Salahuddin Salahuddin

– Conducted LLMs domain-adaptation for cybersecurity.
– Researched alternative architectures for tasks derived from LLMs such as code classification.
– Set up multi-GPU data-distributed training for LLMs, optimizing resource efficiency.
– Conducted model training in AWS SageMaker, focusing on cloud-based ML optimization.

– Investigated PEFT algorithms for transformer LLM architectures.
– Implemented model quantization to enhance performance and reduce computational requirements.
– Set up multi-GPU data-distributed training for LLMs, optimizing resource efficiency.

• Developed and implemented machine learning and deep learning (ML/DL) algorithms for anomaly detection, pattern recognition, behavioral recognition, and the person/object detection. Achieved successful real- world applications, including facial recognition and emotion detection using OpenCV and TensorFlow.

• Prepared and processed synthetic and real-life datasets using statistical and machine learning techniques for training and testing purposes.
• Generated emotional datasets through web scraping and other methods, facilitating the development of robust emotion detection models.

• Conducted research on change detection methods for landscape alterations.
• Built end-to-end ML/DL pipelines encompassing data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment to ensure seamless performance.
• Possess expertise in deep learning frameworks like TensorFlow and PyTorch, along with proficiency in computer vision libraries such as OpenCV.

"Enrolled in the Erasmus SECCLO program, gaining specialized knowledge in Security and Cloud Computing. Expanding expertise in cutting-edge cybersecurity technologies and cloud infrastructure for a promising future in IT security."

"Pursued a Bachelor of Science in Software Engineering , gaining comprehensive knowledge and practical skills in software development, algorithms, and programming languages. I developed a strong foundation for a rewarding career in the dynamic field of software engineering with a focus on innovation and problem-solving."