Maksim Eremeev
NLP Engineer, Researcher
  • Name: Maksim Eremeev

  • Birthday: 02 February 1999

  • Education: MSc. in DS

  • Job: NLP Engineer

  • Email:

    me@maksimeremeev.com

  • Papers: GScholar

  • Github: maks5507

  • LinkedIn: Maksim Eremeev

About Me

Hey,

My name is Max. I am a Machine Learning Engineer and researcher, focusing in Natural Language Processing.

I graduated from Lomonosov Moscow State University in 2020 with BSc. in Applied Mathematics and Computer Science degree. Currently, I am pursuing a MSc. in Data Science degree at New York University.

Software Engineering, Web Programming, designing and embedding Machine Learning models are among my skills, while my primary research interests are Machine Translation, Information Search, and Text Summarization.

At this website you can find some information about me, my career and life. I am looking forward to collaborating with you!

Skills

Programming Languages & Software Engineering

C++ (incl. C++17)
Python3
Parallel Computing
SOA (Microservices)

NLP Techniques

Topic Modeling
Search Engines
Recommender Syst.
Text Summarization

Web programming

JavaScript (Node.JS)
HTML, CSS, PHP
HTTP Server building
REST API

Resume

  • Working History

  • Machine Learning Research Intern -- Curai Health

    Jan 2022 - present
  • Research Assistant -- NYU CILVR lab

    Mar 2021 - present

    Conducting research on mitigating brevity problem in neural machine translation systems.

  • NLP Research Engineer -- MSU Center for Big Data

    Oct 2019 - Jul 2020

    I led the development of the non-profit search engine and analytical system over the collection of 80M research papers (https://scisearch.ai) in a recourse-constrained environment. A product was successfully designed, implemented and acquired by the MIPT Machine Intelligence Lab.

  • Middle NLP Research Engineer -- Digital Decisions LLC

    Feb 2019 - Oct 2019

    I was responsible for to the development of the NLP-driven search engine and recommender system, and introduced a new scheme of building memory efficient sentence embeddings. I also proposed business development strategy extensions helping to achieve the next investment round.

  • NLP Engineer-- MIPT Machine Intelligence Lab

    Jul 2018 - Jan 2019

    I contributed to the development of a search engine for the largest Russian aggregator of the public texts. I designed microservices-based product architecture and ranking model, successfully delivering the project to the customer on time.

  • Developer Intern -- Kaspersky Lab

    Feb 2017 - Jul 2018

    Took part in the developing of the assembly line for the Kaspersky Lab products..

Contract projects

  • Developer -- Sberbank AI Lab

    May 2018, Moscow, Russia

    Designed and implemented an interactive adaptive web-interface for clustering models. The interface was successfully demonstrated at the Sberbank Demo-Day.

  • Developer -- Returno Ltd.

    Sep 2017 -- Nov 2017

    Frontend developer of the Google Chrome Extension prototype. The prototype was presented and approved for the seed investment round.

  • Frontend developer -- Crimson Education

    Jun 2017, Moscow, Russia

    Designed and implemented the web-interface for the SAT testing system. For the successful work the letter of gratitude was issued.

Papers

  • I.Kulikov*, M.Eremeev*, K.Cho. Characterizing and addressing the issue of oversmoothing in neural autoregressive sequence modeling. ArXiv preprint, New York, US. 2021.
  • M.Eremeev, K.Vorontsov. Quantile-based Text Complexity Measure. Dialogue-2020, Moscow, Russia. 2020.
  • M.Eremeev, K.Vorontsov. Quantile-based approach of measuring cognitive complexity of text. In proceedings of Russian National Conference MMPR-2019, Moscow, Russia, 2019.
  • M.Eremeev, K.Vorontsov. Lexical Quantile-Based Text Complexity Measure. In Proceedings of the 12th International Conference on "Recent Advances in Natural Language Processing", Varna, Bulgaria, 2019.
  • M.Eremeev, A.Yanina. Exploratory Search based on Topic Modelling (in Russian). Book of Abstracts of XXVI International Conference of Students, Graduates and Young Scientists "Lomonosov-2019", Computational Mathematics and Cybernetics section, Moscow, Russia, 2019.

Teaching

  • I was a grader for DS-GA 1011 NLP with Representation Learning course (with prof. Kyunghyun Cho as instructor) at New York University Center for Data Science. I designed labs, graded quizzes, and held office hours.
  • I was a teaching assistant at the "My First Paper" course at Moscow Institute of Physics and Technology (MIPT). I supervised the research on Reading Order generation with Topic Models conducted by a third-year MIPT student. The work was awarded the highest grade and the results are now getting prepared for publishing.

    Results:
    You can reach out to me to request more information about this project.

Courseworks and Thesises

Conferences

  • Dialogue-2020

    6/19/2020, Moscow, Russia

    Dialogue -- one of the largest NLP conferences held in Russia. Presented a paper "Quantile-based approach to estimating cognitive text complexity".

  • OpenTalks.AI

    2/20/2020, Moscow, Russia

    OpenTalks.AI -- the largest Russian industrial conference on AI and Data Science. Presented a poster on "Quantile-based approach to estimating cognitive complexity".

  • Mathematical Methods of Pattern Recognition

    11/29/2019, Moscow, Russia

    Gave a talk on "Quantile-based approach to estimating cognitive complexity".

  • Recent Advances of Natural Language Processing

    9/4/2019, Varna, Bulgaria

    Poster Session at the international conference. Topic: "Lexical Quantile-based Text Complexity Measure".

  • DataFest

    5/11/2019, Moscow, Russia

    One of the largest Data Science conferences in CIS. Held a talk at Science day at the BigARTM workshop section on "Estimating text complexity to rank exploratory search results".

Contact Information & Links

I really prefer email or telegram as a communication resource.