With over 20 years of experience working in math, applied linguistics and engineering in both Higher Education and industry, applying his skills to everything from cloud & middleware infrastructures to data science, Natural Language Processing to Machine Learning/AI for knowledge networks, graph systems, interactive visualization platforms, and behavioral modeling, our guest this week, Microsoft’s Krishna Madhavan is easily one of the best examples we’ve probably had so far in Season 3 of what we mean by a ‘Learning Scientist.’
You’ll recall that in Season 3, our ‘The Learning Scientists’ mini-season on LITNW, we’re meeting the innovators drawing on Data/Social Science/Computer Science and Neuroscience-based practices to move the L&D profession forward and mining the new insights and tools we need to help us build a better model for Workplace Learning, especially as we start to move to a post-COVID ‘New Normal.’ A winner of multiple academic rewards and a former tenure faculty member at a leading mid-Western US University, Krishna is now a co-founder and Director of the new Worldwide Learning Innovation Lab at Microsoft, an innovation center set up in Redmond to cross boundaries and experiment – again, things we love to hear on this podcast!
Please note that we recorded our chat with Professor Madhavan before the Lockdown, but in our convorsation we still heard a lot of great things, starting with how a math and stats guy ended up with a PhD from an English department to:
- what his 1.5-year old research entity is all about, and why being able to sit across so many product groups at Microsoft helps it achieve that
- the kind of higher-order problems he’s interested in now, and in his past, all the way back to his start in India
- why speaking six languages isn’t seen as that big a deal where he comes from
- the differences (good and bad) between The Academy and The Corporation
- the central role of ethics in what he and his team are looking at
- why accessing Microsoft’s incredible data treasures is actually (and reassuringly) made as hard as possible
- how, in practical terms, you lead for innovation and set up an experiment-minded culture
- the benefits of a truly multi-disciplinary approach and what that means for the Learning Science project
- and much more.
Post Episode Update
I checked in with this week’s Podcast guest Krishna Madhavan ahead of our publication of the episode featuring a conversation I had with him earlier this year – He and his team are hard at work albeit working remotely from home, and he gave me the reason for their intensity of focus
“The COVID-19 pandemic has impacted learners – particularly those graduating in profoundly serious ways. Learning institutions, moving to completely online education delivery, are on the market for products, tools, and services that can provide their learners with robust career services and learning options that will help address their skilling needs. We continue to innovate on AI-infused experiences that can empower learners to pursue careers they find meaningful and reduce uncertainty during these difficult times.”
I also found an really strong case study example of AI and a broad set of technologies that illustrates this topic and that helps undergraduates get real time answers to their study questions and creating an engaged learning community as a bi-product in this talk by Profesor David Kellerman – Senior lecturer in the School of Mechanical and Manufacturing Engineering at the University of New South Wales (UNSW) in Sydney.
Krishna is very open to people connecting with him on LinkedIn to find out more about the Lab and its works-in-progress here
Microsoft speaking about its work in AI
Find out more about Krishna mentions as being a really game-changing, state-of-the-art new language model for helping computers understand human speech better we all need to know about, BERT (Bidirectional Encoder Representations from Transformers) here and here.
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