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15 Apr 2014

Hiring Research Engineer

Posted by Sid C-K Chau.

We are looking for a research engineer to work on implementing a sensor network testbed for urban environmental monitoring. The initial appointment will be for 1 year, but the position may be extended up to 3 years, depending on the candidate’s performance.

Package: A highly competitive, non-taxable (there is no income tax in the UAE) salary package (basic salary + housing allowance) 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:

  • A Bachelor’s degree in Computer Science or Computer Engineering, from a reputable university. (Candidates who have Master’s degrees or related research experience are preferred).
  • Good knowledge of programming with wireless sensor and embedded systems (e.g., Arduino).
  • Self-motivated and able to work independently.

How to Apply: Interested candidates should send their resumes and statements of present/past research (not to exceed 3 pages), to Dr. Sid Chi-Kin Chau (sidckchau(at), with the “Subject” line: “Research Engineer 2014.” Initial screening of applications will begin immediately and the position will remain open until filled.

23 Aug 2013

Combinatorial Power Allocation in AC Electrical Systems

Posted by Sid C-K Chau.

9 Mar 2013

Ph.D. Positions Available

Posted by Sid C-K Chau.

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.

22 Feb 2013

From Solving Puzzles to Smart Grid

Posted by Sid C-K Chau.

The National

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.

8 Feb 2013

Online Generation Scheduling for Microgrids

Posted by Sid C-K Chau.

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%)