3D modeling and segmentation of diffusion weighted MRI data. - Leonid Zhukov; Ken Museth; David E. Breen; Ross T. Whitaker (Image-Guided Procedures, 2001)

Dynamic deformable models for 3D MRI heart segmentation. - Leonid Zhukov; Zhaosheng Bao; Igor Guskov; John Wood; David E. Breen (Image Processing, 2002)

Level-Set Segmentation From Multiple Non-Uniform Volume Datasets. - Ken Museth; David E. Breen; Leonid Zhukov; Ross T. Whitaker (IEEE Visualization, 2002)

Oriented Tensor Reconstruction: Tracing Neural Pathways from Diffusion Tensor MRI. - Leonid Zhukov; Alan H. Barr (IEEE Visualization, 2002)

Direct Pattern Tracking On Flexible Geometry. - Igor Guskov; Leonid Zhukov (WSCG, 2002)

Heart-Muscle Fiber Reconstruction from Diffusion Tensor MRI. - Leonid Zhukov; Alan H. Barr (IEEE Visualization, 2003)

Level set modeling and segmentation of diffusion tensor magnetic resonance imaging brain data. - Leonid Zhukov; Ken Museth; David E. Breen; Alan H. Barr; Ross T. Whitaker (J. Electronic Imaging, 2003)

Methods for MiningWeb Communities: Bibliometric, Spectral, and Flow. - Gary William Flake; Kostas Tsioutsiouliklis; Leonid Zhukov (Web Dynamics, 2004)

SVD based Term Suggestion and Ranking System. - David F. Gleich; Leonid Zhukov (ICDM, 2004)

Influence of head tissue conductivity in forward and inverse magnetoencephalographic Simulations using realistic head models. - Robert Van Uitert; Chris R. Johnson 001; Leonid Zhukov (IEEE Trans. Biomed. Eng., 2004)

Oriented Tensor Reconstruction Portions reprinted, with permission, from Zhukov and Barr [26]. Copyright © 2002, IEEE. - Leonid Zhukov; Alan H. Barr (The Visualization Handbook, 2005)

From Triconcepts to Triclusters. - Dmitry I. Ignatov; Sergei O. Kuznetsov; Ruslan A. Magizov; Leonid E. Zhukov (RSFDGrC, 2011)

Can triconcepts become triclusters? - Dmitry I. Ignatov; Sergei O. Kuznetsov; Jonas Poelmans; Leonid E. Zhukov (Int. J. Gen. Syst., 2013)

Parallel Corpus Approach for Name Matching in Record Linkage. - Jeffrey Sukharev; Leonid Zhukov; Alexandrin Popescul (ICDM, 2014)

Learning Alternative Name Spellings. - Jeffrey Sukharev; Leonid Zhukov; Alexandrin Popescul (CoRR, 2014)

Classification of Normal and Pathological Brain Networks Based on Similarity in Graph Partitions. - Anvar Kurmukov; Yulia Dodonova; Leonid Zhukov (ICDM Workshops, 2016)

Classification of structural brain networks based on information divergence of graph spectra. - Yulia Dodonova; Sergey Korolev; Anna Tkachev; Dmitry Petrov; Leonid Zhukov; Mikhail Belyaev (MLSP, 2016)

Boosting connectome classification via combination of geometric and topological normalizations. - Dmitry Petrov; Yulia Dodonova; Leonid Zhukov; Mikhail Belyaev (PRNI, 2016)

Kernel classification of connectomes based on earth mover's distance between graph spectra. - Yulia Dodonova; Mikhail Belyaev; Anna Tkachev; Dmitry Petrov; Leonid Zhukov (CoRR, 2016)

Scientific Matchmaker: Collaborator Recommender System. - Ilya Makarov; Oleg Bulanov; Olga Gerasimova; Natalia Meshcheryakova; Ilia Karpov; Leonid E. Zhukov (AIST, 2017)

Classifying Phenotypes Based on the Community Structure of Human Brain Networks. - Anvar Kurmukov; Marina Ananyeva; Yulia Dodonova; Boris Gutman; Joshua Faskowitz; Neda Jahanshad; Paul M. Thompson; Leonid Zhukov (GRAIL/MFCA/MICGen@MICCAI, 2017)

Joint Node-Edge Network Embedding for Link Prediction. - Ilya Makarov; Olga Gerasimova; Pavel Sulimov; Ksenia Korovina; Leonid E. Zhukov (AIST, 2018)

