Experts and Thought Leaders in Statistics

Yseult Héjja-Brichard, Ph.D.

Baltimore, Maryland, United States of America
3 Years Experience
Postdoctoral researcher in Biological Sciences at University of Maryland Baltimore County
Education

Université Paul-Sabatier

Ph.D., Neuroscience, Cognition, Behaviour / June, 2020

Toulouse

Université Paul-Sabatier

Msc, Neuroscience, Cognition, Behaviour / June, 2015

Toulouse

Universite Grenoblé Alpes

Msc, Cognitive Psychology / June, 2014

Saint-Martin-d'Hères
Experience

University of Maryland, Baltimore County

Postdoctoral researcher / November, 2021Present

CNRS Délégation Occitanie Est

Postdoctoral researcher / November, 2020November, 2021

Most Relevant Research Expertise
Cognitive neuroscience
Other Research Expertise (6)
Natural statistics
Visual cognition
Sensory ecology
Stereoscopic vision
Sensory Systems
And 1 more
About
Yseult Héjja-Brichard received her PhD in Neuroscience, Cognition, and Behaviour from Université Paul-Sabatier Toulouse, France in 2020. She subsequently completed her first postdoctoral training at the Centre for functional and evolutionary ecology (CNRS) in Montpellier, France. She is now working as a postdoctoral research associate at the University of Maryland, Baltimore County. Yseult Héjja-Brichard’s research interests lie at the intersection of cognitive neuroscience and behavioural ecology. Her work has primarily focused on understanding how the brain efficiently processes information to enable decisions and behaviours. She informs those processes using an evolutionary and ecological perspective.
Most Relevant Publications (5+)

11 total publications

Processing of Egomotion-Consistent Optic Flow in the Rhesus Macaque Cortex

Cerebral Cortex / Jan 19, 2017

Cottereau, B. R., Smith, A. T., Rima, S., Fize, D., Héjja-Brichard, Y., Renaud, L., Lejards, C., Vayssière, N., Trotter, Y., & Durand, J.-B. (2017). Processing of Egomotion-Consistent Optic Flow in the Rhesus Macaque Cortex. Cerebral Cortex. https://doi.org/10.1093/cercor/bhw412

Connectivity of the Cingulate Sulcus Visual Area (CSv) in Macaque Monkeys

Cerebral Cortex / Oct 17, 2020

De Castro, V., Smith, A. T., Beer, A. L., Leguen, C., Vayssière, N., Héjja-Brichard, Y., Audurier, P., Cottereau, B. R., & Durand, J. B. (2020). Connectivity of the Cingulate Sulcus Visual Area (CSv) in Macaque Monkeys. Cerebral Cortex, 31(2), 1347–1364. https://doi.org/10.1093/cercor/bhaa301

Stereomotion Processing in the Nonhuman Primate Brain

Cerebral Cortex / Mar 28, 2020

Héjja-Brichard, Y., Rima, S., Rapha, E., Durand, J.-B., & Cottereau, B. R. (2020). Stereomotion Processing in the Nonhuman Primate Brain. Cerebral Cortex, 30(8), 4528–4543. https://doi.org/10.1093/cercor/bhaa055

Good scientific practice in EEG and MEG research: Progress and perspectives

NeuroImage / Aug 01, 2022

Niso, G., Krol, L. R., Combrisson, E., Dubarry, A. S., Elliott, M. A., François, C., Héjja-Brichard, Y., Herbst, S. K., Jerbi, K., Kovic, V., Lehongre, K., Luck, S. J., Mercier, M., Mosher, J. C., Pavlov, Y. G., Puce, A., Schettino, A., Schön, D., Sinnott-Armstrong, W., … Chaumon, M. (2022). Good scientific practice in EEG and MEG research: Progress and perspectives. NeuroImage, 257, 119056. https://doi.org/10.1016/j.neuroimage.2022.119056

Symmetry Processing in the Macaque Visual Cortex

Cerebral Cortex / Oct 06, 2021

Audurier, P., Héjja-Brichard, Y., De Castro, V., Kohler, P. J., Norcia, A. M., Durand, J.-B., & Cottereau, B. R. (2021). Symmetry Processing in the Macaque Visual Cortex. Cerebral Cortex, 32(10), 2277–2290. https://doi.org/10.1093/cercor/bhab358

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Jeremy Bernier, Ph.D.

