Optimization
Efficient solutions to large-scale problems.
Much of MERL's research activity involves formulating scientific and engineering problems as optimizations, which can be solved in an efficient way. We have developed fundamental algorithms to better solve classic problems, such as quadratic programs and minimum-cost paths. Our work also involves developing theoretical bounds to understand performance limits.
Quick Links
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Researchers
Daniel N.
Nikovski
Stefano
Di Cairano
Toshiaki
Koike-Akino
Arvind
Raghunathan
Philip V.
Orlik
Rien
Quirynen
Mouhacine
Benosman
Ankush
Chakrabarty
Ye
Wang
Kieran
Parsons
Matthew E.
Brand
Petros T.
Boufounos
Christopher R.
Laughman
Karl
Berntorp
Hassan
Mansour
Scott A.
Bortoff
Devesh K.
Jha
Yebin
Wang
Jianlin
Guo
Saleh
Nabi
Pu
(Perry)
WangHongbo
Sun
Kyeong Jin
(K.J.)
KimDiego
Romeres
Dehong
Liu
Yanting
Ma
Hongtao
Qiao
Rui
Ma
Jinyun
Zhang
Chungwei
Lin
Avishai
Weiss
William S.
Yerazunis
Marcus
Greiff
Marcel
Menner
Gordon
Wichern
Jose
Amaya
Abraham M.
Goldsmith
Jay
Thornton
Abraham P.
Vinod
Bingnan
Wang
Jing
Zhang
Joshua
Rapp
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Awards
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AWARD Outstanding Presentation Award at the 28th Conference of Information Processing Society of Japan/Consumer Device & Systems Date: October 20, 2020
Awarded to: Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik, Hiroshi Mineno
MERL Contacts: Jianlin Guo; Philip V. Orlik
Research Areas: Communications, Optimization, Signal ProcessingBrief- MELCO and MERL researchers have won "Outstanding Presentation Award" at 28th Conference of Information Processing Society of Japan (IPSJ)/Consumer Device & Systems held on September 29-30, 2020. The paper titled "IEEE 802.19.3 Standardization for Coexistence of IEEE 802.11ah and IEEE 802.15.4g Systems in Sub-1 GHz Frequency Bands" reports IEEE 802.19.3 standard development on coexistence between IEEE 802.11ah and IEEE 802.15.4g systems in the Sub-1 GHz frequency bands. MERL and MELCO have been leading this standard development and made major technical contributions, which propose methods to mitigate interference in smart meter systems. The authors are Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik and Hiroshi Mineno.
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AWARD Best conference paper of IEEE PES-GM 2020 Date: June 18, 2020
Awarded to: Tong Huang, Hongbo Sun, K.J. Kim, Daniel Nikovski, Le Xie
MERL Contacts: Kyeong Jin (K.J.) Kim; Daniel N. Nikovski; Hongbo Sun
Research Areas: Data Analytics, Electric Systems, OptimizationBrief- A paper on A Holistic Framework for Parameter Coordination of Interconnected Microgrids Against Natural Disasters, written by Tong Huang, a former MERL intern from Texas A&M University, has been selected as one of the Best Conference Papers at the 2020 Power and Energy Society General Meeting (PES-GM). IEEE PES-GM is the flagship conference for the IEEE Power and Energy Society. The work was done in collaboration with Hongbo Sun, K. J. Kim, and Daniel Nikovski from MERL, and Tong's advisor, Prof. Le Xie from Texas A&M University.
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News & Events
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NEWS Arvind Raghunathan's publication is Featured Article in the current issue of the INFORMS Journal on Computing Date: April 1, 2022
Where: INFORMS Journal on Computing (https://pubsonline.informs.org/journal/ijoc)
MERL Contact: Arvind Raghunathan
Research Areas: Artificial Intelligence, Machine Learning, OptimizationBrief- Arvind Raghunathan co-authored a publication titled "JANOS: An Integrated Predictive and Prescriptive Modeling Framework" which has been chosen as a Featured Article in the current issue of the INFORMS Journal on Computing. The article was co-authored with Prof. David Bergman, a collaborator of MERL and Teng Huang, a former MERL intern, among others.
The paper describes a new software tool, JANOS, that integrates predictive modeling and discrete optimization to assist decision making. Specifically, the proposed solver takes as input user-specified pretrained predictive models and formulates optimization models directly over those predictive models by embedding them within an optimization model through linear transformations.
- Arvind Raghunathan co-authored a publication titled "JANOS: An Integrated Predictive and Prescriptive Modeling Framework" which has been chosen as a Featured Article in the current issue of the INFORMS Journal on Computing. The article was co-authored with Prof. David Bergman, a collaborator of MERL and Teng Huang, a former MERL intern, among others.
