Scientific workshop "Big Data Analytics"

h1. Seminar "Big Data Analytics"

(sorted by later first)

h2. Schedule 2021, spring

Tuesday, 16:20, online: https://zoom.us/j/

h3. June, 2021

|4, |~~25 min slot~~

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

h3. May, 2021

|4, |-*Alexander Rusnak*. Thesis: Investigation of the possibility of generating neural network models for the generation of thematically and stylistically conditioned texts for low-resource languages / Исследование возможности создания нейросетевых моделей для генерации тематически и стилистически обусловленных текстов для малоресурсных языков.- (Postponed to uncertain date)

*Svetlana Kuchuganova*. Bachelor: Применение Mixup-Breakdown алгоритма для улучшения диаризации дикторов / Applying Mixup-Breakdown algorithm for speaker diarization improvement.

*Mukul Wishvas*. Thesis: Recognition, feature space representation, tracking, and performance enhancement in DCNN driven safety systems. / Распознавание, представление пространства функций, отслеживание и повышение производительности в системах безопасности, управляемых DCNN. (Moved from 18 May)

*Walid Koliai*. Thesis (1st year): Управляемая данными онлайн оценка смещений 2D изображения частиц с использованием графического процессора / Data driven online assessment of 2D particle image displacements using GPU.

-*Dinesh Yerukalareddy*. Thesis: Brain Tumor Classification from MRI Images using CNN with Extensive Data Augmentation / Классификация опухолей головного мозга по изображениям МРТ с использованием CNN с расширенной аугментацией данных.- (Moved to 18 May, switched with Mukul)

*Raphael Blankson*. Thesis: Applying Variational Circuits in Deep Learning Architectures for Improving Discriminative Power of  Speaker Identification Embeddings / Применение вариационных схем в архитектурах глубокого обучения для усиления дискриминативных свойств вложений в задаче идентификации дикторов.

*Maxim Kochanov*. Bachelor: Применение алгоритмов сегментации опухолей головного мозга для предсказания состояния пациентов / Applying brain tumor segmentation algorithms to predict patients state.

*Kozinets Roman*. Thesis: Analysis of CNN working with logical decision functions in the task of computer tomography images recognition / Анализ работы сети глубокого обучения с использованием логических решающих функций на примере задачи распознавания изображений компьютерной томографии. (Moved from 20 April)|

|11, |*Kirill Kalmutskiy*. Thesis: Training of deep neural networks with incomplete training information on the example of recognition of tomographic images / Обучение глубоких нейросетей при неполной обучающей информации на примере распознавания томографических изображений.

*Sayed Mohammad Sajjadi*. Thesis (1st year): Нахождение и изучение лидеров мнений в социальных медиа / Finding and studying opinion leaders in social media.

*Mikhail Rodin*. Thesis: Investigation of the possibility of constructing neural network models for thematically and stylistically determined poetic texts / Исследование возможности построения пораждающих нейросетевых моделей для тематически и стилистически обусловленных поэтических текстов.

*Oladotun Aluko*. Thesis: Studying applicability of Proof-of-Reputation as an alternative consensus mechanism for Distributed Ledger Systems / Исследование применимости "доказательства права репутацией" как альтернативного механизма обеспечения консенсуса для систем распределенного реестра.

*Rishab Tiwari*. Thesis: Online tool for linguistic and sociolinguistic studies accessing open online resources / Онлайн инструмент для проведения лингвистического и социолингвистического исследования с привлечением открытых онлайн ресурсов.

*Mark Baushenko*. Bachelor: Исследование алгоритмов синтеза русской речи, основанных на увеличении разрешения спектрограмм / Russian speech synthesis algorithms investigatoin based on spectrogram superresolution.|

|18, |*Daria Pirozhkova*. Thesis: Study of methods for automatic taxonomy enrichment.

*Enes Kuzucu*. Thesis (1st year): Оценка среднего времени отклика парадигмы стоп-сигнала по сигналам электроэнцефалографии (ЭЭГ) / Estimating average response time for Stop-signal paradigm from Electroencephalography (EEG) signals.

*Nikita Nikolaev*. Thesis: Zero-shot learning approach to the problem of short text classification.

*Sergey Verbitskiy*. Bachelor: Разработка алгоритма распознавания звуков с использованием ансамбля сверточных нейронных сетей / Sounds recognition algorithm development based on convolutional neural networks ensemble.

-*Mukul Wishvas*. Thesis: Recognition, feature space representation, tracking, and performance enhancement in DCNN driven safety systems. / Распознавание, представление пространства функций, отслеживание и повышение производительности в системах безопасности, управляемых DCNN.- (Moved to 4 May)

*Dinesh Yerukalareddy*. Thesis: Brain Tumor Classification from MRI Images using CNN with Extensive Data Augmentation / Классификация опухолей головного мозга по изображениям МРТ с использованием CNN с расширенной аугментацией данных.

*Kaivalya Pandey*. Thesis: Improving sentiment analysis for stock trends prediciton / Улучшение анализа тональности для предсказания трендов на бирже.|

|25, |*Khue Luu*. Thesis (1st year): Сегментаций опухолей мозга на основе 3D-Unet / Brain Tumor Segmentation with 3D-UNet.

*Alexey Korolev*. Thesis: Generalized zero-shot learning for intent classification and slot filling.

*Mikhail Liz*. Thesis: Quantitative processing of scanning probe microscopy image with deep learning techniques.

*Watana Pongsapas*. Galaxy detection and identification using deep learning and data augmentation link: https://www.sciencedirect.com/science/article/abs/pii/S2213133718300325, reproducible: https://github.com/astroCV/astroCV.