Bangor, Maine, United States of America
9 Years Experience
Mathematics educator and education researcher
Education

Arizona State University

Ph.D., Learning, Literacies, And Technologies / August, 2024

Tempe, Arizona, United States of America

The University of Maine

M.S., Teaching (Concentration in Mathematics) / May, 2020

Orono, Maine, United States of America

Boston University

B.S., Mathematics Education / May, 2015

Boston
Experience

Bangor School Department

Adult Education Math Teacher / August, 2025Present

Clemson University

Adjunct Research Assistant Professor / August, 2025Present

Postdoctoral Fellow / August, 2024July, 2025

Arizona State University

Graduate Research and Teaching Assistant / September, 2020July, 2024

Most Relevant Research Expertise
statistics
Other Research Expertise (5)
mathematics education
game-based learning
qualitative methods
design-based research
educational technology
About
My name is Jeremy Bernier, and I am a math educator, education researcher, and gamer. I was born and raised in the state of Maine, a little bit all over but mostly in the [Lewiston / Auburn area](https://visitmaine.com/places-to-go/maines-lakes-and-mountains/lewiston-auburn). For my undergraduate studies, I went to [Boston University](https://www.bu.edu/wheelock/) and earned my BS in Mathematics Education in 2015. I spent a year after undergrad working at [Walt Disney World Resort](https://disneyworld.disney.go.com/) in Orlando, Florida, before teaching pre-algebra at [Maine Connections Academy](https://www.connectionsacademy.com/maine-virtual-school), Maine's first all-online charter school. I earned an MS in Teaching with a concentration in Mathematics from the [University of Maine](https://umaine.edu/risecenter/) in 2020, and subsequently earned a PhD in Learning, Literacies and Technologies from ASU in 2024. Presently, I am a Math Teacher at Bangor Adult and Community Education in Maine and an Adjunct Research Assistant Professor at Clemson University. <br> I am available for consulting and part-time work on a variety of types of projects. If you are interested in contracting me for work related to education research, mathematics teaching, or tabletop roleplaying games, please see the relevant pages linked below to learn more about my interest, experience, and knowledge in these areas.

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Robert Gmeiner

Fayetteville, North Carolina, United States of America
7 Years Experience
Professor with Ph.D. in economics with expertise in time series statistics
Education

Florida State University

Ph.D., Economics / May, 2018

Tallahassee, Florida, United States of America

Florida State University

M.S., Economics / May, 2016

Tallahassee, Florida, United States of America

Wake Forest University

B.A., Economics and Russian / December, 2012

Winston-Salem, North Carolina, United States of America
Experience

Methodist University

Assistant Professor of Financial Economics / August, 2021Present

The Sunwater Institute

Scholar / June, 2018August, 2019

Extensive research on economics of intellectual property rights.

