Season 2 episode 2 of The Minhaaj Podcast this week brings on the child prodigy and genius co-creator of dataframes.jl package for Julia, Dr Bogumił Kamiński. Bogumil learned C language without owning a computer from library books at the age of 16 in a small Polish town. In post-communist Poland he went on to study applied problems in management and economics and his interest lies in computational models for real-life problems.
He currently serves as the full professor of economics at the Warsaw School of Economics. He also holds the following positions:
- Head of Decision Analysis and Support Unit
- Chairman of the Scientific Council for the Discipline of Economics and Finance
- Member of the Presidium, Statistics and Econometrics Committee, Polish Academy of Sciences
- Adjunct Professor, Toronto Metropolitan University
- Data Science Laboratory Researcher, Fields Institute, Computational Methods in Industrial Mathematics Laboratory
- Affiliated Faculty, Toronto Metropolitan University, Cybersecurity Research Lab
President, INFORMS Polish Section
- Co-editor, Central European Journal of Economic Modelling and Econometrics
- Editorial board member, Multiple Criteria Decision Making journal
Independent Supervisory Board Member, AutoPartner S.A.
Bogumił Kamiński is an expert in the application of mathematical modeling to solve practical problems in business. In the past, he gathered experience as head of business intelligence and data analytics units in one of the largest Polish consulting and IT solution implementation companies.
His field of expertise is the creation of complex decision-support models that use machine learning, optimization, and simulation methods. He is one of the world-leading experts in the Julia language and has numerous contributions to the core of the language and the package ecosystem. He created the famous dataframes.jl package for data science.
He also created SilverDecisions software, which is freely available online for modeling decision trees. He has written five books one of which I have reviewed earlier, Julia for Data Science.
# Timestamps
00:00 Intro
01:08 Learning Programming, Communist Poland & First Computer
07:07 Polish Education System & STEM teaching
11:35 Julia’s Conceptualization & Expectations
28:05 PetaFLOP club language, Data Type-based Operations & Julia’s Performance
38:11 Project Celeste, 800M astronomical objects detection, HPC in Julia
59:50 Julia in Academia vs Industry - Speed & Ease of Learning
01:21:21 Customer-facing Apps, Streamline vs Genie
01:38:56 Julia and LLMs, Falcon 40B, Training & Inferencing in Julia
01:45:05 Relearning Julia, How to get Started
01:51:09 From in-memory to cluster processing and MIT partnership
01:59:09 Family, Productivity, Community & Work - Juggling different Balls

---

Send in a voice message: https://podcasters.spotify.com/pod/show/minhaaj/message