Artificial Intelligence helps biotechnology researchers analyze complex biological data, discover patterns, automate processes, and improve decision-making in life science research.

Computer Vision enables machines to analyze biological images such as microscopy images and medical images through detection, classification, segmentation, and automated image analysis.

Maryam Hekmat AI focuses on projects combining biotechnology knowledge with Artificial Intelligence, Machine Learning, Deep Learning, and Computer Vision for solving real-world problems.

AI models can analyze medical images to detect patterns, classify images, perform segmentation, and support researchers in extracting valuable information from complex visual data.

Common technologies include Python, PyTorch, TensorFlow, Scikit-learn, OpenCV, YOLO, and modern deep learning architectures.

AI is a powerful supporting tool that helps researchers analyze data faster. Human scientific knowledge remains essential for interpretation and innovation.

My background in Biotechnology helps me understand biological problems, while Artificial Intelligence provides powerful tools to analyze complex data and develop intelligent solutions.

Biological Image Analysis uses Artificial Intelligence and Computer Vision techniques to analyze images from biological research, including microscopy images, cell analysis, and laboratory data.

Artificial Intelligence can support drug discovery by analyzing biological datasets, identifying patterns, predicting molecular properties, and accelerating research workflows in life sciences.

I develop AI solutions focused on Computer Vision, including image classification, object detection, segmentation, biological image analysis, and real-time visual applications.