Optimization and Validation of an Innovative Early Warning System for Pollen, Air Pollutants, and Complex Environmental Factors

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I’m currently pursuing my PhD at the Center for Climate Resilience (CCR) of the 伟德国际_伟德国际1946$娱乐app游戏 of Augsburg. With more than two years of experience as a Research Associate at Technische Hochschule Deggendorf, I’ve worked on projects combining AI, machine learning, and data analysis.

I’m passionate about using AI to tackle real-world challenges, especially those that benefit society and the environment. I believe in the power of technology to drive meaningful change, whether it’s improving health systems or addressing environmental issues. Outside of work, I’m driven by curiosity and a love for continuous learning and exploring new ideas.

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As an area of study, climate resilience is for me a decisive element in tackling one of the greatest challenges of the current world’s society – climate change. It is evident that the approach cannot be restricted solely to mitigation, but rather cope and adapt to changes in a harsh environment. Climate resilience is the protection of societies, the environment, and the economy while promoting better processes.
My focus is on using methods that are data-oriented and on the application of artificial intelligence in achieving climate resilience goals. With the help of advanced technologies, we are enabled to assess environmental effects, estimate climate risks and climate and develop adaptive solutions that are optimal for a region but effective in a global sense.

In my case, it is not an area of professional activity but rather a matter of personal motivation. My goal is to shape a world in which science and technology advances, combined with a society’s comprehension of the issues, resulting in long-lasting sustainable, fair, and robust systems.

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• Bachelor's degree in Electronics & Communication at Tribhuvan 伟德国际_伟德国际1946$娱乐app游戏 in Nepal
• Master's degree in Information & Communication Systems at TU Chemnitz, with a focus on AI and ML
• Master thesis project on medical image concept detection using the Xception Model, achieving top 5 rank group-wise and publishing research
• Research Associate at TH Deggendorf, working on:
  • NLP analysis of medieval church descriptions
  • Time-series analysis and forecasting for meteorological data
  • Development of Streamlit dashboards for data visualization
  • Unsupervised clustering techniques for houses with respect to behavioral patterns

My Master's thesis, centered on concept detection in medical images using deep learning, was published as a conference paper and contributed to a Top 5 group performance in the ImageCLEF competition.
Here is the link.

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