@@ -41,12 +41,12 @@ aabiddanda [at] gmail [dot] com<br>
 ::::
 ----
 
-**I am on the academic job market! If your department is looking for a human geneticist with broad interests - please drop me a line.**
+**I am on the academic job market! If your department is looking for a population geneticist with broad interests - please drop me a line.**
 
 
 <h3>About</h3>
 
-I am a human geneticist developing statistical methods to understand human evolution and fertility traits. I am currently a postdoctoral fellow at [Johns Hopkins University](https://bio.jhu.edu/) advised by [Rajiv McCoy](https://mccoy-lab.org/). My [research interests](/research/) broadly span problems in theoretical and applied population genetics.
+I am a population geneticist developing statistical methods to understand human evolution and reproductive traits. I am currently a postdoctoral fellow at [Johns Hopkins University](https://bio.jhu.edu/) advised by [Rajiv McCoy](https://mccoy-lab.org/). My [research interests](/research/) broadly span problems in theoretical and applied population genetics.
 
 Previously, I was a postdoctoral fellow at the University of Oxford in the group of [Pier Palamara](https://palamaralab.github.io/) and also worked as a computational biologist at a biotechnology startup. I received my PhD in Human Genetics from the University of Chicago working with [John Novembre](http://jnpopgen.org/). 
 
 
@@ -6,14 +6,14 @@
 
 ### Preprints
 
-Yulin Zhang<sup>* &Dagger;</sup>, <strong> Arjun Biddanda<sup>* &Dagger;</sup> </strong>, Sarah A. Johnson, Colm O'Dushlaine, Priya Moorjani<sup>&Dagger;</sup>. Recovering signatures of archaic introgression using ancestral recombination graphs _bioRxiv_ | [Full Text](https://www.biorxiv.org/content/10.64898/2026.03.03.709416v1) | [Software](https://github.com/YulinZhang9806/trace) 
-
 Ben Jeffrey, Yan Wong,  ...<strong> Arjun Biddanda</strong>, ..., Peter L. Ralph, Jerome Kelleher. Population-scale Ancestral Recombination Graphs with tskit 1.0. _arXiv_ | [Full Text](https://arxiv.org/abs/2602.09649)
 
 ### Peer-Reviewed 
 
 #### 2026
 
+Yulin Zhang<sup>* &Dagger;</sup>, <strong> Arjun Biddanda<sup>* &Dagger;</sup> </strong>, Sarah A. Johnson, Colm O'Dushlaine, Priya Moorjani<sup>&Dagger;</sup>. Recovering signatures of archaic introgression using ancestral recombination graphs _Science_ | [Full Text](https://www.science.org/doi/10.1126/science.aef8874) | [Software](https://github.com/YulinZhang9806/trace) | [Press](https://news.berkeley.edu/2026/07/30/new-technique-pinpoints-human-dna-inherited-from-ghost-ancestors/)
+
 Arun Das, <strong> Arjun Biddanda</strong>, Rajiv C. McCoy, Michael C. Schatz. Assembling unmapped reads reveals hidden variation in South Asian genomes. _Nature Communications_ | [Full Text](https://www.nature.com/articles/s41467-026-71755-8)
 
 Sara A. Carioscia<sup>* </sup>, <strong>Arjun Biddanda<sup>* </sup></strong>, Margaret R. Starostik, Xiaona Tang, Eva R. Hoffmann, Zachary P. Demko, Rajiv C. McCoy. Common variation in meiosis genes shapes human recombination phenotypes and aneuploidy risk. _Nature_ | [Full Text](https://www.nature.com/articles/s41586-025-09964-2) | [Research Briefing](https://rdcu.be/e282d) | [Press](https://hub.jhu.edu/2026/01/21/genetic-factors-influencing-pregnancy-loss/)
 
@@ -1,43 +1,43 @@
 ## Research
 
-### Statistical Genetics of Chromosomal Dosage and Aneuploidy
+### Human Population Genetics
 
