The Smart Sustainability Research Group at Masdar Institute, led by Sid Chi-Kin Chau, researches in computing algorithms, systems and data analytics for smartening sustainable energy systems.




 

News


 Finalist for 1 Million Prize Drones for Good Award 2017: IntelliDrones project


 New paper appears in IEEE Transactions on Intelligent Transportation Systems:

“Drive Mode Optimization and Path Planning for Plug-in Hybrid Electric Vehicles”

 New papers appear in IEEE Transactions on Smart Grid:

“Efficient Algorithm for Scalable Event-based Demand Response Management in Microgrids”

“Cost Minimizing Online Algorithms for Energy Storage Management with Worst-case Guarantee”

 New paper appears in IEEE Transactions on Control of Network Systems:

“Optimal Power Flow with Inelastic Demands for Demand Response in Radial Distribution Networks”


 New papers appear in ACM e-Energy 2016:

“Fuel Minimization of Plug-in Hybrid Electric Vehicles by Optimizing Drive Mode Selection”

“Online Microgrid Energy Generation Scheduling Revisited: The Benefits of Randomization and Interval Prediction” [Runner-up for the best paper award]


 New paper appears in ACM Transactions on Economics and Computation:

“Truthful Mechanisms for Combinatorial Allocation of Electric Power in Alternating Current Electric Systems”

 New paper appears in IEEE Transactions on Mobile Computing:

“Effective Static and Adaptive Carrier Sensing for Dense Wireless CSMA Networks”

 New paper appears in IEEE/ACM Transactions on Networking:

“Online Algorithms for Information Aggregation from Distributed and Correlated Sources”


 Grant Awarded: We are awarded a Masdar-Institute/MIT Flagship Research Project on Urban Energy and Micro-climate Monitoring and Modelling, which aims to develop a framework for monitoring, modeling, and ultimately manipulating urban micro-climate phenomena in Abu Dhabi, such as urban heat island effect, climate change, local wind pattern, solar shading.


 Recruiting: We are looking for PhD/MSc students. Apply now

All students granted admissions will be provided full financial aid, including 100% tuition fee scholarship, textbooks, laptop, medical insurance, housing, travel expenses, and a cost of living allowance.

Note: 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 on campus.

About


 

The cumulative CO2 emission since Industrial Revolution has reached 1,100 billion tons. There will be 3,000 billion tons more of CO2 in the next 75-100 years, if we continue to consume fossil fuels at the current pace. Meanwhile, the Earth's average surface temperature rose by 0.74°C over the last century. It is projected to rise by further 3-5°C in the next century.

While wide-spread consumption of energy enables a decent standard of living, it also creates a crisis for our future generations. There are pressing challenges of sustainability that we ought to tackle immediately.

“Sustainability”, the notion of how we cope with depleting resources and galloping demands, is becoming a critical research topic and has far-reaching ramifications for our society. To address sustainability, rather than by relying on new resources or suppressing demands, a more vital approach is to intelligently optimize and balance the matching processes between resources and demands to reach long-term stability, which can be empowered by computing and information technology.

At Smart Sustainability Research Group, we believe that an integrated network-centric view on optimizing and smartening the major energy-using sectors — transportation, buildings, electricity and industry - can provide a viable solution for improving sustainability. Check out our research projects for more details.



Research


 

Our research aims to design and develop viable practical solutions of smart sustainable systems, particularly in the areas of smart buildings, smart grid and intelligent vehicles.


Research in Smart Grid



 

Smart Grid Algorithms and Optimization – Nowadays, a large portion of electrical energy is generated from fossil fuels, which contributes to global climate change (e.g., 0.65 of electricity was generated from fossil fuels in the US). Reducing the reliance on fossil fuels and increasing the adoption of renewable energy can effectively enhance sustainability.

We explore the fundamental aspects of computational algorithms for solving the critical problems of smart grid, such as designing appropriate mechanisms for power allocation and demand response management. We provide computationally effective optimization algorithms in the related management and decision-making processes.



 

Efficient Combinatorial Power Allocation – Electrical networks are governed by unique non-linear operating constraints involving complex numbers to represent time-varying quantities like alternating-current power and voltage. Although combinatorial allocation mechanisms involving real-valued resources have been well-studied in many other systems, complex-valued resources exhibit very different characteristics. Our work reveals new ideas to tackle complex-valued combinatorial resource allocation problems, opening up new frontiers in computer science and electrical power engineering.


