Who
You are surfing Adrin Jalali‘s page, who works in the responsible / ethical AI field as a data scientist/data science consultant and did a PhD in Computational Biology, specifically machine learning in cancer diagnostics. He’s also a scikit-learn and a fairlearn core developer.
Work
These days I work on responsible and ethical AI, helping teams understand the risks, their potential unwanted biases, and to mitigate them. My work on scikit-learn, fairlearn, and model cards is certainly going in this way.
In the past I’ve worked as a consultant solving different problems for different projects, such as NLP and time series related projects. I’ve led multiple teams, been the product owner, scrum master, and tech lead in various past lives.
During my PhD I worked on disease/patient related data and I became more and more interested in healthcare related issues. I still work every now and then on healthcare projects and issues, and maybe I get back to it one day.
Want to Hire Me?
I’m always open to opportunities which are related to projects improving people’s lives, or are purely technical and related to infrastructure used by teams to do their work (my open source work is in this category). I love building communities, to cherish them, and to help them grow, and I learn a ton from those people doing so.
When choosing teammates, I rather go for a team where people bring different perspectives to the table rather than people who are strong individuals. Diversity is a quite important aspect for me in this regard.
Area of research
I used/designed machine learning tools to classify samples. The datasets I worked on vary from microarray to DNA methylation data. I was mostly focused on using gene/protein networks in order to help the classification task, while keeping in mind I need to interpret my results for a biologist. Therefore my goal was to have a method which directly uses or is inspired by the biological networks, classifies my samples, and can be interpreted on the biological level.
- Handl, L., Jalali, A., Scherer, M., Eggeling, R., & Pfeifer, N. (2019). Weighted elastic net for unsupervised domain adaptation with application to age prediction from DNA methylation data. Bioinformatics, 35(14), i154-i163.
- Jalali A., and Pfeifer N., “Interpretable per Case Weighted Ensemble Method for Cancer Associations“, BMC Genomics, volume 17, no. 1, 2016.
- [Poster] Adrin Jalali, Nico Pfeifer, “Analyzing How Protein Interaction Networks Improve Classification Performance in Gene Expression Data Analysis“, ISMB/ECCB 2013, Berlin, Germany.
I also worked on flow-cytometry data which is a single cell level data. I did it mostly when I was for 15 months in Vancouver, Canada, and I was doing research in British Columbia Cancer Research Center and The University of British Columbia. As a result of this part of my research, I can refer you to:
- Kieran O’Neill†, Adrin Jalali†, Nima Aghaeepour†, Holger Hoos, and Ryan R. Brinkman. “Enhanced flowType/RchyOptimyx: A Bioconductor pipeline for discovery in high-dimensional cytometry data.” Bioinformatics (2014), doi: 10.1093/bioinformatics/btt770
- Nima Aghaeepour†, Adrin Jalali†, Kieran O’Neill, Pratip K. Chattopadhyay, Mario Roederer, Holger H. Hoos, and Ryan R. Brinkman. “RchyOptimyx: Cellular hierarchy optimization for flow cytometry.” Cytometry Part A 81, no. 12 (2012): 1022-1030, doi: 10.1002/cyto.a.22209
- Nima Aghaeepour, Pratip K. Chattopadhyay, Anuradha Ganesan, Kieran O’Neill, Habil Zare, Adrin Jalali, Holger H. Hoos, Mario Roederer, and Ryan R. Brinkman. “Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays.” Bioinformatics 28, no. 7 (2012): 1009-1016, doi: 10.1093/bioinformatics/bts082
- [Poster] Adrin Jalali, Nima Aghaeepour, Kieran O’Neill, Andrew P. Weng, Ryan R. Brinkman, “Analysis and Classification of Lymphoma Sub-types“, British Columbia Cancer Agency Annual Conference, Victoria, BC, Canada, 2012.
†: equal contribution
List of publications available on Google Scholar.