24Oct

The first-ever PhD graduation from the department

At the 48th convocation of USJ, the first-ever PhD graduate from the Department, Dr. Manjula Perera was conferred. Her primary supervisor was Dr. Ravindra Lokupitiya of the Department of Statistics, USJ. Her PhD thesis title was “Estimation of global scale carbon fluxes using Maximum Likelihood ensemble filter“. She was co-supervised by the following academics:

Prof. A. Scott Denning, Professor, Department of Atmospheric Science, Colorado State
University, Fort Collins, CO 80523-1371 USA.
Prof. E. Y. K. Lokupitiya, Professor in Environmental Science, Department of Zoology
and Environment Sciences, University of Colombo, Colombo, Sri Lanka.
Dr. Prabir Kumar Patra, Principal Scientist, Research Institute for Global Change,
JAMSTEC, 3173-25 Showa-machi, Kanazawa-ku, Yokohama, 236-0001, Japan.
Prof. R. G. N. Meegama, Professor in Computer Science, Department of Computer
Science, Faculty of Applied Sciences, University of Sri Jayewardenepura, Gangodawila,
Nugegoda, Sri Lanka.

Dr. Perera would like to thank the following institutes for the grants she received for her PhD studies.

National Research Council, Sri Lanka (NRC-036)
Asia-Pacific Network for Global Change Research (APN); grant#ARCP2011-11NMY-
Patra/Canadell).

Her thesis abstract is as follows:

More advanced data assimilation methods based on statistical and mathematical knowledge are needed to cater to the increased amount of CO₂ measurements collected in various platforms. In addition to existing flasks, continuous and aircraft data, CO₂ measurements obtained by passenger aircrafts and satellites increase the observation network and provide more constraints on surface carbon flux estimation. This thesis mainly focuses on estimating the surface carbon sources and sinks using CONTRAIL aircraft observations, in addition to the existing in-situ measurements using the ensemble based data assimilation method called Maximum Likelihood Ensemble Filter (MLEF) coupled with Parameterized Chemistry Transport model (PCTM). A pseudodata experiment was carried out by adding CONTRAIL measurements to the observation vector using MLEF coupled with PCTM model, which was driven by GEOS-4 (Goddard Earth Observation System, version 4) weather data for the model validation. Next, MLEF code was developed to conduct the real data experiment to identify the capability on estimating surface carbon fluxes for the period 2009-2011. PCTM model was driven by Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) weather data. Solving separate multiplicative biases added for photosynthesis, respiration, and air-sea gas exchange fluxes the estimated fluxes were obtained. Hourly land fluxes, Gross Primary Production (GPP) and respiration obtained from Simple Biosphere-version 3 (SiB3) model, Takahashi ocean fluxes and Brenkert fossil fuel emissions were used.

Pseudodata experiment results showed a considerable uncertainty reduction for Asian region and more than 50% reduction for North American and European regions. According to the results of the real data experiment, North America showed about 60-80% uncertainty reduction while the Asian and European regions showed moderate results with 50-60% uncertainty reduction. Most other land and oceanic regions showed less than 30% uncertainty reduction. The results were mainly compared with the results of well-known CarbonTracker (CT2017) which is a CO₂ measurement and modeling system developed by NOAA (National Oceanic and Atmospheric Administration). The spatial distribution of estimated mean annual fluxes over North America, Australia and Tropical Asia showed good agreement with the CarbonTracker results when aggregated into large regions. The biases were poorly constrained in the regions where the CO₂ observations are not sufficiently dense such as South America and Africa. Long-term averaged fluxes were compared with several other inversion studies and showed similar results for the Boreal North America, Temperate North America and Australia. The results reveal the capability of MLEF method to assimilate large CO₂ observation vectors with high performance parallel computing environment with less cost and less time. The impact of satellite observations with MLEF needs to be investigated further and this study forms the basis of the future work in this area.

Keywords: Data assimilation, Maximum Likelihood Ensemble Filter, CONTRAIL aircraft observations, Carbon sources and sinks, CO₂ modeling

20Oct

News, Statistics Soceity

Helping Hands

A financial aid program organized by the “Statistics Society” in affiliation with the Department of Statistics, Faculty of Applied Sciences, University of Sri Jayewardenepura for first and second-year undergraduates who study statistics as a subject with financial difficulties.

Objectives

To help undergraduates financially.

Reduce the number of university dropouts due to financial related problems.

Evaluation Criteria

Sorting the applicants by thoroughly evaluating the details collected through the google form application.
Selected applicants will be interviewed by the panel of lecturers (mainly the degree of the financial burden will be considered in the selection).
Continuous (discipline/attendance/academic performance) monitoring of the 15 selected scholarship holders.