 Paper appears in ACM Trans. Economics and Computation

“Truthful Mechanisms for Combinatorial Allocation of Electric Power in Alternating Current Electric Systems for Smart Grid”


 Paper appears in IEEE Trans. Smart Grid

“Efficient Algorithm for Scalable Event-based Demand Response Management in Microgrids”


 Paper appears in IEEE Trans. Control of Network System

“Optimal Power Flow with Inelastic Demands for Demand Response in Radial Networks”




 

Real-time Microgrid Management – Microgrids are a new kind of autonomous power systems with distributed energy generations in the era of renewable energy. Uncertainty abounds in microgrids due to dynamic demands and renewable energy generation. Reliably operation of a microgrid requires careful design of its control strategy. Our research provides effective control algorithms and systems for real-time microgrid management, which maximize the benefits of renewable energy generation.


 Paper appears in ACM e-Energy 16'

“Online Microgrid Energy Generation Scheduling Revisited: The Benefits of Randomization and Interval Prediction”


 Paper appears in ACM SIGMETRICS 13'

“Online Energy Generation Scheduling for Microgrids with Intermittent Energy Sources and Co-Generation”




 

Smart Energy Storage System – Energy storage is becoming an indispensable part of modern decentralized power systems. It is critical to be able to manage energy storage in the presence of stochastic price fluctuations in demand response management and intermittent renewable energy supply. Our work presents practical energy storage management systems that can deliver assured effectiveness with low computational complexity and using limited prediction data.


 Paper appears in IEEE Trans. Smart Grid

“Cost Minimizing Online Algorithms for Energy Storage Management with Worst-case Guarantee”



 

Optimal Placement of Charging Stations – Public charging stations are becoming a popular option for Electric Vehicle drivers. However, the locations of charging stations require carefully planning to balance the trade-off among infrastructure costs, convenience and impacts on electricity grid. Using real-world vehicle mobility datasets, we are examining the optimal placement schemes of public charging stations at a citywide scale under diverse metrics.




 

Research in Smart Buildings



 

Smart Building Management and Control – Cities are expanding rapidly, and consuming ever more energy. Buildings are among the largest consumers of energy, topping 40% of total energy usage in many countries. A significant portion of energy use in buildings is attributed to the heating, ventilation, and air conditioning (HVAC), which accounts for up to 50% of the total energy consumption in buildings.

Improving energy efficiency of buildings, particularly optimizing HVAC system, is critically important and will have a significant impact in reducing the overall energy consumption. We develop novel management and control solutions for improving the efficiency of smart buildings and environments, utilizing data analytics, wireless sensors and intelligent systems.



 

Intelligent Temperature Control – A prominent application of computing technology for energy saving in buildings is to optimize heating, ventilation, and air-conditioning (HVAC) systems. New generation of wireless sensors for temperature control are increasingly deployed because of their convenience and versatility for built environment monitoring. My work provides real-time algorithms to optimize the trade-off between the energy efficiency of wireless sensors and the effectiveness of HVAC control in the presence of uncertain fluctuations in room temperature.


 Paper appears in IEEE/ACM Trans. Networking

“Online Algorithms for Information Aggregation from Distributed and Correlated Sources”

 Paper appears in ACM e-Energy 13'

“Smart Air-Conditioning Control by Wireless Sensors: An Online Optimization Approach”


Mosques are prevalent in the Gulf region, which consume significant energy every year. Meanwhile, as a proof-of-concept, we launched a pilot project to retrofit three traditional mosques in the UAE with intelligent building management systems, including energy-harvesting wireless sensors and automatic occupancy recognition based on low-cost Raspberry Pi platform. This project is being expanded up to thousands of mosques.


 Paper in submission

“Automatic HVAC Control with Real-time Occupancy Recognition and Simulation-guided Model Predictive Control in Low-cost Embedded System”




 

Urban Environmental Sensing – We design effective distributed sensor networks for a wide rage of critical monitoring and control applications. For example, we optimize the operations of multiple sensors deployed in distributed locations to provide measurements in buildings and urban environment, which are effective for urban heat island mitigation.


In a Masdar-Institute/MIT Flagship Research Project, we develop comprehensive solutions for monitoring, modeling, and ultimately manipulating urban micro-climate for Abu Dhabi. Urban micro-climate phenomena include urban heat island effect, local wind pattern, and solar shading. We develop solar-powered sensor stations mounted on lamp posts to monitor urban heat island effect in Abu Dhabi City, which is first-of-its-kind large-scale sensor network project for micro-climate monitoring.





