Research Projects
My research integrates fieldwork, natural history collections, genomics, and the development of digital tools to address speciation, biogeography, and conservation questions. In particular, it centers on identifying patterns of small mammal diversity and understanding speciation processes within and across islands in the Indo-Australian Archipelago. I have also engaged in projects focusing on other taxa and in different regions. Most of the tools I develop are taxon-agnostic. My collaborative work involves more than a dozen people in some projects. I strive to make research using natural history collections and genomic data accessible to students and researchers with limited technical knowledge and access to computing resources.
Small Mammal Diversity & Speciation
Understanding patterns that generate species diversity within a complex island system
The Indo-Australian Archipelago (IAA) is a complex island system. The Sunda Shelf islands (e.g., Sumatra, Java, Borneo) were connected during the Pleistocene, while the Sahul Shelf islands experienced similar connections. Sulawesi formed from separate islands, and others like the Moluccas and Lesser Sunda islands were never connected to nearby landmasses. Isolated mountains within these islands promote other opportunities for speciation. This project focuses on studying small mammal diversity and speciation, particularly in Sulawesi and the Sunda Shelf, involving extensive fieldwork, genomic studies, and describing undocumented species as necessary. For my dissertation, I focus on in-situ diversification of hill rats (Bunomys) on Sulawesi, aiming to improve phylogenetic resolution and understand how the island's geological history has shaped their diversity. I hope to aid conservation efforts and deepen our understanding of speciation on a large, isolated island like Sulawesi.
A new species of Frateromys from the Northern Peninsula of Sulawesi, Indonesia
Molecular and morphological systematics of the Bunomys division (Rodentia: Muridae), an endemic radiation on Sulawesi
A new species of shrew (Soricomorpha: Crocidura) from Java, Indonesia: possible character displacement despite interspecific gene flow
Local endemism and withinâisland diversification of shrews illustrate the importance of speciation in building Sundaland mammal diversity
Fourteen new, endemic species of shrew (genus Crocidura) from Sulawesi reveal a spectacular island radiation
A new climbing shrew from Sulawesi highlights the tangled taxonomy of an endemic radiation
A hog-nosed shrew rat (Rodentia: Muridae) from Sulawesi Island, Indonesia
Systematics and historical biogeography of Crunomys and Maxomys (Muridae: Murinae), with the description of a new species from Sulawesi and new genus-level classification
Three new species of shrew (Soricidae: Crocidura) from West Sumatra, Indonesia: elevational and morphological divergence in syntopic sister taxa
Inclusive, Open, and Accessible Software
Developing digital tools empowering new learners in evolutionary studies
Every aspect of collection-based evolutionary studies has become increasingly complicated. Museum scientists have now routinely collected voucher specimens with numerous parts and complex derivative data features. Studies using natural history collections often involve intricate and computationally demanding genomic data analyses. To reduce the technical difficulties of these workflows, enhance computing efficiency, and improve data integration, I develop open and accessible software, targeting part of the workflow where investment in quality software is lacking or not yet present. I aim to facilitate inclusive and mutually beneficial international collaborations through innovative data management, data-sharing approaches, and low-cost computing practices. To achieve my goals, I leverage emerging technologies in software development (e.g., Rust, Flutter, and CI/CD ) to create user-friendly, memory-efficient, and cross-platform software. Whenever feasible, I support mobile operating systems, offering a more flexible way to collect data in the field and allowing teaching genomic analyses where access to computing power is limited. I also capitalize on advancements in CPU technology and heterogenous computing to accelerate data processing and reduce reliance on power-hungry and costly High-Performance Computing Clusters. Promoting more energy- and resource-efficient data analysis practices reduces the ecological footprint of evolutionary studies while allowing underfunded labs to benefit from the decreasing cost of genomic sequencing.