Danial Zendehdel
I'm As an ambitious PhD student specializing in Electronics Engineering, I have cultivated a pro- found expertise in applying machine learning and deep learning techniques to complex analytical challenges. My passion for data-driven decision-making and predictive analytics has driven me to explore the cutting edge of digital perception, focusing on image and video processing as well as statistical analysis. With a solid foundation in both theoretical and applied aspects of AI, I am eager to leverage my skills in developing high to mid-frequency trading strategies and predictive models for the equities and futures markets. My academic and project experiences have equipped me with the ability to perform large-scale data analysis, derive statistically significant models, and contribute to interdisciplinary teams aiming to optimize trading decisions through innovative machine learning applications.
Projects
Depth Estimation with Stereo 360 Cameras
Introduced a new dataset in the field of depth estimation validated across various deep learning architectures. Potential applications in autonomous vehicles and driving assistance systems.
Lane Detection by Cascade Neural Networks
Developed a segmentation and classification system for lanes using the TuSimple dataset, employing ERF-Net for segmentation and MobileNetV2 for classification.
Ship Localization and Classification
Implemented multi-output and cascade models for ship localization and classification, enhancing accuracy with modified MobileNetV2 and Xception models.
Detecting & Tracking a Target by Loomo
Focused on enhancing surveillance and monitoring systems by detecting a person of interest using pose estimation and tracking the target with YOLO.
Energy Demand Forecasting with LSTM and Prophet
Predicted future energy demand by leveraging LSTM neural networks and Prophet, analyzing historical energy usage data for accurate forecasts.
Education
PhD in Electronics Engineering
2023 - Present
Erasmus Visiting Student, Vita-Lab
2021 - 2022
Master of Science in Electrical Engineering (Electronics)
GPA: 110 e Lode
2019 - 2023
Bachelor of Science in Electrical Engineering (Electronics)
Specialized Courses GPA: 17.65/20
B.Sc Project: Building Detection via Image Processing by Matlab Software.
2013 - 2018
Skills
- Matlab
- C/C++
- Python
- Simulink
- Git
- GitHub
- ROS
- TensorFlow
- Keras
- Deep Learning
- Image Processing
- Time Series Forecasting
- VHDL
- TensorFlow
- Keras
Interests
Driven by a profound curiosity and passion for technology's potential, I am deeply interested in the application of deep learning solutions to tackle complex problems across various domains. My primary focus includes leveraging advanced algorithms and neural network architectures to enhance energy efficiency, optimize renewable energy usage, and predict energy demand with high accuracy.
Furthermore, the transformative power of computer vision fascinates me, especially in its capacity to interpret and understand visual data at a scale and depth beyond human capabilities. My interest extends to developing innovative computer vision models that can automate and revolutionize tasks in industries such as autonomous driving, healthcare, and public safety.
Time series forecasting is another area where I apply my deep learning expertise, particularly in predicting market trends, financial indicators, and environmental changes. The challenge of analyzing sequential data to forecast future events is both exciting and immensely rewarding, offering endless possibilities for innovation and impact.
Through my work and research, I aim to contribute to the development of intelligent systems that not only solve existing challenges but also anticipate future needs, driving progress and sustainability in our increasingly digital world.