The 53rd episode of Datacast is my conversation with Marcello LaRocca — a research engineer with experience creating large-scale web applications and machine learning infrastructure. Give it a listen to hear about his education in Italy; his career as a full-stack developer; his time working at Twitter, Microsoft, and Apple; his book “Algorithms and Data Structures in Action”; his JavaScript library that implements various graph algorithms; his interest in quantum computing; his thoughts on the tech communities in Dublin, Zurich, and Rome; and more.
Listen to the show on (1) Spotify, (2) Apple Podcasts, (3) Google Podcasts, (4) Stitcher, (5) iHeart Radio, (6) Radio Public, (7) Breaker, and (8) TuneIn
Marcello La Rocca is a research scientist and a full-stack engineer. He works as a consultant, creating large-scale web applications and machine learning infrastructure. He has gained invaluable experience at Twitter, Microsoft, and Apple — working on applied research in academia and industry. His work and interests focus on graphs, optimization algorithms, genetic algorithms, machine learning, and quantum computing.
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.
His Contact Info
His Recommended Resources
“Algorithms and Data Structures in Action” (Marcello’s book with Manning)
“Scalability Rules” (by Martin Abbott and Michael Fischer)
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About the show
Datacast features long-form conversations with practitioners and researchers in the data community to walk through their professional journey and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths - from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.
Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com.
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