Interview with Amina Mević: Machine studying utilized to semiconductor manufacturing


In a collection of interviews, we’re assembly a number of the AAAI/SIGAI Doctoral Consortium contributors to seek 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 to this point, what makes this subject so attention-grabbing, and the way she discovered the AAAI Doctoral Consortium expertise.

Inform us a bit about your PhD – the place are you finding out, and what’s the subject of your analysis?

I’m at the moment pursuing my PhD on the College of Sarajevo, School 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 Necessary Mission of Widespread European Curiosity (IPCEI) in Microelectronics. The subject of my analysis focuses on growing an explainable multi-output digital metrology system based mostly on machine studying to foretell the bodily properties of steel layers in semiconductor manufacturing.

May you give us an outline of the analysis you’ve carried out to this point throughout your PhD?

Within the first yr of my PhD, I labored on preprocessing complicated manufacturing information and making 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 data and course of physics.

Within the second yr, I developed an explanatory technique, designed to establish essentially the most related enter options for multi-output predictions.

Is there a side of your analysis that has been significantly attention-grabbing?

For me, essentially the most attention-grabbing facet is the synergy between physics, arithmetic, cutting-edge expertise, psychology, and ethics. I’m working with information collected throughout a bodily course of—bodily vapor deposition—utilizing ideas from geometry and algebra, significantly projection operators and their algebra, which have roots in quantum mechanics, to reinforce each the efficiency and interpretability of machine studying fashions. Collaborating intently with engineers within the semiconductor trade has additionally been eye-opening, particularly seeing how explanations can instantly help human decision-making in high-stakes environments. I really feel really honored to deepen my data throughout these fields and to conduct this multidisciplinary analysis.

What are your plans for constructing in your analysis to this point in the course of the PhD – what features will you be investigating subsequent?

I plan to focus extra on time collection information and develop explanatory strategies for multivariate time collection fashions. Moreover, I intend to analyze features of accountable AI inside the semiconductor trade and make sure that the options proposed throughout my PhD align with the rules outlined within the EU AI Act.

How was the AAAI Doctoral Consortium, and the AAAI convention expertise basically?

Attending the AAAI Doctoral Consortium was a tremendous expertise! It gave me the chance to current my analysis and obtain worthwhile suggestions from main AI researchers. The networking facet was equally rewarding—I had inspiring conversations with fellow PhD college students and mentors from world wide. The principle convention itself was energizing and numerous, with cutting-edge analysis introduced throughout so many AI subfields. It positively strengthened my motivation and gave me new concepts for the ultimate section 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—have been fairly restricted in my nation. I started in search of roles the place I might apply the mathematical data and problem-solving abilities I had developed throughout my research. On the time, information science gave the impression to be a great and promising subject. Nonetheless, I quickly realized that I missed the depth and objective of elementary analysis, which was typically missing in trade roles. That motivated me to pursue a PhD in AI, aiming to achieve a deep, foundational understanding of the expertise—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 data. Make certain your analysis has a objective that resonates with you personally, as that zeal will assist carry you thru challenges. There will probably be moments while you’ll really feel like giving up, however earlier than making any choice, ask your self: am I simply drained? Generally, relaxation is the answer to a lot of our issues. Lastly, discover mentors and communities to share concepts with and keep impressed.

May you inform us an attention-grabbing (non-AI associated) reality about you?

I’m an enormous science outreach fanatic! I repeatedly 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 educating assistant on the College of Sarajevo, School of Electrical Engineering, Bosnia and Herzegovina. Her analysis is carried out 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 surroundings in her nation.




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AIhub
is a non-profit devoted to connecting the AI neighborhood to the general public by offering free, high-quality info in AI.