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NEWS Toshiaki Koike-Akino gave an invited lecture to USPTO on advanced photonics Date: May 4, 2022
MERL Contact: Toshiaki Koike-Akino
Research Areas: Artificial Intelligence, Communications, Electronic and Photonic Devices, Machine Learning, Optimization, Signal ProcessingBrief- Toshiaki Koike-Akino gave an invited lecture on advanced photonic devices at the United States Patent and Trademark Office (USPTO) Technology Fair on May 4, 2022. Topics of the lecture included the recent progress of applied artificial intelligence (AI) technologies for optical systems, nano-photonic devices, and quantum technology. During the 2-hour interactive online presentation, he lectured to more than 200 patent examiner participants.
USPTO Tech Fair Organizer mentioned:
"Thank you very much for representing Advanced Photonic Devices at this year’s Technology Center 2800 Virtual Tech Fair held May 4th, 2022. Tech Fair is an important part of the United States Patent and Trademark Office’s Patent Examiner Technical Training Program (PETTP). Having a scientifically well-trained examiner workforce and ensuring the quality, consistency, and reliability of issued patents are top priorities at the USPTO. The PETTP is designed to achieve those priorities by giving examiners direct access to technical experts who are willing to share their knowledge about prior art and industry standards for both emerging and established technologies. Experts like yourself help to maintain our high quality of patent examination by keeping examiners updated on technologies and innovations pertinent to their field of examination.
We very much appreciate your efforts, time, and contributions."
- Toshiaki Koike-Akino gave an invited lecture on advanced photonic devices at the United States Patent and Trademark Office (USPTO) Technology Fair on May 4, 2022. Topics of the lecture included the recent progress of applied artificial intelligence (AI) technologies for optical systems, nano-photonic devices, and quantum technology. During the 2-hour interactive online presentation, he lectured to more than 200 patent examiner participants.
See All News & Events for Optimization -
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Research Highlights
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Internships
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CA1706: Perception-aware vehicle control
MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on planning and control algorithms accounting for perception of the uncertain surrounding environment. The ideal candidate is expected to be working towards a PhD with strong emphasis in control or planning algorithms, and to have interest and background in as many as possible of: predictive control algorithms for linear and nonlinear systems, stochastic constrained control, e.g., chance constraints, stochastic optimization, statistical estimation, perception system modeling, and vehicle modeling and control. Good programming skills in MATLAB, Python or C/C++ are required. The expected start of of the internship is in the late Spring/Early Summer 2022, for a duration of 3-6 months.
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MS1851: Dynamic Modeling and Control for Grid-Interactive Buildings
MERL is looking for a highly motivated and qualified candidate to work on modeling for smart sustainable buildings. The ideal candidate will have a strong understanding of modeling renewable energy sources, grid-interactive buildings, occupant behavior, and dynamical systems with expertise demonstrated via, e.g., peer-reviewed publications. Hands-on programming experience with Modelica is preferred. The minimum duration of the internship is 12 weeks; start time is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.
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CA1728: Safe data-driven control of dynamical systems under uncertainty
MERL is looking for a highly motivated individual to work on safe control of data-driven, uncertain, dynamical systems. The research will develop novel optimization and learning-based control algorithms to guarantee safety and performance in various industrial applications, including autonomous driving. The ideal candidate should have experience in either one or multiple of the following topics: optimal control under uncertainty, (robust and stochastic) model predictive control, (convex and non-convex) optimization, and (reinforcement and statistical) learning. Ph.D. students in engineering or mathematics with a focus on control, optimization, and learning are encouraged to apply. A successful internship will result in submission of relevant results to peer-reviewed conference proceedings and journals, and development of well-documented (Python/MATLAB) code for MERL. The expected duration of the internship is 3-6 months, and the start date is Summer 2022.
