Academic staff

• Country:

  Italy

• Education:

  Computer Science

Manuel Mazzara achieved his Masters in 2002 and his Ph.D in 2006 at the University of Bologna. During 2000 he was a Technical Assistant at Computer Science Laboratories (Bologna, Italy). In 2003 he worked as Software Engineer at Microsoft (Redmond, USA). In 2004 and 2005 he worked as a free lance consultant and teacher in Italy. In 2006 Manuel Mazzara was an assistant professor at the University of Bolzano (Italy) and in 2007 a researcher and project manager at the Technical University of Vienna (Austria). From 2008 to 2012 Manuel worked in Newcastle University on the DEPLOY project. This project involved several partners Europe-wide with 4 of them coming from the most varied industrial scenarios: Bosch, Siemens, SAP and Space Finland. The objective was deploying software engineering techniques into the industrial process to guarantee stronger products reliability. In 2012 Manuel also served as a Computer Scientist at UNU-IIST in Macao while still being with Newcastle as a Visiting Researcher. Manuel worked on the automatization of the immunization process for third world countries and on e-health and sustainability projects related to the UN “Agenda 21”. In 2013/14 he also worked on remote assistance and telemedicine domotics tools with Polytechnic of Milan and as a teaching fellow at the same university before joining Innopolis and visiting ETH.

• Education:

  Optical & Electronic Engineering

Ilya Afanasyev graduated in Engineering at Baltic State Technical University (St. Petersburg, Russia) in 2000 and obtained his Ph.D. in Technical Science at Vavilov State Optical Institute (St. Petersburg, Russia) in 2006. In 2010-2013 he worked as a Marie Curie postdoc in Mechatronics Lab. at the University of Trento (Italy), conducting research on 3D sensors and data processing algorithms, co-supervising and teaching master students. He has also been engaged in national and international hardware projects both for academy and industry in the region of sensor applications for aerospace, banking, robotics and oilfield service. His main research interests have revolved around sensors, data acquisition and processing, paying the attention to instrument development for R&D projects and industrial applications. He published 34 papers. He has academical experience at Vavilov State Optical Institute (2000-2007), the University of Trento (2010-2013) and TGT educational center “Prime College” (2013-2014), integrating research and supervising students, interns & employees of different nations, lecturing the courses on sensor/tool technologies and applications. He worked also in industry: (1) as a senior engineer in German company “Giesecke & Devrient GmbH” (2007-2010), developing banknote processing sensors and algorithms, and (2) as a head of Spectral Noise Logging dep. in Kazan office of the emirate company “TGT Oilfield Service” (2013-2015), improving acoustic borehole technology for Well Completion Integrity and Reservoir Flow Analysis, managing people, products & projects (hardware & software).

• Education:

  Physics and Mathematics

Vladimir Ivanov received his PhD degree in Physics and Mathematics from Kazan State University in 2009. He worked as a Researcher/ Assistant Professor at Kazan Federal University (2005-2013), Head of Big Data and Text Analytics Lab at Kazan Federal University (2013-2015) as well as a Researcher at Innopolis University (2015-2018). Dr. Ivanov`s research interests include data analysis, machine learning, software engineering, computational linguistics, natural language processing, information extraction, text mining, software reliability, and software metrics. Vladimir Ivanov is a primary instructor for undergraduate courses: "Advanced Statistics" and "Practical Machine Learning and Deep Learning".

• Education:

  Computer Science

Dr. Andrey Sadovykh received his M.S. degree in Applied Mathematics and Information Technologies from Moscow Institute of Physics and Technology (Russia) in 2001, PhD degree (Airbus company program) in Computer Science from Sorbonne University (France) in 2005 and MBA degree in Digital Business from HEC Paris School of Management (France) in 2014. Dr. Andrey Sadovykh was the Head of Research Unit at SOFTEAM (2006 – 2018), the 1st innovative SME in France and 3rd in the whole EU, which is recognized by Systematic Paris Region in mid-cap category. During his work he conducted research in applied model-driven engineering in 15+ projects, coordinated 5 projects, contributed to standardization with OMG, contributed to Modelio product development. Dr. Sadovykh has ten years` experience in research projects in IT in a cross-cultural international context and strong experience in R&D and software publishing. He successfully leads several international consortia in collaborative projects involving large industries, SMBs and academic partners.

