Hansika Hewamalage
Data Scientist
Melbourne, Victoria, Australia
Summary
🤩
Rockstar🎓
Top SchoolHansika Hewamalage is a data scientist with a decade of experience bridging academic research and industry practice, specializing in time series forecasting. She holds a PhD in Information Technology from Monash and has applied her expertise across roles at Coles Group, UNSW, and research fellowships, teaching forecasting and programming along the way. Hansika contributes to open-source forecasting tools—having improved NeuralProphet’s seasonality and holiday handling—demonstrating practical impact on core model functionality. Comfortable in both back-end engineering and ML model development, she excels at turning research insights into production-ready solutions. Known for a continuous-learning mindset, she seeks challenges that expand the frontier of applied forecasting and bring measurable business value.
10 years of coding experience
7 years of employment as a software developer
Bachelor’s Degree, Computer Science & Engineering, First Class, Overall GPA 3.93, Bachelor’s Degree, Computer Science & Engineering, First Class, Overall GPA 3.93 at University of MoratuwaPrimary Education, Primary Education at Kottawa Dharmapala VidyalayaSecondary Education, Secondary Education at Devi Balika VidyalayaDoctor of Philosophy - PhD, Information Technology, Doctor of Philosophy - PhD, Information Technology at Monash University
English, Sinhalese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
neural-network10
forecasting10
pytorch10
machine-learning10
time-series10
forecast10
python10
data-analysis10
autoregressive-models9
deep-learning9
vector-autoregression9
Programming languages (5)
Github contributions (5)
ourownstory/neural_prophet
Jun 2020 - Aug 2021
NeuralProphet: A simple forecasting package
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:137 commits, 12 PRs, 66 pushes in 1 year 2 months
Contributions summary:Hansika contributed to the NeuralProphet forecasting package by fixing a bug related to the seasonality modeling, specifically within the `time_net.py` file. They also worked on integrating support for holidays and events, as seen in modifications to the `hdays.py`, `neural_prophet.py`, and `time_dataset.py` files and the creation of a demo notebook. The user’s work directly involved improvements to the core forecasting functionality and enhancements to the model’s ability to incorporate external factors like holidays.
forecastingneuralprophetpythonforecasttime-series
HansikaPH/time-series-forecasting
Apr 2018 - Dec 2021
Recurrent Neural Network Implementations for Time Series Forecasting
Contributions:120 commits, 10 pushes, 1 branch in 3 years 8 months
forecastingimplementationstime-series-analysisdeep-learningseries-forecasting
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