Kennesaw State University

Limited Term Assistant Professor of Economics / August, 2019August, 2021

Most Relevant Research Expertise
Statistics
Data Analysis
Other Research Expertise (22)
Economics
Time series statistics
Time Series
Macroeconomics
Financial Economics
And 17 more
About
Robert Gmeiner is an accomplished economist with a strong background in both academic research and teaching. He holds a Ph.D. and M.S. in Economics from Florida State University and a B.A. in Economics and Russian, summa cum laude and Phi Beta Kappa, from Wake Forest University. Currently, Dr. Gmeiner is on the faculty at Methodist University, where he teaches courses in economics and statistics. His areas of expertise include time series statistics, econometrics, macroeconomic policy, inflation, economic policy (fiscal and monetary), international trade, antitrust/competition, and economic forecasting. He has published several articles in top academic journals and has presented his research at numerous conferences and workshops. Prior to working at Methodist University, he worked for the Sunwater Institute, where he researched the economics of intellectual property rights. Gmeiner is known for his dedication to his students, rigorous and timely work, always meeting deadlines. He takes pride in distilling top-level research into actionable insights, easily understood by a non-technical audience, and his ability to make complex economic concepts accessible and engaging. Outside of his work in economics, Gmeiner enjoys gardening, long-distance running, and spending time with his family. He is also an active member of several professional organizations, including Phi Beta Kappa, Omicron Delta Kappa, and the Philadelphia Society.

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Ryan Howell

San Francisco , California, United States of America
18 Years Experience
Professor of Psychology, Department of Psychology, San Francisco State University
Education

University of California, Riverside

PhD, Social / Personality Psychology Division / 2005

Riverside, California, United States of America

University of California, Riverside

MA, Social / Personality Psychology / 2002

Riverside, California, United States of America

Westmont College

BSc, Psychology / 1998

Santa Barbara, California, United States of America
Experience

San Francisco State University, Department of Psychology

Associate Professor / 2012Present

Most Relevant Research Expertise
Cognitive Neuroscience
Health Informatics
Other Research Expertise (32)
Happiness
Psychiatry and Mental health
Clinical Psychology
History and Philosophy of Science
Applied Psychology
And 27 more
About
Dr. Ryan Howell is an Associate Professor at San Francisco State University. His research interests include the psychology of goals and how people pursue and achieve them. Dr. Howell received his PhD in Social/Personality Psychology from the University of California, Riverside in 2005.
Most Relevant Publications (2+)

64 total publications

Understanding Long-Term Trajectories in Web-Based Happiness Interventions: Secondary Analysis From Two Web-Based Randomized Trials

Journal of Medical Internet Research / Jun 08, 2019

Sanders, C. A., Schueller, S. M., Parks, A. C., & Howell, R. T. (2019). Understanding Long-Term Trajectories in Web-Based Happiness Interventions: Secondary Analysis From Two Web-Based Randomized Trials. Journal of Medical Internet Research, 21(6), e13253. https://doi.org/10.2196/13253

Video conferencing during emergency distance learning impacted student emotions during COVID-19

Computers in Human Behavior Reports / Aug 01, 2022

Okabe-Miyamoto, K., Durnell, E., Howell, R. T., & Zizi, M. (2022). Video conferencing during emergency distance learning impacted student emotions during COVID-19. Computers in Human Behavior Reports, 7, 100199. https://doi.org/10.1016/j.chbr.2022.100199

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Edoardo Airoldi

Professor of Statistics & Data Science Temple University & PI, Harvard University
Education

Università Bocconi

B.Sc., Institute for Quantitative Methods

Milano

Carnegie Mellon University

Ph.D., School of Computer Science

Pittsburgh, Pennsylvania, United States of America
Experience

Harvard University

Most Relevant Research Expertise
Statistics
Statistics, Probability and Uncertainty
Statistics and Probability
Analysis
Health Informatics
Other Research Expertise (39)
Causal Inference
Network Science
Cell Biology
Molecular Biology
Pulmonary and Respiratory Medicine
And 34 more
About
Edoardo Airoldi is a Professor in the Department of Machine Learning at Temple University. He is also the Director of the Center for Machine Learning and Health. He is a world-renowned expert in the fields of machine learning and artificial intelligence, with a focus on applications to health. Airoldi is a member of the prestigious Association for the Advancement of Artificial Intelligence (AAAI) and the International Machine Learning Society (IMLS). He has published over 200 papers in leading journals and conferences, and his work has been covered by various media outlets including The New York Times, The Wall Street Journal, The Economist, and Wired.
Most Relevant Publications (20+)