• Education:

  Computer Science

  Moscow State University, Russia

Eugene Zouev graduated from the Computer Science Department of Moscow State University and got his doctoral degree (PhD) there in 1999. He worked in a number of research and development institutions, at Moscow University and in some other universities and companies abroad. For many years, he gave lectures and did research at Moscow University and in several reputable European universities, such as ETH Zurich (2000-2006) and EPFL Lausanne (2009-2010). E. Zouev ran a number of successful research and industrial software projects in the area of programming languages and compilers (C++ and Zonnon compilers are among them). Currently, he is working as a principal engineer (Samsung range R7) at Samsung Research & Development Center, Moscow. E.Zouev also provides consultancy services for some companies and participates in a few research projects (in particular, at London Metropolitan University, England). He is the author of a number of books in the area of software development.

• Education:

  Moscow Institute of Physics and Technology (Russia)

  University of Texas at Austin (USA)

Dr. Andrey Zykov received his M.S. degree in Electrical Engineering from Moscow Institute of Physics and Technology (Russia) in 1999, PhD degree in Electrical and Computer Engineering from The University of Texas at Austin (USA) in 2009. Dr. Zykov worked in R&D department of the company Cadence Design Systems (2010 – 2013) in the area of Electronic Design Automation (EDA). Fall semester 2014 Dr. Zykov spent in the Carnegie Mellon University (USA) performing training in teaching “Master of science in information technology: software engineering” (MSIT-SE). He held the position of Assistant Professor at Innopolis University (2015 – 2016) teaching courses for MSIT-SE program. Dr. Zykov has significant experience in R&D in Computer Engineering domain in an international context.

• Education:

  Mechanical Engineering

Dr. Mohammad Reza Bahrami received his B.S. degree in Mechanical Engineering from Shahid Bahonar-e-Kerman University, Iran in 2005, MS degree in Mechatronics Engineering from Sharif University of Technology, International Campus, Kish Island, Iran in 2010 and PhD degree in Mechanical Engineering from Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia in 2016. Dr. Bahrami was awarded the Grant for working as university teacher, Program 5-100, Peter the Great St. Petersburg Polytechnic University (in 2016, 2017 and 2018) and Grant for PhD students, Program 5-100, Peter the Great St. Petersburg Polytechnic University (in 2014 and 2015). He worked as an Assistant professor at Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia (in 2016-2018), as Visiting professor at ERASMUS +, Aleksandras Stulginskis University, Lithuania (in 2016-2017). Dr. Bahrami`s teaching experience includes the subjects such as Contact Mechanics, System Modeling Using Bond-Graph, Modeling of Contact Mechanics.

• Education:

  Computer Science

Artem Burmyakov received the PhD degree in Computer Science from the University of Porto in 2016, and the Master's degree in Applied Mathematics and Informatics from Moscow Engineering Physics Institute in 2007. In 2006-2010 he worked as a software developer at CERN, and in 2016-2017 he was a postdoctoral researcher at Seoul National University. His research interests are related to mathematics and algorithms, real-time multiprocessor scheduling, parallel computations, software development

• Education:

  Volgograd State Technical University, Russia

Alexander Maloletov is an expert in theoretical mechanics and robotics. He is the author of over 150 scientific publications, including 3 monographs, over 20 patents and over 40 software copyrights. He serves on a Dissertation Council and on the editorial boards of five scientific journals. In 2015, he was awarded the degree of Doctor of Physical and Mathematical Sciences with a specialization in "Theoretical Mechanics". As a research supervisor, he has mentored several students to the completion of their Ph.D. degrees. Alexander Maloletov has an extensive network within the Russian scientific community, keeps abreast of the latest advancements in modern global science, and is an active participant in leading international conferences and forums.

