Industry News Details
Interview with Fangde Liu, Principal Technology Architect, Imperial College London - Speaker at 5th Annual Global Big Data Conf Posted on : Jul 19 - 2017
We feature speakers at 5th Annual Global Big Data Conference - August 2017 to catch up and find out what he or she is working on now and what's coming next. This week we're talking to Fangde Liu, Principal Technology Architect, Imperial College London (Topic : Clinical ABC)
Interview with Fangde Liu
1. Tell us about yourself and your background.
I'm a research associate from the Data Science Institute from Imperial College London. I'm currently working applying big data and ai for clinical applications like surgery or drug prescription. Nowadays, I'm focusing on imaging informatics, until last year, I'm working the navigation software for several surgical robot project also at Imperial College London. Before work in the field of medicine I've extensive experience with robotics and movie VFX.
2. What have you been working on recently?
There are a few projects I'm working on or managing at the moment. I'm working an a cloud platform based on Ai system for autonomous surgery planning, helping surgeons to find out the best surgery plan instantly before each operation. I'm also managing two projects the optimise-ms is for neurology pharmacovigince and effective monitoring system based on big data technology, and also the analysis pipeline infrastructure for SmartHeart project which aims to automatic analysis up to 200,000 cardiac mri image data from several London hospitals and the bio-banks.
As an software developer, I am actively involving building the in house deep learning tool and infrastructure for research application, some of the work are opensource as the tensorlayer project.
3. Tell me about the right tool you used recently to solve customer problem?
In medicine, there are tones of problem and I can hardly say we solve any yet.
As for tools, we built inhouse tools ourself. The TensorLab system is the one I find useful across many project. It is both a data analysis pipeline, an automate factory to build machine learning model, and also designed as a data fusion warehouse. It is like Template solution for many research projects in this group.
4. Where are we now today in terms of the Big data, and where do you think we’ll go over the next five years?
I would say the infrastructure is widely available now for all industry. Now we are at a time to turn technology into productivity and profits. So application is becoming more and more important. some big data system improve existing solution, but a few are quite disruptive in its domain. I feel it is something like my work experience working with doctors, the one has the technology has little knowledge about the industry while the one has knowledge of the industry does not have the out of box thinking of the technology. I wish in the coming 5 years as the domain expert become more familiar with the big data principle, we can see some more insightful and imaginative application.
5. You’ve already hired approximately 13 people in the last year. What would be your pitch to folks out there to join your Organization? Why does your organization matter in the world?
We are a team of about 40 people. I would say the Data Science Institute of Imperial College London is unique because we are applying data science to some cutting edge research, trying to find the answer of some of the most important challenge on the world such as treating heart disease or finding the drugs for dementia. You don't learning just learn the data science here, you know the world better. Data Science Institute is like a pillar support the research activity of all the department of imperial college london, from gene to climate change, energy and digital currency. To prove the importance of your work. The transmart project undertaken by DSI is the industry standard for translational medicine research and adopted by almost all major pharmaceuticals companies
6. What are some of the best takeaways that the attendees can have from your "Clinical ABC" talk?
In principle, big data, AI and cloud maybe very useful for healthcare. However, it is more challenging after scrutinised. Things in medicine is in fact very different from an engineer's mind and technology invader in fact made many important mistakes.
Many product and technology need to be remake to work in medicine, and I will explain to the technology providers what the doctors really want and why existing ABC solution to healthcare industry is very limited.
7. What are the top 5 Big data Use cases in enterprises?
1.gene sequencing for precise medicine treatment
2. product registry
3. enterprise document search engine
4 precise targeting advertisement
5 epidemic prediction and monitoring
8. Which company do you think is winning the global Big Data race?
Ali and amazon are quite good at turning data into value. but I would say a bigger giant may come from the healthcare sector which have not show himself yet.
9. "Can you explain why Big data in medicine is difficult":
many people have an idea to improve the healthcare service he/she received, however, facing a patient dying of cancer, doctors in many times find themselves powerless, with or without big data. Many technology innovation may improve the healthcare service but does not deliver better heath for the patient. Another issue is like medicine, to make it effective, technology have to be applied on the right patient, in the right way at the right time. if we made any mistake, an impactful innovation will become useless.
10. Any closing remarks
Over the years, I start to understand Viktor's idea that not the company have the data win, the company knows how to turn data into value win.