Ming Jin

I am a graduate student in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley advised by Prof. Costas Spanos. I also work closely with Prof. Javad Lavaei on power systems.

I hold a research affiliate position at the Energy Technologies Area of the Lawrence Berkeley National Laboratory (LBNL), working with Dr. Wei Feng and Dr. Chris Marnay.

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My research focuses on cyber-physical energy systems, by employing modeling, optimization, and control theories to design new algorithms and mechanisms for emerging technologies based on the internet-of-things (IoT), mobile sensing, and data mining, in order to facilitate the transition into an energy-efficient and system-wide resilient urban ecosystem.

To this end, I develop novel sensing paradigms for indoor environment monitoring and demand-based, occupancy-aware controls, as well as modeling and incentivization of humans to induce desirable behaviors (e.g., energy saving, demand response).

I also explore the design and operation of community-based micro-grid in support of the mega-grid, which exploits the flexibility of demands, as well as the efficiency from both thermal and electricity energy provision and shared distributed energy resources (DERs) and storages, to address the grand challenge of 20% renewable energy by 2020.

Selected Awards

  • Awards of Student Technology Fund Initiative (2016,2017)
  • Best paper award at MobiQuitous (2016)
  • Finalist for Samsung Fellowship Award (2016)
  • Best paper award at Ubicomm for Mobile Ubiquitous Computing (2015)
  • Top 5 team in Microsoft Indoor Localization Competition, Seattle, Washington (2015)
  • Academic excellence award, first class honors, Dean’s List, 2008-2012
  • ECE Department Scholarship, 2008-2012
  • School of Engineering Scholarship, 2008-2012
  • University Scholarship, 2008-2012

News

June 2017

IEEE Spectrum featured an article What Does Your Smart Meter Know About You? on my recent work Virtual occupancy sensing: Using smart meters to indicate your presence

June 2017

CO2Meter.com featured an article CO2 Sensor Occupancy Detection on my work Sensing by proxy: Occupancy detection based on indoor CO2 concentration (best paper award)

June 2017

Paper "Inverse reinforcement learning via deep Gaussian Process" (paper | code | supplementary) accepted for oral presentation in UAI 2017, Sydney, Australia.

June 2017

Our proposal for "Social Game for Smart Building Energy Efficiency" accepted (Total: $14,000, duration 1 year, with Ioannis Konstantakopoulos)!

May 2017

Three papers "Microgrid to enable optimal distributed energy retail and end-user demand response", "A Robust Utility Learning Framework via Inverse Optimization", and "Measuring fine-grained Metro interchange time via smartphones" accepted in Applied Energy, TCST, and Transportation Research Part C.

May 2017

Talk at ACC, Seattle, on Leveraging correlations in utility learning (slides)

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