News

DSML Reading Club Meeting #10

Speaker: Arystan Shokan

Arystan Shokan earned a master's degree in mathematics from Boston University. His main research interests are in geometry and topology, including algebraic geometry, complex geometry, algebraic topology, differential geometry, and combinatorial geometry. Arystan also wrote a survey paper on Combinatorial Hodge Theory.

At this meeting, Arystan will talk about Topological Data Analysis (TDA). In the seminar, we will explore how Topological Data Analysis can be used to study the shape and structure of data, especially when periodicity and cyclic states are present. We will discuss the key ideas of homology, Laplacians, and Betti numbers.

Prerequisites: Linear Algebra

📅 Thursday, October 1, 12:00 KZ Time ➕ Add to calendar: https://calendar.app.google/rY4ghKSXMTBAQx186

⚠️ Important about the meeting link: Only those who add it to their calendar will get access to the meeting—the Google Meet link will be inside.

NeurIPS 2026 is coming, with the Competition Track featuring 16 competitions on various topics:

• Scientific AI, Physics & Engineering: Learn2Design, Smart Buildings, Fusion Equilibrium, RealPDE, FAIR Universe Weak Lensing.
• Healthcare/Bio: SimulacraBench, AMP Challenge, Speech Accessibility Project Challenge 2, Virtual Embryo.
• Foundation Models, Reasoning & AI Evaluation: Steerability, Predictive AI Evaluation, AIMO Interpretability, QuantiPhy.
• Robotics, Agents & Embodied AI: RoboSyn, RoCo-Spring, Agenthon for qunatitative finance

Several more competitions will take place as part of workshops: EEG/EMG Foundation Challenge, AV Causal Reasoning Retrieval Challenge, Lean Refactor Arena, AgentOdyssey.

Most competitions run in September and October. It is a great opportunity for anyone interested—including school students and people outside research—to tackle frontier problems faced by top labs, publish a paper about their solution, and attend the largest AI conference.

Asel Yermekova has compiled Awesome Kazakh Datasets—a large, carefully structured collection of open datasets for the Kazakh language. It brings together data for:

• NLP and LLM: QA, RAG, instruction tuning, NER, machine translation, and other tasks
• speech: ASR, TTS, speech translation, emotion recognition
• computer vision, OCR, and multimodal tasks

For each dataset, the collection lists its size, scale, task, release year, and download link. It also separately marks resources that were announced but could not yet be independently verified.

Repositories like this make life much easier: instead of spending hours searching, you can quickly see what Kazakh-language data already exists and what you can use for your research or product.

If you know of a dataset that is not yet on the list, the repository is open for contributions: 🔗 https://github.com/Allessyer/awesome-kaz-datasets

Thanks to Asel for this work, and to Alen Issayev for helping develop it!

Our champions! Kazakhstan’s team won 2 gold, 2 silver and 4 bronze medals at IOAI!

Gold: Dauzhan Beketov, Sultanbi Issatay Silver: Abu Kanabek and Alem Amenov. Bronze: Ulugbek Osmanov, Zhanibek Kassymkhan, Islamnur Kusainov and Dinmukhammed Yntyqbay.

Our team delivered excellent results! What’s more, Dauzhan didn’t just win gold—he placed second overall among all participants! This is a tremendous achievement!

We’re incredibly proud of our students and coaches!