Miguel Amável Pinheiru, Ph.D.

ML Engineer, MindMed

Dissertation Thesis: Graph and Point Cloud Matching for Image Registration, 2017
Programme: Electrical Engineering and Information Technology
Branch of study: Artificial Intelligence and Biocybernetics  
Supervisor: prof. Dr. Ing. Jan Kybic
 

Where do you currently work and what is the scope of your work?

I’m an ML Engineer at MindMed, a biotech company focusing on mental health, in particular aiming at using psychedelic medicines to treat psychiatric illnesses such as depression, opioid withdrawal, PTSD or anxiety. My work focuses on creating innovative solutions to improve the way we measure and monitor participants in clinical trials.

What has your doctoral studies given you for your current career?

The industry benefits greatly from a mix of academic and industrial experience when it comes to AI and Machine Learning. While the industrial experience allows you to build production-ready pipelines and improved MLOps, the academic experience provided me with a higher theoretical rigor, improved interpretability of research papers, and more experience when it comes to communicate and explain your work.  For future PhD student candidates I’d recommend two things: read a lot of papers and actively participate in the community. Most ideas for new papers or on how to solve your problem come from reading and participating on community events (conferences, meetups), frequently from areas away from your field or project.

Where have you been during your doctoral studies and where have you been at postdoc?

During my PhD studies I did two internships at the CVLab group at EPFL, Switzerland, and I’ve participated in conferences in US and Europe.  After finishing my PhD, I’ve worked in a couple of startups in Prague (where the business has always been based in the US) before the last one was acquired by my current company. I’ve also had the opportunity of spending some time in San Francisco where I met several people working in the startup world.