I’m a PhD Researcher in Data Science and AI at Monash University, working on time-series analysis and efficient deep learning, with a focus on developing models that are accurate, scalable, and effective for real-world applications.
My current research focuses on efficient sequence modeling and representation learning for time series, with particular interests in State Space Models (SSMs), self-supervised learning, Generative AI, and diffusion models.
- Time-Series Analysis
- State Space Models (SSMs) & Efficient Sequence Modeling
- Representation Learning
- Self-Supervised Learning
- Deep Learning & Machine Learning
- Generative AI
- Diffusion Models
- Feature Selection & Optimization
- Efficient and Scalable AI
I’m particularly interested in understanding how representation learning and generative approaches can improve the learning of complex temporal and sequential data, with applications in AI for Good, including:
- 🏥 Healthcare and biomedical applications
- ⚡ Energy systems and sustainability
- 📊 Complex multivariate time-series problems
My research combines deep learning, sequence modeling, representation learning, and optimization to develop efficient models for complex sequential data.
A particular focus of my work is exploring State Space Models and other efficient architectures for learning long-range temporal dependencies while maintaining computational and memory efficiency.
I’m also interested in the emerging intersection of time-series representation learning, self-supervised learning, Generative AI, and diffusion models, with the goal of developing more capable and generalizable models for temporal data.
Python · MATLAB · PyTorch · Deep Learning · Machine Learning · Time Series · State Space Models · Representation Learning · Self-Supervised Learning · Generative AI · Diffusion Models · Optimization · Feature Selection · Control Systems
I’m interested in research collaborations and projects related to:
- Time-Series Analysis
- State Space Models & Sequence Modeling
- Representation Learning
- Self-Supervised Learning
- Generative AI & Diffusion Models
- Deep Learning & Machine Learning
- Data Mining
- Optimization
- AI for Healthcare and Energy
📫 Feel free to connect or collaborate on research involving efficient learning, representation learning, and generative modeling for sequential and temporal data.