Biometricians – Cramer Fish Sciences

Alex Constandache, Ph.D.

Senior Biometrician

B.S. Physics; Ph.D. Physics

Phone: (530) 240-6365

Meadow Vista, California

Alex spent the past 17 years working as a physicist, software engineer and data scientist. As a physicist, he worked on nonlinear dynamical systems and wrote computational fluid dynamics software for astrophysical simulations. As a software engineer, he worked on information indexing and retrieval systems (search engines). As a data scientist he developed and deployed analytics pipelines for performing statistical analysis, optimization and forecasting, based on large data sets, in various domains, such as e-commerce, advertising and finance.

His interests lie in the areas of Bayesian inference and Markov chain Monte Carlo methods. He has experience applying such methods to causal inference, synthetic counterfactual analysis, and stochastic optimization and control problems.

Selected Publications

Constandache, A., Bari, O., Forecasting a Stock’s Remaining Intraday Volume, 2018 First International Conference on Probabilistic Programming PROBPROG 2018.

Ulicny, B., Constandache, A., Cunningham, J., Traub, M., Yu, K., Azeglio, C., Saito-Varadi, M., 2016. Thomson Reuters and the FEIII challenge. Proceedings of the Second International Workshop on Data Science for Macro-Modeling, DSMM@CIKM 2016.

Constandache, A., Das, A., Popowicz, Z. 2003 A Benney-like lattice. Czechoslovak journal of physics.

Constandache, A., Ashok Das, and F. Toppan. 2002 Lucas polynomials and a standard Lax representation for the polytropic gas dynamics. Letters in Mathematical Physics.

Brunelli, J. C., Constandache, A., Das, A. 2002 A Lax equation for the non-linear sigma model. Physics Letters B.

Barcelos-Neto, J., Constandache, A., Das A. 2000 Dispersionless fermionic KdV. Physics Letters A.

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Apryle Craig, Ph.D.

Biometrician

B.S. BioEngineering; M.S. Ecology; Ph.D. Environmental and Forest Sciences

Phone: (360) 456-4621

Issaquah, Washington

Apryle is a quantitative ecologist, with a focus on assessing changes to vegetation and fish communities before and after an impact. Her work focuses on applications of mixed models, machine learning, multivariate analyses, and data visualization to address a wide range of ecological questions. Apryle excels at study design, data collection, and data management, having led field data collection and data analysis teams for multi-year riparian restoration projects at Rocky Mountain National Park, Colorado.

Kiera McNeely, M.A.S

Biometrician

B.S. Fisheries and Wildlife Sciences; M.A.S. Applied Statistics

Phone: (360) 456-4621

West Sacramento, CA

Kiera is a dedicated biometrician with extensive experience in fisheries research, specializing in rockfish growth studies, marine invertebrate diversity, and quantifying migrating salmonids using sonar technology. Her recent work in the Columbia River and the Sandy River Basin involved extensive field data collection for local salmonid populations through creel efforts and spawning ground surveys. The surveys consisted of live salmonid counts, carcass counts plus sampling, and with redd surveys using GPS technology. She also possesses experience with commercial and tribal fisheries sampling, mark-recapture studies, PIT tagging, and sturgeon population studies. With a recent master’s degree in Statistics, Kiera is transitioning her focus to fisheries population dynamics and modeling. She brings experience with mark-recapture studies, stock assessments, multivariate analyses, Bayesian inferences, Markov chain Monte Carlo analysis, and spatial data modeling. Proficient in R and SQL, with knowledge of conducting machine learning models using python, Kiera excels in data analysis and modeling. Additionally, she is skilled in experimental design, data collection, and data management, which are essential for conducting robust statistical analyses on any given project.

Matt Espe, Ph.D.

Senior Biometrician

B.S. Horticulture and International Studies, M.S. Horticulture and Agronomy, Ph.D. Horticulture and Agronomy

Meadow Vista, California

Matt Espe brings 14 years of experience as a senior biometrician specializing in applied life sciences. He focuses on developing statistical and simulation models in R and Stan, creating custom packages and workflows that leverage diverse data science technologies. Matt’s expertise includes developing new data science tools that enable researchers to collect, manage, and manipulate data more efficiently. Before joining Cramer Fish Sciences in 2021, Matt served as a Post-Doctoral Researcher at the UC Davis Data Science Initiative where he taught data science best practices, programming languages, and emerging technologies. His Ph.D. research investigated the drivers of yield variability in US rice production systems using both mechanistic and statistical models that utilized large datasets from multiple sources.

Selected Publications

Johnston, M., J. Frantzich, M.B. Espe, P. Goertler, G. Singer, T. Sommer, and A. Peter Klimley. 2020. Contrasting the migratory behavior and stranding risk of white sturgeon and chinook salmon in a modified floodplain of California. Environmental Biology of Fishes 103:481-493.

Espe, M.B., J.E. Hill, M. Leinfelder-Miles, L.A. Espino, R. Mutters, D. Mackill, C. van Kessel, and B.A. Linquist. 2018. Rice yield improvements through plant breeding are offset by inherent yield declines over time. Field Crops Research 222:59 – 65.

Espe, M.B., J.E. Hill, R.J. Hijmans, K. McKenzie, R.Mutters, L.A. Espino, M. Leinfelder-Miles, C. van Kessel, and B.A. Linquist. 2017. Point stresses during reproductive stage rather than warming seasonal temperature determine yield in temperate rice. Global Change Biology 23(10):4386-4395.

Tao, A., R.K. Afshar, J. Huang, Y.A. Mohammed, M.B. Espe, and C. Chen. 2017. Variation in yield, starch, and protein of dry peas grown across Montana. Agronomy Journal 109(4):1491-1501.

Espe, M.B., H. Yang, K.G. Cassman, N. Guilpart, H. Sharifi, and B.A. Linquist. 2016. Yield gap analysis of US rice production systems shows opportunities for improvement. Field Crops Research 193:123–132.

Espe, M.B., H. Yang, K.G. Cassman, N. Guilpart, H. Sharifi, and B.A. Linquist. 2016. Estimating yield potential in temperate high-yielding, direct-seeded US rice production systems. Field Crops Research 193:123–132.

Ye, R., M.B. Espe, B.A. Linquist, S.J. Parikh, T.A. Doane, and W.R. Horwath. 2016. A soil carbon proxy to predict CH 4 and N 2 O emissions from rewetted agricultural peatlands. Agriculture Ecosystems and the Environment 220:64–76.

Espe, M.B., E. Kirk, C. van Kessel, W.R. Horwath, and B.A. Linquist. 2015. Indigenous nitrogen supply of rice is predicted by soil organic carbon. Soil Science Society of America Journal 79(2).