Sustainable Energy Informatics Lab

Host University

Lahore University of Management Sciences

Scope:

Sustainable Energy Informatics Lab (SEIL) at LUMS is driven by the mission of carrying out cutting-edge interdisciplinary research in the broad field of renewable energy analytics, energy policy, smart grids, and energy efficiency. SEIL has been actively involved in developing solutions for the power sector of Pakistan and creating evidence-based energy policy frameworks for government entities for many years now. 

The research domains of SEIL include short, medium, long term forecasting techniques for energy demand, renewable energy generation forecasting for solar and wind resources, and demand-side management in agricultural, residential, and commercial sectors. Further, SEIL has carried out research on the prospects and challenges of integrating renewable energy resources into the electric grid, soft load shedding techniques, and other related areas.

Under the banner of the National Center in Big Data and Cloud Computing (NCBC), SEIL has developed forecasting tools for power sector entities of Pakistan in collaboration with CPPA. After the successful deployment of the short-term load forecasting tool (STLF), we are in the process of developing MTLF. SEIL has conducted a market assessment for Electric Vehicles adaption in Pakistan, collaborating with USAID.

 

In the wake of aggravating smog crisis in Lahore, SEIL has initiated real-time Spatio-temporal mapping exercise using indigenously developed low-cost sensors. The project, which is well underway, aims to map Lahore’s air quality in real-time and uncover the causes of the smog in Pakistan. 

Our team

Meet the Principal Investigator as well the as Co – Principal Investigators of the Lab.

Dr. Fiaz Chaudhry

Principal Investigator

I am text block. Click edit button to change this text. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.




Dr. ImdadUllah Khan

Co - Prinicipal Investigator

Imdad Ullah Khan is an Assistant Professor of Computer Science at LUMS School of Science and Engineering. He received his Ph.D. in Computer Science from Rutgers, The State University of New Jersey.

Prior to joining LUMS Dr. Khan was an Assistant Professor at the department of Computer Science, in Umm Al-Qura University, KSA. 

Dr. Suleman Shahid

Co - Principal Investigator

Suleman Shahid is working as an Assistant Professor in Computer Science where he directs the ‘Computer Human Interaction and Social Experience Lab’ (CHISEL).  His research interests include assistive technologies (mobile apps and VR/AR systems) to enhance the quality of life of persons with disabilities (e.g. autism, dyslexia, visual impairment) and older adults, educational technologies for children (child-computer interaction), and affective computing. More recently he has become interested in ‘information and communication technologies for development’ (ICT4D) where he takes a multidisciplinary approach for designing interventions in the areas of education and health. Since 2009, he has been offering consultancy and training services in the areas of design thinking and user experience (UX) design and strategy.

Suleman received his PhD in human-computer interaction in 2011 from Tilburg University, the Netherlands and PDEng (Professional Doctorate in Engineering) in 2007 in User System Interaction program from Eindhoven University of Technology, the Netherlands. Prior to joining LUMS, he was working as an assistant professor in human computer interaction (HCI) at Tilburg University. He has been associated as a researcher with Tilburg center for Cognition and Communication (TiCC), Tilburg, the Netherlands and as a visiting assistant professor with Eindhoven University of Technology, the Netherlands. He also worked for PHILIPS Research (High Tech Campus), the Netherlands and Fraunhofer FIT, Germany.

Dr. Hassan MohyUddin

Co - Prinicpal Investigator

Dr. Hassan Mohy-ud-Din is the Director of Clinical and Translational Imaging lab and an Assistant Professor at the LUMS School of Science and Engineering. He completed his PhD and MSE in Electrical and Computer Engineering and MA in Applied Mathematics and Statistics from Johns Hopkins University (2009 – 2015). From 2015 – 2017 he was a postdoctoral associate in the Department of Radiology and Biomedical Imaging at the Yale School of Medicine. From 2017 – 2018 he was a Clinical Research Scientist at Shaukat Khanum Memorial Cancer Hospital and Research Centre.

His research lies at the intersection of Applied Mathematics and Medical Imaging. His work on dynamic cardiac PET imaging won the 2014 SNMMI Bradley-Alavi fellowship and the 2014 SIAM student award. He is also a recipient of 2019 Charles Wallace Fellowship from the British Council, Pakistan. His work on non-invasive biomarker quantification for coronary microcirculation was featured as a news story in Medical Physics followed by a dedicated review article from Stanford. He also serves as a reviewer on major scientific journals (Clinical Cancer Research, Neuro-oncology Advances, Medical Image Analysis, Neuroimage, Physics in Medicine and Biology, Medical Physics, IEEE Transactions on Image Processing to name a few) and is a member of IEEE and SIAM societies. He also carries a university teaching experience of over 14 years (UET Lahore, SBASSE LUMS, and Johns Hopkins University). He is a Principal Organizer of an annual workshop on Radiomics and Radiogenomics in Neuro-oncology using AI held under MICCAI.

Research Domains

Spatiotemporal Energy Forecasting

SEIL aims to develop fine-grained energy forecasting methods that look at energy demand in space and time. It is in contrast to traditional energy forecasting techniques, which emphasize on factors such as per capita energy consumption and population growth. This means that we should predict the energy demand between one to ten years for any given locale in the country, in hourly granularity..

Power & Energy Data Repository

To ensure a successful rollout of the smart grid in Pakistan, the foremost challenge is to harness big data in smart grids. At SEIL, we develop strategies to do this. We are developing methods of industrial strength with strong storing and querying methods since smart grids have a tremendous amount of data. The lab has developed data respositories of generation, demand data at low granularity. We are progressively working on developing consumer-level and commercial data sets. One such is PRECON.

Smart Metering Strategy

This domain focuses on developing strategies and policy frameworks for smart-meter deployments in Pakistan. Smart meters are fundamental to emerging scenarios for electric grids. The intermittent nature of renewable resources, energy efficiency requirements, and incorporation of technologies such as IoT requires smarter meters for monitoring and evaluation of parameters up to consumer scale. While smart meters are already deployed at the feeder level, consumer scale deployment is a vacant space SEIL is working on.

Analysis of Wind & Solar Generation Data

Through advanced analytics, SEIL aims to develop forecasting models with high accuracy to mitigate uncertainties due to renewable energy resources. This is important in developing effective strategies, from commissioning new systems to the operational strength of the utility companies.

Location

Department of Computer Science,
School of Science & Engineering,
LUMS 54792

Our hours

10:00 AM – 05:00 PM
Monday – Friday

Contact us

Phone: +92 42 35608000
EXT: 8329/3337
Email: contact@ncbc.pk