Latest news and updates from DSML Kazakhstan community
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SemEval is an international series of NLP workshops and competitions. Task 13C classifies code authorship into four classes: Human, AI, Hybrid, and Adversarial AI.
Agzam and Yeraly built a multimodal ensemble that analyzes code from three perspectives: code semantics through UniXcoder with Multiple Instance Learning for long files; textual patterns through MazgaBERT, which identifies characteristic templates; and statistical anomalies through XGBoost using hand-crafted style and code-structure features.
Congratulations to our young residents, and we wish them many more victories!
Our community is especially proud that a team from Kazakhstan received a spotlight talk at the Foundation Models for Brain and Body workshop. Ayana presented the EEG Foundation Challenge solution in person in San Diego, while Anuar joined remotely because of visa difficulties.
The talk was followed by a panel discussion on the future of brain–computer interfaces and brain-activity analysis, moderated by Alex Gramfort, Research Science Director at Meta and one of the creators of scikit-learn.
📅 On Tuesday, December 16, at 12:00 Kazakhstan time, Ayana and Anuar will give a detailed walkthrough of their EEG Foundation Challenge solution: the architecture, data, key insights, and how it connects to practical machine learning. It will be a highly applied session for everyone interested in ML for neuroscience and biosignals.
Meeting link: meet.google.com/vie-gohs-wnr
Kuat Gazizov, a PhD student at the University of California, Merced, presented “A Faster Training Algorithm for Regression Trees with Linear Leaves, and an Analysis of Its Complexity”. Kuat shows that Tree Alternation Optimization for regression trees can be accelerated substantially with the Sherman–Morrison–Woodbury formula while preserving accuracy. This lets deep trees train faster and potentially even outperform ordinary linear regression in training speed.
Congratulations to Kuat on a successful publication, and we wish him continued success in research!
On November 22, Russia's national artificial intelligence olympiad for students in Grades 8–11 and international participants from Armenia, Uzbekistan, Cyprus, and Kazakhstan concluded. The olympiad initially registered 52,123 students. Sixty-two finalists met in Moscow for the final stage from November 17 to 22, which included an individual round with two problems and a team round.
Congratulations to our students on their excellent results:
We look forward to even more success from our young dsml.kz members!
![MBZUAI [dsml.kz] wins the EEG Foundation Challenge](https://swfxusemimczhhhfzjhc.supabase.co/storage/v1/object/public/telegram-images/bf0de014-033b-414e-b1df-94acd9b3145a.jpg)
We are happy to share that our MBZUAI [dsml.kz] team—Anuar Aimoldin, Ayana Mussabayeva, and Yedige Mussabayev—placed first overall by the combined metric in the EEG Foundation Challenge at the NeurIPS Competition Track 2025!
The challenge had two tasks: 1️⃣ Predict reaction time from stimulus-dependent EEG; 2️⃣ Predict the externalizing factor from EEG, a psychometric characteristic representing the shared dimension of psychopathology across different disorders.
The final score combined the metrics from both tasks: 30% for Task 1 and 70% for Task 2.
As winners, we were invited to present our work at the NeurIPS 2025 Competition Track and the Workshop on Foundation Models for the Brain and Body.
🏆 Our solution is available as open source: https://github.com/sneddy/neurosned
Neurosned is a fully reproducible end-to-end training pipeline that includes helper scripts, our manually designed lightweight models, and Jupyter-notebook tutorials.
We hope the project is useful to researchers interested in neuroscience, BCI, or EEG modeling!
GitHub stars and LinkedIn likes are highly appreciated 😂
