IFTNEXT

I didn’t go to Las Vegas last year for the IFT17. I knew IFTNEXT just recently when I was submitting an abstract for IFT18. Sponsored by ingredion, Inc., IFTNEXT session was first launched in last year’s exhibition (http://www.ift.org/iftnext.aspx). I didn’t have the chance to be there and see, but thankfully there is a website to check out (http://iftevent.org/video). With the mission of “Being inspired to think big”, the initiative of IFTNEXT was aimed to have people from different disciplines sit together and rethink the global challenges in food. On the website (http://www.iftevent.org/sessions/call-for-proposals), I found one session called “Data intelligence, AI, and driving innovation in the food industry“, which really surprised me. I was also very excited, oh no, thrilled, actually, to see it because that’s what exactly I am doing now! I guess probably next time I could explain my work to people around me more easily by introducing IFTNEXT, which I believe will be more and more familiar to food science students in the future.

My research interest is to apply data mining or more specifically text mining, naturally language processing and machine learning to help solving decision making problems in food science. The first project I’m now doing is to employ social media platform Twitter to collect food-related data and try to distill some useful information relevant to sensory and consumer sciences. Social media data mining is not new any more and there are some food companies leverage social medias for their marketing purposes. But I was more interested to incorporate food science knowledge and computer science skills, which I’d like to call it “food hacking”. One day when I was searching for “food textural terms”, a wheel made by Ingredion Idea Labs interested me. Tools developed by the company were created to help modify and optimize the texture quality of food products, which sounds pretty cool to me. The work is published on a book “Food Texture Design and Optimization” (http://onlinelibrary.wiley.com/doi/10.1002/9781118765616.ch1/summary).

Well, there is a story of me, about why I want to study food science. When I was 18, about to decide which major to go. I had not idea in my mind at that young age. But there was a question lingered over my head: why everybody in China so worried about food safety? Can we make our food safer and healthier and our people less concerned about food? Then I choose food science as my major and I went to China Agricultural University (CAU) which was well known for its food science program. Till now, over 8 years past, the question is still a question in my mind. It turns out that the question was too big and probably too hard to answer by just studying food science.

After 4-year undergraduate and 3-year graduate training in food science, I realize that we food science people are trained to be good at examine food in very much details, such as investigating its chemical composition, physical properties, and biological activities, etc,. Given a sample, taking apple for instance, food scientists would study it as a soft material and nutrition scientists would treat it as a combination of multiple nutrients and compounds that’s good/bad for our health. But all are only focused on the apple. One problem solved one a sample won’t apply to the other samples. Considering the variations in different food, we still need to examine them one by one. When going into too much details and spending most of the time on examining food one by one, it’s hard to hold the big picture. Then after 8 years of food science training, I realized that I don’t want to study food by food or one bioactive by another, I want to create something that can be applied to other food materials, other markets,  or other food problems. Gradually, I found what I was looking for is methodology.