Hello everyone, I am applying for the Erasmus Mundus Joint Master in IPCVAI (Image Processing, Computer Vision & AI) and have drafted my motivation letter. I would greatly appreciate a review for clarity, coherence, alignment with EMJM requirements, and suggestions for improvement.
Motivation Letter
Master Program in Image Processing &
Computer Vision AI
Respected Members of the Selection Committee,
I am seeking a Master's program that offers advanced research in image processing, computer vision, and multimodal AI, while providing an interdisciplinary and international learning environment. The Erasmus Mundus Joint Master in IPCVAI aligns perfectly with my ambition to develop AI systems capable of reasoning about complex 3D environments and understanding spatial relationships with human-like intuition. This program's combination of foundational, advanced, and research-oriented courses across three partner universities presents a unique opportunity to gain comprehensive expertise and international exposure.
I completed my Bachelor's in Computer Science, earning a Gold Medal for achieving the highest academic standing in my program. My undergraduate studies provided a solid foundation in machine learning, deep learning, and computer vision, along with practical skills in data preprocessing, algorithmic design, and software development. During my Master's research, I focused on unstructured 3D point cloud segmentation, gaining hands-on experience with sparse 3D data and complex geometric structures. While current systems could identify objects, they often failed to reason about spatial relationships and contextual meaning-for instance, detecting chairs in a room but not determining which chair was closest to a window or whether a table could hold multiple objects. This limitation highlighted the need for AI systems that integrate geometric understanding with semantic reasoning, inspiring my current research vision: developing 3D Vision-Language Models (3D-VLMs) capable of interpreting spatial relationships, scene layouts, and object interactions, while remaining data-efficient through instruction-guided fine-tuning and geometric representation learning.
I have carefully chosen the IPCVAI partner universities to align with my research and learning goals. PPKE, Budapest, offers foundational courses such as Basic Image Processing Algorithms, Data Mining and Machine Learning, and Fundamentals for Deep Learning, which will provide a solid technical base. UAM, Madrid, provides advanced courses in Deep Learning for Visual Signal Processing, High-Performance Computing, and Vision for Multiple or Moving Cameras, perfectly complementing my research focus on efficient 3D-VLM development and multi-camera reasoning. Finally, UBx, Bordeaux, focuses on Explainable AI, AI for Sustainability, Advanced Computer Vision, and Medical Imaging, which aligns with my interdisciplinary goals and introduces considerations of ethical, interpretable, and sustainable AI.
During my first year, I plan to focus on building a strong foundation in image processing, deep learning, and computer vision at PPKE and UAM, completing the core courses and small research projects to refine my technical skills. The second year at UBx will be dedicated to advanced research, Explainable AI, sustainability, and my Master's thesis, where I will integrate my learning into developing novel 3D Vision-Language Models capable of reasoning about complex spatial relationships in real-world 3D scenes. For my thesis, I plan to explore geometric representation learning, instruction-guided fine-tuning, and efficient data utilization, addressing the critical challenge of creating AI models that understand both geometry and semantics while minimizing dependence on large annotated datasets.
In addition to my academic preparation, my professional experience as an Android engineer has honed my skills in designing, implementing, and testing complex software systems under strict constraints. These skills are directly transferable to AI research, where clean, reliable code and efficient experimentation pipelines are crucial. Managing complex projects, coordinating technical tasks, and delivering robust solutions have strengthened my ability to contribute effectively to IPCVAI's collaborative research environment.
My goal is to become a leading researcher in 3D Vision-Language AI, creating systems capable of interpreting complex 3D environments with human-like spatial reasoning. I aim to contribute to innovations in robotics, AR/VR applications, autonomous systems, and energy-efficient AI solutions. By integrating my technical expertise with insights from IPCVAI, I aspire to create AI solutions that advance both academic knowledge and real-world technological progress.
I am confident that the Erasmus Mundus IPCVAI program represents a unique opportunity to accelerate my research and career ambitions. By combining advanced coursework, practical lab experience, and exposure to multiple European research environments, the program will equip me to develop AI systems that integrate visual perception, spatial reasoning, and language comprehension. I sincerely hope for the opportunity to join IPCVAI, contribute meaningfully to its research community, and further my journey toward becoming a leading researcher in multimodal AI.