 

Smart Plugs with Online Learning – Smart plugs have limited storage and processing power. My research develops low-cost smart plugs integrated with online learning algorithms to support energy consumption tracking of appliances and consumption pattern classifications. We develop a prototype based on Arduino platform, as an open-source project (OS|Plug). The smart plugs can support diverse features, such as prediction of energy consumption, diagnosis of appliance anomaly, data analytics, privacy and security extensions. A smartphone is also developed to control the smart plugs.




 

Smart Lighting Control – Lighting constitutes 10-30% of the total electricity consumption of commercial and residential buildings. Automatic lightening controls can reduce lightening energy consumption significantly. This is typically achieved through the interplay of light controls and wireless sensors, deployed within an optimization model with the objective of minimizing energy consumption, while maintaining user satisfaction. We devise an adaptive intelligent smart lightning system for comprehensive energy expenditure minimization in real-world dynamic environments.




 

Research in Intelligent Vehicles



 

Intelligent Vehicles and Transportation Systems – Vehicles and transportation systems take up 20-25% of energy consumption and CO2 emissions. Exhaust and greenhouse gas emission from transportation is a primary contributor to local air pollution and smog, at a faster rate than any other energy sectors.

Meanwhile, modern transportation systems and vehicles are experiencing a tremendous transformation. Vehicles are evolving to be highly intelligent, computerized and network-enabled systems. Merging vehicles with advanced computing systems, we develop the next-generation intelligent vehicles and transportation systems with emerging embedded and mobile computing systems, geared toward more sustainable transportation systems.



 

Smart Driving Apps – Various smartphone apps are developed for assisting energy-efficient driving. One application is for plug-in hybrid electric vehicles (PHEVs), which enjoy both convenience of fuel refilling and cheap electrical energy. Typical PHEVs have options of driver selectable drive modes, for example, electric vehicle (EV) mode (drawing fully on battery) and charge sustaining (CS) mode (utilizing internal combustion engine to charge battery while propel-ling the vehicle). We develop algorithms to optimize drive mode selection based on trip information, which are implemented in a smartphone app and evaluated empirically on a Chevrolet Volt.



 Paper appears in IEEE Trans. Intelligent Transportation Systems

“Drive Mode Optimization and Path Planning for Plug-in Hybrid Electric Vehicles”

 Paper appears in ACM e-Energy 16'

“Fuel Minimization of Plug-in Hybrid Electric Vehicles by Optimizing Drive Mode Selection”


Another application is to provide more accurate estimation of Distance-to-Empty (DTE) for electric vehicles, which is vital for not only the scheduling for refueling, but also for the choice of routes for the budget- and/or environmentally-conscious drivers. We develop methodology and systems that predict fuel efficiency accurately based on crowd-sourcing data using the paradigm of participatory sensing.



 Paper appears in IEEE Trans. Intelligent Transportation Systems

“Personalized Prediction of Vehicle Energy Consumption based on Participatory Sensing”

 Paper appears in ACM e-Energy 15'

“A Participatory Sensing Approach for Personalized Distance-to-empty Prediction and Green Telematics”



 

Autonomous Vehicle Systems – Autonomous vehicles will fundamentally transform our transportation system, with crucial im-pacts on electrification of transportation system. Information exchanges play a critical role in enabling autonomous driving by overcoming the limitation of perception and decision of a single autonomous vehicle. For assuring safety, facilitating regulations, and enhancing intelligent decisions, it is vital to enable a detailed global view of mapping data in terms of 3D point cloud (from LIDAR laser-based perception system) synchronized among autonomous vehicles and roadside infra-structure. Our research develops an efficient information dissemination system of 3D point cloud mapping data for autonomous vehicles. We implement our system in a multi-robotic autonomous vehicle testbed for practical evaluation.



 Paper in submission

“Efficient Information Dissemination of 3D Point Cloud Map Data for Autonomous Vehicles”



 

Viable Sharing Mechanisms – Sharing rides, cabs and cars strikes a balance between the flexibility of private vehicles and the cost of public transportation. The advantages are saving travel costs, alleviating traffic, conserving fuel, and reducing parking space. We devise efficient and incentive-driven mechanisms and smartphone apps for sharing vehicles.


