Dmitry Storcheus is an Engineer at Google Research NY, where he does scientific work on novel machine learning algorithms. Dmitry has a Masters of Science in Mathematics from the Courant Institute and despite his very young age he is already an internationally recognized scientist in his field of expertise. He has published in a top peer-reviewed machine learning journal JMLR and spoken at an international conference NIPS. Dmitry Storcheus got peer recognition for his foundational research contribution published in his paper “Foundations of Coupled Nonlinear Dimensionality Reduction”, which has been cited by scientists and engineers. He is a full member of reputable international academic associations: Sigma Xi, New York Academy of Sciences and American Mathematical Society. This year Dmitry is also a primary chair of the NIPS workshop “Feature Extraction: Modern Questions and Challenges”.
- Hi Dima, you were recently invited to give a talk at DataEngConf in NYC and we are very excited to hear about your novel machine learning research. You have a pretty unique situation where you joined Google Research right after your Masters, you are a very young scientist, working together with top notch professors and Phds. Tell me about your path overall. How did you manage to get in?
- Let me first talk about my path. I studied at a Russian college called ICEF, and then I came for graduate studies to the USA, where I did my masters in math at the Courant Institute. I started machine learning research very early - back in Russia I used machine learning to forecast financial time series and in the USA I continued machine learning studies on a theoretical level. Straight after graduation I was hired by Google Research in New York to work on machine learning algorithms. I think that they key to my employment is that my unique skills and strong technical background was recognized by Google. Also, Google Research recognized my foundational scientific work that I had already done and sound machine learning algorithms that I had developed. What I did is I derived generalization bounds for coupled dimensionality reduction and created an algorithm called SKPCA.
- So why did you choose Google over any other company?
- 2 reasons. First, a job at Google naturally followed after my research work at my graduate school as I could apply my research directly, and I wanted it to benefit the Machine Learning community. The second reason is that I think that Google is a company that values potential in people. It selects people based on their projected individual growth, and that appealed to me as a young professional because it guaranteed continued growth and mentorship by best scientists in the industry.