*Watana Pongsapas*. Thesis: Deep learning-based Machine Vision for the Task of Grasping Chemical Hardware.

*Alix Bernard*. Thesis: Enhancement of Turbulence Models by Machine Learning Techniques.|

h3. April, 2021

|6, |[Optional] Data Scientist - values and functions of a professional|

|13, #5601|*Sergey Verbitskiy*. wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations link: https://arxiv.org/pdf/2006.11477.pdf.

-*Oladotun Aluko*. Depth-Aware Video Frame Interpolation link: https://arxiv.org/pdf/1904.00830.pdf, reproducible: https://github.com/baowenbo/DAIN/.- (Moved back to 29 March)

*Rishabh Tiwari*. ResNeSt: Split-Attention Networks link: https://arxiv.org/pdf/2004.08955.pdf, reproducible: https://github.com/zhanghang1989/ResNeSt.

*Mark Baushenko*. WaveGlow: A Flow-based Generative Network for Speech Synthesis link: https://arxiv.org/abs/1811.00002v1, reproducible: https://github.com/NVIDIA/waveglow.

-*Dinesh Reddy*. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks link: https://arxiv.org/abs/1511.06434, reproducible: https://github.com/eriklindernoren/PyTorch-GAN/tree/master/implementations/dcgan.- (Moved to April 27)

*Maria Matveeva*. Thesis (1st year): Обнаружение текстовых связей с использованием методов иерархической кластеризации / Text relation detection using hierarchical clustering techniques.

*Andrey Yashkin*. A U-Net Based Discriminator for Generative Adversarial Networks link: https://arxiv.org/pdf/2002.12655.pdf, reproducible: https://github.com/boschresearch/unetgan.

*Vladislav Panferov*. Master thesis: Recognition of Rocks Lithology on the Images of Core Samples

-*Mohammed Nasser* (Moved from 29 March)- (Moved to 20 April)

*Daria Pirozhkova*. SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing link: https://arxiv.org/pdf/1808.06226v1.pdf, reproducible: https://github.com/google/sentencepiece (Moved from 20 April)|

|20 |-*Daria Pirozhkova*. SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing link: https://arxiv.org/pdf/1808.06226v1.pdf, reproducible: https://github.com/google/sentencepiece-

-*Kirill Kalmutskiy*. Wide & Deep Learning for Recommender Systems link: https://arxiv.org/abs/1606.07792, reproducible: https://github.com/shenweichen/DeepCTR.- (Moved to next time)

*Alexey Korolev*. Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data link: https://arxiv.org/abs/1909.06312, reproducible: https://github.com/Qwicen/node.

-*Mikhail Liz*. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks link: https://arxiv.org/abs/1506.01497, reproducible: https://github.com/facebookresearch/detectron2.- (Discarded as student took acad.vacation)

-*Sayed Mohammad*. Opinion leader detection using whale optimization algorithm in online social network link: https://www.sciencedirect.com/science/article/pii/S095741741930733X?casa_token=Sj6ySbKY5j0AAAAA:mPgOKDf9RS_AzUACoTAH7G6uu9-gUy_R5E4l6p7j6p916VcGwykuBDZKhfWqsSOeRSRfQ-D6yA.-  (Moved to the next time)

-*Mikhail Rodin*. Paper.-

-*Kozinets Roman*. Thesis: Analysis of CNN working with logical decision functions in the task of computer tomography images recognition / Анализ работы сети глубокого обучения с использованием логических решающих функций на примере задачи распознавания изображений компьютерной томографии.- (Moved to 4 May)

*Sergey Garmaev*. SpectralNet: Spectral Clustering using Deep Neural Networks link: https://arxiv.org/abs/1801.01587, reproducible: https://github.com/kstant0725/SpectralNet

*Mohammed Nasser* Thesis: Enhancement of consistent depth estimation for monocular videos / Улучшение согласованной оценки глубины для монокулярных видео (Moved from 29 March, 13 April)|

|27, #5616|*Hami bin Ismail*. Thesis (1st year): Распознавание различных объектов нефтепромысловой инфраструктуры методами машинного обучения / Recognition of different objects of oilfield infrastructure by machine learning methods.

*Nikita Nikolaev*. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer link: https://arxiv.org/abs/1910.10683v3, reproducible: https://github.com/google-research/text-to-text-transfer-transformer.

*Mukul Vishwas*. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks link: https://arxiv.org/abs/1703.10593.

*Kaivalya Pandey*. Practical Deep Reinforcement Learning Approach for Stock Trading link: https://arxiv.org/pdf/1811.07522v2.pdf, reproducible: https://github.com/AI4Finance-LLC/FinRL-Library.

*Raphael Blankson*. The power of data in quantum machine learning link: https://arxiv.org/pdf/2011.01938v2.pdf, reproducible: https://github.com/prantik-pdeb/Quantum-Machine-Learning.

*Sergey Berezin*. Thesis (1st year): Анализ современных алгоритмов распознавания именованных сущностей и аннотирования текста / Analysis of modern algorithms for named entitiy recognition and text summarization.

*Dinesh Reddy*. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks link: https://arxiv.org/abs/1511.06434, reproducible: https://github.com/eriklindernoren/PyTorch-GAN/tree/master/implementations/dcgan. (Moved from 13 April)

*Kirill Kalmutskiy*. Wide & Deep Learning for Recommender Systems link: https://arxiv.org/abs/1606.07792, reproducible: https://github.com/shenweichen/DeepCTR. (Moved from 20 April)|

h3. March, 2021

|2, #5537|-Enes. Paper-

Svetlana Kuchuganova. Audio Super Resolution using Neural Networks link: https://arxiv.org/abs/1708.00853v1, reproducible:https://github.com/kuleshov/audio-super-res.