 Paper in submission

“Quantifying Inefficiency of Fair Cost-Sharing Mechanisms for Sharing Economy”



 

Efficient Drone Management – Drones (also known as unmanned aerial vehicles) are becoming a convenient means of logistics. In particular, the civilian markets for drones are forecasted to be booming globally. The notable areas of drone applications include delivery (e.g., for light-weight parcels, medical items, airmail) and remote operations (e.g., farming, environmental surveying, search and rescue operations). Our research develops a prototype for fully automated intelligent management system for drone fleet together with a mobile charging station to conduct inductive recharging for drones, which intelligently optimizes flight path and its control operations to maximize drones' battery life.



 Drones for Good Award: Check out IntelliDrones project



 

Research in Networking



 

The critical issues of sustainability facing in today’s society call for an emerging new breed of information networks that can integrate seamlessly with electricity grid, buildings, and environments.

Traditional communication networks were designed to operate in the presence of sufficient stationarity, homogeneity, and cooperation. To support for sustainability based applications, we also research in broad areas of networking algorithms and cyber-physical systems that complement our work in sustainability and energy systems.



 

We provide designs and analyses of algorithms and protocols for providing high throughput and low latency in wireless networks.


 Paper appears in IEEE Trans. Mobile Computing

“Effective Static and Adaptive Carrier Sensing for Dense Wireless CSMA Networks”


 Paper appears in IEEE INFOCOM 12'

“Impact of Directional Transmission in Large-scale Multi-hop Wireless Ad hoc Networks”


 Paper in IEEE Journal on Selected Areas in Communications and IEEE INFOCOM 10'

“Green Wave Sleep Scheduling: Optimizing Latency & Throughput in Duty Cycling Wireless Networks”


 Paper appears in IEEE/ACM Trans. Networking and ACM MobiCom 09'

“Capacity of Large-scale CSMA Wireless Networks”


 Paper appears in IEEE Journal on Selected Areas in Communications

“Harnessing Battery Recovery Effect in Wireless Sensor Networks: Experiments & Analysis”




 

We cast insights on how the Internet becomes more viable and robust that can better support seamless interoperation for heterogeneous applications and non-cooperative users.


 Paper appears in ACM Trans. Internet Technology and IEEE INFOCOM 10'

“Economic Viability of Paris Metro Pricing for Digital Services”


 Paper appears in IEEE/ACM Trans. Networking and IEEE INFOCOM 09'

“Analysis of Latency of Stateless Opportunistic Forwarding in Intermittently Connected Networks”


 Paper appears in IEEE Journal on Selected Areas in Communications

“A Game-theoretical Study of Robust Networked Systems”


 Paper appears in ACM Computer Communication Review and ACM SIGCOMM 06'

“Policy-based Routing with Non-strict Preferences”




 

Team


 

Sid Chi-Kin Chau

Faculty

About

I am an assistant professor of the Department of EECS at Masdar Institute, UAE, which was created in collaboration with MIT to be the world’s first graduate-level university dedicated to the research of sustainability.

My primary research area is Sustainability and Computing, which applies computing algorithms, systems and data analytics to develop sustainable energy systems, including smart grid, smart buildings, and intelligent vehicles. I also research in broad areas of algorithms, optimization, computer networking, and cyber-physical systems.

Previously, I was a visiting professor at MIT, a senior research fellow at A*STAR in Singapore, a Croucher Foundation research fellow at University College London with a research fellowship awarded by the Croucher Foundation Hong Kong, a visiting researcher at IBM Watson Research Center and BBN Technologies, and a post-doctoral research associate at University of Cambridge.

I received the Ph.D. from University of Cambridge with a scholarship by the Croucher Foundation Hong Kong, and B.Eng. (First-class Honours) from the Chinese University of Hong Kong.

I am a co-founder of Qudra Technology, a start-up specializing in intelligent systems and data analytics for smart building management.


