In Fall 2022, I joined Northeastern University as an Assistant Professor in the Department of Mechanical & Industrial Engineering. My group, the Data-Driven Renewables Research (D2R2) group, is seeking to discover novel materials for renewable energy applications using high-throughput, ab-initio calculations, and data-driven materials property predictions. Check for current openings on my group website. If you have an interest and a background in the above-described fields kindly reach out to me and send me your CV. Looking forward to many exciting collaborations in this new chapter of my career!
Before I joined Northeastern University, I was Senior Scientist at Aionics Inc. and I am now supporting them as a member of their Scientific Advisory Board.
From 2020 to 2021, I was a senior postdoctoral researcher at the University of Vienna and a visiting researcher at Stanford University. My research during that time was focused on the discovery of novel materials for energy conversion applications for which I was awarded the prestigious Erwin-Schrödinger fellowship by the Austrian Science Fund (FWF). I consider myself a bilingual Scientist who can apply skills in both experimental synthesis and computational simulation to establish new material solutions for renewable energy challenges.
During my doctoral research I focused on the synthesis and characterization of nanoscale thin films for new high-efficiency solar cell and next-generation integrated circuit applications. I employed atomic layer deposition (ALD) to synthesize films with atomic precision and used transmission electron microscopy (TEM), among other techniques, to characterize the deposited materials.
My postdoctoral research focused on exploring the prediction of material properties using computational modeling and machine learning. Diving into computational material science and data-driven material discovery allowed me to broaden my expertise as a scientist. As I feel very passionate about renewable energy solutions, I crafted a research proposal aimed to discover new materials for thermionic energy conversion (TEC). Through that proposal I was awarded the prestigious Erwin-Schrödinger fellowship (from the Austrian Science Fund, FWF) which enabled me to publish my research in the high-impact journal ACS Energy Letters where it was displayed on the cover. Further, it was featured in various news outlets in Austria.
To further facilitate my material discovery goal, I have been screening a wide range of materials for potential low work function candidates with high performance computing. The work focuses on using machine learning to develop a statistically driven surrogate model to predict material surfaces’ work function.
Most of my research interests are based on (directly or indirectly) a deep understanding of properties of material surfaces, including research I have worked on with my collaborators.
Teaching is a big passion of mine and I consider it one of the main missions of any academic institution. Further details on the courses I teach are on my group's website.
Lastly, a list of all my publications can be found on here and I would be excited to hear from you and chat about science, research, teaching, among many other nerdy topics! My contact information is listed here.