Masdar Institute of Science and Technology, located in Abu Dhabi, United Arab Emirates (UAE), is a private, not-for-profit, independent, graduate-level, research-driven institute developed with the support and cooperation of Massachusetts Institute of Technology (MIT). The goal of the Institute is to develop, over a period of years, indigenous R&D capacity in Abu Dhabi, addressing issues of importance to the region in critical areas such as: renewable energy, sustainability, environment, water resources and microelectronics. The Institute offers graduate degree programs (MSc & PhD) in science and engineering disciplines with a focus on advanced energy and sustainable technologies (http://www.masdar.ac.ae and http://web.mit.edu/mit-mi-cp/).

Position: We are looking for a post-doctoral researcher to work on approximation algorithms and algorithmic mechanism design issues with special focus on applications in electricity markets and energy exchange in smart grids. The initial appointment will be for 1 year but it can be extended up to 2 years depending on the availability of funding and the candidate’s performance.

Package: A highly competitive non-taxable (there is “no” income tax in the UAE) salary package (basic salary + housing allowance) of USD 70,000 to USD 75,000 per annum will be offered as well as provision of health insurance and an annual two-way flight ticket to the candidate’s home country.

Selection criteria: The applicant should meet the following criteria:

• PhD in Computer Science, Computer Engineering, Information Technology, Mathematics, Operations Research, or a related discipline from a reputable university. (Candidates who have submitted their PhD thesis are also welcome.)
• Strong background in at least one of the following topics: algorithmic game theory, combinatorial optimization, mathematical programming, approximation algorithms.
• Good research experience and published at least 3 full research papers (excluding posters) in reputable international conferences/journals.
• Self-motivated and able to work independently.
• Familiarity with electricity markets and smart grids is a plus.

How to apply: Interested candidates should send their resume and a statement of present/past research (not exceeding 3 pages) to Drs. Khaled Elbassioni and Sid Chi-Kin Chau (email: kelbassioni@masdar.ac.ae, ckchau@masdar.ac.ae). Initial screening of applications will begin immediately and the positions will remain open until filled.

Masdar Institute offers an Interdisciplinary Doctoral Degree Program(IDDP) for the Doctor of Philosophy (PhD) degree.

All students granted admissions will be provided full financial aid and access to our world-class facilities as well as the opportunity to work as part-time research assistants during their studies. The financial aid includes 100% tuition fee scholarship, textbooks, laptop, medical insurance, housing, travel expenses, and a cost of living allowance.

MIT is a primary partner and stakeholder in the creation of Masdar Institute. MIT’s involvement in this program enables Masdar Institute doctoral candidates to spend up to 2 semesters at MIT taking courses (maximum of 3 courses per semester) on campus. This creates synergy and collaboration between the research agendas of both Institutes.

Appears as an op-ed on the National

Imagine you are at a ski resort, but don’t have any skiing gear. You can rent or buy it, but which should you do? The answer hinges on how much you’re likely to ski in the future. But you don’t yet know that, so how do you decide? This is not just an innocuous problem. We face many similar decisions that depend on unknowable information about the future. How much stock should I buy to satisfy future demand? How much should I save to support my retirement? Computer systems are teeming with similar so-called “online problems”, such as deciding which data to store in a form that can be quickly accessed, and when to send data into a network.

They do it using “algorithms” – sets of rules and instructions that break down how a computer is going to set about a particular task. And some of these algorithms are inspired by studying puzzles like the ski- rental problem. Algorithms can also cope with increasing complexity. Do you like solving puzzles such as Sudoku or the Rubik’s cube, but are getting tired of the typical 9×9 Sudoku and 3x3x3 Rubik’s cube? How about solving a super-sized 16×16 Sudoku or a 6x6x6 Rubik’s cube?

While puzzles of such sizes stretch human capabilities, computers can breeze through them with just a bit more computing power. The amount of extra processing power required isn’t necessarily linear, though – doubling the size of a puzzle can require a million- times more computational grunt. Indeed, there are tons of problems, from puzzles to practical applications, which steadfastly resist computer scientists’ attempts to find an efficient algorithm. Some of these are problems that on the face of it don’t seem that hard at all – how to optimally pack a knapsack with any set of different sized objects, for example, or how to find the shortest cycle route on a map – can actually be extremely tricky, to the extent that finding the best solution requires an absurd or impractical amount of computing power.

In these cases, the answer is sometimes to look for a solution that is “good enough”, rather than necessarily the best. It can be the case that an algorithm produces outcomes approximately close to the best, while using far less computing power than the dead-accurate alternative.