Research Interests

  • Smart Grid
  • Smart Buildings
  • Intelligent Vehicles
  • Algorithms
  • Optimization
  • Data Analytics
  • Networking
  • Cyber-Physical Systems
  • Internet-of-Things
 

Researchers


Majid Khonji

Past PhD Student
  • Senior R&D Researcher at Dubai Electricity and Water Authority (DEWA)
  • Graduated with PhD from Masdar Institute, UAE
    • Thesis: Combinatorial Allocation of Alternating Current Power in Smart Grid
  • Obtained MSc from Institut Polytechnique de Grenoble, France
  • Research Interests: Algorithms, Optimization, Theory, Smart Grid

Muhammad Aftab

PhD Student
  • Obtained MSc from Masdar Institute, UAE
  • Research Interests: Sensor Networks, Embedded Systems

Chien-Ming Tseng

PhD Student
  • Obtained MSc from National Cheng-Kung University, Taiwan
  • Research Interests: Intelligent Vehicular Systems, Autonomous Vehicles

Areg Karapetyan

PhD Student (Co-advised)
  • Obtained MSc from Masdar Institute, UAE
  • Research Interests: Algorithms, Optimization, Theory, Smart Grid

Mukesh Jha

Research Engineer
  • Graduated with MSc from Masdar Institute, UAE
  • Research Interests: Embedded Systems

 

Teaching


 

The following related postgraduate courses are taught at Masdar Institute:

  •  Topics in Intelligent Vehicles (CIS 623)
    -- Vehicular Communications, Vehicular Systems and Autonomous Vehicles

    Highly intelligent and autonomous vehicles are becoming an important part of transportation infrastructure in the near future. Through this course, students will be able to keep abreast of the latest development in this exciting area of technology. This course covers topics in autonomous vehicles, vehicular computing systems and applications, vehicular communication and information systems and infrastructure.

  •  Sustainability and Computing (CIS 618)
    -- Smart Grid, Smart Buildings, Environmental Sensing, and Energy Efficient Computations

    While computation has revolutionized the information era, a bigger challenge lies ahead - how do we harness the power of computation to address the pressing issues of sustainability? In this course, we explore the state-of-the-art work in sustainable computing and novel uses of computation to address sustainability challenges, as well as enjoying hands-on experiences such as building smart plug and smart thermostat systems.

  •  Advanced Topics in Algorithms (CIS 617)
    -- Approximation, Online and Randomized Algorithms

    Making sub-optimal or random choices, an apparently silly idea, can have unexpectedly drastic improvement in the efficiency, complexity and other desirable properties of algorithms for diverse problems. In this course, we embark on an amazing journey to explore the power of using approximate, incomplete, or probabilistic knowledge in algorithmic design, and the elegant theories that explain such power.

  •  Distributed Computer Systems Engineering (CIS 508)
    -- Networked, Cloud and Embedded Computing Systems

    Computer systems need to work together. But figuring out how computer systems can work together efficiently isn’t easy. This course offers both principles and hands-on experiences for engineering distributed computer systems (ranging from large-scale Internet-wide cloud computing to embedded systems in a car). This course is designed with a dozen of practical and creative projects (featuring Arduino embedded systems, Android mobile systems, Amazon Web Services).

  •  Computer Systems Modelling
    -- Lessons on Randomized Algorithms
    Previously co-lectured course at University of Cambridge.

Publications


 

Preprints:

  1. Chi-Kin Chau, Ivan Ho, Elmer Magsino, Chien-Ming Tseng and Kanghao Jia, “Efficient Information Dissemination of 3D Point Cloud Mapping Data for Autonomous Vehicles”.

  2. Areg Karapetyan, Majid Khonji, Chi-Kin Chau and Khaled Elbassioni, “Online Algorithm for Demand Response with Inelastic Demands and Apparent Power Constraint”.

  3. Majid Khonji, Areg Karapetyan, Khaled Elbassioni and Chi-Kin Chau, “Complex-demand Scheduling Problem with Application in Smart Grid”.

  4. Chi-Kin Chau and Khaled Elbassioni, “Quantifying Inefficiency of Fair Cost-Sharing Mechanisms for Sharing Economy”.

Journal Publications:

  1. Chi-Kin Chau, Khaled Elbassioni and Chien-Ming Tseng, “Drive Mode Optimization and Path Planning for Plug-in Hybrid Electric Vehicles”, to appear in IEEE Transactions on Intelligent Transportation Systems, 2017.

  2. Chien-Ming Tseng and Chi-Kin Chau, “Personalized Prediction of Vehicle Energy Consumption based on Participatory Sensing”, to appear in IEEE Transactions on Intelligent Transportation Systems, 2017.

  3. Majid Khonji, Chi-Kin Chau, Khaled Elbassioni, “Optimal Power Flow with Inelastic Demands for Demand Response in Radial Distribution Networks”, to appear in IEEE Transactions on Control of Network Systems, 2017.