106 total publications

A Model of Text for Experimentation in the Social Sciences

Journal of the American Statistical Association / Jul 02, 2016

Roberts, M. E., Stewart, B. M., & Airoldi, E. M. (2016). A Model of Text for Experimentation in the Social Sciences. Journal of the American Statistical Association, 111(515), 988–1003. https://doi.org/10.1080/01621459.2016.1141684

Stochastic blockmodels with a growing number of classes

Biometrika / Apr 17, 2012

Choi, D. S., Wolfe, P. J., & Airoldi, E. M. (2012). Stochastic blockmodels with a growing number of classes. Biometrika, 99(2), 273–284. https://doi.org/10.1093/biomet/asr053

Quantitative visualization of alternative exon expression from RNA-seq data

Bioinformatics / Jan 22, 2015

Katz, Y., Wang, E. T., Silterra, J., Schwartz, S., Wong, B., Thorvaldsdóttir, H., Robinson, J. T., Mesirov, J. P., Airoldi, E. M., & Burge, C. B. (2015). Quantitative visualization of alternative exon expression from RNA-seq data. Bioinformatics, 31(14), 2400–2402. https://doi.org/10.1093/bioinformatics/btv034

Identification and Estimation of Treatment and Interference Effects in Observational Studies on Networks

Journal of the American Statistical Association / Jun 30, 2020

Forastiere, L., Airoldi, E. M., & Mealli, F. (2020). Identification and Estimation of Treatment and Interference Effects in Observational Studies on Networks. Journal of the American Statistical Association, 116(534), 901–918. https://doi.org/10.1080/01621459.2020.1768100

Asymptotic and finite-sample properties of estimators based on stochastic gradients

The Annals of Statistics / Aug 01, 2017

Toulis, P., & Airoldi, E. M. (2017). Asymptotic and finite-sample properties of estimators based on stochastic gradients. The Annals of Statistics, 45(4). https://doi.org/10.1214/16-aos1506

Improving and Evaluating Topic Models and Other Models of Text

Journal of the American Statistical Association / Oct 01, 2016

Airoldi, E. M., & Bischof, J. M. (2016). Improving and Evaluating Topic Models and Other Models of Text. Journal of the American Statistical Association, 111(516), 1381–1403. https://doi.org/10.1080/01621459.2015.1051182

Model-assisted design of experiments in the presence of network-correlated outcomes

Biometrika / Aug 06, 2018

Basse, G. W., & Airoldi, E. M. (2018). Model-assisted design of experiments in the presence of network-correlated outcomes. Biometrika, 105(4), 849–858. https://doi.org/10.1093/biomet/asy036

Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study

Statistics in Medicine / Jan 01, 2017

Lunceford, J. K. (2017). Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study. Statistics in Medicine. Portico. https://doi.org/10.1002/sim.7231

The proximal Robbins–Monro method

Journal of the Royal Statistical Society: Series B (Statistical Methodology) / Dec 09, 2020

Toulis, P., Horel, T., & Airoldi, E. M. (2020). The proximal Robbins–Monro method. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 83(1), 188–212. Portico. https://doi.org/10.1111/rssb.12405

Testing for arbitrary interference on experimentation platforms

Biometrika / Sep 30, 2019

Pouget-Abadie, J., Saint-Jacques, G., Saveski, M., Duan, W., Ghosh, S., Xu, Y., & Airoldi, E. M. (2019). Testing for arbitrary interference on experimentation platforms. Biometrika, 106(4), 929–940. https://doi.org/10.1093/biomet/asz047

Geometric Representations of Random Hypergraphs

Journal of the American Statistical Association / Jan 02, 2017

Lunagómez, S., Mukherjee, S., Wolpert, R. L., & Airoldi, E. M. (2017). Geometric Representations of Random Hypergraphs. Journal of the American Statistical Association, 112(517), 363–383. https://doi.org/10.1080/01621459.2016.1141686

