement learning.

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.

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'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/

Neil Lawrence is the DeepMind Professor of Machine Learning at the University of Cambridge, a Visiting Professor at the University of Sheffield, and Co-host of Talking Machines. Prior his appointment at Cambridge he led Amazon Research Cambridge, where he was a Director of Machine Learning.
Neil's main research interest is machine learning through probabilistic models. He focuses on both the algorithmic side of these models and their application. He has a particular focus on applications in personalized health and computational biology, but happily dabbles in other areas such as speech, vision and graphics. He is one of the founders of the DALI Meeting and Data Science Africa.

Mr. Andrey Kuleshov specializes in applied mathematics, economics and finance. He has over 20 years experience in technology, agriculture, global value chains, impact investing. He is currently heading Strategy and Development at the Common Fund for Commodities (Amsterdam) and advising the Centre for AI Science and Technology at the Moscow Institute of Physics and Technology (Moscow). His current research interests include international regulation, standardization of AI, ethics, robustness of AI. Previously he worked at Oxford Economics (Oxford) and the House of Commons (London). He holds an MSc in Economics from the London School of Economics and Political Science (1994) and a Masters' in applied mathematics from the Moscow Institute of Physics and Technology (1989).

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.

Dr. Utkin is the Chairman of the Technical Committee 194 "Cyber-Physical Systems" and specialist for standardization of Skoltech Center for Computational and Data-Intensive Science and Engineering (CDISE). His experience in the field of the technology business is very large and include investment, consulting, technology analytics and regulation. He is a leading expert in the national regulatory formation in the field of digital technologies, and also represents the Russian Federation at international regulatory platforms, especially ISO/IEC. Being a part of advisory bodies of federal executive bodies, he often participates in the development and approval of national and international standards: IoT, Digital Twins, AI, Big Data, Smart Manufacturing, Smart Cities etc.

Ivan Oseledets graduated from Moscow Institute of Physics and Technology in 2006, got Candidate of Sciences degree in 2007, and Doctor of Sciences in 2012, both from Marchuk Institute of Numerical Mathematics of Russian Academy of Sciences. He joined Skoltech CDISE in 2013. Ivan's research covers a broad range of topics. He proposed a new decomposition of high-dimensional arrays (tensors) – tensor-train decomposition, and developed many efficient algorithms for solving high-dimensional problems.
He got several awards for his research and industrial cooperation, including two gold medals of Russian academy of Sciences (for students in 2005 and young researchers in 2009), Dynasty Foundation award (2012), SIAM Outstanding Paper Prize (2018), Russian President Award for young researchers in science and innovation (2018), Ilya Segalovich award for Best PhD thesis supervisor (2019), Best Professor award from Skoltech (2019), the best cooperation project leader award from Huawei (2015, 2017). He also has been a Pi and Co-Pi of several grants and industrial projects (230 million of rubles since 2017).

Pavel Gotovtsev is the Deputy Head of the Department of Biotechnology and Bioenergy at the Research Center "Kurchatov Institute", and also concurrently holds the position of MIPT Associate Professor. His main research interests are the creation of intelligent control and management systems in biotechnology and bioenergy, the Internet of Things and biotechnology. Since 2017, Dr. Gotovtsev has been the coordinator of the Russian working group under the auspices of the IEEE global initiative on the ethics of autonomous and intelligent systems.

Dmitry graduated from the Department of Mechanics and Mathematics of Moscow State University in 1998, where he also obtained his Candidate of Sciences degree in 2002. Later on, he worked at the Institute for Information Transmission Problems (IITP), Dublin Institute for Advanced Studies, and Munich University. In 2015, he obtained his Doctor of Sciences degree from IITP. Dmitry's interests cover a wide range of topics in Applied Mathematics. He started his research career with studies of stochastic processes and quantum lattice systems, gradually shifting to topics related to engineering, data analysis, and optimization. You can find more details about his research on his personal web page.

In January 2018, Gonzalo joined the Skolkovo Institute of Science and Technology as an Assistant Professor. He is heading the Mobile Robotics lab., focusing his research on planning, perception and how to combine both into new solutions in robotics. He completed his PhD thesis in 2015 on robot navigation algorithms in urban environments at the Institut de Robotica i Informatica Industrial IRI, a group inside the Universitat Politecnica de Catalunya (UPC), in Barcelona, Spain. This work resulted finalist on the Georges Giralt Award the European award in robotics.
Before joining Skoltech, Gonzalo worked during two years as a Research Fellow (postdoc) at the APRIL lab. and Intermittent Lecturer in the department of Computer Science and Engineering at the University of Michigan.
Gonzalo has collaborated on international research projects and industry research initiatives, such as the URUS project on human robot cooperation in urban areas or the NGV project in alliance with the Ford Motor Co. on autonomous driving.

