Dr.Alex Van Dam

Vita

I am a research scientist at the Center for Integrative Biodiversity Discovery, Museum für Naturkunde Berlin, with a background spanning integrative taxonomy, phylogenomics, and AI-driven biodiscovery. 

I hold a PhD in Entomology from UC Davis (2013), followed by an NSF Postdoctoral Fellowship at the Technical University of Denmark, where I investigated differential gene expression in scale insects and developed metagenomic workflows. I later applied these approaches to genome recovery of the plantain weevil via PacBio HiFi metagenomics and to phylogenomic inference in Coleoptera using ultraconserved elements (UCEs). I subsequently spent nine years as Associate Professor of Biology at the University of Puerto Rico–Mayagüez, where I led an independent research group, secured over USD 700,000 in competitive federal funding as principal investigator, and established molecular laboratory infrastructure encompassing standard molecular techniques, NGS library preparation (Illumina, PacBio-HMW-extraction, Oxford Nanopore), ONT sequencing, and CRISPR-Cas9 micro-injection for arthropod embryos. During this period I also digitised and made the UPRM Invertebrate Collection globally accessible through GBIF, and supervised four MSc students to completion, resulting in students publishing in peer-reviewed journals.

My current work centers on two open-source platforms I developed to address the taxonomy of unsubscribed and hyperdiverse "dark taxa." Descriptron is an AI-assisted specimen annotation and morphological data acquisition platform integrating SAM2 image segmentation, Detectron2 instance detection, and a structured morphological vocabulary mapped to biodiversity ontologies, enabling scalable and reproducible morphometric data extraction from insect specimens. Its browser-based companion, the Descriptron-GBIF Annotator, supports crowdsourced annotation of GBIF specimen images across 25 taxonomic groups with zero installation required. DINOSAR v2 (DINOv3 Species Auto-Recovery) is a contrastive learning framework built on DINOv3 Vision Transformers that learns discriminative morphological representations across hyperdiverse insect taxa, supporting open-set species recognition, multi-modal trait regression, and DNA–image cross-modal alignment for automated species discovery.

Further information

Awards and Academic Distinctions

    • NSF Postdoctoral Research Fellowship in Biology (2013) — competitive national fellowship, USD 163,601

    • NSF–NASA EPSCoR RII Track-4 (2023) — PI, USD 248,138

    • USDA NIFA HSI Grant (2018) — PI, USD 274,868

    • USDA RIIA (2019) — PI, USD 148,523

    • NSF XSEDE/ACCESS computational allocations (2015–2024) — multiple competitive HPC award cycles