  4. Areg Karapetyan, Majid Khonji, Chi-Kin Chau, K. Elbassioni, H. Zeineldin, “Efficient Algorithm for Scalable Event-based Demand Response Management in Microgrids”, to appear in IEEE Transactions on Smart Grid, 2017.

  5. Chi-Kin Chau, Khaled Elbassioni and Majid Khonji, “Truthful Mechanisms for Combinatorial Allocation of Electric Power in Alternating Current Electric Systems for Smart Grid”, ACM Transactions on Economics and Computation, Vol. 5, No. 1, Article 7, Nov 2016.

  6. Chi-Kin Chau, Ivan W. H. Ho, Zhenhui Situ, Soung Chang Liew, Jialiang Zhang, “Effective Static and Adaptive Carrier Sensing for Dense Wireless CSMA Networks”, to appear in IEEE Transactions on Mobile Computing, 2016.

  7. Chi-Kin Chau, Guanglin Zhang, Minghua Chen, “Cost Minimizing Online Algorithms for Energy Storage Management with Worst-case Guarantee”, IEEE Transactions on Smart Grid, Vol. 7, No. 6, pp2691-2702, Nov 2016.

  8. Chi-Kin Chau, Majid Khonji and Muhammad Aftab, “Online Algorithms for Information Aggregation from Distributed and Correlated Sources”, to appear in IEEE/ACM Transactions on Networking, 2016.

  9. E. Wilhelm, J. Siegel, S. Mayer, L. Sadamori, S. Dsouza, C-K. Chau, S. Sarma, “CloudThink: A Scalable Secure Platform for Mirroring Transportation Systems in the Cloud”Transport, Special Issue in Smart and Sustainable Transport, Vol. 30, No. 3, 2015.

  10. Chi-Kin Chau, Qian Wang and Dah-Ming Chiu, “Economic Viability of Paris Metro Pricing for Digital Services”ACM Transactions on Internet Technology, Special Issue on Pricing and Incentives in Networks and Systems, Vol. 14, No. 12, Issue 2-3, pp12:1-12:21, Oct 2014.

  11. Chi-Kin Chau, Minghua Chen and Soung Chang Liew, “Capacity of Large-scale CSMA Wireless Networks”, IEEE/ACM Transactions on Networking, Vol. 19, No. 3, pp893-906, Jun 2011.

  12. Chi-Kin Chau and Prithwish Basu, “Analysis of Latency of Stateless Opportunistic Forwarding in Intermittently Connected Networks”IEEE/ACM Transactions on Networking, Vol. 19, No. 4, pp1111-1124, Aug 2011.

  13. Saikat Guha, Prithwish Basu, Chi-Kin Chau and Richard Gibbens, “Green Wave Sleep Scheduling: Optimizing Latency and Throughput in Duty Cycling Wireless Networks”IEEE Journal on Selected Areas in Communications, Special Issue in Energy-Efficient Wireless Communications, Vol. 29, No. 8, pp1595-1604, Sep 2011.

  14. Chi-Kin Chau, Fei Qin, Samir Sayed, M. H. Wahab and Yang Yang, “Harnessing Battery Recovery Effect in Wireless Sensor Networks: Experiments and Analysis”, IEEE Journal on Selected Areas in Communications, Special Issue in Wireless Sensor Networking Solutions, Vol. 28, No. 7, pp1222-1232, Sep 2010. (Acceptance rate: 25%)

  15. Chi-Kin Chau, “A Game-theoretical Study of Robust Networked Systems”IEEE Journal on Selected Areas in Communications, Special Issue in Game Theory in Communication Systems, Vol. 26, No. 7, pp1250-1260, Sep 2008.(Acceptance rate: 25.2%)

  16. Chi-Kin Chau, “Policy-based Routing with Non-strict Preferences”ACM Computer Communication Review, (Proceedings of ACM SIGCOMM 06’), Vol. 36, No. 4, pp387-398, Oct 2006.

  17. Chi-Kin Chau and Kwang Mong Sim, “The Price of Anarchy for Non-atomic Congestion Games with Symmetric Cost Maps and Elastic Demands”Operations Research Letters, vol. 31 (5), pp327-334, Sep 2003.

  18. Chi-Kin Chau and Kwang Mong Sim, “Analyzing the Impact of Selfish Behaviors of Internet Users and Operators”IEEE Communications Letters, vol. 7, no. 9, pp463-465, Sep 2003.