-Maxim Kochanov. Paper.-

-Vasiliy Baranov. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation link: https://arxiv.org/pdf/1612.00593v2.pdf, reproducible:https://github.com/charlesq34/pointnet.-

Hami Ismail. TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images link: https://arxiv.org/abs/2001.01469.|

|9, #5536|*Rohan Rapthore*. Enriching Pre-trained Language Model with Entity Information for Relation Classification link: https://arxiv.org/abs/1905.08284, reproducible:https://github.com/wang-h/bert-relation-classification.

*Alexander Rusnak*. The Effectiveness of Data Augmentation in Image Classification using Deep Learning link: https://arxiv.org/pdf/1712.04621.pdf, reproducible: https://github.com/kandluis/nn-data-augmentation.

*Maria Matveeva*. Fake News Detection on Social Media using Geometric Deep Learning link: https://arxiv.org/abs/1902.06673.

*Mohammed Sweilam*. Unsupervised Monocular Depth Estimation with Left-Right Consistency link: https://arxiv.org/pdf/1609.03677.pdf, reproducible: https://github.com/mrharicot/monodepth.

*Khue Luu*. MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentationS3D-UNet: Separable 3D U-Net for Brain Tumor Segmentation link: https://arxiv.org/abs/1902.04049, reproducible: https://github.com/nibtehaz/MultiResUNet.

*Enes Kuzucu*. Age and gender classification using brain–computer interface link: https://link.springer.com/article/10.1007/s00521-018-3397-1 (moved from 2 March)|

|16, #5532|-*Alexander Rusnak*. Report from previous time about the paper results reproducibility.-

*Vladislav Panferov*. ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing link: https://arxiv.org/abs/1902.07669, reproducible:https://github.com/allenai/scispacy

*Rohan Rathore*. Thesis: Explorative Study of Explainable Artificial Intelligence Techniquest for Sentiment Analysis Applied for English Language.

*Alix Bernard*. Gradient Centralization: A New Optimization Technique for Deep Neural Networks link: https://arxiv.org/pdf/2004.01461v2.pdf, reproducible:https://github.com/Yonghongwei/Gradient-Centralization

*Virgilio Espina*. Thesis (1st year): Применение искусственного интеллекта в прогнозировании вспышки лихорадки Денге на Филиппинах / Application of Artificial Intelligence in Predicting Dengue Outbreak in the Philippines.

*Sergey Pnev*. TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation link: https://arxiv.org/pdf/2102.04306v1.pdf, reproducible:https://github.com/Beckschen/TransUNet.

*Maxim Kochanov*. Image-to-Image Translation with Conditional Adversarial Networks link: https://arxiv.org/pdf/1611.07004.pdf, reproducible:https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix. (Moved from 2 March)|

|23, |-*Vladislav Panferov*. Master thesis: Recognition of Rocks Lithology on the Images of Core Samples- (Moved to 13 April)

*Walid Koliai*. End to End Learning for Self-Driving Cars link: https://arxiv.org/abs/1604.07316, reproducible: https://github.com/SullyChen/Autopilot-TensorFlow.

*Vigrilio Espina*. Developing a dengue forecast model using machine learning: A case study in China link: shorturl.at/lwEFT.

*Sergey Berezin*. Big Bird: Transformers for Longer Sequences link: https://arxiv.org/abs/2007.14062v2, reproducible: https://github.com/google-research/bigbird.

*Kozinets Roman*. YOLOv4: Optimal Speed and Accuracy of Object Detection link: https://arxiv.org/pdf/2004.10934.pdf.

*Vasiliy Baranov*. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation link: https://arxiv.org/pdf/1612.00593v2.pdf, reproducible: https://github.com/charlesq34/pointnet. (Moved from 2 March)

-*Alexander Rusnak*. Report from previous time about the paper results reproducibility. (Moved from 16 March)- (Moved to 30 March)

*Alix Bernard*. Report from previous time about the paper results reproducibility. (Moved from 16 March)|

|30, |-*Mohammed Sweilam*. Thesis: Enhancement of consistent depth estimation for monocular videos / Улучшение согласованной оценки глубины для монокулярных видео- (Moved to 13 April)

*Alexander Donets*. Thesis: Automated thesaurus enrichment for the Russian Language using self-supervised deep learning approach.

*Alexander Donets*. FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP link: https://www.aclweb.org/anthology/N19-4010/, reproducible: https://github.com/flairNLP/flair.

*Sergey Pnev*. Thesis (1st year): Алгоритм семантической сегментации томографических изображений с использованием DNN / Algorithm of semantic segmentation of tomographic images using DNN.

*Vasiliy Baranov*. Thesis: Classification of COVID-19 in Computed Tomography using Deep Neural Networks.

*Alexander Rusnak*. Report from previous time about the paper results reproducibility. (Moved twice from 16,23 March)|

h3. February, 2021

|9, |Planning the semester|

|16, |Planning the semester

~~25 min slot~~

~~25 min slot~~|

|23, |Holiday|

h2. Schedule 2020, fall

Tuesday, 16:20, online: https://zoom.us/j/86212050320

h3. September, 2020

|8, #3879|Planning the semester|

|15, #3898|Invited lecture: Anton Kolonin, "scientific topics for master":https://trello.com/c/AYkBULyA

Planning the semester|

|22, #4005|Invited lecture: Dmitry Tailakov, "scientific topics for master":https://trello.com/c/TQEQuTvs/4-dmitry-taylakov-phd, "Enterprise Practice from DFT, and from SDAML NSU":/issues/4005

Planning the semester|

|29, #4100|Evgeniy Pavlovskiy @euxsun. "Topics for master thesis":https://trello.com/c/eRW2rCoI/5-evgeniy-pavlovskiy-phd.

