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Jon Krohn
Chief Data Scientist and Co-Founder at Nebula.io
Jon Krohn is a prominent figure in the field of data science and machine learning. He is the Co-Founder and Chief Data Scientist at Nebula.io, a machine learning company.2 With an extensive background in data science and artificial intelligence, Krohn has established himself as a thought leader and educator in the industry.
Professional Experience
Krohn's career spans several notable positions:
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Co-Founder & Chief Data Scientist at Nebula.io (2021 - Present): In this role, he manages scientists and developers, works on commercially-oriented R&D, and develops natural language models, including generative LLMs.2
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Director at Wynden Stark (2021 - Present): This group includes Nebula, GQR Global Markets, and untapt in its portfolio.2
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Chief Data Scientist at untapt (2015 - 2021): He held similar responsibilities as his current role at Nebula before the company was acquired by Wynden Stark Group.2
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Data Scientist at Omnicom (2014 - 2015): Krohn worked on automated digital advertisement trading platforms and contributed to winning significant client accounts.2
Education and Research
Krohn holds a Ph.D. in Neuroscience from the University of Oxford, where he was a Wellcome Trust Doctoral Scholar. His research focused on applying machine learning models to high-dimensional genomic, neuroscientific, and behavioral data.2
Contributions to the Field
Jon Krohn is known for his multifaceted contributions to data science and machine learning:
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Author: His book "Deep Learning Illustrated" became a #1 bestseller and has been translated into seven languages.1
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Podcast Host: He hosts the SuperDataScience podcast, a popular technical program on machine learning applications with millions of downloads annually.1
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Educator: Krohn creates video tutorials, teaches online courses, and gives lectures at universities, conferences, and companies.1
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Content Creator: His Udemy course has over 100,000 students, and his YouTube channel received the 2021 Data Community Content Creator Award for the AI/ML category.1
Through these various roles and contributions, Jon Krohn has established himself as a respected and influential figure in the data science and machine learning community.
Highlights
I'm on holiday this week so today's "Five-Minute Friday" episode of my podcast is (mercifully??) short. In it, I reflect on our impermanence and how precious that makes each moment we have.
The photo was captured this (northern-hemisphere) summer, atop the tower of Magdalen College, University of Oxford at sunset.
At the furthest point of the lush Magdalen College grounds lies a tranquil, hidden pond. The prominent inscription on the sole bench alongside the pond reads: "All things leave us. If not, we leave them."
So simple and so obvious... yet so easy to forget. I hope you're enjoying and making the most of your time outside of work; the sunsets and the autumns will only keep coming 🍂
To hear more of my (brief) summer reflections, listen to today's episode (#814). The "Super Data Science Podcast with Jon Krohn" is available on your favorite podcasting platform and the video version (which today is simply an audio waveform!) is on YouTube.
For many real-world commercial problems, the best approach is not machine learning or statistics; it's Mathematical Optimization. In today's episode, hear all about optimization from the guru Jerome Yurchisin.
Jerry's an extraordinarily clear communicator of complex topics and a world-leading expert on real-world applications of mathematical optimization. He: • Works as a Data Science Strategist at Gurobi Optimization, a leading decision-intelligence company that provides mathematical optimization solutions to the likes of Uber, Air France and the NFL (indeed, a wild 8 out of 10 Fortune 10 companies use Gurobi!) • Previously spent eight years as a mathematical consultant where he paired mathematical optimization with machine learning, statistics and simulation to inform decision-making. • He was also previously an instructor at the University of North Carolina at Chapel Hill, where he obtained his Master’s in Operations Research and Statistics. • He holds an additional Master’s in Applied Math from Ohio University.
Today’s episode may appeal most to hands-on practitioners like data scientists and ML engineers, but it does also have tons of content that will be of interest to anyone who’d like to leverage data to make better commercial decisions or optimize commercial processes.
In this episode, Jerry details: • What mathematical optimization is. • The kinds of real-world problems where mathematical optimization is a far better approach than a machine learning or statistics approach. • The history of mathematical optimization including why it wasn’t popular until recently. • The cutting-edge hardware and software innovations in mathematical optimization today.
The "Super Data Science Podcast with Jon Krohn" is available on your favorite podcasting platform and a video version is on YouTube. This is Episode #813.
#superdatascience #optimization #data #datadriven #business
