Sara Hamdan, MSc student in Computational Sciences and Engineering

Can you briefly introduce yourself and share your background in AI research?

I am Sara Hamdan, currently a graduate student in the Computational Sciences and Engineering (CMSE) department at Koç University, where I am engaged in advanced research in robotic learning. My journey in AI and robotics spans nearly 14 years, starting with a deep-rooted interest in technology during my undergraduate studies. I earned my BSc in Computer Engineering and Automation, which laid the foundation for my subsequent specialization in robotics. Over the years, I have actively participated in teaching, learning, and training in AI and robotics, not only through formal education but also via self-training and involvement in international competitions. My academic path includes a master’s degree in Robotics from Damascus University, and now, my pursuit of a PhD at Koç University represents the latest chapter in my commitment to advancing AI and robotics.

 

What initially sparked your interest in the field of AI? Was there a particular moment or experience that inspired you to pursue this area of study?

My fascination with technology began early, guiding my decision to pursue a BSc in Computer Engineering and Automation. During my fourth and fifth years of undergraduate studies (2009-2010), I enrolled in courses on Control Theory and Neural Networks. These subjects introduced me to the possibilities of AI and robotics, revealing a new direction for my academic and professional pursuits. However, the pivotal moment that truly inspired me to delve deeper into AI and robotics came shortly after I graduated. A friend told me about a volunteer opportunity to train school students in robotics. They were looking for someone with a background in computer and electronic engineering, and I saw it as a chance to apply my knowledge in a practical, impactful way. Volunteering as a robotics trainer was a transformative experience. I became a certified robotics trainer and became actively involved in organizing and supervising robotics competitions like FLL (First Lego League) and WRO (World Robot Olympiad) in Syria. This hands-on experience ignited a passion for robotics and AI that went beyond academic curiosity. 

Motivated by this experience, I sought advanced knowledge and found an opportunity to pursue a master’s degree in Robotics Engineering and Programming at Damascus University. My master’s research involved significant hands-on work with robotics equipment, such as a robot from FESTO in a pneumatic lab. Under the supervision of my professor, I investigated this robot and began teaching robotics lab sessions to university students from 2013 to 2015. This period marked a transition from teaching school students to university students, allowing me to mentor and guide projects that achieved remarkable recognition, including coverage by the BBC Tech program and the Syrian national channel. These achievements were particularly significant given the challenging conditions of the Syrian war, with our university located near conflict zones. Despite the war, I remained committed to my voluntary work, contributing to robotics training and competitions across the Middle East, including Syria, Lebanon, Jordan, Qatar, and Oman. In 2015, we launched the first Arab Robotics magazine, where I served as the editor-in-chief. I also played a key role in establishing a robotics club at Damascus University, providing a platform for students to explore robotics technology.

After completing my master’s in July 2015, the ongoing conflict in Syria pushed me to seek opportunities abroad. I moved to Turkey, where I taught robotics in Gaziantep and developed a robotics curriculum for a local company. Later, I established a robotics club for another organization, introducing robotics to students for free. My journey continued at Ozyegin University in Istanbul, where I worked as a research and teaching assistant, contributing to significant projects such as CoMRAde, which involved developing a mobile manipulator capable of learning impedance-critical tasks through physical interactions with humans. These experiences honed my research skills and deepened my understanding of robotic systems and machine learning applications. Eventually, I joined Koç University’s graduate program to further my knowledge and pursue my dream of becoming a professor.

 

Could you tell us about your current research or thesis topic in AI? What motivated you to choose this specific area?

My current research focuses on robotic learning, a fascinating intersection of robotics and machine learning. This field captivates me because of its potential to enhance human capabilities, particularly in dangerous or monotonous tasks. My thesis, titled “Robotic Learning of Haptic Skills for Contact-Rich Manufacturing Tasks,” seeks to integrate human expertise with robotic precision. I am particularly interested in human-robot interaction and cooperation, believing that robots should be able to learn from humans and utilize human intelligence in decision-making processes.

In manufacturing, many tasks involve intricate contact with the environment, presenting challenges such as vibration, friction, stability, and safety. My supervisor and I are developing a Learning from Demonstration (LfD) approach that employs an interaction (admittance) controller and dual force sensors. This setup allows the robot to learn the force applied by an expert during contact-rich tasks, like robotic polishing. The aim is to imbue the robot with the haptic expertise of a human expert while enabling user intervention at any stage of the task via the interaction controller. The use of two force sensors is pivotal, as it provides critical environmental data, facilitating the training of our system to handle workpieces with varying material and surface properties, ensuring consistent and effective task performance.

 

What are some of the key challenges you’ve encountered during your research? How have you been able to overcome them?

Several key challenges have marked my research journey. One major challenge was dealing with malfunctioning hardware, such as robots and sensors, which often required ordering new parts or contacting providers for repairs. These issues consumed significant research time. The COVID-19 pandemic further complicated matters by limiting access to resources and support. To overcome these obstacles, I focused on maintaining progress despite delays, though it required considerable patience and adaptability.

Another challenge was my initial lack of knowledge about the specific difficulties faced in manufacturing tasks. To bridge this gap, I visited workshops and industry fairs, learning firsthand about the challenges in environments like car polishing. This hands-on exposure informed my research focus and strategy. Additionally, since my research involves learning from human experts, but I did not have immediate access to one, I sought out and learned from professionals in the field. I observed their techniques and invited a polishing expert to demonstrate tasks, collecting valuable data and insights.

Balancing coursework, teaching assistant responsibilities, and research was another significant challenge. Effective time management and prioritization were crucial in handling these demands, ensuring that I could excel in all areas without compromising my research progress.

