Bilawal Singh Deu
I'm a Software Enginner
About Me
I am a third-year B.Tech student at Plaksha University, specializing in Computer Science and Artificial Intelligence, with a strong foundation in algorithms, machine learning, and software development. I am passionate about leveraging AI to solve complex problems and driving innovation through technology.
AI/ML Developer.
Driven AI/ML enthusiast with expertise in developing innovative solutions to solve real-world challenges using cutting-edge technologies. Passionate about pushing the boundaries of artificial intelligence in creative and impactful ways.
- Degree: B. Tech. in CS & AI
- Phone: +91 90419 44120
- Seeking: Summer Internship
- Email: bilawaldeu[@]gmail[dot]com
I strongly believe in the intertwining of technology and entrepreneurship. I won the best customer validation award at TYE Global Competition USA. I won the Strawberry Fields High School Shark Tank competition and was also recognised as a top 10 global finalist in the quality education challenge of UN sustainable development goals. Fascinated by the limitless possibilities of AI, I have undertook various courses related to Machine Learning and Pattern Recognition, Data mining and Design and Analysis of Algorithms to name a few.
Skilled in leveraging advanced machine learning algorithms and data analytics to build intelligent systems that deliver meaningful results. Proficient in Python, TensorFlow, and deep learning frameworks, with a strong focus on innovation and efficiency. Eager to contribute to dynamic teams and impactful projects during a summer internship.
Programming Skills:
C, C++, Python and its libraries like - Pandas, NumPy, PyTorch, Keras, OpenCV, Shapely, TensorFlow, Matplotlib, rasterio, GeoPandas, Linux shell scripting, Matlab, ROS2, MySQL, VI/VIM editor, Cursor, PyCharm, GIT, GitHub.
Other Skills:
Strong problem-solving and critical thinking abilities, combined with analytical skills, adaptability, and creativity. Excellent teamwork, communication, time management, and attention to detail.
Projects
This portfolio showcases a range of innovative IT solutions, from data-driven platforms to social impact initiatives. Each project demonstrates proficiency in designing user-centric systems, leveraging technology to address real-world challenges, and delivering impactful outcomes.
- All
- Personal
- University
- Internships
Neural Style Transfer
The project focuses on exploring neural style transfer (NST) to merge artistic styles with content images, addressing the challenge of achieving high-quality style integration while preserving content fidelity. It evaluates various deep learning architectures and loss functions to optimize NST methodologies.
Price Predictability of Key Commodities
The project aims to analyze the price predictability of key commodities—Gold, Crude Oil, and Coffee—by addressing challenges in time series data, such as non-stationarity, seasonality, and volatility clustering. It seeks to understand interdependencies and enhance forecasting accuracy for global commodity markets.
Stubble Burning Prediction
The project tackles the issue of stubble burning in Punjab, India, a significant contributor to air pollution and public health hazards. It aims to predict stubble burning hotspots, identify sustainable alternatives to crop residue burning, and create practical frameworks to incentivize environmentally friendly farming practices.
Mining the Mines
The project addresses the challenges of detecting and monitoring unauthorized mining activities in resource-rich regions like Africa and Southeast Asia. These activities often cause severe environmental, social, and economic issues due to inadequate regulation and monitoring. The goal is to develop an accurate system for identifying mining sites using satellite imagery to support enforcement, conservation, and sustainable resource management.
Sugarcane Yield Prediction
The project aims to enhance precision agriculture by accurately estimating sugarcane yields using satellite imagery. It addresses challenges such as identifying water and nitrogen stress factors, estimating crop heights, and optimizing farming practices across diverse farm sizes for better resource management and sustainability.
