Science Collaboration Mentors

Dark Energy (DESC)

Camille Avestruz She/Her Contact \| Website My research group is interested in a range of computational methods in cosmology. Within DESC, group members are involved with projects in the clusters, large scale structure, and blending working groups. We have contributed to DESC infrastructure including the cluster mass modeling and blending toolkit topical teams. Furthermore, the group has several ongoing efforts that make use of machine learning applications in several subfields of cosmology and astrophysics. Complementary to current DESC activities, there are also a number of projects that leverage cosmological simulations to und - More -	Franz E. Bauer He/Him Contact \| Website My research group at UCatólica in Santiago, Chile works on a wide variety of topics involving massive BH and galaxy classification, demographics, evolution, and accretion physics, as well as rapid/extreme extragalactic variability events (Changing-State AGN, SNe, TDEs, FXRTs, ULXs, GW events, ...), using both traditional and machine-learning approaches. - More -	Eric Gawiser He/Him Contact \| Website As the Analysis Coordinator of DESC, I pay attention to all cosmological probes of dark energy and dark matter. Previously, I served as Deputy Spokesperson and as a Large-Scale Structure working group convener. I am also a member of the Galaxies SC and active in the Simons Observatory, HETDEX, ODIN, LADUMA, and JWST-CEERS collaborations. Most of my previous postdoctoral mentees now occupy faculty positions. - More -
Tesla Jeltema She/Her Contact \| Website Cosmology with cluster of galaxies including calibration of cluster selection with multiwavelength data and simulations; Astrophysical probes of dark matter including probes of self-interacting dark matter and dark matter indirect detection - More -	Akhtar Mahmood He/Him Contact \| Website I am interested in working on developing algorithms and software needed to pursue accurate cosmological studies using weak lensing - quantitative assessment of potential biases in photometric redshift/cosmic shear estimators, and to develop solutions for tomographic cosmic shear analyses. At DESC, I am involved with DESC’s PhoSim (Photon Simulator) project. I am running the PhoSim jobs (generating the PhoSim simulation data) on the Bellarmine Tier 2 HPC cluster that is linked to the Open Science Grid (OSG) cyberinfrastructure using Condor. - More -	Vivian Miranda She/Her Contact \| Website My research is focused on probing inflation, the epoch of reionization, and dark energy with the Cosmic Microwave Background. I am also keen on understanding how extensions of the LCDM model can be constrained by combining the CMB with low redshift probes. As a postdoc, I have developed research on testing fundamental assumptions about the standard model using model-independent techniques. Finally, my work stands on the bridge between theory and data, and I am open to radically new ideas, as long as they can be falsified by either the CMB or the DES/LSST/Roman surveys. - More -
Gautham Narayan He/Him Contact \| Website My research interests are at the intersection of multi-messenger and time-domain astrophysics, cosmology, statistics, and data science. I works on wide-field surveys including LSST DESC (where I am Deputy Analysis Coordinator) and the Young Supernova Experiment (where I am one of the co-PIs). - More -	Jeffrey Newman He/Him Contact \| Website My primary DESC activity has been focused on photometric redshifts (methods, training data, and characterization of the results). I served as inaugural Convener of the DESC Photometric Redshifts working group and inaugural Analysis Coordinator of the collaboration, two terms as Deputy Spokesperson, and now am Co-convener of the DESC External Synergies Working Group. Although my primary focus is DESC, I am also a member of the Galaxies, AGN, and ISSC Science Collaborations. - More -	Brian Nord He/Him Contact \| Website I'm working to apply simulation-based (implicit likelihood) inference techniques for strong lensing and galaxy cluster analyses. I also work on Citizen Science for LSST. - More -
Ricardo Vilalta He/Him Contact \| Website Our research laboratory intends to provide state-of-the-art techniques in analyzing scientific data, emphasizing the use of machine learning to analyze astrophysics data—the laboratory centers mainly on developing machine learning tools tailored to astrophysics and cosmology problems. Specifically, we aim at developing physics-informed machine learning models that incorporate domain knowledge as bias into the induction of predictive models. We consider specialized deep neural networks and differential equations as part of the model-building process. - More -