Planning the semester|

h3. October, 2020

|6, #4197|Sergey Berezin. Towards a Human-like Open-Domain Chatbot https://arxiv.org/abs/2001.09977.

Nikita Nikolaev. Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks - IJCNLP 2019 - cited by 194. https://paperswithcode.com/paper/sentence-bert-sentence-embeddings-using.

Virgilio Espina. Reinforcement learning applied to Forex trading. https://bit.ly/33p4qXT.

Khue Luu. Generative Adversarial Networks https://arxiv.org/abs/1406.2661.

Vladislav Panferov. Progressive Semantic-Aware Style Transformation for Blind Face Restoration https://arxiv.org/pdf/2009.08709.pdf.|

|13, #4325|Daria Pirozhkova. OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction https://paperswithcode.com/paper/opennre-an-open-and-extensible-toolkit-for.

-Oladotun Aluko. Transformer-OCR https://github.com/fengxinjie/Transformer-OCR.- (moved due illnes of the reporter)

Dinesh Reddy. Community detection in social networks https://bit.ly/32u1jP2.

Kirill Lunev. Data mining with big data https://ieeexplore.ieee.org/abstract/document/6547630.

Walid Koliai. VoiceFilter from Google https://google.github.io/speaker-id/publications/VoiceFilter/.|

|20, #4448|Kaivalya Pandey. 3D Self-Supervised Methods for Medical Imaging https://arxiv.org/abs/2006.03829, https://paperswithcode.com/paper/3d-self-supervised-methods-for-medical.

Maria Matveeva. The value of big data for credit scoring: Enhancing financial inclusion using mobile phone data and social network analytics https://arxiv.org/pdf/2002.09931v1.pdf.

Enes Kuzucu. Deep Learning Applications in Medical Image Analysis /2018/251cit https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8241753.

Andrey Yashkin. Semantic Image Synthesis with Spatially-Adaptive Normalization https://arxiv.org/abs/1903.07291.

Oladotun Aluko. Transformer-OCR https://github.com/fengxinjie/Transformer-OCR.|

|27, #4525|Rusnak Alexander. Neural oblivious decision ensembles for deep learning on tabular data https://arxiv.org/pdf/1909.06312.pdf, https://github.com/Qwicen/node.

Vladislav Panferov. Thesis: Recognition of Rocks Lithology on the Images of Core

Samples (Supervisor: Dmitry Tailakov).

Virgilio Espina. Thesis: Dengue Prediciton (Supervisor: Alexey Kolesnikov).

Ahmed Fakhry. Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers /2017/59 Cit. https://arxiv.org/pdf/1708.09757.pdf.

Vassily Baranov. Zero-Shot Learning - A ComprehensiveEvaluation of the Good, the Bad and the Ugly https://arxiv.org/pdf/1707.00600.pdf.|

h3. November, 2020

|3, #4622|Khue Luu. Thesis: Brain Tumor Segmentation (Sci.advisor: Evgeniy N. Pavlovskiy, PhD).

Mikhail Liz. Activate or Not: Learning Customized Activation https://arxiv.org/abs/2009.04759.

Enes Kuzucu. Thesis: EEG (Sci.advisor: Alexander N. Savostyanov, PhD)..

Aaron Xu Zhang. You Only Look Once: Unified, Real-Time Object Detection https://arxiv.org/abs/1506.02640 (and YOLO-5).

-Ahmed Fakhry. Thesis: ?.-

Watana Pongsapas. Automatic License Plate Recognition with Pyhton and OpenCV.|

|10, #4730|Alexey Korolev. Plug and Play Language Models: A Simple Approach to Controlled Text Generation https://arxiv.org/pdf/1912.02164.pdf.

Rishabh Tiwarri. Mask R-CNN https://arxiv.org/abs/1703.06870.

Kirill Kalmutskiy. XGBoost: A Scalable Tree Boosting System https://arxiv.org/pdf/1603.02754.pdf.

Hami Asmai. Predictive big data analytics for supply chain demand forecasting: methods, applications, and research opportunities https://journalofbigdata.springeropen.com/articles/10.1186/s40537-020-00329-2.

Vassily Baranov. Thesis: Classification of COVID-19 in Computed Tomography using Deep Neural Networks (Supervisor: V.B. Berikov).|

|17, #4731|Sayed Mohammad Sajjadi. Online actions with offline impact: How online social networks influence online and offline user behavior  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5361221/.

Alix Bernard. Field Inversion and Machine Learning With Embedded Neural Networks: Physics-Consistent Neural Network Training https://www.researchgate.net/publication/333808531_Field_Inversion_and_Machine_Learning_With_Embedded_Neural_Networks_Physics-Consistent_Neural_Network_Training.

Alexander Donets. Entity, Relation, and Event Extraction with Contextualized Span Representations https://paperswithcode.com/paper/entity-relation-and-event-extraction-with.

Sergey Pnev. Deep neural networks for youtube recommendations  https://research.google/pubs/pub45530.pdf.

Mikhail Rodin. Classification is a Strong Baseline for Deep Metric Learning https://arxiv.org/abs/1811.12649v2.|

|24, #4776|Mukul Vishvas. DeepFaceDrawing: Deep Generation of Face Images from Sketches https://research.fb.com/wp-content/uploads/2020/06/Neural-Supersampling-for-Real-time-Rendering.pdf.

Segery Berezin. Thesis: ?.

Mohammed Sweilam. Consistent Video Depth Estimation https://arxiv.org/abs/2004.15021.

