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Vladimir Vinogradov

4 accepted papers

2025

ChemX: A Collection of Chemistry Datasets for Benchmarking Automated Information Extraction

Anastasia Vepreva, Julia Razlivina, Mariia Eremeyeva, Nina Gubina, Anastasia Orlova, Aleksei Dmitrenko +7
NeurIPS 2025poster

Despite recent advances in machine learning, many scientific discoveries in chemistry still rely on manually curated datasets extracted from the scientific literature. Automation of information extraction in specialized chemistry domains has the potential to scale up machine learning applications an…

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2025

MADD: Multi-Agent Drug Discovery Orchestra

Gleb Vitalevich Solovev, Alina Borisovna Zhidkovskaya, Anastasia Orlova, Nina Gubina, Anastasia Vepreva, Rodion Golovinskii +15
EMNLP 2025

Hit identification is a central challenge in early drug discovery, traditionally requiring substantial experimental resources. Recent advances in artificial intelligence, particularly large language models (LLMs), have enabled virtual screening methods that reduce costs and improve efficiency. Howev

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2024

Hybrid Generative AI for De Novo Design of Co-Crystals with Enhanced Tabletability

Nina Gubina, Andrei Dmitrenko, Gleb Vitalevich Solovev, Lyubov Yamshchikova, Oleg Petrov, Ivan Lebedev +4
NeurIPS 2024poster

Co-crystallization is an accessible way to control physicochemical characteristics of organic crystals, which finds many biomedical applications. In this work, we present Generative Method for Co-crystal Design (GEMCODE), a novel pipeline for automated co-crystal screening based on the hybridization…

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2024

Unveiling the Potential of AI for Nanomaterial Morphology Prediction

Ivan Dubrovsky, Andrei Dmitrenko, Aleksei Dmitrenko, Nikita Serov, Vladimir Vinogradov
ICML 2024poster

Creation of nanomaterials with specific morphology remains a complex experimental process, even though there is a growing demand for these materials in various industry sectors. This study explores the potential of AI to predict the morphology of nanoparticles within the data availability constraint…

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