Vladimir Dvorkin

Vladimir Dvorkin

Postdoctoral Researcher

Massachusetts Institute of Technology

Biography

I am a postdoctoral researcher at the Massachusetts Institute of Technology, affiliated with MIT Energy Initiative and Laboratory for Information and Decision Systems. Before joining MIT, I pursued a PhD degree in electrical engineering at the Technical University of Denmark in 2017-2020. In 2019, I also visited the School of Industrial and Systems Engineering of Georgia Tech. In March 2021, I defended my thesis titled Stochastic and Private Energy System Optimization (video, slides). Through my PhD studies, I was most interested in decision-making models under uncertainty, in economics of uncertainty, and most recently in algorithmic privacy, all with applications to energy systems. Today, I broaden this portfolio towards certifying decisions under uncertainty (e.g., a priori performance guarantees for multi-stage stochastic programs), providing privacy guarantees for arbitrary convex optimization programs (moving from linear to quadratic and semidefinite private programming), and developing optimization algorithms to assist machine learning tasks. In 2021, I co-organized enOPTIMAL seminar series to promote research exchange during the pandemic.

Resumé

Interests
  • Stochastic optimization
  • Algorithmic privacy
  • Energy economics
Education
  • MSc+PhD in Electrical Engineering, 2021

    Technical University of Denmark

  • MSc in Economics, 2014

    Higher School of Economics (Russia)

  • BSc in Electrical Engineering, 2012

    Moscow Power Engineering Institute (Russia)

News

Jun 2022 Presented our work Multi-Stage Linear Decision Rules for Stochastic Control of Natural Gas Networks with Linepack at the XXII Power System Computational Conference in Porto (slides)

Jun 2022 I am glad to share our new preprint Multi-Stage Investment Decision Rules for Power Systems with Performance Guarantees (paper, data and code, slides)

May 2022 Presented Privacy-Preserving Perturbation of Convex Optimization Programs at the casual seminar series Stats&LIDS Tea Talks at MIT (slides)

Apr 2022 I won a postdoctoral fellowship co-funded by Marie Skłodowska-Curie Actions and Iberdrola Group to research optimization, learning and privacy for future energy systems at MIT Energy initiative.

Mar 2022 I recieved 2021 Best Paper Award for Differentially Private Optimal Power Flow for Distribution Grids and 2021 Outstanding Reviewer Award from IEEE Transactions on Power Systems.

Mar 2022 We are launching the Spring 2022 edition of the enOPTIMAL: Energy, Optimization and Learning online seminar series (see speakers and seminar logistics here).

Feb 2022 Our paper Multi-Stage Linear Decision Rules for Stochastic Control of Natural Gas Networks with Linepack is accepted at the XXII Power System Computational Conference in Porto! (paper, code)

Oct 2021 Happy to announce the Fall 2021 enOPTIMAL Seminar Series! Check the new lineup here.

Jun 2021 Our paper Stochastic Control and Pricing for Natural Gas Networks is accepted for publication in the IEEE Transactions on Control of Network Systems (CONES). (paper, Anubhav’s talk).

Jun 2021 Presented our paper Differentially Private Optimal Power Flow for Distribution Grids at the PowerTech Conference in Madrid (paper, video).

Jun 2021 Presented our work Linear Decision Rules with Performance Guarantees for Scalable Multi-Stage Generation Planning at the Federal Energy Regulatory Commission workshop (slides, event).

Apr 2021 We are launching a new online seminar series enOPTIMAL: Energy, Optimization and Learning. Many thanks to all speakers who agreed to kick off this seminar series.

Mar 2021 Defended my Ph.D. thesis titled “Stochastic and Private Energy System Optimization” on Zoom. Thank you all who tuned in and supported me today! (thesis, video, slides).

Featured Publications

Browse all publications here or on Google Scholar.

(2022). Multi-Stage Linear Decision Rules for Stochastic Control of Natural Gas Networks with Linepack. XXII Power System Computational Conference, forthcoming.

Cite arXiv GitHub

(2021). Stochastic Control and Pricing for Natural Gas Networks. IEEE Transactions on Control of Network Systems, forthcoming.

Cite arXiv GitHub

(2020). Differentially Private Distributed Optimal Power Flow. 59th IEEE Conference on Decision and Control (CDC), pp. 2092-2097.

Cite arXiv Published Version GitHub

(2020). Differentially Private Optimal Power Flow for Distribution Grids. IEEE Transactions on Power Systems, forthcoming.

Cite arXiv Published Version GitHub

(2019). Electricity Market Equilibrium under Information Asymmetry. Operations Research Letters, 47(6), pp. 521-526.

Cite arXiv Published Version GirHub