WiDS Sri Lanka Datathon Workshop 2023

  • 4Speakers
  • 100+Registrants
  • 1Days

This event has passed. We thank all of you who attended

January 21, 2023
10.00 a.m - 4.00 p.m

Welcome to WiDS Conference Sri Lanka 2023

WiDS Sri Lanka is an independent event that is organized by WiDS Ambassadors Sri Lanka as part of the annual WiDS Worldwide conference organized by Stanford University and an estimated 200+ locations worldwide, which features outstanding women doing outstanding work in the field of data science. All genders are invited to attend all WiDS Worldwide conference events.

About Women in Data Science (WiDS) Stanford Conference


Shenali is a data scientist with more than 5 years of experience, currently working on analytics and data science at HNB PLC. Prior to joining HNB, she was working as a talent analyst at MAS Holdings. Apart from her experience in the domain of data science, she is also an award-winning public speaker, youth development mentor, teacher and creative writer.

Shenali Fernando

Data Scientist,
Hatton National Bank PLC

Vimukthini is a PhD candidate at the School of Computing, Australian National University, conducting research on developing evaluation measures for open-world learning systems. She is working as a member of the DARPA-initiated project “Science of Artificial Intelligence and Learning for Open-world Novelty (SAIL-ON)”. She has worked as a data analyst for the Australian Capital Territory Government, the CSIRO and as an Assistant Lecturer at the University of Colombo.

Vimukthini Pinto

PhD Candidate,
Australian National University

Beshani is an Associate Data Engineer at IPCIS data services and a Consultant at Kainovation Technologies, which specializes in transforming business processes with Data and AI-driven solutions. She graduated from the University of Colombo with a Gold Medal for the Best Research in Statistics. She co-supervised several undergraduate research projects during the last couple of years. Her current research interests include machine learning, deep learning, and NLP.

Beshani Weralupitiya

Kainovation Technologies

Presenting to you the most outstanding Science Student in the Faculty of Science University of Colombo for the year 2021. Saumya is currently working at Acuity Knowledge Partners after graduating as a Statistics honours graduate with 4 gold medals from the University of Colombo. She is a speaker and an announcer, who is eagerly starting her career in Data Science.

Saumya Karunadhika

Analyst in Specialized Solutions,
Acuity Knowledge Partners

WiDS Datathon 2023 Challenge

This year’s datathon will focus on longer-term weather forecasting to help communities adapt to extreme weather events caused by climate change. The dataset for Phase I was created in collaboration with Climate Change AI (CCAI). In Phase I, WiDS participants will submit forecasts of temperature and precipitation for one year, competing against the other teams as well as official forecasts from NOAA.

  • WiDS Datathon Phase I will be open January - March 2023
  • WiDS Datathon Phase II will be open March - June 2023
  • Open to individuals or teams of up to 4, at least half of each team must be individuals who identify as women.
  • Participants can be students, faculty, government workers, members of NGOs, or industry members.

Watch Video

Want to know more?

Extreme weather events are sweeping the globe and range from heat waves, wildfires and drought to hurricanes, extreme rainfall and flooding. These weather events have multiple impacts on agriculture, energy, transportation, as well as low resource communities and disaster planning in countries across the globe. Accurate long-term forecasts of temperature and precipitation are crucial to help people prepare and adapt to these extreme weather events. Currently, purely physics-based models dominate short-term weather forecasting. But these models have a limited forecast horizon. The availability of meteorological data offers an opportunity for data scientists to improve sub-seasonal forecasts by blending physics-based forecasts with machine learning. Sub-seasonal forecasts for weather and climate conditions (lead-times ranging from 15 to more than 45 days) would help communities and industries adapt to the challenges brought on by climate change.
In Phase II, the Data Science Exploration Challenge, we will invite participants to take a deeper dive into one of multiple climate-change related datasets from CCAI and affiliated partners, and MIT, encouraging open-ended and deeper exploration of a topic of interest. Structured mentorship will be provided by the WiDS Datathon team and collaborators to help participants engage with more creative, open-ended problem solving. Participants will submit a blog post on Medium for either a general or a research audience.
The datasets and challenge will be accessible to both beginners and experienced participants from industry, government, NGOs and academia. Whether you’re currently working in the field or just starting to learn about data science, we welcome all participants. For those who have never tried machine learning, we will be releasing a series of guides to help you get started with the algorithms and dataset. Many WiDS ambassadors will host datathon workshops, where participants will be able to receive mentorship, form teams, and hone their data science skills. The datathon is open to individuals or teams of up to 4; at least half of each team must be individuals who identify as women.
You can participate in the Kaggle competition (Phase I) from early January to late February and the Data Science Exploration Challenge (Phase II) from March to June. The WiDS Datathon team provides webinars, tutorials, resources, team building opportunities, and other materials to help guide teams. Training and validation sets will be provided for model development; you will then upload your predictions for a test set to Kaggle and these will be used to determine the public leaderboard rankings and the winners of the competition. Winners will be announced at the WiDS Stanford conference held in-person, and online, on March 8, 2023. Beyond the leaderboard rankings, Phase I prizes will also be awarded to winners by continent and for the best high school and undergraduate teams. Phase II blog post submissions will be reviewed for their potential for real-world impact, rigor in scientific methodology, and clarity of communication by subject matter experts. Winners will be determined by “Popular Votes” on Medium.com and honorary mentions.
Make plans to join us for the WiDS Datathon 2023. We recommend you:
  • Sign up now to participate.
  • Set up your account on Kaggle.
  • Join the WiDS datathon mailing list to make sure you receive datathon news and announcements.