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Visualizing segment trees and range queries.
  • Dr. Ingrid Falk-Weller
  • September 10, 2026
  • (0)
  • Algorithms

Answering Range Questions Faster Than Reading the Range

I spent most of my PhD watching brilliant engineers implement segment trees for range queries when a simple Fenwick tree or even a sorted array would have been faster, leaner, and significantly easier to debug. There is this pervasive, almost…

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Principles of idempotent API design for retries.
  • Dr. Ingrid Falk-Weller
  • September 10, 2026
  • (0)
  • Software Engineering

A Retry Should Not Charge the Card Twice

I remember sitting in a windowless operations room three years ago, watching a dashboard turn a violent shade of crimson because a simple retry logic loop had just doubled every single transaction in our ledger. We weren’t facing a sophisticated…

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Consensus and raft algorithm comparison diagram.
  • Dr. Ingrid Falk-Weller
  • September 9, 2026
  • (0)
  • Systems

Agreeing on Order Is Harder Than Agreeing on Value

I still remember the smell of ozone and burnt coffee from my first real production outage—a 3:00 AM disaster caused by a cluster that thought it was in agreement when it was actually just shouting into a void. Most textbooks…

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Scientist keeping a research notebook.
  • Dr. Ingrid Falk-Weller
  • September 9, 2026
  • (0)
  • Research Practice

Write Down the Idea That Did Not Work and Why

I remember sitting in a windowless lab three years ago, staring at a perfectly formatted digital log that told me exactly what happened, but absolutely nothing about why it happened. I had spent six months optimizing a distributed consensus algorithm,…

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Adam and SGD optimisers compared.
  • Dr. Ingrid Falk-Weller
  • September 8, 2026
  • (0)
  • Machine Learning

Adam Converges Faster and Generalises Differently

I remember sitting in a windowless lab three years ago, staring at a loss curve that looked more like a mountain range than a smooth descent. I had swapped out my standard Adam implementation for a “state-of-the-art” variant I’d read…

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Deep training made practical via batch normalisation.
  • Dr. Ingrid Falk-Weller
  • September 3, 2026
  • (0)
  • Machine Learning

Normalising Between Layers Made Deep Training Practical

I remember sitting in a windowless lab three years ago, watching a training loss curve oscillate so violently it looked more like a seismograph reading than a convergence plot. I had followed every “best practice” in the literature, yet my…

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Visualizing cap theorem in practice.
  • Dr. Ingrid Falk-Weller
  • September 3, 2026
  • (0)
  • Systems

You Do Not Choose Two, You Choose During a Partition

I remember sitting in a windowless operations center three years ago, watching a dashboard bleed red while a senior architect tried to explain away a massive data drift by quoting the formal definitions of the CAP theorem like they were…

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Visualizing convex hull algorithms with points.
  • Dr. Ingrid Falk-Weller
  • September 1, 2026
  • (0)
  • Algorithms

Wrapping a Set of Points in the Tightest Possible Rubber Band

I remember sitting in a windowless lab during my postdoc, staring at a simulation that was crawling to a halt because I had blindly implemented a textbook version of Graham scan for a dataset that was essentially a perfect circle.…

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Managing a research project timeline successfully.
  • Dr. Ingrid Falk-Weller
  • September 1, 2026
  • (0)
  • Research Practice

Research Slips Because the Unknown Cannot Be Scheduled

I remember sitting in a windowless lab at 3:00 AM, staring at a Gantt chart that looked beautiful, symmetrical, and utterly useless. I had spent three weeks meticulously mapping out every milestone for a distributed systems simulation, only to have…

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Caching strategies and invalidation decision process.
  • Dr. Ingrid Falk-Weller
  • August 31, 2026
  • (0)
  • Software Engineering

Deciding When to Forget Is the Hard Half

I spent three months in a windowless lab during my PhD trying to prove that a specific distributed consensus model was “perfectly scalable,” only to watch it crumble the moment we introduced a real-world workload. The culprit wasn’t the consensus…

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