Qingqing Huang (黄清清)



I am a postdoc in EECS at UC Berkeley, in the research group led by Prof. Ben Recht.

Long ago, I was a graduate student in EECS at MIT, and my advisor was Prof. Munther Dahleh.

qqh@mit.edu Google Scholar Resume

Research interest

  • After my PhD, I continue to explore the two aspects of {robustness} and {dynamics} in learning, yet with a set of completely new questions from new perspectives. If I have to give it some tags, for now, my research interest lies in the intersection of machine learning, system identification, and robust control. It is evolving overtime as I adventure into this wonderland.
    I stay open and curious about ANY interesting questions in learning :)
  • During my PhD studies, my research interest lied in statistical learning theory, machine Learning, networked systems.
    Here is my research statement , and here is a set of slides that gives an overview of my thesis.

    In my PhD thesis, I focus on a set of statistical learning problems regarding mixture models.

    Mixture models (examples include Gaussian Mixtures (GMM), topic models, and Hidden Markov Models (HMM)) serve to model the scenario where the underlying mechanism of each observed data sample belongs to a finite number of different sources. It is a class of powerful models which finds application in a wide range of unsupervised learning tasks, such as speech recognition, document classification, super-resolution imaging, community detection, and low rank matrix recovery for recommendation tasks.

    The structural property of the distribution with the latent variable introduces non-convexity to the learning problem, making it much harder than the unstructured problems. To this end, I ask and attempt address three questions:

    • Can we efficiently learn the model parameters, assuming some non-degeneracy of the instances?
    • Can we achieve it with optimal sample complexity with fast algorithms?
    • Can we make the learning algorithms robust to model mis-specifications?

Papers

Statistical Learning Theory

(authors are ordered alphabetically for TCS papers)

Smart Grid

Misc

Research Experience

  • PostDoc in EECS, UC Berkeley (UCB), (2016 September - now) Advisor: Ben Recht
  • Graduate Student at Lab of Information and Decision Systems (LIDS) MIT, (2011 September - Now) Advisor: Munther Dahleh
  • Research Intern at Microsoft Research New England (MSR-NE), (2014 May - 2014 August) Mentor: Sham Kakade
  • Research Intern at Microsoft Research New England (MSR-NE), (2015 May - 2015 August) Mentor: Sham Kakade
  • Visiting Researcher at Baidu, Beijing, (2014 December - 2015 January) Host: Tong Zhang
  • Research Assistant at Wireless Communication Group, ECE, HKUST (2009 June - 2011 January) Advisor: Vincent K.N. Lau
  • UROP at Wireless Communication Group, ECE, HKUST (2008 June - 2008 August) Advisor: Roger Cheng

Education

  • Doctor in EECS, Massachusetts Institute of Technology (MIT), (2013 July - 2016 August)
  • Master in EECS, Massachusetts Institute of Technology (MIT), (2011 September - 2013 June)
  • Bachelor of Engineering in Electrical Engineering, Hong Kong University of Science and Technology (HKUST) , (2006 September - 2011 June)
  • Bachelor of Business Administration, Hong Kong University of Science and Technology (HKUST) , (2006 September - 2011 June)
  • The First High School of Changsha (長沙市第一中學), Hunan, China (2003 September - 2006 June)
  • No. 7 Middle School of Changsha (长沙市第七中学), Hunan, China (2000 September - 2003 June)
  • Yanwachi Primary School (砚瓦池小学), Changsha, Hunan, China (1994 September - 2000 June)

Teaching Experience

  • Instructor of Discrete Math in Women in Technology Program (2016 Summer)
    Summer program at MIT EECS
  • Teaching assistant of 6.UAR Prep for Undergrad Research (2015 Fall )
    Undergraduate level class at MIT
    Instructor: Prof.Anantha Chandrakasan
  • Teaching assistant of 6.207 Network Science (2014 Spring)
    Undergraduate level class at MIT
    Instructors: Prof.Munther Dahleh and Prof.Asuman Ozdaglar
  • Teaching assistant of 6.438 Algorithms for Inference (2013 Fall)
    Graduate level class at MIT
    Instructor: Prof.Devavrat Shah

Extracurricular

  • Co-chair of LIDS student conference 2016
    in charge of conference organization, website maintenance, coordination with invited plenary speakers and student speakers
  • Publication Chair of Graduate Student Association, MIT (2013 January - 2013 December)
    in charge of website maintenance, poster design for publicizing events
  • Co-chair of Graduate Women in Course 6 (GW6), MIT (2012 Janurary - 2012 December)
    in charge of organizing extra curricular activities for graduate women in EECS department of MIT
  • Software Engineer Intern at Yunzhou-Tech Company, China (2011 June - 2011 August)
    worked on navigation algorithm improvements for unmanned surface vehicles
  • IT Engineering at Kwong Wah Hospital, Hong Kong (Student Civic Fellow Program) (2011 January - 2011 May)
    Developed a web-based medical image archiving system
  • Project Assistant at Heep Hong Society, Hong Kong (2010 June - 2010 October)
    Collaborated to develop a computer-based learning package for autistic children