-```{image} ./images/research_images/aneuploidy_dosage.jpg
-:width: 300px
+```{image} ./images/research_images/geographic_dist.jpg
+:width: 200px
 :align: right
 ```
 
-While it is normal for most healthy individuals to contain two copies of our genome within each cell, there can be deviations to this property either due to mutation (copy-number variants) or errors in chromosome segregation. A more recent research direction of mine has been to develop statistical methods for the analysis large-scale changes in chromosomal dosage (e.g. copy-number variation, or whole-chromosome aneuploidy). Much of my research has been focused on pre-implantation genetic testing (PGT) data from in-vitro fertilization (IVF) embryos, to infer properties of aneuploidy and meiotic recombination related to fertility.
+A large fraction of my research is centered on human population genetics - with a goal to better understand human evolutionary history and studies of human disease. A major throughline has been models of genealogical relationships within large samples, both for statistical genetics of complex traits or inference of population history. Some recent topics of interest include:
 
-Some active topics of research in this area:
-
-* Inferring crossover rates in embryo PGT datasets and their genetic architecture
-* Refining dosage constraint estimates of genes from segmental aneuploidies
-* Evolution of dosage constraint/relaxation across somatic tissue evolution
+* Population genetic inference using ARGs for demographic history, natural selection, and phenotypes 
+* Refining genealogical inference with noisy samples and diverse mutational mechanisms (e.g., repeat polymorphisms)
+* Effective multi-ancestry study design and meta-analysis in genome-wide association studies
 
 <ins>**Representative Publications**</ins>
 
-* Sara A. Carioscia<sup>* </sup>, <strong>Arjun Biddanda<sup>* </sup></strong>, Margaret R. Starostik, Xiaona Tang, Eva R. Hoffmann, Zachary P. Demko, Rajiv C. McCoy. Common variation in meiosis genes shapes human recombination phenotypes and aneuploidy risk. _Nature_ | [Full Text](https://www.nature.com/articles/s41586-025-09964-2) 
+* Yulin Zhang<sup>* &Dagger;</sup>, <strong> Arjun Biddanda<sup>* &Dagger;</sup> </strong>, Sarah A. Johnson, Colm O'Dushlaine, Priya Moorjani<sup>&Dagger;</sup>. (2026) Recovering signatures of archaic introgression using ancestral recombination graphs _Science_ | [Full Text](https://www.science.org/doi/10.1126/science.aef8874) | [Software](https://github.com/YulinZhang9806/trace)  
+* Brian C Zhang, <strong>Arjun Biddanda</strong>, Árni F Gunnarsson, Fergus Cooper, Pier Francesco Palamara. (2023) Biobank-scale inference of ancestral recombination graphs enables genealogy-based mixed model association of complex traits. _Nature Genetics_ | [Full Text](https://www.nature.com/articles/s41588-023-01379-x) | [Software](https://palamaralab.github.io/software/argneedle/)
+* <strong>Arjun Biddanda</strong>, Daniel P Rice, John Novembre. (2020). Geographic patterns of human allele frequency variation - a variant-centric perspective. _eLife_ | [Full Text](https://elifesciences.org/articles/60107) | [Software](https://aabiddanda.github.io/geovar/)
 
 
-### Human Statistical and Population Genetics
+### Statistical Genetics of Chromosomal Abnormalities
 
-```{image} ./images/research_images/geographic_dist.jpg
-:width: 200px
+```{image} ./images/research_images/aneuploidy_dosage.jpg
+:width: 300px
 :align: right
 ```
 
-Much of my current work is centered on human population genetics -with a goal to understand human evolutionary history and improve experimental design for studies of human disease. A subset of my research has been developing methods for using inferred ancestral recombination graphs (ARGs) for both statistical genetics of complex traits or inference of population history. Some recent topics of interest include:
+Nearly half of conceptions in humans fail to lead to live birth. A major driver of pregnancy losses are errors in chromosome segregation, resulting in an improper number of chromosomes, or aneuploidy. I have developed statistical models for the analysis of both chromosomal errors and other diverse error types, focusing primarily on interptation of pre-implantation genetic testing (PGT) data from in-vitro fertilization (IVF) embryos. My broader goal is to develop novel statistical methods to infer a wider spectrum of genetic errors occurring during early development and improve our understanding of such errors, the fitness consequences of these errors, and parental genetic risk --- collectively informing precision reproductive health.  
 
-* Leveraging ARGs for population genetic inference and association testing for complex variants (e.g., CNVs)
-* Statistical considerations for meta-analysis of complex traits across multiple ancestries
+Some active topics of research in this area:
+
+* Improving haplotype-based models for whole-chromosome and segmental aneuploidy detection 
+* Mathematical models of negative selection and evolutionary rescue during gestation
 
 <ins>**Representative Publications**</ins>
 
-* Yulin Zhang<sup>* &Dagger;</sup>, <strong> Arjun Biddanda<sup>* &Dagger;</sup> </strong>, Sarah A. Johnson, Colm O'Dushlaine, Priya Moorjani<sup>&Dagger;</sup>. Recovering signatures of archaic introgression using ancestral recombination graphs _bioRxiv_ | [Full Text](https://www.biorxiv.org/content/10.64898/2026.03.03.709416v1) | [Software](https://github.com/YulinZhang9806/trace)  
-* Brian C Zhang, <strong>Arjun Biddanda</strong>, Árni F Gunnarsson, Fergus Cooper, Pier Francesco Palamara. (2023) Biobank-scale inference of ancestral recombination graphs enables genealogy-based mixed model association of complex traits. _Nature Genetics_ | [Full Text](https://www.nature.com/articles/s41588-023-01379-x) | [Software](https://palamaralab.github.io/software/argneedle/)
+* Sara A. Carioscia<sup>* </sup>, <strong>Arjun Biddanda<sup>* </sup></strong>, Margaret R. Starostik, Xiaona Tang, Eva R. Hoffmann, Zachary P. Demko, Rajiv C. McCoy. (2026) Common variation in meiosis genes shapes human recombination phenotypes and aneuploidy risk. _Nature_ | [Full Text](https://www.nature.com/articles/s41586-025-09964-2) 
 
-* <strong>Arjun Biddanda</strong>, Daniel P Rice, John Novembre. (2020). Geographic patterns of human allele frequency variation - a variant-centric perspective. _eLife_ | [Full Text](https://elifesciences.org/articles/60107) | [Software](https://aabiddanda.github.io/geovar/)
 
 ### Theoretical Population Genetics
 
@@ -48,9 +48,9 @@ Much of my current work is centered on human population genetics -with a goal to
 
 Much of my applied work draws on results from population genetic theory, and I enjoy working on problems that involve more mathematical rigor. Typically, these are oriented towards understanding how theory can be used to intuit or improve statistical population genetic inference. Some active topics of research in this domain are: 
 
-* Two-locus genealogies with spatial and temporal structure
-* Evolution of recombination rates and meiosis-related traits
-* Genealogical models for intra-cellular/somatic evolutionary inference 
+* Genealogical models with spatial and temporal structure
+* Evolution of recombination rates and modifiers of meiotic fidelity
+* Mathematical models for intra-cellular/somatic evolutionary inference 
 
 <ins>**Representative Publications**</ins>