daruki's profile

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Research Engineer, Machine Learning, Google, Mountain View, California, USA
Academic Profile
Academic Summary: 

I did my Ph.D. in School of Computing at the University of Utah and a was a graduate member of The Data Group. I worked under supervision of Suresh Venkatasubramanian. In addition, I was fortunate to collaborate with Jeff M. Phillips, Justin Thaler, and Aditya Bhaskara.

I was a visiting research scholar at Simons Institute for the Theory of Computing at University of Berkeley for the research program on Theoretical Foundations of Big Data Analysis during 2013-2014. I was also a research intern at Search and Content Science Team at Yahoo Research with Kostas Tsioutsiouliklis and Stergios Stergiou during summer 2016.

I did my Bachelor on Computer Science at Sharif University of Technology in Iran, where I had Dr. Ebadollah S. Mahmoodian as my advisor. As my B.S. thesis, I worked mainly on Algorithms on Massive Graphs and Complex Networks.

Research Sketch and Projects (Ph.D.)

I successfully defended my PhD dissertation titled "Sublinear Algorithms for Massive Data Computations: Streaming and Coresets" on May 2017.

My PhD research was focused on designing algorithms for problems motivated from massive data analysis: focusing on resources like time, space, and communication, as well as accuracy. I also studied algorithmic design techniques in modern data models and explored how randomization and approximation can be utilized as a powerful resource for developing beautiful, simple, and efficient algorithms with provable theoretical and performance guarantees.

In particular, I focused on research problems in the general area of sublinear algorithms such as streaming, core sets and sublinear verification with a special interest in problems arising from data analysis including data summarization, clustering, matrix problems and massive graphs.

About Me: 

I have joined Google, as of May 2019. I work in both research and applied aspects of Deep Learning, currently more focused on Language and Vision Models.

My current work is focused on Multi-Modal Vision+Language Models and Representation Learning. This line of research can be potentially applied to improve Search Ranking by bringing Query/Document/Image Understanding together. I am also interested in recent research advances in Graph Representation Learning, where we utilize the graph structure on the data as extra information in training deep models.

I have also served as area chair for Women in Machine Learning (WiML) workshop at NeurIPS19.

Before Google, I was an Applied Research Scientist at Data Science and Machine Learning Team at Expedia, where I worked on designing scalable optimization algorithms and machine learning models for online auctions and search ranking.

Current Status: 

Member since
May 2011
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