Co-authorship Network Embedding and Recommending Collaborators via Network Embedding. - Ilya Makarov; Olga Gerasimova; Pavel Sulimov; Leonid E. Zhukov (AIST, 2018)

Recommending Co-authorship via Network Embeddings and Feature Engineering: The case of National Research University Higher School of Economics. - Ilya Makarov; Olga Gerasimova; Pavel Sulimov; Leonid E. Zhukov (JCDL, 2018)

Dual network embedding for representing research interests in the link prediction problem on co-authorship networks. - Ilya Makarov; Olga Gerasimova; Pavel Sulimov; Leonid E. Zhukov (PeerJ Comput. Sci., 2019)

Fault detection in Tennessee Eastman process with temporal deep learning models. - Ildar Lomov; Mark Lyubimov; Ilya Makarov; Leonid E. Zhukov (J. Ind. Inf. Integr., 2021)

Uncertainty Estimation of Transformer Predictions for Misclassification Detection. - Artem Vazhentsev; Gleb Kuzmin; Artem Shelmanov; Akim Tsvigun; Evgenii Tsymbalov; Kirill Fedyanin; Maxim Panov; Alexander Panchenko; Gleb Gusev; Mikhail Burtsev 001; Manvel Avetisian; Leonid Zhukov (ACL (1), 2022)

Towards Computationally Feasible Deep Active Learning. - Akim Tsvigun; Artem Shelmanov; Gleb Kuzmin; Leonid Sanochkin; Daniil Larionov; Gleb Gusev; Manvel Avetisian; Leonid Zhukov (NAACL-HLT (Findings), 2022)

Advanced service data provisioning in ROF-based mobile backhauls/fronthauls. - Mikhail E. Belkin; Leonid Zhukov; Alexander S. Sigov (CoRR, 2022)

Eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI. - Semen A. Budennyy; Vladimir D. Lazarev; Nikita Zakharenko; Alexey N. Korovin; Olga Plosskaya; Denis Dimitrov; Vladimir Arkhipkin; Ivan V. Oseledets; Ivan Barsola; Ilya Egorov; Aleksandra Kosterina; Leonid Zhukov (CoRR, 2022)

Anomaly segmentation model for defects detection in electroluminescence images of heterojunction solar cells. - Alexey N. Korovin; Artem I. Vasilyev; Fedor Egorov; Dmitry Saykin; Evgeny Terukov; Igor Shakhray; Leonid Zhukov; Semen A. Budennyy (CoRR, 2022)

New drugs and stock market: how to predict pharma market reaction to clinical trial announcements. - Semen A. Budennyy; Alexey Kazakov; Elizaveta Kovtun; Leonid Zhukov (CoRR, 2022)

Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough. - Alexander Ponomarchuk; Ilya Burenko; Elian Malkin; Ivan Nazarov; Vladimir Kokh; Manvel Avetisian; Leonid Zhukov (IEEE J. Sel. Top. Signal Process., 2022)

SensorSCAN: Self-supervised learning and deep clustering for fault diagnosis in chemical processes. - Maksim Golyadkin; Vitaliy Pozdnyakov; Leonid Zhukov; Ilya Makarov (Artif. Intell., 2023)

SensorSCAN: Self-supervised learning and deep clustering for fault diagnosis in chemical processes (Abstract Reprint). - Maksim Golyadkin; Vitaliy Pozdnyakov; Leonid Zhukov; Ilya Makarov (IJCAI, 2024)

Plug-and-Play Unsupervised Fault Detection and Diagnosis for Complex Industrial Monitoring. - Maksim Golyadkin; Maria Shtark; Petr Ivanov; Alexander Kozhevnikov; Leonid Zhukov; Ilya Makarov (IJCAI, 2024)

Graph-Based Retriever Captures the Long Tail of Biomedical Knowledge. - Julien Delile; Srayanta Mukherjee; Anton Van Pamel; Leonid Zhukov (CoRR, 2024)

TEDDY: A Family Of Foundation Models For Understanding Single Cell Biology. - Alexis Chevalier; Soumya Ghosh; Urvi Awasthi; James Watkins; Julia Bieniewska; Nichita Mitrea; Olga Kotova; Kirill Shkura; Andrew Noble; Michael Steinbaugh; Julien Delile; Christoph Meier; et al. (CoRR, 2025)