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University
Innopolis University
Education, research and development in the field of IT and Robotics
- Education
- International applicants
- Bachelor's program
- Master's programs
- Postgraduate study
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- International relations office
- Teaching Excellence Center
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Writing Hub
IU Writing Hub (WH) offers editing and proofreading service for IU faculty, researchers and students.
- ALUMNI
Education
World-class IT education in Russia in English
- Research
- Scientific Research activities
- Institute of Software Development and Engineering
- Institute of Data Science and Artificial Intelligence
- Institute of Information security and cyberphysical systems
- Institute of Robotics and computer vision
Science
Innopolis University has 15 laboratories and 7 research centers, which conduct research in the field of artificial intelligence, robotics, big data, software development, information security
- Innovation
- Education
Data Meaning and Bioinformatics Laborotaory
Lab's mission is to conduct cutting-edge research in data analysis areas through both applied and theory based approaches in order to produce noteworthy results that are not only publishable, but applicable to our daily lives.
Also, it is significantly important for us to provide an environment to university students that will help them develop and polish their research skills.
Head of the Laboratory – Yaroslav Kholodov
ya.kholodov@innopolis.ruLaboratory Activities
Main research areas of the laboratory today:
— Protein interaction modeling
— Deep learning for peptide-protein docking
— Traffic data fusion from various types of sources
— Traffic flow modeling with adaptive control of traffic lights to improve efficiency of transportation network
— Road state forecast in situation of regular and unpredicted overloads of transportation network
— Engineering and development of algorithms for automated intelligent transport systems
MEMBERS
Yaroslav Kholodov
Head of the laboratoty, PhD, associate professor
Viktor Kazorin
Assistant
Projects
01
Computational Modeling in Molecular Biology
Predicting the protein-ligand affinity with machine learning methods; сonvolutional neural networks for protein structure prediction; Monte-Carlo-based iterative generation of multiple sequence alignments for protein homolog search; development of FFT-based algorithm to compute Born radii in the generalized Born theory of biomolecule solvation
02
Traffic modeling by using SUMO tools with platoons and AI routing of intersection
Mathematical modelling of traffic flows (at micro and macro levels) including modeling of traffic flow consisting of unmanned vehicles and development of algorithms for their interaction
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