Maxim received his Bachelor and Master degrees from the Moscow Institute of Physics and Technology in 2010 and 2012, respectively. His Bachelor thesis addressed the problem of filling missing data values in the support vector machine classification framework. The Master thesis focused on the Gaussian processes regression and adaptive design of experiments. In 2012, Maxim started his postgraduate studies and switched the direction to the field of Mathematical Statistics. He concentrated on obtaining tight bounds for the Gaussian approximation of posterior distribution (Bernstein-von Mises phenomenon). The research resulted in a series of publications in peer-reviewed journals and formed the core of Maxim's Candidate of Sciences thesis defended at the Institute for Information Transmission Problems in January 2016. Starting in 2010, Maxim also worked part time as a research scientist in DATADVANCE Company, which is a resident of Skolkovo Innovation Center. There he participated in developing the library of data analysis methods for engineering applications. This library, pSeven, is now used by a number of companies worldwide, including Airbus, Porsche, Mitsubishi, Toyota, Limagrain and many others.

Raul is Turing AI Fellow and Associate Professor in Data Science and AI at the Department of Engineering Mathematics, University of Bristol. His research aims to redefine the way humans and AI systems interact. Focusing on the human side, including data and AI practitioners and end-users across multiple fields, his goal is to produce tools that allow all of them to actively shape the behaviour of AI systems and provide clarity on how data, annotations and feedback influence these systems.

Dr. Filip is ISO/IEC JTC 1 PAS Mentor | ISO/IEC JTC 1 AG 14 SIF Expert | Convenor, ISO/IEC JTC 1/SC 42/WG 3 Trustworthiness of AI | National (mirror) chair, NSAI TC 02/SC 18 AI | Head of the Irish national delegation, ISO/IEC JTC 1/SC 42 AI & CEN-CENELEC/JTC 21 AI | W3C ODRL CG C-Chair| Chair & Editor, OASIS XLIFF OMOS TC | Secretary & Lead Editor, OASIS XLIFF TC | NSAI expert to ISO/IEC JTC 1/SC 38 Cloud Computing, ISO TC 37/SC 3 Terminology management, /SC 4 Language resources, /SC 5 Language technology | GALA TAPICC Steering Committee Member | Unicode CLDR TC/MFWG Chair Group Member.

Dr. Filip's specialties include open standards and process metadata, workflow and meta-workflow automation. He works as Senior Director of Standards and Industry Development at Huawei's global corporate strategy department, responsible for ISO/IEC JTC 1 strategy. Before 2021, he worked as a Research Fellow at ADAPT Centre, Trinity College Dublin, Ireland. Before 2011, he oversaw key research and change projects for Moravia (now part of RWS) worldwide operations. Dr. Filip held research scholarships at universities in Vienna, Hamburg, and Geneva, he graduated in 2004 from Masaryk University Brno with a PhD in analytic philosophy. David also holds master's degrees in philosophy, art history, theory of art and German philology.

Founder of the largest CIS community of data specialists, Open Data Science. CEO of Data Souls ML Competition Platform. Organizer of the largest specialized conference Data Fest in the CIS and Eastern Europe. Alexey has completed over 20 projects at DM Labs, Deloitte, Diginiteca and Siemens.

Director General of the International Research Institute of Management Problems (MNIIPU) and the Institute for Economic Strategies of the Russian Academy of Sciences (INES). Doctor of Economics, professor, academician of the Russian and European Academy of Natural Sciences and several leading Moscow universities. Head of Working Group 01, Fundamental Standards, Technical Committee No. 164, Artificial Intelligence. Ageev specializes in the issues of economic growth, the global economy as a whole, integration processes, digital transformation, foreign regional studies, management of various sectors of the high-tech complex and energy, entrepreneurship, development of competition, creation of information systems, development and application of international standards in the field of artificial intelligence, investments, risk management, integrated reporting, etc. He is the author of more than 700 scientific papers, including 30 monographs. More than 30 scientific papers published in the USA, Germany, Portugal, Finland, Italy, China and several other foreign countries in English, German, Chinese and other languages. Editor-in-chief of the journal Economic Strategies and the international journal Partnership of Civilizations. Dr. Ageev is the Member of the Union of Writers of Russia and the Union of Journalists of Russia.

