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About Us

Welcome to our Research Group's webpage!

We are a group of human geneticists and computational biologists. We utilize cutting-edge analytic tools to address questions at the intersection of human medical and population genetics. These insights will be critical for future medical genetics studies and in practicing personalized medicine.

For new and current members of the group, please check out Lab Expectations and Resources and the Lab Activities for what we have been up to outside of doing rigorous research!

Recent News

3.2024: Soyoung Jeon's final chapter of her dissertation (with help from Tsz Fung Chan and Jalen Langie from our group), identifying a Latino-enriched risk allele for childhood leukemia and examining the ancestral and adaptive signature at this locus is published in Cell Genomics! With co-first authors Adam de Smith and Lara Wahlster, and co-senior author Vijay Sankaran, here is a short video describing the findings of this study!

3.2024: Bryan Dinh successfully defended his qualifying exam proposal and has now officially advanced to candidacy. Congrats Bryan!

3.2024: Charleston Chiang gave a talk on the genealogy-based framework to estimate population structure and demographic history at The Allied Genetics Conference 2024 (Population, Evolutionary, Quqantitative Genetics) session.

3.2024: Charleston Chiang has been promoted to Associate Professor with tenure! There was a short funny story behind how notification of tenure was received. Thanks to all past and present members of the lab for making this happen, and for making the journal as enjoyable as it can be!

2.2024: We published a persepctive in Genome Biology and Evolution on the promise of inferring the past using Ancestral Recombination Graph (ARG). This work stemmed from our SMBE symposium back in 2022 on the use of ARGs to infer Evolutionary History.

1.2024: Our paper on recombination landscapes of Native Hawaiians and Polynesian-ancestry individuals, led by Bryan Dinh with helps from Echo Tang is now published in Human Genetics! It is open access too so everyone can check it out! Congrats to Bryan and Echo!

12.2023: Charleston Chiang gave a talk on the genetic genealogy-based framework to estimate population structure and demographic history at the third AsiaEvo conference in Singapore.

12.2023: Our lab is 6 years old! Check here to see how the lab has grown over the years!

12.2023: Yingchu Lo has posted a preprint on her work with us during her postdoc, on evaluating the accuracies of polygenic score models for anthropometric and metabolic traits in Native Hawaiians! We generally find that polygenic score models trained using the largest GWAS would not transfer well to prediction in Hawaiians, particularly those enriched with Polynesian ancestries, though performance is variable. Congrats Yingchu!

11.2023: New members joining the lab before we wrap up the Fall semester! Indu Sharma is a postdoc who previously working on characterizing isolated populations in India/Himalayas, Indu is interested in examining the signature of selection and its modern day consequences on complex traits and diseases. Eunice Lee joined as a senior research associate. Trained as an environmental epidemiologist, she will incorporate her background in working with environmental variables with genetics data! Welcome Indu and Eunice!

11.2023: Jordan Cahoon's project for evaluating imputation accuracy for populations across the globe received the best poster award at International Genetic Epidemiology Society annual meeting in Nashville, TN! (though unfortunately she could not make it).

11.2023: Charleston Chiang was awarded the early career investigator award by HGG Advances this year, though the credit should really go to Grace Sheng who relentlessly tracked down a QC anomaly impacting only 0.2% of the data, but in the end taught all of us something new in genomic analysis!

11.2023: Our lab is well-represented at the 2023 American Society of Human Genetics meeting, including three posters and a talk from Jalen Langie on her work in admixture mapping for childhood leukemia! Check out the photos and links to posters and presentation here!

10.2023: Caoqi Fan's second chapter of his dissertation is now on bioRxiv! In a method we called gLike, we can obtain maximum likelihood estimates of demographic history parameters based on the genealogical trees from the genetic data. We showed that this method is much more accurate over previous methods based on summary statistics of the genetic data. Please let us know if you have any questions or comments! A tweetorial is here.

10.2023: A pair of preprints from members in the group are officially published! Tsz Fung Chan's method HAMSTA that estimates genome-wide heritability and evaluates biases in test statistics of admixture mapping studies was published in American Journal of Human Genetics, and Soyoung Jeon's paper in constructing and evaluating genome-wide PRS for childhood leukemia was published in HGG Advances! Congrats to Tsz Fung and Soyoung!

9.2023: Our lab has been awarded a R01 grant from NIH/NHGRI (R01HG012605), where we will develop methods leveraging genome-wide genealogies inferred from the genetic data (aka ancestral recombination graph) to gain knowledge about population history and to improve trait mapping. This is the third major grant obtained by the lab over the last three years, thanks so much for everyone involved every step along the way!

9.2023: New members joining the lab! While dear old friends left the lab over the summer, we also have multiple new members joining the lab. These include Xinran Wang, who is taking a year focusing on research before applying for Ph.D. this fall, joins us as a Program Analyst; He Tian, a second year Epidemiology PhD student joining the lab after completing her screening exam; and Ji Tang, a new postdoc interested in developing machine learning methods to address population genetic questions. Welcome Xinran, He, and Ji!

Read our older news here.


The overarching theme of our research group is to use genetic approaches to understand how evolutionary forces shaped the genetic architecture of complex traits within and between populations. To this end, we have been involved in a number of past and ongoing medical genetics studies in mapping genetic loci underlying human complex traits. We are also continually interested in investigating the evolutionary forces, namely demography and selection, that shaped the pattern of genetic variability and phenotypic distribution. We are particularly interested in diverse, global human populations and our successes result from collaborating with innovative colleagues and thriving in resourceful consortiums. Read a more detailed description of our work here.



PM534: Statistical Genetics (Fall 2021, 2022)
Introduction to Medical Population Genetics
syllabus (Fall 2021)

Guest Lectures

BISC577: Computational Biology Laboratory (Fall 2019, Fall 2020, Fall 2021)
"Genetics and Evolution": slides (2020.09.15)
(This is a huge slide deck! ~17Mb)

Contact Us

We are part of the Center for Genetic Epidemiology, in the Department of Population and Public Health Sciences at USC Keck School of Medicine, and jointly affiliated with the Department of Quantitative and Computational Biology at USC Dornsife College of Letters, Arts, and Sciences.

Charleston can be reached via email at:
charleston [dot] chiang [at] med [dot] usc [dot] edu

We are located in the Harlyne J. Norris Research Tower (NRT) on the Health Science Campus at USC

Mailing Address:
1450 Biggy Street
Los Angeles, CA 90033

Join Us

Postdoctoral Fellows: We are always looking for talented and motivated individuals to join our group! Interested individuals are encouraged to contact Charleston Chiang for inquiries. There are multiple ways a postdoctoral fellow can be funded, through NIH grants in the lab, collaborative funds, or unrestricted funds. This means you have the stability as well as the flexibility to explore topics broadly of interest to the lab. Positions are generally for at least 2 years, with salary commensurate with experience and adjusted for cost of living in LA (definitely higher than NIH scale!). Applicants ideally should have extensive exposure and experience in human medical and/or population genetics research and have analyzed large genetic datasets. Programming skills (in at least one of, e.g., python, perl, C, R, etc.) and proficiency in Unix-based computing environments are very desirable. Successful candidates may also develop projects broadly within the scope of the group's research interests.

Inquiries or applications (cover letter, CV, and contact information to at least two references) should be emailed to Charleston Chiang.

Graduate Students:We are open to accepting doctoral and master students. Generally, doctoral students are enrolled through Program in Biomedical and Biological Sciences (PIBBS), Computational Biology and Bioinformatics (CBB), or one of the Public Health Sciences programs (such as Biostatistics or Epidemiology) at USC. Email Charleston Chiang for inquiries.


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