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Dorsa Ziaei

“In my research, I study the dynamics involved in Big Data technologies to facilitate mining big data in different applications and solve classes of interdisciplinary problems, like healthcare analytics, with focus on machine learning.”

 

Degree Program: Computer Science (Ph.D.)

Faculty Advisor: Dr. Yelena Yesha

Thesis/research topic:
In my research, I study the dynamics involved in Big Data technologies to facilitate mining big data in different applications and solve classes of interdisciplinary problems, like healthcare analytics, with focus on machine learning. Due to the background of my research on infectious diseases, a potential problem to be focused on, is an emerging field “Digital Epidemiology” which is concerned about the application of digital sources of data for improving public health. I would like to study the content of data of various internet resources and propose and design infrastructure algorithms that could be use to improve medical big data analysis.

Undergraduate Study:
Computer Science, 2005, BA, Tehran Central Azad University

Previous Graduate Study:
Computer Science, 2009, Ms, Science & Research University in Tehran

Briefly describe your graduate research and its purposes/applications.
My motivation for my PhD dissertation is discovering new methodologies and approaches to analyze and exploit unstructured data of internet, study its complexity and size in order to design and implement novel tools and algorithms which facilitate mining data for Big Data applications, since Big Data analytics helps toward data-driven decisions.

Have you worked on any specific research projects that you would like to highlight?
My contribution in proposals and new projects is mainly to propose techniques and algorithms to relate data science and real-time problem statements. I am mostly interested in machine leaning and natural language processing tools to do data mining and extract structured knowledge from unstructured text. As for the social media analysis, I proposed and implemented algorithms to do classification and clustering using various machine learning techniques such as neural networks, regression. As for the image and satellite data I implemented deep network approaches to extract information from images. I focused on text analysis in different aspects such as topic modeling of health related texts, POS tagging, sentiment analysis and query models for filtering and extracting information.

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