Карпов Максим Евгеньевич

Responsibilities

Teaching Data Culture courses in Bachelor's degree programs;
Teaching courses at the professional retraining programs of the Center for Continuing Education.

Education

2022

Doctoral programme
HSE University

2020

Master's in Applied Mathematics and Informatics
HSE University, Faculty of Computer Science

2014

Degree in International Relations
Lomonosov Moscow State University, Faculty of Global Studies

Continuing education / Professional retraining / Internships / Study abroad experience

Advanced training program "Artificial Intelligence for Teaching Various Courses", certificate issue date September 18, 2024 Certificate;

Advanced training program "Pedagogical Skills in Teaching Computer Science", certificate issue date June 3, 2024 Certificate;

Advanced training program "Digital Humanities: Level A1", certificate issue date October 27, 2023 Certificate;

Postgraduate diploma in the field of training 09.06.01 Computer Science and Computer Engineering (October 28, 2022) Diploma;

International Seminar «Distance-Based Education in The New Decade of XXI century» (November 27, 2020) Certificate;

Process Mining: Data Science in Action, Eindhoven University of Technology (Coursera, with honors) Certificate;

Data Culture Workshop on Mastering Teaching Skills (April 2019, Faculty of Computer Science, HSE University) Certificate;

Workshop «Modern machine learning and methods of teaching data analysis» (January 2018, HSE Study Center Voronovo, Moscow region) Certificate;

Third Machine Learning Summer School (July 17 - 23, 2017, Reading University, UK) Certificate of Attendance.

Professional Interests

machine learning deep learning

Awards and Accomplishments

Young Faculty Support Programme (Group of Young Academic Professionals)
Category "New Researchers" (2019)

Courses (2024/2025)

Basics of Programming in Python (Bachelor’s programme; Faculty of World Economy and International Affairs; 1 year, 2 module)Rus
Data Analysis (Bachelor’s programme; Faculty of Economic Sciences; 3 year, 1 module)Rus
Deep Learning (Bachelor’s programme; Faculty of Computer Science; 3 year, 3, 4 module)Eng
Introduction into Python (Bachelor’s programme; School of Foreign Languages field of study Linguistics, field of study Linguistics; 2 year, 2, 3 module)Rus
Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Eng
Python Basic (Mago-Lego; 1 module)Eng
Python Basic (Master’s programme; Faculty of Computer Science; 1 year, 1 module)Eng
Statistics for Social Science (Bachelor’s programme; Faculty of World Economy and International Affairs; 2 year, 1, 2 module)Eng
Past Courses

Scientific and Practical Workshop on Reproduction of State-of-the-art Scientific Results (4-18 April 2021)

Mentoring a group of students at the third project workshop from Yandex and Sirius. The theme of the project: «Clustering of CERN Logs».

Project Workshop for Developers, Educational Center «Sirius» (1-14 February 2019)

Mentoring a group of students at the first project workshop from Yandex, HSE and Sirius. The theme of the project: «Segmentation of images of city scenes for controlling self-driving vehicles».

Summer Workshop «Island 10-21», the Far Eastern Federal University (11-13 July 2018)

Crowd-science for solving big data processing problems. Increasingly, in business and science, we are faced with tasks that require data science expertise to solve them. Is it necessary to develop our own expertise in this area? Is it possible to attract external experts? Can I use the expertise of the data science community through platforms such as kaggle, coda lab or Yandex contest? How to formulate a problem in terms of clear and adequate solutions on these platforms. We will tell you about the ways to prepare tasks, features of the platforms and will go from the idea to the publication of the contest on one of them.

Timetable for today

Full timetable

Conferences

2022
46-я школа-конференция ИППИ РАН «Информационные технологии и системы» (ИТиС-2022) (Огниково Московской области). Presentation: Predicting a Next Activity in Event Logs: an Approach based on LSTMs and Gradient Boosting

Grants

Performer of the RFBR grant ‎‎«‎Basic research projects carried out by young scientists studying in doctoral school», application no. 20-37-90136, project topic: «‎Development of natural language processing methods for detecting anomalies in the event logs of big data storage systems» (2020-2022) under the supervision of Andrey Ustyuzhanin, Head of the laboratory.

14

Aug

2017

Third Machine Learning Summer School Held in UK

On July 17-23 the Third Machine Learning summer school organized by Yandex School of Data Analysis, Laboratory of Methods for Big Data Analysis at the National Research University Higher School of Economics and Imperial College London was held in Reading, UK. 60 students, doctoral students and researchers from 18 countries and 47 universities took part in the event.

Maksim Karpov