• Education:

  Computer Engineering

Adil Mehmood Khan is a Professor of Machine Learning and the Director of the Machine Learning and Knowledge Representation Lab. Possessing a solid foundation in Machine Learning, Deep Learning, and Representation Learning, he is devoted to both education and research within the artificial intelligence domain. Adil's research journey started in 2006 in South Korea, where he concentrated on human activity recognition through wearable sensors. His groundbreaking discoveries were published in reputable journals and employed by leading technology firms for their health applications. Over his career, Adil has undertaken more than ten research projects, obtaining substantial funding, and has published in excess of 80 research papers. He has mentored four Ph.D. and over 20 MS students to completion and maintains active research collaborations with numerous international universities. As an educator, Adil has instructed a diverse array of computer science courses at both undergraduate and graduate levels. Acknowledged for his exceptional teaching abilities, Adil has been awarded the Best Teacher Award twice. Adil has also contributed as an academic consultant, creating and delivering specialized graduate online machine learning courses for various universities throughout the globe. His courses have consistently garnered praise from students and colleagues alike. As Associate Dean of Education and the Director of the Institute of Data Science & Artificial Intelligence at Innopolis University, Adil has overseen multiple facets of the educational process, such as admissions, curriculum design, course execution, and student internships. Moreover, as the Institute's Director, he has lead a team of faculty and staff, managed research budgets, and collaborated with various committees to guarantee top-notch education and research opportunities for students.

• Education:

  Applied Mathematics and Physics

From 2001 Yaroslav Kholodov had been a senior lecturer at the Department of Computational Mathematics of the Moscow Institute of Physics and Technology (MIPT). In 2007, he became an Associate Professor. During 2009-2012 Yaroslav Kholodov had been a Chairman of the Organizing Board of the Annual MIPT School in High-Performance Computing for Young Scholars. During 2010-2012 Yaroslav had been the Head of the MIPT research and educational center “High-Performance Computing and Distributed Computer Systems”. Yaroslav gave lectures at the Department of Computational Mathematics of MIPT on the following topics: Computational Mathematics Non-Linear Computing Numerical Modeling of Traffic Flows Dynamics Yaroslav co-authored 3 study guides and one book. 4 post-graduate students of MIPT received PhDs in Mathematical Modeling, Numerical Methods and Software Complexes under his scientific supervision. Over 25 MIPT students received Master and Bachelor’s degrees in Applied Computing and Software Complexes. Key research area is represented by intelligent analysis of traffic data and road traffic modeling using adaptive control algorithms. Today safe and effective operation of intelligent traffic control systems requires tools for acquisition and analysis of data about current traffic conditions. Assimilation of large data volumes regarding road traffic received from different sources is among the top areas of this research since it allows to enhance the accuracy of data mining by means of generalization of measurements using numerous approaches. Yaroslav Kholodov has authored over 50 research works published in peer-reviewed journals, and owns 17 state registration certificates of computer programs. Yaroslav is a member of review committees of the following journals: Mathematical Modeling; Computer Research and Modeling.

• Education:

  Moscow Institute of Physics and Technology

Mohammad Alkousa received his bachelor’s and master’s degrees in mathematics at Damascus University (Syria), completing his master’s thesis in elliptic functions theory. In 2020, he received his PhD in Mathematical Sciences fr om the Moscow Institute of Physics and Technology, Phystech School of Applied Mathematics and Informatics, wh ere he worked under the supervision of Professor Alexander V. Gasnikov. His dissertation focused on numerical methods for non-smooth convex optimization problems with functional constraints. He joined Innopolis University in December 2024 as an Assistant Professor in the Lab of High Performance Computing, and in September 2025, he became a Senior Researcher at the Laboratory of Modern Adaptive Computational Methods. His research interests include convex and non-convex optimization, saddle-point problems, variational inequalities, and their applications to machine learning.

Doctor of Sciences, Russia, Kazan Federal University, Full Professor, Institute of Data Science and Artificial Intelligence, Head, Lab of Algorithmic and Numerical Methods in Mathematics and Artificial Intelligence

In 2004 Andrey Frolov defended his PhD thesis at Novosibirsk State University (Russian Federation). In 2014 he defended thesis of Doctor of Science at Kazan Federal University (Russian Federation). From 2004 to 2017 he held various positions at Kazan Federal University. From 2018 to the present he has held the position of full professor at Innopolis University, and since 2025, the head of the laboratory.
Research interests: Theoretical Computer Science, Algorithm therory, Mathematical and computer modeling.

