Arturo Lopez Pineda, PhD
Being part of one of the foundational Biomedical Informatics programs in the world was an extraordinary experience in my life, which has carried over through my professional career with an extended network of peers and collaborators. During my time at Pitt DBMI, I experienced the breadth and depth of biomedical informatics ranging from public health and clinical informatics to translational bioinformatics, including an immersive experience in clinical settings, internships, and rigorous methodological training.
My journey at DBMI started with Dr. Rich Tsui, with whom I learned about natural language processing (NLP) and machine learning (ML) to support influenza detection in a real-world setting. I also had a fantastic group of professors including Drs. Shyam Visweswaran and Greg Cooper who specialize in the development of novel artificial intelligence methodologies, a characteristic which I heavily value about my training at Pitt DBMI.
I continued my journey with a summer internship on Global Health Informatics in Lilongwe, Malawi, where Dr. Gerry Douglas was a fantastic mentor given my interest in enhancing the biomedical informatics capabilities of low- and middle-income countries. This experience was nicely rounded with Dr. Harry Hochheiser’s classes on the human computer interaction (HCI) of electronic health records (EHR). To this day, I remember this internship as a fulfilling experience where I realized how simple tools, yet very powerful ones, can have great impact on healthcare and people's lives.
Evidently, my journey would have not been completed without a deep dive into bioinformatics and the emerging genomic technologies that are now transforming our healthcare systems (in the USA and in the world). I was extremely fortunate to have Dr. Vanathi Gopalakrishnan as my mentor and PhD advisor, with whom I explored the use of machine learning models to the classification of lung cancer subtypes with gene expression and methylation data. The goal of my dissertation was to obtain parsimonious models that can be both accurate from a ML perspective, but also small enough in the number of genomic variables that they employ, so that these models can be interpreted and understood by human experts. A simple analogy to this approach would be an extremely leafy tree which is significantly trimmed until a shorter smaller, more manageable tree emerges, retaining all the nice properties from the original tree. Dr. Gopalakrishan's guidance was fundamental in the successful completion of my dissertation.
My experience in Pittsburgh included seeing snow for the first time in my life, eating new international food, and also making great friends. Pitt and DBMI are a welcoming place, which is reflected by its fantastic faculty (I've mentioned most already, but I'll also acknowledge Dr. Roger Day, my Spanish statistics course and discussions was something unique); the inspiring leadership by DBMI's department chair, Dr. Michael Becich; and program director, Dr. Rebecca Jacobson (now at UPMC enterprises); and the fantastic admin staff, where Ms. Toni Porterfield truly deserves my upmost admiration and gratitude for making my grad school experience a fantastic one, from admissions to now an alumnus of the program. Hail to Pitt!
- The International Fulbright Science and Technology Award (2010-2013)
- Marco Ramoni Award for Translational Bioinformatics (2015)
- Mexico’s National System of Researchers (2016-current)
Publications (link to myNCBI): https://www.ncbi.nlm.nih.gov/myncbi/arturo.lopez-pineda.1/bibliography/public/