Laleh Jalali

I am passionate about creating innovative ideas, translating them into concepts, and executing on them in the context of a project. Currently, I am Research Scientist at Hitachi America, R&D Healthcare Big Data Lab (BDL) focusing on Big Data Analytics in Healthcare. With large amounts of data being generated from all segments of healthcare, from image data coming from MRI machines, to clinical data from Electronic Health Records; all the way to personal health data from wearable devices, I am looking at harnessing all this data to develop advanced analytics technologies to help improve outcomes and reduce costs across the healthcare continuum.

Before BDL, I was Computer Science PhD student at University of California, Irvine and a member of Social Life Networks lab. I developed EventMiner --a comprehensive knowledge-based event mining framework for analyzing heterogeneous big data. In this framework one utilizes different event relationship operators to formulate complex events and compute co-occurrences among them using available data. These co-occurrences are used to formulate potential hypotheses as contextual knowledge, and must then be verified using other set of data. The framework allows ingestion of multiple event streams and can be used for exploring either in data driven mode, for visualizing and finding potential hypotheses, or for formulating a hypothesis by using hypothesis-driven approach to verify or refute it. This framework extends traditional complex event processing significantly by including multiple event streams, point and interval events, event attributes, and novel event mining algorithms. By utilizing EventMiner, a domain expert can iteratively perform event mining, create hypotheses by formulating complex inter-relations among events based on either domain knowledge or event mining results, and verify those hypotheses.