-Watana Pongsapas. Automatic License Plate Recognition with Pyhton and OpenCV.- Moved to 3-Nov-2020

Raphael Blankson. A variational Algorithm for Quantum Neural Networks https://link.springer.com/chapter/10.1007/978-3-030-50433-5_45.|

h3. December, 2020

20 minutes for each presentation.

|1, #4873|Aaron Xu Zhang. Thesis: Social structure and dynamics mining for TikTok (social network may change). Supervisor: A.Kolonin.

Rohan Rathore. Does BERT Make Any Sense? https://arxiv.org/pdf/1909.10430.pdf

-Mikhail Rodin. Thesis: Investigation of the possibility of constructing neural network models for thematically and stylistically determined poetic texts. Supervirsor: V.B.Barakhnin, I.Bondarenko.- Not delivered.

-Sayed Mohammed Sajjadi. Thesis: ?. Supervisor: A.Kolonin.?- Moved to a next seminar

-Oladotun Aluko. Thesis: Studying Applicability of PoR as an alternative consensus mechanism for Distributed Ledger Systems. Supervisor: A.Kolonin.- Not delivered.

Walid Koliai. Thesis: 2D online GPU correlation analysis of streamed particle images. Supervisor: Mikhail Tokarev, PhD|

|8, #4965|Rohan Rathore. Thesis: Explorative study of explainable artificial intelligence technique for sentiment analysis applied for English language. Supervisor: A.Kolonin.

Kirill Kalmutskiy. Thesis: Training of deep neural networks with incomplete training information on the example of recognition of tomographic images. Supervisor: V. Berikov

Kirill Lunev. Thesis: . Supervisor: A. Kolonin

Mikhail Liz. Thesis: Quantitative processing of scanning probe microscopy image with deep learning techniques. Supervisor: A. Okunev

Rusnak Alexander. Thesis: Investigation of the possibility of generating neural network models for the generation of thematically and stylistically conditioned texts for low-resource languages. Supervisor: V. Barakhnin

Hami Ismail. Thesis: Recognition of different objects of oilfield infrastructure by machine learning methods. Supervisor: Dmitry Tailakov.

_Maxim Kochanov. DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation https://arxiv.org/pdf/2006.04868.pdf. (15 min)_

-_Mark Baushenko. Neural Supersampling for Real-time Rendering. (15 min)_- moved to the next week|

|15, #5110|-Kaivalya Pandey. Thesis.- Not ready.

Alix Bernard. Thesis.

Daria Pirozhkova. Thesis: Study of methods for automatic taxonomy enrichment for the Russian language. advisor: Batura T.

Mukul Vishwas. Thesis.

Andrey Yashkin. Thesis.

_Sergey Verbitsky. Residual Audio Neural Networks with Multiple Features for Sound Classification. (10 min)_

Sayed Mohammed Sajjadi. Thesis: ?. Supervisor: A.Kolonin. (moved from 1 Dec)

Oladotun Aluko. Thesis: Studying Applicability of PoR as an alternative consensus mechanism for Distributed Ledger Systems. Supervisor: A.Kolonin. (moved from 1 Dec)

_Mark Baushenko. Neural Supersampling for Real-time Rendering. (10 min)_ (moved from 8 Dec)|

|22, #|-Rishabh Tiwarri. Thesis.- Moved to the next week

Nikita Nikoaev. Thesis.

Alexey Koroloev. Thesis.

Watana Pongsapas. Thesis

Mohammed Sweilam. Thesis.

_Svelana Kuchuganova. Mixup Breakdown Algorithm. (15 min)_

Raphael Blankson. Thesis. (moved from the next week)|

|29, #5467|Sergey Pnev. Thesis.

Alexander Donets. Thesis.

Maria Matveeva. Thesis.

-Raphael Blankson. Thesis.- Moved to the previous week

Dinesh Reddy. Thesis.

Rishabh Tiwarri. Thesis. (moved from the previous week)|

h2. Schedule 2020, spring

Thursday, 16:20, -cab 0207 NSU new building, '-1' elevator floor-, online: https://zoom.us/j/910812617

h3. June, 2020

|4, #3424|*Elena Voskoboy* Coursework

*Abhishek Saxena* Coursework

*Vladislav Panferov* Traditional Method Inspired Deep Neural Network for Edge Detection

*Sergey Garmaev* Coursework

*Nikita Nikolaev* Coursework

*Owen Siyoto* Learning to interpret satellite images in global scale using wikipedia

*Mohamed Nasser* Coursework

*Watana Pongsapas* Coursework

*Alix Bernard* Coursework

*Andrey Yashkin* Coursework

*Thibault Kollen* Gogioso S. A Corpus-based Toy Model for DisCoCat //arXiv preprint arXiv:1605.04013. – 2016. URL: https://arxiv.org/pdf/1605.04013.pdf	

*Geoffroy de Felcourt* Shen J. et al. Natural tts synthesis by conditioning wavenet on mel spectrogram predictions //2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). – IEEE, 2018. – С. 4779-4783. URL: https://arxiv.org/pdf/1712.05884.pdf	