• Education:

  Ufa State Aviation Technical Institute

Doctor of Sciences degree in Physics and Mathematics, specializing in "Differential Equations, Dynamical Systems, and Optimal Control." Ph.D. (1993) and D.Sc (2002) dissertations defended at the Institute of Mathematics of the Ufa Scientific Center of the Russian Academy of Sciences. Worked there from 1988 to 2022. Professor at Innopolis University since 2020. Research interests: nonlinear dynamics of wave and discrete systems, bifurcations and theory of chaotic systems, asymptotic methods. Application areas: resonances and synchronization, control theory of unstable objects, quantum computing.

• Country:

  Russia

• Education:

  Physical and Mathematical Sciences

Julia Tsyganova is the author of more than 180 scientific publications in peer-reviewed Russian and international journals (including those with Q1 impact factor), 18 certificates of state registration for computer programs, and co-author of the monograph “Adaptive Systems of Filtering, Control and Fault Detection” (2011). She regularly reviews papers in leading Russian and international journals. Since 2012, Julia has been a principal investigator and/or project leader on projects funded by the Russian Science Foundation, the Russian Foundation for Basic Research and other organizations. Her former main position was as a professor in the Department of Information Technology at the Faculty of Mathematics, Information, and Aviation Technologies at Ulyanovsk State University. Julia Tsyganova taught several courses to UlSU students, including “Mathematical Modeling of Complex Systems”, “Modern Methods of Parameter Estimation in Conditions of Uncertainty”, “Computational Mathematics”, and “Software Tools for Computational Mathematics”. Currently, Julia works as a professor at Institute of Data Science and Artificial intelligence at Innopolis University.

• Education:

  Dnipropetrovsk National University (DNU)

Yegor Bugayenko graduated from Dnipropetrovsk National University (DNU) in 1998 with a degree in Computer Systems and Networks. He has built a distinguished career in software development and AI. His early research focused on automating database system configuration. After founding Zerocracy (USA), he served as CTO until 2019, developing AI-driven systems for managing developer teams. Currently, he is the Director of the Development Tools Lab at Huawei and teaches software engineering and object-oriented programming.

• Education:

  Applied mathematics

Salman Ahmadi-Asl was born in Ilam, Iran, in 1987. He did his bachelor's degree at Ilam University and master's degrees at Tarbiat Modares University and his PhD at Vali-e-Asr University of Kerman, all in applied mathematics (numerical analysis). He was selected as the best researcher during his PhD and the first-rank student in his bachelor. After the PhD, he started to work as a senior research scientist on the tensor decomposition topic. His research topic was the development of randomized algorithms for fast computation of different types of tensor decompositions. His main contribution was providing new perspectives and simulations to show the importance of the randomization framework for fast low-rank tensor approximation. He has joined Innopolis University since November 2024 as an assistant professor in the Lab of Machine Learning and Knowledge Representation. His main research interests are developing fast randomized algorithms for computing different types of tensor decompositions and their applications in signal processing, machine learning, and deep learning.

• Education:

  Physical and Mathematical Sciences

Research interests of Anna Maslovskaya are focused on mathematical modeling and in silico studies of microbiological systems, methods for intelligent analysis of biomedical signals and images, models of field effects in functional materials. Education: Anna Maslovskaya graduated from the Amur State University with a degree in Applied Mathematics, in 2014 she defended her higher Doctoral Dissertation at Saint Petersburg State University in Mathematical Modelling, Numerical Methods and Software Packages, she was awarded the title of Full Professor in 2022. The main disciplines are mathematical modelling and computer simulation, numerical methods, techniques for data processing, time series data mining, methodology and organization of research. Anna Maslovskaya is the author of 57 publications in peer-reviewed national and international journals, 4 books and 28 registered computer programs. Three candidates supervised by Anna Maslovskaya have received PhD degree. She is a member of the editorial board of the journal "Informatics and Control Systems" (RF), a member of the Dissertation Defense Committee, a reviewer of scientific journals of Elsevier, Springer, MDPI and Russian scientific journals, a member of programme committees of international scientific conferences.

