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leffff/README.md

Lev Novitskiy

Machine learning engineer / Data Scientist

Fields of interest: Diffusion Distillation, Diffusion, Mulimodal models, Flow Matching, GANs


πŸ“Š ML stack

python pytorch pytorch-geometric albumentations huggingface diffusers wandb catbost catbost pandas spark plotly seaborn

πŸ”§ Other skills

bash git

πŸ‘¨β€πŸ’» Work experience

  • DL Researcher at SBER AI (April 2024 - Present day):

    • Developed a universal Multistage Video Diffusion Distillation Pipeline (Ρ…2 - Ρ…8), CFG distill -> Consistency distill -> Adversarial Distillation
    • Kandinsky 4.1 Video Distillation (Ρ…8 speedup)
    • WAN 2.1, Hunyuan Video Distillation (Ρ…8 speedup)
    • 1000+ GPU distirubuted training pipeline (PyTorch)
    • Kandinsly 4.0 T2V Flash (Distillation x25 speedup)
    • Video Diffusion Distillation (LADD, ReFlow, LCM)
    • Auto-Encoders (VQ, KL) Created SOTA KL-VAE for LDMs
    • FlowModels Inprementation of Flow-based models and distillation technoiques
    • Dragon Diffusion on Kandinsky 3.0
    • 3D Microstructures generation
  • DL Researcher at AIRI (April 2023 - May 2024)
    As a result of the research we propose several new models for crystal structure generation and modification code

    • New materials design with VAEs (VAEs)
    • Formation Energy regression with neural networks (GNNs, PointNet, CNNs, Transformers)
    • Crystall structure generation, optimization (Diffusion, Flow Matching, Bridge Matching, Auto-Encoders, CNNs, Transformers, En-Transformers)
  • DL Engeneer at SBER Cyber Security (July 2022 - April 2024):

    • NLP: fraud call analisys
    • Classic ML: fraud detection with gradient boosting
    • Transaction Graph Neural Networks (GCN, GAT, GraphSAGE, Graphormer, GIN)
    • Transaction Graph Neural Network pretraining (self-supervised: ARGA, ARGVA, GAEs, VGAEs, Contrastive Learning)
    • Transaction Graph Neural Network (Temporal GNNs)
    • Transaction sequence scoring (LSTM, GRU, Transformer Encoder)
    • User scoring (Gradient Boosting, Ensembling)
    • Vulnerability detection in assembly with neural networks (Angr, GNNs)
    • Antifraud Voice Bot for preventinng call fraud (BERT, NSP, Pretraining, SFT, GPT, FAISS, HNSW, Retrieval, Whisper, ConFormer)

πŸŽ“ Education

Cources

πŸ† Competition Background

πŸŽ‰ Other Achievements

πŸ‘¨β€πŸ« Other activities

🐢 Projects

Languages

πŸ‡·πŸ‡Ί Russian - Native
πŸ‡¬πŸ‡§ English - C1
πŸ‡¨πŸ‡³ Chinese - A2

Hobbies

  • πŸ„β€β™‚οΈ Surfing
  • πŸŠβ€β™‚οΈ Swimming
  • πŸ‚ Snowboarding

Contacts

android android

My blog

android

Pinned Loading

  1. ai-forever/Kandinsky-5 ai-forever/Kandinsky-5 Public

    Kandinsky 5.0: A family of diffusion models for Video & Image generation

    Python 80 4

  2. ai-forever/Kandinsky-4 ai-forever/Kandinsky-4 Public

    Text and image to video generation: Kandinsky 4.0 (2024)

    Python 147 12

  3. Diffusion-Reward-Modeling-for-Text-Rendering Diffusion-Reward-Modeling-for-Text-Rendering Public

    Jupyter Notebook 61 1

  4. FlowModels FlowModels Public

    The aim of this repository is to test and implement Flow-Matching-based models

    Jupyter Notebook 111 3

  5. graphormer-pyg graphormer-pyg Public

    Microsoft Graphormer (https://arxiv.org/abs/2106.05234) rewritten in Pytorch-Geometric

    Python 152 17

  6. adversarial-diffusion-distillation adversarial-diffusion-distillation Public

    My Implementation of Adversarial Diffusion Distillation https://arxiv.org/pdf/2311.17042.pdf

    Jupyter Notebook 86 9