Selected Recent Publications in Conferences and Book Chapters:

  1. Majid Khonji, Areg Karapetyan, Khaled Elbassioni and Chi-Kin Chau, “Complex-demand Scheduling Problem with Application in Smart Grid”, in Proc. of International Computing and Combinatorics Conference (COCOON), Aug 2016.

  2. Chi-Kin Chau, Khaled Elbassioni and Chien-Ming Tseng, “Fuel Minimization of Plug-in Hybrid Electric Vehicles by Optimizing Drive Mode Selection”, in Proc. of ACM International Conference on Future Energy Systems (e-Energy), Jun 2016. (Acceptance rate: 29%)

  3. Mohammad Hajiesmaili, Chi-Kin Chau, Minghua Chen and Longbo Huang, “Online Microgrid Energy Generation Scheduling Revisited: The Benefits of Randomization and Interval Prediction”, in Proc. of ACM International Conference on Future Energy Systems (e-Energy), Jun 2016. (Acceptance rate: 29%) [Runner-up for the best paper award]

  4. Chein-Ming Tseng, Wenshen Zhou, Mohammad Al Hashmi, Chi-Kin Chau, Soh Gim Song and Erik Wilhelm, “Data Extraction from Electric Vehicles through OBD and Application of Carbon Footprint Evaluation”, in Proc. of ACM International Conference on Future Energy Systems (e-Energy) EV-Sys Workshop, 2016.

  5. Chein-Ming Tseng and Chi-Kin Chau, “On the Privacy of Crowd-sourced Data Collection for Distance-to-Empty Prediction and Eco-routing”, in Proc. of ACM International Conference on Future Energy Systems (e-Energy) EV-Sys Workshop, 2016.

  6. Chi-Kin Chau and Lin Yang, “Competitive Online Algorithms for Geographical Load Balancing in Data Centers with Energy Storage”, in Proc. of ACM International Conference on Future Energy Systems (e-Energy) E2DC Workshop, 2016.

  7. Chien-Ming Tseng, Chi-Kin Chau, Sohan Dsouza and Erik Wilhelm, “A Participatory Sensing Approach for Personalized Distance-to-empty Prediction and Green Telematics”, in Proc. of ACM International Conference on Future Energy Systems (e-Energy), Jul 2015. (Acceptance rate: 22.8%)

  8. Chi-Kin Chau, Richard Gibbens and Don Towsley, “Connectivity of Large-scale Wireless Networks with Directional Antennas”, in Wireless Network Performance Enhancement via Directional Antennas: Models, Protocols and Systems, CRC Press, 2015.

  9. Majid Khonji, Chi-Kin Chau and Khaled Elbassioni, “Inapproximability of Power Allocation with Inelastic Demands in AC Electric Systems and Networks”, in Proc. of the International Conference on Computer Communication and Networks (ICCCN) SCENE Workshop, Aug 2014.

  10. Prithwish Basu, Ben Baumer, Amotz Bar-Noy and Chi-Kin Chau, “Social-Communication Composite Networks”, in Opportunistic Social Networks, CRC Press, 2014.

  11. Chi-Kin Chau, Khaled Elbassioni, Majid Khonji, “Truthful Mechanisms for Combinatorial AC Electric Power Allocation”, in Proc. of Autonomous Agents and Multi-Agent Systems (AAMAS), May 2014. (Acceptance rate: 23.8%)

  12. 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”, in Proc. of ACM Annual Conference of the Special Interest Group on Computer Systems Performance Evaluation (SIGMETRICS), Jun 2013. (Acceptance rate: 13.7%)

  13. Yu Lan and Chi-Kin Chau, “Complex-Demand Knapsack Problems and Incentives in AC Power Systems”, in Proc. of Autonomous Agents and Multi-Agent Systems (AAMAS), May 2013. (Acceptance rate: 22.8%)

  14. Muhammad Aftab, Chi-Kin Chau and Peter Armstrong, “Smart Air-Conditioning Control by Wireless Sensors: An Online Optimization Approach”, in Proc. of ACM International Conference on Future Energy Systems (e-Energy), May 2013. (Acceptance rate: 25%)

  15. Lian Lu, Jinlong Tu, Chi-Kin Chau, Minghua Chen, Xiaojun Lin and Zhao Xu, “Towards Real-Time Energy Scheduling in Microgrids with Performance Guarantee”, in Proc. of IEEE Power & Energy Society (PES) General Meeting, Jul 2013.