Intersection of the Web-Based Vaping Narrative With COVID-19: Topic Modeling Study

Journal of Medical Internet Research / Oct 30, 2020

Janmohamed, K., Soale, A.-N., Forastiere, L., Tang, W., Sha, Y., Demant, J., Airoldi, E., & Kumar, N. (2020). Intersection of the Web-Based Vaping Narrative With COVID-19: Topic Modeling Study. Journal of Medical Internet Research, 22(10), e21743. https://doi.org/10.2196/21743

Scalable estimation strategies based on stochastic approximations: classical results and new insights

Statistics and Computing / Jun 11, 2015

Toulis, P., & Airoldi, E. M. (2015). Scalable estimation strategies based on stochastic approximations: classical results and new insights. Statistics and Computing, 25(4), 781–795. https://doi.org/10.1007/s11222-015-9560-y

Estimating a Structured Covariance Matrix From Multilab Measurements in High-Throughput Biology

Journal of the American Statistical Association / Jan 02, 2015

Franks, A. M., Csárdi, G., Drummond, D. A., & Airoldi, E. M. (2015). Estimating a Structured Covariance Matrix From Multilab Measurements in High-Throughput Biology. Journal of the American Statistical Association, 110(509), 27–44. https://doi.org/10.1080/01621459.2014.964404

Generalized Species Sampling Priors With Latent Beta Reinforcements

Journal of the American Statistical Association / Oct 02, 2014

Airoldi, E. M., Costa, T., Bassetti, F., Leisen, F., & Guindani, M. (2014). Generalized Species Sampling Priors With Latent Beta Reinforcements. Journal of the American Statistical Association, 109(508), 1466–1480. https://doi.org/10.1080/01621459.2014.950735

Estimating Latent Processes on a Network From Indirect Measurements

Journal of the American Statistical Association / Mar 01, 2013

Airoldi, E. M., & Blocker, A. W. (2013). Estimating Latent Processes on a Network From Indirect Measurements. Journal of the American Statistical Association, 108(501), 149–164. https://doi.org/10.1080/01621459.2012.756328

Multi-way blockmodels for analyzing coordinated high-dimensional responses

The Annals of Applied Statistics / Dec 01, 2013

Airoldi, E. M., Wang, X., & Lin, X. (2013). Multi-way blockmodels for analyzing coordinated high-dimensional responses. The Annals of Applied Statistics, 7(4). https://doi.org/10.1214/13-aoas643

Confidence sets for network structure

Statistical Analysis and Data Mining / Sep 09, 2011

Airoldi, E. M., Choi, D. S., & Wolfe, P. J. (2011). Confidence sets for network structure. Statistical Analysis and Data Mining, 4(5), 461–469. https://doi.org/10.1002/sam.10136

Ranking relations using analogies in biological and information networks

The Annals of Applied Statistics / Jun 01, 2010

Silva, R., Heller, K., Ghahramani, Z., & Airoldi, E. M. (2010). Ranking relations using analogies in biological and information networks. The Annals of Applied Statistics, 4(2). https://doi.org/10.1214/09-aoas321

Who wrote Ronald Reagan's radio addresses?

Bayesian Analysis / Jun 01, 2006

Airoldi, E. M., Anderson, A. G., Fienberg, S. E., & Skinner, K. K. (2006). Who wrote Ronald Reagan’s radio addresses? Bayesian Analysis, 1(2). https://doi.org/10.1214/06-ba110

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Jeffrey Townsend

New Haven, CT, Connecticut, United States of America
29 Years Experience
Professor of Biostatistics and Ecology & Evolutionary Biology
Education

