توهم، بهایِ خلاقیت ست.

Channel
Complex Networks (SBU)
@Complexity_SBU
On this record: Growth · Engagement · Posts · Citations · Cite this entry
1,199subscribers
+3 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
Register entry
| Telegram ID | -1001400429988 |
|---|---|
| Type | Channel |
| Username | @Complexity_SBU |
| Created | Between 1 August 2018 and 30 September 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 13 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/Complexity_SBU |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 00:27 | 1,199 | +3 |
| 6 Aug 2026, 08:48 | 1,196 | no change |
| 6 Aug 2026, 05:48 | 1,196 | first reading |
Engagement
20 posts held, back to 11 December 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 11 July 2026. An engagement rate over an empty window would be a number about nothing.
Recent posts
https://youtu.be/CnT7jaQX4X8?si=wiJe8OxPoGXrmJM5 هیچ چیز در زیستشناسی جز در سایه تکامل معنا پیدا نمیکند.
📜جلسه دفاع از پایان نامه کارشناسی ارشد 👩🏻🎓آذین شیرمحمدی 📖 موضوع: معماری محاسباتی مبتنی بر نانونوسانگرهای اسپینترونیکی برای تحلیل شبکههای مغزی EEG 🕘 زمان: ۲۶ خردادماه - ۱۲ ظهر 🏢 مکان: دانشکده فیزیک، طبقه ۳، اتاق سمینار 🌐 لینک گوگل میت: https://meet.google.com/hix-hwgv-hpn --------------------------------------------------------- 🌐 http://ccnsd.ir 🆔 @Complexity_SBU
پژوهشکده علوم شناختی و مغز دانشگاه شهید بهشتی با همکاری انجمن علوم و فنآوریهای شناختی ایران و انجمن علمی دانشجویی مغز و شناخت دانشگاه شهیدبهشتی برگزار میکند: 🟨تغییرات الگوی حالتهای نامتوازن شبکههای عملکردی مغز در حین رشد سخنرانها: فهمیه احمدی، دانشآموخته کارشناسی ارشد فیزیک سامانههای پیچیده، دانشکده فیزیک دانشگاه شهید بهشتی دکتر رضا جعفری،استاد فیزیک سامانههای پیچیده، دانشکده فیزیک دانشگاه شهید بهشتی 📆 ز…
Master's 2 in Computational Neuroscience at the University of Lyon (France). This program trains students in modern computational and analytical methods to study the brain: from the electrical activity of single neurons to neural networks, interacting brain regions, and animal behavior.
PhD Position: Robust Game Theory for Complex Systems Modern society depends on complex, interconnected systems such as renewable energy grids, autonomous vehicles and human-machine collaborative systems. Ensuring that these systems operate safely, efficiently and fairly is a major scientific and societal challenge. It requires new approaches to control and decision-making in environments where multiple agents interac…
NeuralModelS NeMoS (Neural ModelS) is a statistical modeling framework optimized for systems neuroscience and powered by JAX.
Pynapple is a light-weight python library for neurophysiological data analysis. The goal is to offer a versatile set of tools to study typical data in the field, i.e. time series (spike times, behavioral events, etc.) and time intervals (trials, brain states, etc.). It also provides users with generic functions for neuroscience such as tuning curves, cross-correlograms and filtering.
🔷 Applied ML seminar meetings 📜 موضوع: شکل گیری باشگاه ثروتمندان 👩🏽💻 ارائه دهنده: امیرحسین یکتا 🕒 زمان: شنبه 20 دی، ساعت ۱۶:۳۰ 📍مکان: سالن سمینار، طبقه سوم دانشکده فیزیک 💻 لینک گوگل میت: https://meet.google.com/rge-pfgs-mxx ------------------------------------- 🌐http://ccnsd.ir 🌐 https://complexity.sbu.ac.ir/ 🆔 @Complexity_SBU
Complex Networks (SBU) pinned a photo
جلسه دفاع از پایان نامه کارشناسی ارشد 👨🏫 👨🎓 سعید رضائی افشار 📖 موضوع: تعادل هم تکاملی شبکههای مغزی حالت استراحت در اختلال طیف اتیسم 🕘 زمان: 10 دیماه، چهارشنبه ساعت ۱۳:۰۰ 🏢 مکان: سالن سمینار، پژوهشکده علوم شناختی و مغز 🌐 لینک گوگل میت: http://meet.google.com/gqh-cemp-nhm --------------------------------------------------------- 🌐 http://ccnsd.ir 🆔 @Complexity_SBU
🔷 جلسات سمینار هفتگی فیزیک اماری و سامانه های پیچیده 📜 موضوع ارائه: Dynamic pattern of imbalance states between resting state functional brain networks during development 👨🏻💻 ارائه دهنده: فهیمه احمدی 🕒 زمان: یکشنبه ۷ دی، ساعت 13:45 📍مکان: سالن سمینار، طبقه سوم دانشکده فیزیک 💻 لینک گوگل میت: https://meet.google.com/ymq-gryq-wzs ------------------------------------- 🌐http://ccnsd.ir 🌐 https://complexity.sbu.ac.…
Showing the 12 most recent of 20 posts we hold for @Complexity_SBU. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank
Citation-graph rank — 238,240 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 4 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 13 August 2026 — this entry's latest reading, not the date you are reading this.
“Complex Networks (SBU)” (@Complexity_SBU), 1,199 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/Complexity_SBU.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.