• Country:

  Belgium

• Education:

  University of Mons

Valentin Leplat received engineering degrees in mechanical engineering fr om the Gramme Institute in Liège, Belgium, in 2012, and in computer science and applied mathematics engineering from the University of Mons, Belgium, in 2017. He worked for six years as an aerospace engineer at SONACA in Gosselies, Belgium. His main activities involved the numerical analysis (aerodynamics and structural) of aircraft and spacecraft structures. He participated in the design and certification of the wings of the CS-100 Bombardier, EMBRAER 190E2, and EMBRAER 175E2 aircraft. He completed his Ph.D. in applied mathematics in January 2021 on the topic of Nonnegative Matrix Factorizations (NMF), associated with the Department of Mathematics and Operations Research at the University of Mons, Belgium, under the supervision of Nicolas Gillis and Xavier Siebert. His main results are threefold: (1) the analysis of the geometry behind NMF, which allowed for the proposal of new models and efficient algorithms capable of recovering and identifying the factors that gave rise to the data (also referred to as the problem of uniqueness of the factorization); (2) the algorithmic aspect of NMF; in fact, computing a nonnegative factorization requires the resolution of challenging non-linear non-convex optimization problems under constraints, for which new optimization frameworks have been proposed; and (3) the first conic formulation of NMF, which allows for the simultaneous update of all factors of the decomposition instead of using block-coordinate schemes. In 2021, he was a postdoctoral research associate in applied mathematics at Université Catholique de Louvain (Belgium) under the supervision of Yurii Nesterov, wh ere he studied the complexity of some variants of NMF and derived optimization methods for minimizing concave functions over convex sets. Between October 2021 and July 2024, he worked at Skoltech (Moscow) as a senior research scientist and later as a leading research scientist under the supervision of Ivan Oseledets and Anh Huy Phan on the topics of machine learning, stochastic optimization, and tensor decompositions. Since July 2024, he joined Innopolis University as Assistant Professor among the Faculty of Computer Science and Engineering and the Institute of Data Analysis and Artificial Intelligence. His current research activities revolve around the development of efficient optimization methods for solving large-scale non-convex problems in both deterministic and stochastic settings, the development of randomized methods to compute tensor decompositions, and the study of modern tensor decomposition models (such as deep Nonnegative Matrix Factorization) with an emphasis on the problems of automatic model order selection, robustness, and identifiability.

• Country:

  USA

• Education:

  Georgia Institute of Technology

Sergio Mayorga got his bachelor's degree in mathematics at the Universidad de Antioquia (Medellín, Colombia) and went on to earn a Ph.D. in mathematics at Georgia Tech (USA). His dissertation subject was the first-order mean field games master equation. He taught at Georgia Tech and at Baylor University (Texas) where he was a post-doc. Since arriving in Russia he has taught at Saint-Petersburg State University and the Moscow Institute of Physics and Technology. He also collaborates with the private industry. His research interests include mean field games and control theory, optimal transport and mathematical modelling.

• Country:

  Switzerland

• Education:

  University of Bern

Rustam A. Lukmanov received his Ph.D. in Physics from the University of Bern in 2021 and continued his research there as a Postdoctoral Researcher. In 2023, he was recognized with a BRICS and SCO Young Leaders Award. Dr. Lukmanov's research focuses on data analysis, machine learning, bioinformatics, data mining, and the explainability of AI models. He is a primary instructor for undergraduate courses in Explainable AI, Data and Knowledge Representation, and Capstone Project.

• Education:

  University of British Columbia (UBC)

Nikola Zlatanov was born in Macedonia. He received his Dipl.Ing. and Master degrees in electrical engineering fr om Ss. Cyril and Methodius University, Skopje, Macedonia in 2007 and 2010, respectively, and his PhD degree from the University of British Columbia (UBC) in Vancouver, Canada in 2015. Immediately after his PhD, he became a Lecturer (US equivalent to Assistant Professor) in the Department of Electrical and Computer Systems Engineering at Monash University in Melbourne, Australia, wh ere he was promoted to Senior Lecturer in 2020. Since 2022, Dr Zlatanov has been a Professor at Innopolis University, Russia.