*Antoine Logeais* Skip-thoughts, Infersent, RandSent - Facebook

*Richard Fambon* Vorontsov K. et al. Bigartm: Open source library for regularized multimodal topic modeling of large collections //International Conference on Analysis of Images, Social Networks and Texts. – Springer, Cham, 2015. – С. 370-381. URL: http://www.machinelearning.ru/wiki/images/e/ea/Voron15aist.pdf	||

h3. May, 2020

|7, #3241|*Ravi Kumar* Master

*Owen Siyoto* Master

*Oladotun Aluko* Coursework

*Alexander Rusnak* Coursework

*Vladislav Panferov* Coursework

*Abhishek Saxena* Blockchain for AI: Review and open research challenges

*Mikhail Liz* Coursework|

|14, #3248|*Kaivalya Pandey* Coursework

*Andrey Yashkin* Coursework

*Rohan Rathore* Coursework

-*Sergey Garmaev* Coursework- rescheduled for June 4

*Dinesh Reddy* Coursework

-*Elena Voskoboy* Coursework- rescheduled for June 4

*Munyaradzi Njera* Paper

*Munyaradzi Njera* Master Thesis|

|21, #3283|*Daria Pirozhkova* Coursework

*Alexey Korolev* Coursework

*Mohamed Nasser* End-to-End 3D Face Reconstruction with Deep Neural Networks

-*Alexander Donets* Coursework- (academic vacation)

-*Rishabh Tiwari* Coursework- shifted to the next week

*Olga Yakovenko* Master thesis|

|28, #3325|-*Alix Bernard* Coursework- postponed to the next week

*Mukul Vishwas* Coursework

-*Watana Pongsapas* Coursework- postponed to the next week

*Raphael Blankson* Coursework

-*Nikita Nikolaev* Coursework- rescheduled for June, 4

-*Olga Yakovenko* Master thesis- (presented 21.05.2020)

*Rishabh Tiwari* Coursework|

h3. April, 2020

|2, #|[Optional] Daia Scientist - values of a professional|

|9 -2-, #3202|*Thibault Kollen* Flipout: Efficient pseudo-independent weight perturbations on mini-batches

*Richard Fambon* Tensor Networks

*Alexander Rusnak* GPT-2

*Dinesh Reddy* Brain Tumor Sementation Using Deep Learning by Type Specific Sorting of Images

*Alix Bernard* Deep Learning based Approach to Reduced Order Modelling

*Ravi Kumar* Complex Convolution. IEEE

*Olga Yakovenko* University of Pau|

|16 -9-, #3226|*Rohan Rathore* Layer-wise relevance propagation: an overview

*Antoine Logeais* Weight uncertainty in neural networks

-*Owen Siyoto* Learning to interpret satellite images in global scale using wikipedia-

*Alexey Korolev* Bert-dst: Scalable end-to-end dialogue state tracking with bidirectional encoder representations from transformer

*Alexander Donets* Implicit weight uncertainty in neural networks|

|23 -16-, #3225|*Jetina Tsvaki* Understanding mixup training methods

*Jetina Tsvaki* Master

*Mukul Vishwas* A Study on Face Recognition Techniques with Age and Gender Classification

*Rishabh Tiwari*

*Geoffroy de Felcourt* Jasper: An end-to-end convolutional neural acoustic model

*Fishman Daniil* XGBoost: A Scalable Tree Boosting System

*Fishman Daniil* Master

-*Mikhail Rodin* Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization-|

|30, #3240|*Raphael Blankson* Towards quantum machine learning with tensor networks 

*Vassily Baranov* Coursework

*Kalmutskiy Kirill* Coursework

-*Mikhail Liz* Coursework- (illness)

*Mikhail Rodin* Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization|

h3. March, 2020

|5, #3137|-*Elena Voskoboy* Hybrid VAE for NLG-

*Mikhail Liz* Deep learning for symbolic mathematics

*Vassily Baranov* Distilling knowledge

-*Andrey Yashkin*-

*Sergey Garmaev* Reservoir Computing|

|12, #3138|*Oladotun Aluko* NASNet and AutoML

*Watana Pongsapas*  Deep learning: A Generic approach for extreme condition traffic

*Kirill Kalmutsky* Variational Quantum Circuits and Deep Reinforcement Learning

*Andrey Yashkin* Quantum circuit learning|

|19, #3139|*-Geoffroy de Felcourt-*

*Elena Voskoboy* Hybrid VAE for NLG

~~25 min slot~~|

|26, #3190|*Omid Razizadeh* Reynolds Averaged Turbulence Modeling using Deep Neural Networks with Embedded Invariance.

*Omid Razizadeh* Master thesis

*Kaivalya Pandey* Deep Reinforcement Learning

-*Alix Bernard* Deep Learning based Approach to Reduced Order Modelling-.|

h3. February, 2020

|6, #3133|Planning the semester|

|13, #3133|Planning the semester|

|20, #3136|*Nikita Nikolaev* Zero and Few shot learning

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|27, #3135|*Daria Pirozhkova* ERNIE

-*Sergey Garmaev* Reservoir Computing-

~~25 min slot~~

~~25 min slot~~|

h2. Schedule 2019, fall

Thursday, 18:10, cab 5239 NSU new building

h3. December, 2019

|5, #2819|*Rohan Rahore* “Why Should I Trust You?” Explaining the Predictions of Any Classifier

*Jetina Tsvaki* Thesis

*Omid Razizadeh* Thesis

-*Mihail Rodin* Style transfer-

-*Mohammed Sweilam*-|

|12, #2860|*Ravi Kumar* Thesis

*Raphael Blankson*

*Nikita Nikolaev*

*Abhishek Saxena*

*Rishabh Tiwarri*|

|19, #2946|Conducted by *Kaivalya Anand Pandey*

*Jetina Tsvaki* Paper

-*Elizaveta Tagirova* Paper with code: Deep-speare: A Joint Neural Model of Poetic Language, Meter and Rhyme-

-*Elizaveta Tagirova* Master thesis-

-*Vladislav Panferov*-

*Mikhail Liz* CosFace

*Alexander Rusnak*|

|26, #|*Mihail Rodin* Style transfer

*Mohammed Sweilam*

-*Alexander Rusnak*-

*Owen Siyoto* Master thesis

*Owen Siyoto* Efficient Net

Rescheduled:

