In a sequence of interviews, we’re assembly among the AAAI/SIGAI DOCTORAL Consortium members to search out out extra about their analysis. On this newest interview, we hear from Amina Mević who’s making use of machine studying to semiconductor manufacturing. Discover out extra about her PhD analysis up to now, what makes this subject so fascinating, and the way she discovered the AAAI Doctoral Consortium expertise.
Inform us a bit about your PhD – the place are you learning, and what’s the matter of your analysis?
I’m presently pursuing my PhD on the College of Sarajevo, College of Electrical Engineering, Division of Pc Science and Informatics. My analysis is being carried out in collaboration with Infineon Applied sciences Austria as a part of the Essential Venture of Frequent European Curiosity (IPCEI) in Microelectronics. The subject of my analysis focuses on growing an explainable multi-output digital metrology system primarily based on machine studying to foretell the bodily properties of metallic layers in semiconductor manufacturing.
May you give us an summary of the analysis you’ve carried out up to now throughout your PhD?
Within the first 12 months of my PhD, I labored on preprocessing complicated manufacturing knowledge and getting ready a strong multi-output prediction setup for digital metrology. I collaborated with trade specialists to grasp the method intricacies and validate the prediction fashions. I utilized a projection-based choice algorithm (ProjSe), which aligned nicely with each area information and course of physics.
Within the second 12 months, I developed an explanatory technique, designed to determine essentially the most related enter options for multi-output predictions.
Is there a side of your analysis that has been notably fascinating?
For me, essentially the most fascinating facet is the synergy between physics, arithmetic, cutting-edge know-how, psychology, and ethics. I’m working with knowledge collected throughout a bodily course of—bodily vapor deposition—utilizing ideas from geometry and algebra, notably projection operators and their algebra, which have roots in quantum mechanics, to boost each the efficiency and interpretability of machine studying fashions. Collaborating carefully with engineers within the semiconductor trade has additionally been eye-opening, particularly seeing how explanations can straight help human decision-making in high-stakes environments. I really feel actually honored to deepen my information throughout these fields and to conduct this multidisciplinary analysis.
What are your plans for constructing in your analysis up to now in the course of the PhD – what elements will you be investigating subsequent?
I plan to focus extra on time sequence knowledge and develop explanatory strategies for multivariate time sequence fashions. Moreover, I intend to analyze elements of accountable AI inside the semiconductor trade and make sure that the options proposed throughout my PhD align with the ideas outlined within the EU AI Act.
How was the AAAI Doctoral Consortium, and the AAAI convention expertise on the whole?
Attending the AAAI Doctoral Consortium was a tremendous expertise! It gave me the chance to current my analysis and obtain helpful suggestions from main AI researchers. The networking facet was equally rewarding—I had inspiring conversations with fellow PhD college students and mentors from all over the world. The primary convention itself was energizing and numerous, with cutting-edge analysis offered throughout so many AI subfields. It undoubtedly strengthened my motivation and gave me new concepts for the ultimate part of my PhD.
Amina presenting two posters at AAAI 2025.
What made you wish to examine AI?
After graduating in theoretical physics, I discovered that job alternatives—particularly in physics analysis—had been fairly restricted in my nation. I started on the lookout for roles the place I might apply the mathematical information and problem-solving abilities I had developed throughout my research. On the time, knowledge science seemed to be a really perfect and promising subject. Nonetheless, I quickly realized that I missed the depth and function of basic analysis, which was usually missing in trade roles. That motivated me to pursue a PhD in AI, aiming to realize a deep, foundational understanding of the know-how—one that may be utilized meaningfully and utilized in service of humanity.
What recommendation would you give to somebody considering of doing a PhD within the subject?
Keep curious and open to studying from completely different disciplines—particularly arithmetic, statistics, and area information. Ensure your analysis has a function that resonates with you personally, as that zeal will assist carry you thru challenges. There shall be moments while you’ll really feel like giving up, however earlier than making any choice, ask your self: am I simply drained? Typically, relaxation is the answer to lots of our issues. Lastly, discover mentors and communities to share concepts with and keep impressed.
May you inform us an fascinating (non-AI associated) truth about you?
I’m an enormous science outreach fanatic! I usually volunteer with the Affiliation for the Development of Science and Expertise in Bosnia, the place we run workshops and occasions to encourage youngsters and highschool college students to discover STEM—particularly in underserved communities.
About Amina
Amina Mević is a PhD candidate and instructing assistant on the College of Sarajevo, College of Electrical Engineering, Bosnia and Herzegovina. Her analysis is performed in collaboration with Infineon Applied sciences Austria as a part of the IPCEI in Microelectronics. She earned a grasp’s diploma in theoretical physics and was awarded two Golden Badges of the College of Sarajevo for reaching a GPA increased than 9.5/10 throughout each her bachelor’s and grasp’s research. Amina actively volunteers to advertise STEM training amongst youth in Bosnia and Herzegovina and is devoted to enhancing the analysis atmosphere in her nation.
AIhub
is a non-profit devoted to connecting the AI group to the general public by offering free, high-quality data in AI.
AIhub
is a non-profit devoted to connecting the AI group to the general public by offering free, high-quality data in AI.