Thank you for your valuable time and consideration.
Motivation Letter
Master Program in Image Processing &
Computer Vision AI
Respected Members of the Selection Committee,
I am seeking a Master's program that offers advanced research in image processing, computer vision, and multimodal AI, while providing an interdisciplinary and international learning environment. The Erasmus Mundus Joint Master in IPCVAI aligns perfectly with my ambition to develop AI systems capable of reasoning about complex 3D environments and understanding spatial relationships with human-like intuition. This program's combination of foundational, advanced, and research-oriented courses across three partner universities presents a unique opportunity to gain comprehensive expertise and international exposure.
I completed my Bachelor's in Computer Science, earning a Gold Medal for achieving the highest academic standing in my program. My undergraduate studies provided a solid foundation in machine learning, deep learning, and computer vision, along with practical skills in data preprocessing, algorithmic design, and software development. During my Master's research, I focused on unstructured 3D point cloud segmentation, gaining hands-on experience with sparse 3D data and complex geometric structures. While current systems could identify objects, they often failed to reason about spatial relationships and contextual meaning-for instance, detecting chairs in a room but not determining which chair was closest to a window or whether a table could hold multiple objects. This limitation highlighted the need for AI systems that integrate geometric understanding with semantic reasoning, inspiring my current research vision: developing 3D Vision-Language Models (3D-VLMs) capable of interpreting spatial relationships, scene layouts, and object interactions, while remaining data-efficient through instruction-guided fine-tuning and geometric representation learning.
I have carefully chosen the IPCVAI partner universities to align with my research and learning goals. PPKE, Budapest, offers foundational courses such as Basic Image Processing Algorithms, Data Mining and Machine Learning, and Fundamentals for Deep Learning, which will provide a solid technical base. UAM, Madrid, provides advanced courses in Deep Learning for Visual Signal Processing, High-Performance Computing, and Vision for Multiple or Moving Cameras, perfectly complementing my research focus on efficient 3D-VLM development and multi-camera reasoning. Finally, UBx, Bordeaux, focuses on Explainable AI, AI for Sustainability, Advanced Computer Vision, and Medical Imaging, which aligns with my interdisciplinary goals and introduces considerations of ethical, interpretable, and sustainable AI.
During my first year, I plan to focus on building a strong foundation in image processing, deep learning, and computer vision at PPKE and UAM, completing the core courses and small research projects to refine my technical skills. The second year at UBx will be dedicated to advanced research, Explainable AI, sustainability, and my Master's thesis, where I will integrate my learning into developing novel 3D Vision-Language Models capable of reasoning about complex spatial relationships in real-world 3D scenes. For my thesis, I plan to explore geometric representation learning, instruction-guided fine-tuning, and efficient data utilization, addressing the critical challenge of creating AI models that understand both geometry and semantics while minimizing dependence on large annotated datasets.
In addition to my academic preparation, my professional experience as an Android engineer has honed my skills in designing, implementing, and testing complex software systems under strict constraints. These skills are directly transferable to AI research, where clean, reliable code and efficient experimentation pipelines are crucial. Managing complex projects, coordinating technical tasks, and delivering robust solutions have strengthened my ability to contribute effectively to IPCVAI's collaborative research environment.
My goal is to become a leading researcher in 3D Vision-Language AI, creating systems capable of interpreting complex 3D environments with human-like spatial reasoning. I aim to contribute to innovations in robotics, AR/VR applications, autonomous systems, and energy-efficient AI solutions. By integrating my technical expertise with insights from IPCVAI, I aspire to create AI solutions that advance both academic knowledge and real-world technological progress.
I am confident that the Erasmus Mundus IPCVAI program represents a unique opportunity to accelerate my research and career ambitions. By combining advanced coursework, practical lab experience, and exposure to multiple European research environments, the program will equip me to develop AI systems that integrate visual perception, spatial reasoning, and language comprehension. I sincerely hope for the opportunity to join IPCVAI, contribute meaningfully to its research community, and further my journey toward becoming a leading researcher in multimodal AI.
Thank you for your valuable time and consideration.
