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60 EpisodesProduced by James LeWebsite

Datacast follows the narrative journey of data practitioners and researchers to unpack the career lessons they learned along the way. James Le hosts the show.


Episode 53: Algorithms and Data Structures In Action with Marcello La Rocca

Show Notes
  • (2:09) Marcello described his academic experience getting a Master’s Degree in Computer Science from the Universita di Catania in the early 2000s, where his thesis is called Evolutionary Randomized Graph Embedder.
  • (6:14) Marcello commented on his career phase working as a web developer across various places in Europe.
  • (9:18) Marcello discussed his time working as a software engineer at INPS, a government-owned company that now handles most Italian citizens' pubic-related data.
  • (10:42) Marcello talked about his time as a data visualization engineer at SwiftIQ. He created a data visualization library that allows the inclusion of dynamic charts in HTML pages with just a few JavaScript lines.
  • (13:40) Marcello went over his projects while working as a full-stack software engineer for Twitter’s User Services Engineering team in Dublin.
  • (17:19) Marcello reflected on his time at Microsoft Zurich’s Social and Engagement team, contributing to machine learning infrastructure and tools.
  • (21:28) Marcello briefly touched on his one-year stint at Apple Zurich as a Senior Applied Research Engineer.
  • (23:49) Marcello talked about the challenges while writing “Algorithms and Data Structures in Action,” which introduces a diverse range of algorithms used in web apps, systems programming, and data manipulation.
  • (27:11) Marcello expanded upon part 1 of the book, including advanced data structures such as D-ary Heaps, Randomized Treaps, Bloom Filters, Disjoint Sets, Tries/Radix Trees, and Cache.
  • (34:51) Marcello brought up data structures to perform efficient multi-dimensional queries, including various nearest neighbor searches and clustering techniques, in part 2 of the book.
  • (39:21) Marcello briefly described the algorithms in part 3 of the book — graph embeddings, gradient descent, simulated annealing, and genetic algorithms.
  • (48:28) Marcello talked about his work on jsgraph — a lightweight library to model graphs, run graphs algorithms, and display them on screen.
  • (52:06) Marcello compared Python, Java, and JavaScript programming languages.
  • (54:13) Marcello discussed his current interest in quantum computing.
  • (56:18) Marcello shared his thoughts regarding Dublin, Zurich, and Rome's tech communities.
  • (57:37) Closing segment.
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