* *Elizaveta Tagirova* Paper with code: Deep-speare: A Joint Neural Model of Poetic Language, Meter and Rhyme-

* *Elizaveta Tagirova* Master thesis

* *Vladislav Panferov*|

h3. November, 2019

|7, #2660|*Sergey Garmaev*

*Dinesh Reddy*

*Daria Pirozhkova*

-*Oladotun Aluko*-

*Ravi Kumar* Segmentation of Brain Tumors and Patient Survival Prediction: Methods for the BraTS 2018 Challenge|

|14, #2720|*Roman Kozinets*, Weight Agnostic Neural Networks

*Roman Kozinets*, Master thesis

*Elena Voskoboy* A neural algorithm of artistic style

*Alix Bernard*

-*Oladotun Aluko*-|

|21, #2726|*Kaivalya Pandey*

*Alexander Donets*

-*Rishabh Tiwari*-

*Andrey Yashkin*

*Oladotun Aluko*|

|28, #2766|*Alexey Korolev*

*Kirill Kalmutskiy*

*Mukul Vishwas*

*Antoine Kristanek*|

h3. October, 2019

|3, #2447|~~25 min slot~~

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|10, #2456|Scientific Advisor: prof. Yakovenko S.N.

Scientific Advisor: Postovalov S.N.

Scientific Advisor: Bondarenko I., Batura T.V.

~~25 min slot~~|

|17, #2473|*Munyaradzi Njera* Paper

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|24, #|Scientific Advisor: prof. Palchunov D.E.

*Munyaradzi Njera* Thesis

*Vassily Baranov*|

|31, #2638|*Omid Razizadeh*, Data-driven predictive using field inversion

~~25 min slot~~

*Watana Pongsapas*

-*Ravi Kumar* Segmentation of Brain Tumors and Patient Survival Prediction: Methods for the BraTS 2018 Challenge-|

h3. September, 2019

1. Introduction

2. Scientific advisors presentations: https://trello.com/b/859tElZm/scientfic-advisors-19-21

Presented:

# Taylakov D. (Digital Field Technology)

# Kolonin A.

# Okunev A.

# Usov E. (NNTC.pro)

To be presented:

# ... see https://trello.com/b/859tElZm/scientfic-advisors-19-21

3. Planning the semester #2435 (20.09.2019, 26.09.2019)

h2. Schedule 2019, spring

Thursday, 16:20, cab 5212 NSU new building

h3. May, 2019

|23, #|*Munjaradzi Njera* Master thesis

*Andrey Marinov*: Selsam, D., Lamm, M., Bünz, B., Liang, P., de Moura, L., & Dill, D. L. (2018). Learning a SAT solver from single-bit supervision. arXiv preprint arXiv:1802.03685.

*Ravi Kumar* Course work

-*Klim Markelov* Master thesis-

*Roman Kozinets* Master thesis (imaging)

*Anton Dorozhko* Reinforcement Learning for long-term reward optimization in recommender systems (Master thesis)

*Omid Razizadeh* Coursework: Detecting Alzheimer's disease using different machine learning approaches

*Artem Sergeev* Paper: Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

*Artem Sergeev* Master Thesis|

|16, #|*Jetina Tsvaki* Master thesis

*Anik Chakrabarthy* Master thesis

*Dylan Bersans* Outside the closed world: On Using ML for Network Intrusion Detection

*Andrey Marinov* Master thesis: Research on an efficiency of the bilingual model for the silent speech recognition.

*Ivan Rogalsky* Open System Categorical Quantum Semantics in NLP (master thesis, review)

*Jetina Tsvaki* Predicting Oil Movement in a development System Using Deep Latent Dynamic Models|

h3. April, 2019

|25, #|Open Seminar jointly with Open Data Science Siberia

*Andrey Zubkov* Master thesis: Separability of silent speech phonemes for English language. Speaker and session independence.

*Evgeniy Kurochkin* Master thesis

*Alexandra Luchkina* Master thesis

*Leyuan Sheng* Master thesis: Text to speech synthesis using Generative Adversarial networks for speech enhancement.

*Malysheva Anastasia* Master thesis: The development and research of the prediction methods for time series obtained by the combination of different patterns.

*Olga Yakovenko* Course work

*Juan Pinzon* Master thesis: Sentiment Analysis in Social Media Texts (Spanish language)

Video: https://www.youtube.com/watch?v=T7Oa4hBR3g4|

|18, #|-*Ivan Rogalsky* Open System Categorical Quantum Semantics in NLP (master thesis, review)

*Ravi Kumar* Master thesis

*Jetina Tsvaki* Predicting Oil Movement in a development System Using Deep Latent Dynamic Models

*Dylan Bersans* Outside the closed world: On Using ML for Network Intrusion Detection

*Olga Yakovenko* Course work

*Juan Pinzon* Master thesis- replaced by

*Natalia Loukashevich* Modern trends on NLP (Tochka Kipenia, Academpark, 16:00, 18.04.2019)|

|11, #2164|*Leyuan Sheng* Tacotron 2

-*Klim Markelov* Master thesis-

-*Juan Pinzon* Master thesis-

*Ravi Kumar* State of the art Deep Learning: Evolving Machine Intelligence Toward Tomorrow's

*Malysheva Anastasia* Attention is all you need https://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf |

|4, #2146|*Roman Kozinets* CNN for speech command recognition. Review

-*Ivan Rogalsky* Quantum-Theoretic Approach in Dicstr. Semantics-

*Akilesh Sivaswamy* Master thesis: Data classification using superposition and HMM