 

What are some of the recent advancements or breakthroughs in AI that you find particularly fascinating or promising? How do you think these advancements can contribute to the overall progress of the field?

Recent advancements in AI, such as the development of sophisticated language models like ChatGPT, are particularly fascinating. These models demonstrate the potential for AI to understand and generate human-like text, which can be leveraged in various applications, including robotics, where natural language processing can improve human-robot communication. Additionally, deep learning techniques have significantly enhanced the learning capabilities of AI systems, enabling more complex and accurate models. Reinforcement learning is another promising area, allowing robots to learn from their environment through trial and error, leading to more adaptive and autonomous systems.

 

Can you share a memorable experience or achievement from your AI research journey so far? What did you learn from that experience?

One of the most memorable experiences in my AI research journey was establishing AI and robotic clubs to help the community learn about these technologies. This initiative required not only technical knowledge but also strong management skills. It taught me the importance of leadership and community engagement in fostering interest and expertise in AI and robotics.

A significant achievement was winning first place at the ARC conference in Qatar in 2016 with my swarm robots project. This project demonstrated the power of collaborative robotic systems and showcased the practical applications of AI in coordinating multiple robots to achieve complex tasks. The experience reinforced my understanding of AI’s potential and the importance of teamwork and innovation in research.

 

How do you balance your academic workload, personal life, and the demands of your AI research? Do you have any strategies or tips that have helped you maintain a healthy work-life balance?

Maintaining a balance between academic workload, personal life, and research is crucial. Initially, I focused entirely on research and technology, neglecting my personal life, which led to health issues. I learned the importance of prioritizing my well-being alongside my professional responsibilities. Effective time management is key—prioritizing tasks, avoiding procrastination, and setting clear goals help manage the workload. Taking time for self-care, meditation, and regular self-reflection is essential. These practices help maintain mental and physical health, ensuring sustained productivity and creativity in research. Regularly reassessing my goals and adjusting my plans helps maintain a healthy work-life balance, ensuring I can excel in both my professional and personal life.

 

How do you stay updated with the latest developments and research papers in the field of AI? Are there any particular resources or platforms you rely on?

Staying updated with the latest developments in AI is crucial for my research. I follow several YouTube channels that provide insights into recent advancements and trends. Regularly searching academic websites for the latest research papers helps me stay informed about new discoveries and methodologies. Subscribing to Google mailing lists and newsletters from AI research organizations also ensures I receive timely updates. Attending conferences, workshops, and summer schools provides opportunities to learn from experts and network with peers in the field. Following influential AI and robotics researchers on Twitter (X) and other social media platforms allows me to keep abreast of their latest work and insights, enriching my knowledge and understanding of the field.

Examples: 

• Youtube: https://www.youtube.com/@PROROBOTS
• Scopus database, online
• Google mailing lists:
  • Women in machine learning https://groups.google.com/g/women-in-machine-learning/about
  • Computer vision and machine learning: https://lists.auth.gr/sympa/info/cvml
  • Reinforcement learning: https://groups.google.com/g/rl-list/about?hl=en
  • Machine Learning news: https://groups.google.com/g/ml-news
  • Human – robot interaction: https://humanrobotinteraction.org/resources/

AI robotics: https://groups.google.com/g/ai-robotics?pli=1

 

Are there any specific mentors or role models who have influenced your AI journey? How have they inspired you?

Several mentors and role models have significantly influenced my AI journey. Ossama Khatib, a renowned robotics and AI expert, has been a major inspiration due to his remarkable achievements and resilience in the face of challenges. His work demonstrates the potential and impact of AI in robotics, motivating me to pursue excellence in my research. My high school physics teacher played a pivotal role in sparking my interest in technology and encouraging me to pursue computer engineering. Additionally, a university professor who taught control theory significantly shaped my academic path, providing me with the foundational knowledge and inspiration to delve deeper into AI and robotics.

 

What advice would you give to aspiring students who are interested in pursuing a career in AI and considering graduate studies?

For those aspiring to a career in AI, it’s essential to stay updated with the latest technologies and trends in the field. Gaining real-world experience through internships, projects, and research collaborations is invaluable. Don’t isolate yourself with just theoretical knowledge—actively participate in summer schools, conferences, and seminars to broaden your understanding and network with experts and peers.

Sharing your knowledge with the community through presentations, publications, and teaching can enhance your learning and establish your presence in the field. Focus on developing strong problem-solving skills and be persistent in overcoming challenges. Always be curious and open to learning new things, as AI is a rapidly evolving field that requires continuous learning and adaptation.

A book and movie that you recommend (they don’t have to be related to ai)

I highly recommend the movie “Interstellar,” which inspired my interest in technology, AI, and space. The film’s exploration of complex scientific concepts and its portrayal of human ingenuity and perseverance resonate deeply with my passion for AI and robotics. For a book, “Harry Potter” is my choice. The series features characters who demonstrate hard work, determination, and resilience, qualities essential for success in any field. The magical world of Harry Potter also sparks creativity and imagination, which are crucial in innovative fields like AI.

 

During the research did you have any experiences with unexpected or surprising results? How did you navigate those outcomes and what insights did you gain from that experience?

Yes, the environmental contact in my research introduced significant variability, leading to unexpected results. Navigating these outcomes involved conducting numerous experiments, meticulously recording observations, and continuously refining my approach. This iterative process taught me the importance of adaptability and persistence in research. These unexpected results also highlighted the complexity of real-world applications, emphasizing the need for robust and flexible AI models.