(Identity of the student will not be revealed to the sponsor without consent)

How to apply

If you are a student who requires financial support through the Helping Hands scholarship program, please apply by filling the google form using the following link. You will be asked to upload a signed request letter written by you justifying why you should be selected and a letter from the Grama Niladhari of your GN division confirming your family’s financial status.

Link to the google form: https://forms.gle/SAy9V3uyFSzEPB4D8

Fill the google form on or before 22^nd of November 2022.

Implemented by Statistics society in affiliation with the Department of statistics, University of Sri Jayewardenepura.

7Oct

MSc, News

Three Day workshop on Machine Learning for Professional

A three day workshop was jointly conducted by the Department of Statistics and Department of Computer Science on 3^rd, 4^th and 10^th September 2022. The workshop was organized as an outcome of the project “Curriculum Development in Data Science and Artificial Intelligence DS&AI” which is an Erasmus + KA2 Project co-funded by the Erusmus+ program of the European Union.

The course emphasized on machine learning techniques and applications for finding interesting patterns / information from large amount of data. Participants were able to learn to design, implement, and evaluate intelligent systems incorporating models learned from large data. The target audience was the Business leaders, mid to senior managers, data specialists, consultants, and business professionals. The curriculum for the workshop was developed with the partnership of European experts aiming to up skill the professionals of ICT industry in Sri Lanka. Dr. Ravimal Bandara, Department of Computer Science, was the resource person of the workshop and it was coordinated by Dr. Chitraka Wickramarachchi, Department of Statistics.

At the end of the workshop, a certificate of participation was awarded to the participant. Further, those who successfully participated the workshop were eligible to sit for the examination conducted by Leiden University Netherlands, one of our partners from the European Union, and obtain a certificate if passed.

There were 39 participants for the workshop and the overall feedback was positive.

25Sep

News, Statistics Soceity

Higher Education webinar

Higher Education webinar; Lay the foundation to an enlightening adventure

The thinking process of a recent Statistics graduate would likely go along the lines of “now that I’ve completed my bachelors, do I apply for higher studies and pursue an academic career or do I join headfirst to the workforce?”. However, being presented with multiple crossroads can be daunting at times. Therefore educating them on what to expect when applying for higher studies can help shed some light on untangling the uncertainty of their future prospects. With this objective in mind, the Statistics Society of University of Sri Jayewardenepura organized a higher studies webinar; a knowledge sharing session from the university alumni to the undergraduates of the Faculty of Applied Sciences. This event was a continuation of the webinar on higher studies that first took place in 2021.

The higher studies webinar was successfully held on 27th August 2021, 7.00 PM onwards via Zoom with over 150 participants from all years who joined with the sole purpose of educating themselves about the opportunities that lie ahead of them in Sri Lanka and overseas. The speakers of the webinar were Ms. Vihanga Gunadasa (PhD. candidate at University of Sydney, Australia), Mrs. Dovini Jayasinghe (PhD. candidate at University of South Australia, Australia), and Mrs. Kalpani Perera (Msc. student at Simon Fraser University, Canada), who collectively shared their diverse overseas experiences on both academic and non-academic aspects.

The session started with the speakers addressing their own unique takes on managing time as an undergraduate and other general queries. In addition to the topic time management, the speakers shared their personal experiences on the level of grades and other academic qualifications that undergraduates are expected to maintain to be eligible for higher studies in foreign universities. Among other topics, the differences between different types of PhD programs and scholarships were also discussed. Finally, insights on the different outbound activities and the leisure time that is available for graduate students was shared through speakers’ personal experiences. Through this, the importance of prioritizing mental health and communicating effectively with supervisors was harped on, highlighting not only on academics but on the overall well being of higher studies candidates studying around the globe.

We thank Ms. Vihanga Gunadasa, Mrs. Dovini Jayasinghe and Mrs. Kalpani Perera from the bottom of our hearts for accepting our invitation and dedicating their precious time to inspire our fellow undergraduates. Our gratitude also extends to Dr. Rajitha Silva for his utmost support and guidance given to us in organizing the webinar and finding the right resources. We convey our thanks to the Executive Board and members of the Statistics Society for organizing and facilitating this knowledge transfer and finally all the participants for taking part in this event and sharing their queries and feedback.

Written by : Ms. Maleesha Panangala & Mr. Janith Wanniarachchi

Executive Board – 2020/2021

Statistics Society of University of Sri Jayewardenepura

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Higher Education webinar; Lay the foundation to an enlightening adventure