*Madina Tussupova* Master Thesis: Determination of grammatical categories using machine learning algorithms

*Madina Tussupova* 5.3. Wieting J., Kiela D. No Training Required: Exploring Random Encoders for Sentence Classification //arXiv preprint arXiv:1901.10444. – 2019. URL (20 min)|

h3. March, 2019

|28, #2105|-*Ravi Kumar* State of the art Deep Learning: Evolving Machine Intelligence Toward Tomorrow's-

*Munjaradzi Njera* Human-level control through deep reinforcement learning

*Thomas Vialars* Artificial Intelligence Safety and Cybersecurity: a Timeline of AI Failures

*Petr Gusev* MXNet

*Petr Gusev* Master Thesis|

|21, #2086|*Juan Pinzon* Universal Language Model Fine-tuning for Text Classification

*Elizaveta Tagirova* Master Thesis

-*Petr Gusev* MXNet-

-*Seth Gyamerah* Understanding consumer behavior-|

|14, #2076|*Omid Razizadeh* Pixel Recurrent Neural Networks.

*Klim Markelov* A Style-Based Generator Architecture for Generative Adversarial Networks.

*Anik Chakrabarthy* DisCoCat toy model

*Akilesh Sivaswamy* CosFace|

|7, #2071|-*Andrey Zubkov* Performance of Word Embeddings- (previously reported)

*Alexandra Luchkina* Triplet loss

*Evgeniy Kurochkin* Self-Taught Convolutional Neural Networks for Short Text Clustering

*Olga Yakovenko* BigARTM|

h3. February, 2019

|28, #2058|*Elizaveta Tagirova* Universal Sentence Encoder

*Andrey Zubkov* Neurohackathon on autism disorder: prized solution

~~time slot (25 min)~~

~~time slot (25 min)~~|

|21, #2054|*Vyacheslav Mukhortov* Project Management Practice: teambiudling and project tasks.

*Evgeniy Pavlovskiy* Planning of academic seminar for Spring, 2019|

h2. Schedule 2018, fall

Thursday, 18:10, cab 5273 NSU new building

h3. December, 2018

|6, #2034|*Leyuan Sheng*, CycleGAN

*Tagirova Elizaveta*. LIME (local interpretable model-agnostic explanations) https://arxiv.org/pdf/1602.04938v1.pdf

*Luchkina Alexandra*, Sobolev Training

*Fishman Daniil*, Prediction of enhancer-promoter interactions via natural language processing|

|13, #|*Anton Kolonin*. Topics for master work.

*Evgeniy Averyanov*, Schmidt, Mark. Minimizing finite sums with the stochastic average gradient / M. Schmidt, N. Le Roux, F. Bach // Mathematical Programming. — 2017. — Vol. 162(1). — P. 83–112. — URL: https://link.springer.com/article/10.1007/s10107-016-1030-6

*Polina Potapova*, XNOR-Net, https://arxiv.org/pdf/1603.05279.pdf

*Lee Wonjai*. Bayesian CDF (continue with example)

|

|20, #|-*Artem Sergeev*. ArcFace-

*Gyamerah Seth*, Fuzzy time series on financial forecasting

-*Mulley Loic*, Triplet Loss https://arxiv.org/pdf/1503.03832.pdf-

*Kurochkin Evgeniy*, DenseNet

|

|27, #|*Julien Machet*, Machine learning top down and bottom up.

*Ivan Rogalsky*

*Arsentiy Melnikov* Teacher student curriculum learning https://arxiv.org/pdf/1707.00183.pdf

*Loic Mulley*, Triplet Loss https://arxiv.org/pdf/1503.03832.pdf

*Artem Sergeev*, ArcFace|

h3. November, 2018

|1, #|*Petr Gusev*. ResNet, ResNeXt K. He, X. Zhang, S. Ren, and J. Sun. Deep Residual Learning for Image Recognition. In CVPR, 2016

*Anastasia Malysheva*, Variational Autoencoders

*Anik Chakrabarthy*. Quantum Semantics

~~25 min slot~~|

|8, #|*Akilesh Sivawamy*, Mobile NN.

*Lee Wonjai*. Bayesian CDF

-*Polina Potapova*, XNOR-Net, https://arxiv.org/pdf/1603.05279.pdf- (moved to December)

*Olga Yakovenko*, RNN for Speech Recognition|

|15, #|*Ravi Kumar*, Deep Learning in Mobile and Wireless Networks: a Survey

*Munjaradzi Njera*, Attentioned based LSTM

*Juan Fernando Pinzon Correa*, Rapids AI

*Urynbassarov Mukhtar*, GAN|

|22, #|lost|

|29, #|*Roman Kozinets*, Siamese NN

*Omid Razizadeh*, tSNE

*Jetina Tsvaki*, Natural language based financial forecasting: a survey

*Owen Siyoto*, Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network|

h3. October, 2018

|18, #2028|Planning the semester|

|25, #|*Klim Markelov*, Capsule NN

*Andrey Zubkov*, Dynamic Word Embeddings https://arxiv.org/abs/1804.07983

*Vitaly Poteshkin*, MixUp

Planning the semester|

h3. September, 2018

1. 2nd year students coursework pre-defence: (1) #2008, (2) 14.09.2018.

2. Scientific advisors presentations: https://trello.com/b/ZlMTMsS8/bdaai-scientific-topics

# Taylakov D.

# Savostyanov A.N.

# Duchkov A.

# Golovin S.

# Pavlovskiy E.

# Kohanovskiy A.

# Sviridenko D.

# Redyuk A.

# Vityaev E.

h2. [[Archive]]