All these algorithms underpin the information economy on which we all depend, making information processing faster and more cost-effective. They power our gadgets, which use ingenious algorithms that continuously optimize the quality of their graphics and speed up processing time.

And they can help us with the new challenges of sustainability. How do we balance energy supplies and demands for an uncertain future? How do allocate scarce resources effectively, despite the growing complexity? One such problem we are working on at the Masdar Institute is how to efficiently regulate power generation in the presence of an unsteady renewable energy supply, such as wind or solar.

We are designing algorithms that can determine when the backup power supply – a traditional power plant – should be turned on to meet a shortage of energy from a renewable source, in real-time. The result, we hope, will be a more efficient and reliable renewable energy-powered electricity grid – essential if Abu Dhabi is to meet its target of getting seven per cent of its power from renewable sources by 2030.

Dr Sid Chi-Kin Chau is an assistant professor of computing and information science at the Masdar Institute.

Microgrids are an emerging paradigm of future electric power systems that can utilize both distributed and centralized generations, in particular, due to the increasingly more integration of local renewable energy sources (such as wind farms) and the use of co-generation (i.e., to supply both electricity and heat).

In our recent paper, we study online algorithms for the micro-grid generation scheduling problem with intermittent renewable energy sources and co-generation, in order to maximize the cost-savings with local generation. We propose a class of competitive online algorithms. Under certain settings, we show that our online algorithms achieve the best competitive ratio of all deterministic online algorithms. We also extend our algorithms to intelligently leverage on limited prediction of the future, such as near-term demand or wind forecast. By extensive empirical evaluation using real-world traces, we show that our proposed algorithms can achieve near-offline-optimal performance.

Check out our preprint.

Lian Lu, Jinlong Tu, Chi-Kin Chau, Minghua Chen and Xiaojun Lin, “Online Energy Generation Scheduling for Microgrids with Intermittent Energy Sources and Co-Generation”, accepted to ACM Annual Conference of the Special Interest Group on Computer Systems Performance Evaluation (SIGMETRICS), 2013. (Acceptance rate: 27/196=13.7%)

Call for Papers: ACM e-Energy 2013

http://conferences.sigcomm.org/eenergy/2013/

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Date and location:
May 21-24 2013, Berkeley CA

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Computing and communication technologies impact energy systems in two distinct ways. The exponential growth in deployment of these technologies has made them large-scale energy consumers. Therefore, new architectures, technologies and systems are being developed and deployed to make computing and networked system more energy efficient. Additionally, and perhaps more importantly, these technologies are at the center of the on-going revolution in next-generation ‘smart’ and sustainable energy systems. They measure, monitor and control energy systems such as the smart grid; inform and shape human demand; aid in the prediction, deployment, storage and control of energy resources; and determine how utilities, generators, regulators, and consumers measure, analyze, and collectively control system elements.

The fourth International Conference on Future Energy Systems (ACM e-Energy), to be held in Berkeley, CA in May 2013, aims to be the premier venue for researchers working in the broad areas of computing and communication for smart energy systems (including the smart grid), and in energy-efficient computing and communication systems. By bringing together researchers in a high-quality single-track conference with significant opportunities for individual and small-group interaction, it will serve as a major forum for presentations and discussions that will shape the future of this area.

We solicit high-quality papers in the area of computing and communication for the Smart Grid and energy-efficient computing and communications. We welcome submissions describing theoretical advances as well as system design, implementation and experimentation. ACM e-Energy is committed to a fair, timely, and thorough review process providing authors of submitted papers with sound and detailed feedback.

Relevant topics for the conference include, but are not limited to the following:

• Advances in monitoring and control of smart homes and buildings
• Sensing, monitoring, control, and management of energy systems
• Energy-efficient computing and communication, including energy-efficient data centers
• The impact of storage integration on the smart grid
• Electric Vehicle monitoring and control
• Distribution and transmission network control techniques
• Microgrid and distributed generation management and control
• Modeling, control, and architectures for renewable energy generation resources
• Smart grid communication architectures and protocols
• Privacy and security of smart grid infrastructure
• Innovative pricing and incentives for demand-side management
• Novel technologies to enhance reliability and robustness of energy systems
• HCI for energy monitoring, management, and awareness
• User studies and behavioral change enabled by computing and communication technologies
• Data analytics for the smart grid and energy-efficient systems

Full submission details can be found at the conference website:

http://conferences.sigcomm.org/eenergy/2013/

Important Dates:

• January 15, 2013 (11:59:59 PM, PST): paper registration deadline
• January 22, 2013 (11:59:59 PM, PST): paper submission deadline
• March 20, 2013: Author notification
• April 20, 2013: Camera ready papers due
• May 21-24 2013, Berkeley CA: 2013 e-Energy conference