Johns Hopkins' Professor Jim Liew
Can you speak to me a little about your time at University of Chicago?
When I think about my time at the U of C, it brings back many fond memories. Although I initially assumed that I would study Economics, since my dad was an Econ professor, it was my faculty advisor who steered me to study Mathematics, a decision that ultimately made a huge difference in my career arc.
Having a solid academic basis in math has served to be critically useful in navigating my career, through the usual ups and downs of a career in finance. I know that there's folks out there that claim that the college path may not be a good investment of time and money, but for me I wouldn't trade it for anything. From where I stand now, I see the tremendous value of my time at Chicago – both for the rigorous education and the lifelong friendships.
Did you originally want to work in finance?
I equated finance with Wall Street and after watching the 80’s movie Wall Street, I became a huge GG fan and couldn’t imagine a career more exciting than working on Wall Street. Since we did not have an undergrad Finance major at U of C, I sat in some business school-level courses. It was a treat to be in the same room with Fama - he’s known for his electrifying classroom lectures.
What prompted you to get your PhD from Columbia?
Growing up in Oklahoma, moving out east to the microcosm of the financial universe, New York City, was definitely on top of my bucket list. So naturally Columbia Business School was my top choice for graduate school. My parents, who were both professors, mandated that my older brother and I get our Ph.D. before starting our careers, so I followed that path.
How was the transition from Finance to education, and then education to AI and Machine Learning?
Again, this is how useful my mathematics degree has been over the course of my career. Shortly after transitioning from Wall Street to Academia, I realized there was a perfect Trifecta forming amongst big data, exponentially faster computational power and open source algorithms.
As these stars aligned, I advocated to start teaching the first "Big Data Machine Learning" course, which was supportable by my math background, and I've been teaching this course ever since. Even now, it's amazing to see new students who have never been previously exposed to AI begin their journey. My present curiosity is to figure out a way to teach the basics of machine learning and AI to any MBA who can find their way around an Excel spreadsheet.
BlockMedx -- my father is a court officer and has seen many of the effects of the opioid crisis in person, from losing co-workers and seeing young kids in and out of jail directly resulting from addiction. Watching your 2018 talk on it at the DC Blockchain Summit, I was instantly amazed by how effective a solution of documenting every step of the way and then identifying where issues were coming up. Are you still an advisor there?
It can’t be said enough that the Opioid crisis has been devastating to our country and its origins are especially tragic. I was asked by one of my students to join BlockMedX -- the company had a great mission so it was an easy decision to jump on board as an advisor to the company.
With BlockMedX, we tried to do an ICO, but caught the downside of the crypto bubble in 2017-2018, so were not successful at that time in raising the necessary funds to make a run out of it. With that said, BlockMedX was incredibly effective in bringing the opioid crisis into the stream of awareness and dialogue within the political community in DC.
SoKat – Can you tell me a little bit about why you founded SoKat / how you got into consulting?
SoKat is named after my two daughters -- Sophie and Katherine. As I always tell my students, never name a company after yourself if you want any hope of success! But more seriously, SoKat provides full-stack software development services for our range of clients from commercial asset managers to Federal agencies.
We have won several awards for the work that we’ve completed: the 2018 and 2019 GCN Government Innovation Award, 2020 ACT-IAC Igniting Innovation Transformer Winner for GrantSolutions Recipient Insight, and recently the 2020 GSA Artificial Intelligence and Machine Learning EULA Challenge winner, placing 3rd. I’m very proud of our team, which consists almost exclusively of Johns Hopkins University faculty and graduate student engineers.
I started SoKat because as much as I enjoyed the academic side of AI, because of my Wall Street background, I was also equally interested in working on real-world AI business problems. Helping organizations drowning in a deluge of data by framing their business problem and then using technology to formulate and deploy scalable solutions is more fun than you can imagine!
Also, I’ve always had a strong entrepreneurial streak, and since I was teaching Entrepreneurial Finance, it was about time I translated those academic principles to actionable strategies to starting and scaling a successful company. Since then, I’ve completely embraced the entrepreneurial journey, which doesn’t have to be a lonely one – organizations like the Entrepreneurial Organization in DC, of which I’m a member, is a thriving community of successful entrepreneurs.
What’s next for SoKat?
We are working on several projects at this time. One project is to provide easy access to AI education for the Government community. We envision an “AI-ramp” that anyone can enter to begin or strengthen their AI education and training journey, now sprinkle in our 3D AI Chatbot and it's going to be an out of this world user experience -- even the late Steve Jobs would've loved it!
I’m sure we can all agree that improving our ability to effectively leverage AI will help our workforce stay globally competitive. AI will continue to disrupt every industry so it’s critical to fully engage in AI as a national strategy. Our goal is to make learning AI on your mobile phone as exciting as watching Tik-Tok videos!
Another exciting project involves expanding the utility of the mobile phone – this is our Loonshot, and since the technology is still in its R&D phase, that’s as much as I can say about it for now. But with this project, I’ll be returning to my Wall Street roots by rolling out more Fintech technologies. The hint here is capitalizing on the convergence of the traditional and digital investment worlds.
What’s next for you?
I continue to enjoy teaching at Johns Hopkins Business School, meeting new people, and working on disruptive FinTech business projects. If you have interest leveraging Big Data and AI to disrupt financial norms, feel free to reach out -- I’m more than happy to share my thoughts, lessons learned, and experiences with next generation disruptors!
Written by Owen Deignan & Edited by Alexander Fleiss