Aziz Khan

Before joining MBZUAI, Professor Khan was a senior research scientist at Stanford Cancer Institute, Stanford University where he led a bioinformatics team and developed scalable infrastructure for analyzing large-scale cancer multi-omic datasets. He contributed to major multi-institutional consortiums, including the Human Tumor Atlas Network (HTAN) and the Metastasis Research Network (MetNet). At Stanford University he also served as an Instructor for Stanford Biosciences to develop and teach a course on the art of reproducible science.

His academic journey, spanning a PhD and postdoctoral work, deciphered the mechanisms underlying gene regulation, particularly by developing tools and resources for regulatory genomics. For over five years at Stanford Cancer Institute, he expanded his focus to cancer genomics by contributing to large-scale consortia to understand the mutational processes and complex rearrangements driving cancer initiation, progression, and evolution.

Beyond his research, Professor Khan is a strong advocate for open science, reproducibility, and collaborative computational biology. He has developed widely used bioinformatics tools and resources such as JASPAR, Intervene, dbSUPER, and UniBind, which have become essential resources in regulatory genomics and transcription factor binding studies. He is also a Certified Instructor for The Carpentries, providing hands-on training in software and genomics data science. His commitment to open research is further demonstrated through his roles as an eLife and ASAPbio Community Ambassador, where he has actively promoted transparency and accessibility in scientific publishing.

Professor Khan has been deeply engaged in teaching and mentorship, designing and leading courses on computational reproducibility, bioinformatics, and multi-omics analysis. He has organized numerous workshops and training programs globally, equipping early-career researchers with the skills needed to work with large-scale genomic datasets. He is passionate to contribute to advancing computational biology and translational genomics in the Global South.

• Postdoctoral Fellow, NCMM, University of Oslo, Norway
• PhD in Bioinformatics, Tsinghua University, China
• MS in Computer Science, National University of Computer and Emerging Sciences, Pakistan
• MSc in Information Technology, Quaid-i-Azam University, Pakistan
• BSc in Mathematics and Physics, Forman Christian College, Pakistan

• Exchange Grant, Life Science Alliance, EMBL and Stanford University (2023)
• Staff Affiliate, Stanford Data Science - Center for Open and Reproducible Science (SDS-CORES) (2024-2025)
• STEM Teaching Certificate, CIRTL, Stanford University, USA (2024)
• PMP Certification, Project Management Institute (2024)
• Certified Carpentries Instructor, The Carpentries (2023)
• Academic Advisor, Namal University, Pakistan (2021 – 2023)
• Erasmus+ Mobility Grant, European Commission (2019)
• Program Review Committee, The Bioinformatics Open Source Conference (2020-2024)
• Open Bioinformatics Foundation (OBF) Travel Fellowship (2019)
• CSC full PhD Scholarship, Chinese Scholarship Council (2012 – 2016)
• Outstanding Doctoral Dissertation (runner-up), Tsinghua University, China (2016)
• Biocuration Travel Fellowship, Biocuration Conferences (2019, 2018)
• TWAS BioVision.Next Fellowships, The World Academy of Sciences (2013, 2014)
• Research Travel Grant, Higher Education Commission (HEC), Pakistan (2012, 2016)
• Community Ambassador, ASAPbio (2020 – 2022)
• Community Ambassador, eLife (2018 – 2020)
• Co-Chair, Web Committee, ISCB Student Council (2016 – 2019)
• Organizer, Tsinghua ENCODE Journal Club (2013 – 2014)

Professor Khan’s research bridges computational biology, (epi)genomics, machine learning, and software engineering to understand gene regulation in diseases such as cancer. His lab pioneers cutting-edge open-source tools, methods, and infrastructure to analyze, visualize, and interpret multi-omic, multi-model, and multi-ethnic data, deciphering the non-coding genome to empower precision oncology and medicine.

Professor Khan has published over 30 high-impact peer-reviewed research papers in leading journals across diverse topics from genomics, epigenomic, machine learning, cancer, science policy, with over 8,800 citations.

• Houlahan KE*, Mangiante L*, Sotomayor-Vivas C*, Adimoelja A*, Park S, Khan A, Pribus S, Ma Z, Caswell-Jin J, Curtis C. Complex rearrangements fuel ER+ and HER2+ breast tumors, Nature DOI: 10.1038/s41586-024-08377-x
• Houlahan KE, Khan A, Greenwald NF, Sotomayor-Vivas C, West RB, Angelo M, Curtis C. Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity, Science 2024; 384(6699), DOI: 10.1126/science.adh8697
• Karlsson K, Przybilla MJ, Kotler E, Khan A, [13 co-authors], Curtis C. Deterministic evolution and stringent selection during pre-neoplasia, Nature 2023; 618:383–393
• Maeser N*, Khan A*, Sun R. Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline, STAR Protocols. 2022; 4(1):101927
• Strand SH, [7 co-authors], Khan A, [32 co-authors], Curtis C, Tibshirani R, Angelo RM, Hall A, Owzar K, Polyak K, Maley C, Marks JR, Colditz GA, Hwang ES, West RB. Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts, Cancer Cell. 2022; DOI: 10.1016/j.ccell.2022.10.021
• Sarabipour S, Khan A et al. Changing scientific meetings for the better. Nature Humman Behaviour 2021; 5:296-300.
• Khan A, Riudavets Puig R, Boddie P, Mathelier A. BiasAway: command-line and web server to generate nucleotide composition matched DNA background sequences. Bioinformatics 2021; 37(11):1607-1609
• Khan A*, Fornes O*, Stigliani A* et al. JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework. Nucleic Acids Res 2018; 46(D1):D260-D26
• Khan A†, Mathelier A†. Intervene: a tool for intersection and visualization of multiple gene or genomic region sets. BMC Bioinformatics 2017;18:287