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Recent Publications
- "Safe multi-agent motion planning via filtered reinforcement learning", IEEE International Conference on Robotics and Automation (ICRA) 2022, May 2022.BibTeX TR2022-053 PDF Video
- @inproceedings{Vinod2022may,
- author = {Vinod, Abraham P. and Safaoui, Sleiman and Chakrabarty, Ankush and Quirynen, Rien and yoshikawa, nobuyuki and Di Cairano, Stefano},
- title = {Safe multi-agent motion planning via filtered reinforcement learning},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA) 2022},
- year = 2022,
- month = may,
- url = {https://www.merl.com/publications/TR2022-053}
- }
, - "Variational Quantum Compressed Sensing for Joint User and Channel State Acquisition in Grant-Free Device Access Systems", IEEE International Conference on Communications (ICC), May 2022.BibTeX TR2022-052 PDF Video Presentation
- @inproceedings{Liu2022may3,
- author = {Liu, Bryan and Koike-Akino, Toshiaki and Wang, Ye and Parsons, Kieran},
- title = {Variational Quantum Compressed Sensing for Joint User and Channel State Acquisition in Grant-Free Device Access Systems},
- booktitle = {IEEE International Conference on Communications (ICC)},
- year = 2022,
- month = may,
- url = {https://www.merl.com/publications/TR2022-052}
- }
, - "Semi-Persistent Scheduling Scheme for Low-Latency and High-Reliability Transmissions in Private 5G Networks", IEEE International Conference on Communications Workshops (ICC), May 2022.BibTeX TR2022-050 PDF
- @inproceedings{song2022may,
- author = {song, Hao and Kim, Kyeong Jin and Guo, Jianlin and Orlik, Philip V. and Parsons, Kieran},
- title = {Semi-Persistent Scheduling Scheme for Low-Latency and High-Reliability Transmissions in Private 5G Networks},
- booktitle = {IEEE International Conference on Communications Workshops (ICC)},
- year = 2022,
- month = may,
- url = {https://www.merl.com/publications/TR2022-050}
- }
, - "Global Phase Correction Improves Metalens Efficiency", Conference on Lasers and Electro-Optics (CLEO), May 2022.BibTeX TR2022-049 PDF
- @inproceedings{Zhu2022may,
- author = {Zhu, Dayu and Kojima, Keisuke and Koike-Akino, Toshiaki and Brand, Matthew E.},
- title = {Global Phase Correction Improves Metalens Efficiency},
- booktitle = {Conference on Lasers and Electro-Optics (CLEO)},
- year = 2022,
- month = may,
- url = {https://www.merl.com/publications/TR2022-049}
- }
, - "Application of Pontryagin’s Maximum Principle to Quantum Metrology in Dissipative Systems", Physical Reivew A, May 2022.BibTeX TR2022-048 PDF
- @article{Lin2022may,
- author = {Lin, Chungwei and Ma, Yanting and Sels, Dries},
- title = {Application of Pontryagin’s Maximum Principle to Quantum Metrology in Dissipative Systems},
- journal = {Physical Reivew A},
- year = 2022,
- month = may,
- url = {https://www.merl.com/publications/TR2022-048}
- }
, - "Finding the Right Deep Neural Network Model for Efficient Design of Tunable Nanophotonic Devices", Conference on Lasers and Electro-Optics (CLEO), May 2022.BibTeX TR2022-047 PDF Video Presentation
- @inproceedings{Jung2022may,
- author = {Jung, Minwoo and Kojima, Keisuke and Koike-Akino, Toshiaki and Wang, Ye and Zhu, Dayu and Brand, Matthew E.},
- title = {Finding the Right Deep Neural Network Model for Efficient Design of Tunable Nanophotonic Devices},
- booktitle = {Conference on Lasers and Electro-Optics (CLEO)},
- year = 2022,
- month = may,
- url = {https://www.merl.com/publications/TR2022-047}
- }
, - "AutoML Hyperparameter Tuning of Generative DNN Architecture for Nanophotonic Device Design", Conference on Lasers and Electro-Optics (CLEO), May 2022.BibTeX TR2022-046 PDF Presentation
- @inproceedings{Koike-Akino2022may3,
- author = {Koike-Akino, Toshiaki and Kojima, Keisuke and Wang, Ye},
- title = {AutoML Hyperparameter Tuning of Generative DNN Architecture for Nanophotonic Device Design},
- booktitle = {Conference on Lasers and Electro-Optics (CLEO)},
- year = 2022,
- month = may,
- url = {https://www.merl.com/publications/TR2022-046}
- }
, - "Optimal Dynamic Transmission Scheduling for Wireless Networked Control Systems", IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, May 2022.BibTeX TR2022-043 PDF
- @article{Ma2022may,
- author = {Ma, Yehan and Guo, Jianlin and Wang, Yebin and Chakrabarty, Ankush and Ahn, Heejin and Orlik, Philip V. and Guan, Xinping and Lu, Chenyang},
- title = {Optimal Dynamic Transmission Scheduling for Wireless Networked Control Systems},
- journal = {IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY},
- year = 2022,
- month = may,
- url = {https://www.merl.com/publications/TR2022-043}
- }
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- "Safe multi-agent motion planning via filtered reinforcement learning", IEEE International Conference on Robotics and Automation (ICRA) 2022, May 2022.
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Videos
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Toshiaki Koike-Akino Gives Seminar Talk at IEEE Boston Photonics
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[MERL Seminar Series Spring 2022] RLMPC: An Ideal Combination of Formal Optimal Control and Reinforcement Learning?
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[MERL Seminar Series Spring 2022] Extreme optics design as a large-scale optimization problem
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[MERL Seminar Series 2021] Integration of Analytics Techniques for Algorithmic Sports Betting
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Multiview Sensing with Unknown Permutations: An Optimal Transport Approach
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Imaging for inverse scattering in Reflection Tomography
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Electric Satellite Station Keeping, Attitude Control, and Momentum Management by MPC
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Polar Coding with Chemical Reaction Networks for Molecular Communications
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EMI reduction in PWM inverters using adaptive frequency modulated carriers
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Globally Optimal Power Flow
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Five Axis Additive Manufacturing
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Fast Pattern Search in Big Data
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Software Downloads