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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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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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Greedy algorithms and when they fail.
  • Dr. Ingrid Falk-Weller
  • February 27, 2026
  • (0)
  • Algorithms

Greedy Works Until Somebody Constructs the Counterexample

I remember sitting in a windowless lab during my second year of grad school, staring at a distributed scheduler that was eating its own tail. We had implemented a classic greedy approach, convinced that picking the shortest task first was…

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Memoisation versus tabulation memory profile comparison.
  • Dr. Ingrid Falk-Weller
  • February 21, 2026
  • (0)
  • Algorithms

Same Answer, Different Memory Profile

I spent three years in academia watching brilliant students lose sleep over textbook definitions that felt more like religious dogma than engineering principles. Most tutorials treat the debate of memoisation versus tabulation as a simple choice between “top-down” and “bottom-up,”…

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Learning dynamic programming from scratch with recursion.
  • Dr. Ingrid Falk-Weller
  • February 12, 2026
  • (0)
  • Algorithms

Recursion With a Notebook Is Dynamic Programming

I remember sitting in a windowless grad student lounge at 3:00 AM, staring at a whiteboard covered in recursive calls that felt more like a fever dream than actual logic. Everyone around me was treating dynamic programming like some mystical…

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Visualizing divide and conquer patterns.
  • Dr. Ingrid Falk-Weller
  • February 6, 2026
  • (0)
  • Algorithms

Cutting the Problem in Half Twice Is Not the Same as Cutting It in Four

I spent three weeks in my late twenties trying to optimize a distributed sorting routine, only to realize I had fallen into the classic trap of applying divide and conquer patterns where they didn’t belong. I was so enamored with…

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Amortised analysis explained via cost distribution.
  • Dr. Ingrid Falk-Weller
  • February 1, 2026
  • (0)
  • Algorithms

One Expensive Operation Paid for by a Thousand Cheap Ones

I remember sitting in a windowless lab during my PhD, staring at a performance trace that made absolutely no sense. My simulation was hitting massive, inexplicable latency spikes every few thousand cycles, even though my algorithm was supposedly “efficient.” I…

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Why constant factors still matter in algorithms.
  • Dr. Ingrid Falk-Weller
  • January 19, 2026
  • (0)
  • Algorithms

The Slower Algorithm Wins Below Ten Thousand Elements

I remember sitting in a windowless lab during my postdoc, staring at a beautiful, $O(n log n)$ implementation that was being absolutely slaughtered by a “theoretically inferior” $O(n^2)$ algorithm. The student who wrote the faster one had barely looked at…

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Learning how to analyse time complexity.
  • Dr. Ingrid Falk-Weller
  • January 17, 2026
  • (0)
  • Algorithms

Big O Describes Growth, Not Speed

I remember sitting in a windowless lab during my PhD, staring at a profiler output that made absolutely no sense because I had spent three weeks memorizing Big O rules without actually understanding what they meant. Most textbooks treat learning…

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