About Me
I am a PhD candidate in the Computer Learning Research Center at Royal Holloway University of London working with Professor Chris Watkins.
Prior to this I was a research associate in VIDA Lab at NYU Tandon School of Engineering where I worked with Professor Juliana Freire on DARPA Memex and D3M projects. Before joining NYU, I did a summer internship with Microsoft Research and Cloud AI Group in Redmond.
Research
My areas of interest include machine learning, deep learning, reinforcement learning, data mining, distributed computing and data visualization especially applying them to automation of machine learning (AutoML), information retrieval and applications for social good. Most recently I worked on automated generation of data mining pipelines, for the DARPA D3M project, through sequence modeling using a deep neural network and Monte Carlo Tree Search (MCTS)
Top News
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My poster, AlphaD3M: Machine Learning Pipeline Synthesis, has been selected for presentation at the Deep Learning and Reinforcement Learning Summer School 2019.
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Our paper, Automatic Machine Learning by Pipeline Synthesis using Model-Based Reinforcement Learning and a Grammar, has been accepted to AutoML workshop at ICML 2019.
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Our poster, Agent-based Modelling of Collective Algorithms Implementable by T Cells, has been selected for presentation at the Mathematics in Life Sciences (MiLS) Meeting on Modelling Challenges in Cancer and Immunology at King's College London this summer.
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Selected for and will be attending the Deep Learning and Reinforcement Learning Summer School 2019 in Edmonton, Alberta, Canada this summer.
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Co-chairing ECML PKDD 2019 workshop on Decentralized Machine Learning at the Edge.
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Our paper, AlphaD3M: Machine Learning Pipeline Synthesis, has been accepted to AutoML workshop at ICML 2018
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Co-chairing ECML PKDD 2018 workshop on Decentralized Machine Learning at the Edge.
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Received 3rd Prize (among 70 teams) at NYU Tandon School of Engineering Research Expo 2017 for presenting our DARPA Memex work. It was covered by the local Technical.ly, Brooklyn.
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Mentored the 2nd Place winning team in End Human Trafficking Hackathon, 2016, organized by Manhattan District Attorney’s (DANY) office in partnership with Cornell Tech.
Selected Publications
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AlphaD3M: Machine Learning Pipeline Synthesis
Iddo Drori, Yamuna Krishnamurthy, Remi Rampin, Raoni de Paula Lourenco, Jorge Piazentin Ono, Kyunghyun Cho, Claudio Silva, Juliana Freire.
International Workshop on Automatic Machine Learning 2018, International Conference on Machine Learning (ICML), Stockholm, July 2018
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Interactive Exploration for Domain Discovery on the Web
Yamuna Krishnamurthy, Kien Pham, Aecio Santos, Juliana Freire.
Workshop on Interactive Data Exploration and Analytics (IDEA) 2016, Knowledge Discovery and Data Mining (KDD), San Francisco, Aug 2016
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Bayesian Optimal Active Search and Surveying
Roman Garnett, Yamuna Krishnamurthy, Xuehan Xiong, Jeff Schneider, Richard P Mann.
29th International Conference on Machine Learning (ICML) 2012, Madison, WI, USA, June 2012
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Bayesian Optimal Active Search on Graphs
Roman Garnett, Yamuna Krishnamurthy, Donghan Wang, Jeff Schneider, and Richard Mann
Ninth Workshop on Mining and Learning with Graphs (MLG ’11), Knowledge Discovery and Data Mining (KDD), San Diego, Aug 2011