Peter Grindrod is Professor in the Mathematical Institute, University of Oxford. His research interests are:

• The theory and applications of dynamically evolving networks, including nonlinear node-based dynamics, fully coupled through time dependent network dynamics.
• Stochastic modelling and classification of behaviour within evolving peer-to-peer communication and social networks.
• Applications of mathematics to social media, digital media and marketing
• Dynamical systems and Delay Differential Equations Analysis of fMRI scans of human brains, including measures of network "fragility" as predictors of future performance and early cognitive degradation.
• Modelling, analysis and forecasting of domestic and small business energy consumption on low voltage networks including dynamic behaviour driven segmentations of consumers via smart meter data
• Inference and forecasting problems for the retail, consumer goods, and telecommunications sectors. Behaviour-based risk measures and targetted-marketing applications.
• Models for counter terrorism and real time recognition of anomalies within vast communications data sets.
• Strategy for investment in science and technology research and innovation. Knowledge exchange and balancing open public research with confidential commercial interests through open innovation.

Dr. Logacheva is a research scientist at Skoltech's Natural Language Processing group. She got her PhD from the University of Sheffield (UK). Her main research interests are dialogue systems, information extraction, sequence-to-sequence models, evaluation of NLP systems. Before joining Skoltech she was a researcher in Moscow Institute of Physics and Technology (IPavlov project).

Alexander Lunkov was educated as a teacher of history, sociology and philosophy in 2003. Since 2004, he has been teaching postgraduate students of the Russian Academy of Sciences in the subject of history and philosophy of science, research methodology, etc. In 2008, he defended a dissertation on the history of Russia during the Great Patriotic War. His main scientific interest is the philosophy of war and peace and philosophical issues of technology. Since 2019, he is an expert in the Technical Committee 164 "Artificial Intelligence". In this Committee, he deals with the ethical issues of the development of AI technology in terms of academic research and technical standardization. His main goal in this area is to create a comprehensive ethics for people dealing with AI or involved in situations, which were determined by AI technologies.

Info TBD

Nikolay obtained Master's degree in Computational linguistics in Higher School of Economics. His industrial experience is linked with companies Lingualeo and Ozon, and currently he works at Skoltech NLP lab as an NLP research engineer.
Recently published works by Nikolay and NPL Lab are dedicated to detecting inappropriate text content which can harm the reputation of an author.

Anna Abramova is Head of the Department of Digital Economy and Artificial Intelligence ADV group at MGIMO-University, Academic Director for the Masters' Programme on Artificial intelligence and Associate Professor at School of International Economic Relations (MGIMO-University). She has more than 10 years of experience in research and lecturing on e-commerce, ICT market and digital trade developments, as well as official development assistance in ICT sector. She has worked as a consultant for UNCTAD and World Bank.

Daryna is doing PhD in Natural Language Processing (NLP) field under the supervision of Pr. Alexander Panchenko at Skolkovo Institute of Science and Technology. Her current research interests are connected with important sociological issues like fake news detection and combating; the topic includes knowledge extraction, fact checking, models explainability, texts detoxification and other text style transfer. In general, her goal is to develop transparent technology for better society.

Dr. Valery Karpov graduated from Moscow Institute of Electronics and Mathematics in 1993. He is an Associate Professor, Ph.D., Head of the Robotics Laboratory of the National Research Center "Kurchatov Institute". His research interests include intelligent robotics, group control models, ethical problems of AI, machine creativity. Together with Dr. P. Gotovtsev and Dr. G. Royzenzon, he is an author of the work in the social robotics well-known in many areas of robotics research.

Dmitry graduated from the Faculty of Law at the Kazan State University in 1999 and subsequently received a Ph.D. in 2002 (Institute of State and Law of the Russian Academy of Sciences). Later, Dmitry worked as a researcher at the Institute of Legislation and Comparative Law under the Government of the Russian Federation, as a legal adviser at one of the largest Russian companies in the oil and gas sector. Dmitry's legislative experience (due to being the expert council of the State Duma - the Russian Parliament) covers the development and discussion of laws on electronic digital signature (2002), commercial secrets (2004) and personal data (2006). Today Dmitry resolves disputes as an arbitrator of the International Commercial Arbitration Court at the Chamber of Commerce and Industry of the Russian Federation.
Dmitry's interests include a wide range of private (civil) law topics, especially in the field of regulation of new technologies such as AI, UAV and other robotics, art and AI, telecommunications, cryptography, biomedical technologies, etc.