His current research interests include machine learning and wireless communications.
Dr. Zlatanov received several scholarships/awards/grants for his work including UBC's Four Year Doctoral Fellowship in 2010, UBC's Killam Doctoral Scholarship and Macedonia's Young Scientist of the Year in 2011, the Vanier Canada Graduate Scholarship in 2012, best journal paper award from the German Information Technology Society (ITG) in 2014, best conference paper award at ICNC in 2016, and ARC Discovery Early Career Researcher Award (DECRA) in 2018.
Dr. Zlatanov served as an Editor of IEEE Communications Letters in the period 2015-2018, and as an Editor of IEEE Wireless Communications Letters 2020-2023.

• Education:

  Bashkir State University

Ruslan Saduov holds a cum laude degree in Philology, Teaching, and Translation from Bashkir State University. Previously, taught at Bashkir State University and held a position of Director of Fundamental Applied Linguistics Program. Designed and implemented courses such as academic writing, public speaking, forensic linguistics, translation praxeology. Candidate of Philology with a focus on linguistic landscape, multimodal texts, political and media linguistics, communication studies, and translation criticism. Authored and edited over 100 publications. Managed several grant projects (Russian Fundamental Research Grant, Russian Presidential Grant, Kostomarov Grant). Provider of translation and interpretation (simultaneous and consecutive) services.

• Country:

  Russia

• Direction:

  Linguistics, technical translation

Georgy V. Gelvanovsky is a PhD in comparative linguistics and a Member of American Association of Teachers of English to Speakers of Other Languages (TESOL). He has been teaching Business English and English for Specific Purposes for 21 years overall, of which 16 years were at university level. During his university employment, Dr. Gelvanovsky, among other things, taught such courses as: Business Correspondence in English,
-Understanding Contracts in English, Telephone Conversation in English, Effective Presentations in English, Effective Meetings in English Dr. Gelvanovsky holds a Certificate of Honor issued by the Russian Federation Ministry of Education and Science for the successful contribution into training business specialists. He also trained a team of students which won the second place in All-Russia English Competition for International Business Students. Dr. Gelvanovsky spent 11 months in the USA within the Junior Faculty Development Program (JFDP) majoring in applied linguistics. Dr. Gelvanovsky has extensive translation experience in oil-and-gas sphere. At Innopolis University, Dr. Gelvanovsky teaches English for Academic Purposes, Academic Writing and Research Culture, and English for PhD students. Dr. Gelvanovsky also offers writing consultations for students and faculty.

• Education:

  Mathematical modeling, numerical methods, software packages

Ivan Konyukhov graduated from the Applied Mathematics Department of the Institute of Computational Mathematics and Informational Technologies of Kazan (Volga region) Federal University (Russian Federation) in 2012 as mathematician and system programmer. In 2016 Ivan Konyukhov successfully defended his PhD thesis in physics and mathematics by specialty 05.13.18 — mathematical modeling, numerical methods and software packages in Kazan Federal University (Russian Federation). Since 2010 he has been holding different positions in the scientific-production center LLC «NPC Nefte-Gaz» (Sarov, Russian Federation) and has been working on the development of software packages aimed at improving of the oil production technologies. From 2012 to 2016 he worked as an assistant at the Applied Mathematics Department of Kazan (Volga region) Federal University (Russian Federation) and was engaged in scientific activities by the specialty and teaching different classes in mathematics and computer science. Since 2017 he has worked as a Researcher of Innopolis University and since January of 2019 he has been holding a position of a postdoctoral researcher of the laboratory of data analysis and machine learning in oil and gas industry.His field of scientific interests is mathematical and computer modeling of the oil fields penetrated by the systems of injecting and producing wells equipped with submersible centrifugal pumping units.

• Education:

  PhD, Università di Pisa, Italy

Paolo Ciancarini is Professor of Computer Science at the Univ. of Bologna. He has been Director of the School in Computer and Internet Sciences (both graduate and undergraduate). He is member of the PhD school in Informatics. His research interests include: software engineering, software architectures, formal methods, advanced Web technologies for groupware and digital documents, entertainment computing. He has been involved as a site leader in several projects funded by the European Commission. He is member of IFIP TC2 8Software) and TC16 (Entertainment Computing). He is member of ACM, IEEE, and ICGA (International Computer Games Association). He has published several books, more than 50 papers in International Journals and more than 120 papers in International Conferences and Workshops.