There is a common impression from PhD students that the set of skills they acquire while researching for their degree is not directly applicable to industry. I was happy to participate in the Macquarie Minds Showcase Panel on Pathways From A PhD: Transferable Skills, Employability And Career Options Outside Academia and address some of this misconceptions.
For this panel, I represented my employer, the Commonwealth Bank of Australia. From a Data Science practice perspective, PhD students have a unique set of skills, including the depth of thought and creativity that is required to solve an ever-so-complicated range of problems in the field of machine learning / analytics in large corporations.
The main takeaways from our panel discussion were that transferable skills are key and the ability to communicate plays a major role for anyone’s employability.
PhD students tend to be overly modest. Perhaps because they live in the academic world where everyone has a PhD and where most people will have more publications that they do. This means PhD students tend not to know how to value themselves and their work. It is hard to understand the value of your skills, and it is difficult to say how one can objectively assess that. I only realised the true value of my own skills when some of the work I did was sold for a lot of money to a large organisation.
I am glad that I took part in this discussion. As an alumnus of Macquarie University, I feel that it is important to help the current students realise that they can work in the industry if that is what they desire and that their degrees are valued. As the panel ended, I talked to many students who were wondering what to do and I hope that what we discussed helped them on their journey.
Here are some tweets from the day.
— Long Li (@sokeven) December 13, 2016
— Belinda Fabian (@BeaCurious) December 13, 2016
#MQMinds16 Top 5 transferrable skills sought by employers (UK study)
— Livia Gerber (@GerberLiv) December 13, 2016
U have highly valuable skills. Don’t be overly modest in articulating them. Don’t sell yourself short. #MQMinds16
— Long Li (@sokeven) December 13, 2016
It’s not every day that you get to go to Massachusetts Institute of Technology (MIT) and in front of a crowd of 200+ people share your experience in your area of expertise. I had the pleasure of doing that during the 10th ACM Conference on Recommender System.
On the 17th of September, Ido Guy and I presented the Tutorial on People Recommendation. As the name suggests, we focused on recommender systems that recommend people to other people.
I presented an introduction to the area with special focus on reciprocal recommenders. This includes topics I have closely worked on, including people recommender for online dating and for employer-employee recommendations. I also talked about recent and up-and-coming work. Ido focused on social media recommendations and building relationships in social networks.
Here are the slides of our presentation.
Just for fun. Ido and I presenting, the view from Twitter.
— matt corkum (@matt_corkum) September 17, 2016
— ACMRecSys (@ACMRecSys) September 17, 2016
You never know where life takes you, so I normally say yes to interesting opportunities. From mid June to the end of September I agreed to teach a 12-week, full-time data science course in Hong Kong. This was the first cohort for the Data Science Immersive at General Assembly.
The course was quite demanding for the students and for myself. In particular, given the full-time nature of the course, I had very little time to enjoy the city of Hong Kong. My schedule was 9am-5pm teaching (lots of speaking, lots of helping), and late at night preparing for the following day. For the students, it was a similar drill: lots of in-class paying attention and exercises, and after class revision and project work.
The course covered a lot of ground in data science and the eleven students were very good by keeping up with the course. In particular, I had no problem explaining advanced machine learning concepts with students understanding every graph and formula.
I am very happy with the final outcome of the course, and I am confident that students are quite ready to take on data science challenges in the real world.
Below is a presentation I gave to a number of industry guests and the students on graduation day. It gives an idea of the course and the projects they worked on.
So my Hong Kong experience was an example of one such challenge to which I said yes. It was not easy but it was highly rewarding. Not only did I meet and help shape a group of excellent data scientists but also I made some good friends along the way.
I had the privilege to be part of a panel on the ethics of online dating held at the Saint James Ethics Centre. The panel consisted of myself, ethicist Matthew Beard, HIV/sex activist Nic Holas, and academic and internet dater Emma Jane.
Before the panel Jackie Dent interviewed me for an article for the Ethics Centre website: Does your dating site knows you better than you?
Today I was a guest speaker on the Industry and Business panel at the 2014 IEEE International Conference on Communication. The topic was “Path from Research to Industry”. It was a huge privilege to sit beside a number of very distinguished people who had built their entire careers on helping research come to market. The panel was moderated by Daniel Austin, Head of Research of the Smart Services CRC, and had the following speakers:
- Dean Economou, Technology Strategist, NICTA
- Paul McCarthy, Director, Strategy & Innovation, Sirca Group Ltd
- Luiz Pizzato, Co-Founder of Octosocial, and Pizzato Data Science Consultancy
- Jeremy Brun, Staff Software Engineer, Dolby Australia
- Khimji Vaghjiani, Business Advisor, NSW Department of Trade and Investment
- Dean Gingell, Principal, Lens10 Pty Ltd
The heavy weight of experience in this panel was impressive. They were directly involved in the creation and the development of a number of high profile and extremely successful examples of research commercialisation.
My main contribution was to give an insight into the mind frame of researchers, how they view commercialisation and why it is so hard for them to think of commercialisation as a good thing for themselves and their careers. But more importantly, how researchers can overcome this and perhaps even start a company of their own.
Brad and Simon were the perfect hosts for the event. They shared with a small group of entrepreneurs the art and science of negotiation including a number of study cases of big negotiation (i.e. billion-dollar deals) that Brad conducted as part of the Virgin group.
A great deal of the workshop involved role playing and getting feedback from Simon and Brad. For the main exercise, we were divided into 4 groups where two groups played the part of entrepreneurs building a chain of gyms and the other two groups would be Virgin executives. We would negotiate the terms of our deal to get Virgin into the fitness business. Even though role playing does not reflect the situation perfectly as you have no real stakes, it was easy to see where you are making a mistake and how you should approach and behave under non-favourable conditions.
I am happy to report that the negotiations I was involved were quite successful. We not only reached a good agreement for all parts but we also did slightly better than the other similar group negotiating the part for the gyms.
To learn how to negotiate is a very important business skill that is perhaps overlooked among all other business fundamentals. I cannot say I have mastered this skill yet, but I am pretty sure I am much better prepared now for whatever deals I am going to face in my startup.
Welcome to my newly created blog and website.
In this blog I will document my journey through the development of my next big project, which is building my own startup. Finally after many years of working on exciting research projects, I decided to quit my job at the University of Sydney and purse a dream that I always had – to become an entrepreneur.
At the University of Sydney, I was part of a very successful project, in which I built reciprocal recommendations algorithms for a major Australian online dating website. This project was very fulfilling as it showed me that maths and algorithms can have a real positive impact in people’s lives. I know that because of our system, the rejection rate declined considerably and people were more successful in getting dates. I do not know how many people got married in the end, but I would like to think that it is a big number 🙂
The startup I am building focus on a related problem – to help people make new friends. The way we will achieve this will be very different to online dating. To start, it will also be suitable for couples and families, and it will be very useful for people who just moved to a new city.
Our startup website is Octosocial.com. We are using lean-methodology to building our product and we are constantly running experiments. We experimented with the idea of social lunches and dinners and have so far run four events. We also signed up nearly one hundred users. So the idea of social lunches and dinners are very promising, but there are quite a few difficulties there. For instance, what is the best way to match people? Is it age, interests, background, location, education, or is it something else? What is the best way to invite people to an event? And, how to guarantee commitment from people to attend an event? We had an overwhelming positive feedback from the social meetings we organised. We also learned a lot about the expectations of people of different age groups, personalities and backgrounds.
With all that we learned so far, we are right now in full development mode. We are building the next generation social discovery start-up with one main goal in mind: helping people making new friends.
Stay tuned and sign up on the website if you want to join in the fun!