AI for a Better Prediction COVID-19 Model
A team of Caltech students, led by Professor Yaser Abu-Mostafa, have developed a tool to predict the impact of COVID-19 using artificial intelligence (AI). While many models to predict the spread of a disease already exist, few if any incorporate AI, which makes predications based on observations of what is actually happening as opposed to what the model's designers think should happen. AI has the power to discover patterns hidden in data that the human eye might not recognize. [Caltech story]
Alexander Popov Receives 2020 Henry Ford II Scholar Award
Computer science student Alexander Popov, advised by Professor Yaser Abu-Mostafa, is a recipient of the 2020 Henry Ford II Scholar Award. Some of the most interesting classes that Alexander has taken at Caltech have been team-based interdisciplinary project classes. These classes have allowed him to gain experience working in teams with varying specialties, while designing and implementing interesting projects (for example, a robot arm designed to recognize users’ hand gestures and assist them in executing complicated drawing-related tasks, such as exactly copying an area of a whiteboard). This summer he will be working as a software engineer at Facebook. After graduation, he aims to work at a company where he is able to further develop his knowledge of machine learning and the application thereof. The Henry Ford II Scholar Award is funded under an endowment provided by the Ford Motor Company Fund. The award is made annually to engineering students with the best academic record at the end of the third year of undergraduate study.
Henry Ford II Scholar Award
Undergraduate Students Win International Data Science Competition
Undergraduate students Hongsen Qin, Emma Qian, Thomas Hoffmann, and Alexander Zlokapa (advised by Professors Aaron Ames, Erik Winfree, Jonathan Katz, Maria Spiropulu, and Yaser Abu-Mostafa) have won the Citadel Data Open International Data Science Competition. This winning team chose to investigate the optimal way to spend $1 billion to save lives from malaria and sanitation-related diseases, allocating funds for different prevention methods and optimizing budget breakdowns country by country. To quantify the socioeconomic impacts of their policy proposal, they modeled a variety of aspects from mosquito feeding cycles to climate change using techniques ranging from causal discovery methods to interpretable machine learning. The Caltech team was among 24 teams that were evaluated and questioned by a panel of experts including the former Chief Scientist of AI at Microsoft, a Princeton professor, and the chief of equities at Citadel. The Caltech team was chosen as the first place winner based on the depth, rigor, and comprehensiveness of their analysis.