My name is Chao Deng. I am from China. Currently I study at University of Southern Callifornia.
I am a Ph.D. candidate in Computational Biology and Bioinformatics at USC. Meanwhile in Dec. 2016, I obtained a M.S. in Computer Science at USC. Before came to US, I finished my M.S. in the math department at Peking University in China, advised by Prof. Minghua Deng. I finished my B.S. in the math department at Shandong University in China.
My research is about estimating the expected number of unseen species in a population, given partial observations. For example, Shakespeare's known work contain 884,647 words, which have 31,534 word types. If another amount of work by Shakespeare are discovered, say 884,647t words, how many new word types do we expect to observe? When t is equal to 1, the answer is supurisingly consistent. However, in the era of big data, emerging applications require large t, which present new challenges.
We develop two softwares preseq & preseqR to see the unseen
preseqR, an R package to predict the number of species represented at least r times in a random sample
preseq, a C++ package to predict the complexity of a genomic sequencing library
Numbe of heros
Number of items
Prize pool for TI6
I like to play video games in my spare time. Among all games I ever played, Dota2 has to be the best. For me, two key factors in a game are diversity and balance. Dota2 is an excellent example in archiving both game diversity and game balance. Below are numbers showing how diverse this game is: 10 online players are required to play the game; 113 heros are available to pick; 148 items can be equipped to enhance attributes of a hero. For such a complicated game system, there is no doubt that many people complain about the steep learning curve.
Meanwhile, Dota2 is surprisingly balanced once you get used to it. In the recent competition event TI6, more than 100 heros were selected in at least one game, and almost every item is used. Of course the balance can be not achieved by one step. Here are patches of Dota2 in history.
As a data analyst, I am particularly interested in using machine learning approaches to automatically balance video games.