OOmar Essam El Sherbiny3d ago · 4 min readThe year the Nile changed: change-point detection on 100 years of river flowThe annual flow of the Nile at Aswan from 1871 to 1970 is one of the classic series in statistics: a hundred numbers that every time-series textbook seems to use. It is famous for one feature, a drop omaressam.hashnode.dev
FFred FengOct 5 · 7 min readVortex TSDB: Live Metrics in One CommandHTTP Writes, Minute Aggregates, Sliding Windows, Replicated in Memory 1. Overview Lightweight. Replicated. Real-time. Vortex TSDB is a distributed time series database for live metrics. Push numbersfredfeng.hashnode.dev
HHarouneSep 29 · 18 min readBuilding a crypto spillover pipelineThe question needed a measurement system For my 2026 Master's thesis, I wanted to understand whether economies with more open capital accounts were more exposed to cryptocurrency volatility. When crypharoune.hashnode.dev
PPLOMID PlatformSep 29 · 13 min readWhy We’re Building PLOMID: Rethinking Data Infrastructure for Modern ApplicationsModern applications increasingly work with more than one kind of data. A single system may need relational transactions, JSON documents, time-series events, vectors, graphs, and large binary objects. plomid.hashnode.dev
RRodrigo AlvesAug 31 · 16 min readTopological Data AnalysisIntroduction When thinking about data, the first thing that probably comes to your mind is numbers. You might picture standard metrics used to characterize datasets, like the mean, median, and standarrodrigoalves.hashnode.dev
KKavindu NimeshAug 9 · 44 min readNeural Ordinary Differential EquationsHi guys, so in this blog post, I want to discuss the main idea behind Neural Ordinary Differential Equations (Neural Ordinary Differential Equations, Chen et al., 2018). I want to explain to you guys kavindu-nimesh.hashnode.dev
TTiger DataAug 4 · 18 min readThe Data Layer for the AI Data CenterOriginally published on July 8, 2026. Written by Hien Phan, Noah Hein, Matty Stratton, and Nate O'Farrell. This is Part II of a two-part series on the AI data center stack. Part I, AI's Physical Consttigerdata.hashnode.dev
JJeremy LongshoreJul 1 · 4 min readNixtla Baseline Lab: Real statsforecast Baselines via MCP ServerYesterday was plugin scaffolding. Today the Baseline Lab gets real models running real data through a real MCP server. Phase 2: Plugin Manifest and MCP Config The Baseline Lab plugin needed two piecesjeremylongshore.hashnode.dev
BBerkan SesenJun 9 · 14 min readChangepoint Detection: Finding Regime Shifts in Financial DataMarkets do not stay in one regime. The S&P 500 can cruise at 10% annualised volatility for months, then a crisis hits and volatility doubles overnight. Any model trained on the calm period is useless sesenai.hashnode.dev
SScott McMahanApr 13 · 3 min readAI Time Series Forecasting Has Crossed a ThresholdFor a long time, time series forecasting was a solved-enough problem. ARIMA and its variants handled most production use cases. Seasonal decomposition filled in the gaps. The tooling was mature, the maitransformeronline.hashnode.dev