  16. Prithwish Basu, Chi-Kin Chau, Richard Gibbens, Saikat Guha and Ryan Irwin, “Multicasting Under Multi-domain and Hierarchical Constraints”, in Proc. of International Symposium of Modeling and Optimization of Mobile, Ad Hoc and Wireless Networks (WiOpt), May 2013.

  17. Chi-Kin Chau, Anand Seetharam, Jim Kurose and Don Towsley, “Opportunism vs. Cooperation: Comparing Forwarding Strategies in Multihop Wireless Networks with Random Fading”, in Proc. of International Conference on COMmunication Systems and NETworkS (COMSNETS), Jan 2013. (Acceptance rate: 26%)

  18. Ka Kit Lam, Chi-Kin Chau, Minghua Chen and Soung Chang Liew, “Mixing Time and Temporal Starvation of General CSMA Networks with Multiple Frequency Agility”, in Proc. of IEEE International Symposium on Information Theory (ISIT), Jul 2012.

  19. Chi-Kin Chau, Jialiang Zhang, Minghua Chen and Soung Chang Liew, “Interference-safe CSMA Networks by Local Aggregate Interference Power Measurement”, in Proc. of International Symposium of Modeling and Optimization of Mobile, Ad Hoc and Wireless Networks (WiOpt), May 2012.

  20. Chi-Kin Chau, Richard Gibbens and Don Towsley, “Impact of Directional Transmission in Large-scale Multi-hop Wireless Ad hoc Networks”, in Proc. of IEEE Conference on Computer Communications (INFOCOM), Apr 2012. (Acceptance rate: 18%)

  21. Chi-Kin Chau, Richard Gibbens, Robert Hancock and Don Towsley, “Robust Multipath Routing in Large Wireless Networks”, in Proc. of IEEE Conference on Computer Communications (INFOCOM) mini-conference, Apr 2011. (Total acceptance rate for INFOCOM main and mini-conferences: 23.4%)

  22. Xingang Shi, Chi-Kin Chau and Dah-Ming Chiu, “Space-efficient Tracking of Network-wide Flow Correlations”, in Proc. of IEEE Conference on Computer Communications (INFOCOM) mini-conference, Apr 2011. (Total acceptance rate for INFOCOM main and mini-conferences: 23.4%)

  23. Chi-Kin Chau, Qian Wang and Dah-Ming Chiu, “On the Viability of Paris Metro Pricing for Communication and Service Networks”, in Proc. of IEEE Conference on Computer Communications (INFOCOM), Mar 2010. (Acceptance rate: 17.5%)

  24. Saikat Guha, Chi-Kin Chau and Prithwish Basu, “Green Wave: Latency and Capacity-Efficient Sleep Scheduling for Wireless Networks”, in Proc. of IEEE Conference on Computer Communications (INFOCOM), Mar 2010. (Acceptance rate: 17.5%)

  25. Chi-Kin Chau, Minghua Chen and Soung Chang Liew, “Capacity of Large-scale CSMA Wireless Networks”, in Proc. of ACM Annual International Conference on Mobile Computing and Networking (MobiCom), Sep 2009. (Acceptance rate: 10.6%)

  26. Chi-Kin Chau and Prithwish Basu, “Exact Analysis of Latency of Stateless Opportunistic Forwarding”, in Proc. of IEEE Conference on Computer Communications (INFOCOM), Apr 2009. (Acceptance rate: 19.6%)

  27. Chi-Kin Chau, “Policy-based Routing with Non-strict Preferences”, in Proc. of ACM Annual Conference of the Special Interest Group on Data Communications (SIGCOMM), Sep 2006. (Acceptance rate: 12.4%)

  28. Chi-Kin Chau, Richard Gibbens and Timothy Griffin, “Towards a Unifying Theory for Policy-based Routing”, in Proc. of IEEE Conference on Computer Communications (INFOCOM), Apr 2006. (Acceptance rate: 18%)

Patent:

  1. Chi-Kin Chau, Kang-won Lee and Starsky H. Y. Wong, “Assigning Gateways for Heterogeneous Wireless Mobile Networks”, Patent N0.: US 8,855,010 B2. (Date of Patent: Oct. 7, 2014)

Contact


 

Email: ckchau(at)masdar.ac.ae

Address: B.2.2., Masdar Institute, Masdar City, PO Box 54224, Abu Dhabi, UAE

Phone: +971-810-9333