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Graph representations compared: matrix vs list.
  • Dr. Ingrid Falk-Weller
  • March 13, 2026
  • (0)
  • Algorithms

Dense Graphs Want a Matrix, Sparse Graphs Want a List

I spent three weeks of my life in a graduate research lab trying to optimize a GNN, only to realize I had wasted hundreds of compute hours because I’d chosen an adjacency matrix for a graph that was almost entirely…

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Statistical significance explained: unlikely by chance.
  • Dr. Ingrid Falk-Weller
  • March 12, 2026
  • (0)
  • Research Practice

Significant Means Unlikely by Chance, Not Important

I remember sitting in a windowless seminar room during my PhD, watching a senior researcher present a series of charts where every single result was “significant,” yet the actual effect sizes were so microscopic they wouldn’t have moved the needle…

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Optimizing performance with simd and vector instructions.
  • Dr. Ingrid Falk-Weller
  • March 11, 2026
  • (0)
  • Systems

One Instruction, Eight Results

I remember sitting in a windowless lab during my PhD, staring at a profiler that told me my optimized C++ code was running at a pathetic fraction of the theoretical peak. I had followed the textbook instructions to the letter,…

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Deprecate loudly: backwards compatibility discipline.
  • Dr. Ingrid Falk-Weller
  • March 9, 2026
  • (0)
  • Software Engineering

Deprecate Loudly and Remove Slowly

I remember sitting in a dimly lit server room during my first year in industry, watching a “minor” patch trigger a cascading failure that took down a distributed cluster I had spent months stabilizing. The culprit wasn’t a massive bug,…

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Comparison of categorical encoding methods.
  • Dr. Ingrid Falk-Weller
  • March 9, 2026
  • (0)
  • Machine Learning

High Cardinality Breaks One Hot Encoding Quietly

I spent three months in a research lab during my PhD chasing a marginal accuracy gain, only to realize I had spent half that time debugging a catastrophic data leak caused by a poorly implemented one-hot encoder. It is infuriating…

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Analyzing the impact of handling missing data.
  • Dr. Ingrid Falk-Weller
  • March 7, 2026
  • (0)
  • Machine Learning

Why the Data Is Missing Matters More Than That It Is

I remember sitting in a windowless lab during my PhD, staring at a dataset that looked less like a coherent signal and more like a sieve. I had spent three weeks trying to implement a sophisticated, multi-stage Bayesian imputation model…

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Exchange argument proving greedy correctness.
  • Dr. Ingrid Falk-Weller
  • March 6, 2026
  • (0)
  • Algorithms

An Exchange Argument Is the Only Honest Proof

I remember sitting in a windowless graduate lab at 2:00 AM, staring at a trace of a scheduling algorithm that looked perfect on paper but was failing spectacularly in production. I had spent weeks convinced that my logic was sound,…

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Choosing evaluation metrics for optimization success.
  • Dr. Ingrid Falk-Weller
  • March 6, 2026
  • (0)
  • Research Practice

The Metric You Optimise Becomes the Thing You Get

I remember sitting in a windowless lab during my postdoc, staring at a loss curve that looked absolutely beautiful, while the actual system was collapsing in real-time. I had spent three weeks optimizing for a metric that looked impressive on…

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Effective api versioning strategies prevent breaking changes.
  • Dr. Ingrid Falk-Weller
  • March 5, 2026
  • (0)
  • Software Engineering

Breaking Changes Are a Cost You Pass to Everyone Else

I remember sitting in a dimly lit server room during my first industry role, watching a deployment fail because we had tried to be “clever” with our header-based versioning. We thought we were being elegant by hiding the versioning logic…

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Out of order execution processor diagram.
  • Dr. Ingrid Falk-Weller
  • March 3, 2026
  • (0)
  • Systems

Your Instructions Do Not Run in the Order You Wrote Them

I spent three years in academia watching people treat out of order execution like a magic black box that just “makes things faster” by some inscrutable divine will. It drives me half-mad when I see high-level tutorials gloss over the…

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