Harvard University

Ph.D., Organismic and Evolutionary Biology / May, 2002

Cambridge, Massachusetts, United States of America

Brown University

Sc.B., Biology / May, 1994

Providence, Rhode Island, United States of America
Experience

Yale University

Professor / July, 2018Present

Elihu Professor of Biostatistics / July, 2018Present

Elihu Associate Professor of Biostatistics / July, 2017June, 2018

Associate Professor / July, 2013June, 2018

Associate Professor / July, 2013June, 2017

Assistant Professor / July, 2006June, 2013

University of Connecticut

Assistant Professor / August, 2004May, 2006

St. Ann's School

Teacher / September, 1994June, 1997

Most Relevant Research Expertise
Health Informatics
Statistics and Probability
Other Research Expertise (51)
Evolutionary Genomics
Microbiology
Infectious Diseases
Genetics
Cell Biology
And 46 more
About
Jeffrey Townsend is a Professor of Organismic and Evolutionary Biology at Yale University. He received his Ph.D. from Harvard University in 2002 and his Sc.B. from Brown University in 1994. He has been a teacher at St. Ann's School and an Assistant Professor at the University of Connecticut. He is currently the Elihu Professor of Biostatistics at Yale University.
Most Relevant Publications (6+)

207 total publications

Jot: guiding journal selection with suitability metrics

Journal of the Medical Library Association / Dec 08, 2022

Gaffney, S. G., & Townsend, J. P. (2022). Jot: guiding journal selection with suitability metrics. Journal of the Medical Library Association, 110(3), 376–380. https://doi.org/10.5195/jmla.2022.1499

PathScore: a web tool for identifying altered pathways in cancer data

Bioinformatics / Aug 08, 2016

Gaffney, S. G., & Townsend, J. P. (2016). PathScore: a web tool for identifying altered pathways in cancer data. Bioinformatics, 32(23), 3688–3690. https://doi.org/10.1093/bioinformatics/btw512

H-CLAP: hierarchical clustering within a linear array with an application in genetics

Statistical Applications in Genetics and Molecular Biology / Jan 01, 2015

Ghosh, S., & Townsend, J. P. (2015). H-CLAP: hierarchical clustering within a linear array with an application in genetics. Statistical Applications in Genetics and Molecular Biology, 14(2). https://doi.org/10.1515/sagmb-2013-0076

AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification

Bioinformatics / Jun 03, 2013

Dai, L., Tian, M., Wu, J., Xiao, J., Wang, X., Townsend, J. P., & Zhang, Z. (2013). AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification. Bioinformatics, 29(14), 1837–1839. https://doi.org/10.1093/bioinformatics/btt284

LOX: inferring Level Of eXpression from diverse methods of census sequencing

Bioinformatics / Jun 10, 2010

Zhang, Z., López-Giráldez, F., & Townsend, J. P. (2010). LOX: inferring Level Of eXpression from diverse methods of census sequencing. Bioinformatics, 26(15), 1918–1919. https://doi.org/10.1093/bioinformatics/btq303

HCLS 2.0/3.0: Health care and life sciences data mashup using Web 2.0/3.0

Journal of Biomedical Informatics / Oct 01, 2008

Cheung, K.-H., Yip, K. Y., Townsend, J. P., & Scotch, M. (2008). HCLS 2.0/3.0: Health care and life sciences data mashup using Web 2.0/3.0. Journal of Biomedical Informatics, 41(5), 694–705. https://doi.org/10.1016/j.jbi.2008.04.001

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Giuliana Noratto

15 Years Experience
Food Scientist PhD and Registered Dietician - Texas A&M University
Education

Texas A&M University

Texas A&M University System

Ph.D., Department of Food Science and Technology

College Station

Universidad Nacional Agraria La Molina

M.Sc., Food Science and Technology

Lima
Experience

Texas A&M AgriLife

Senior Associate Research Scientist / August, 2016Present

Washington State

Assistant Professor - Head of Food Science lab / 20122016

Research focus is on the role of nutrition in the prevention or progress of obesity-related chronic diseases. We investigate food bioactive compounds with the main goal of uncovering the molecular mechanisms by which diet derived compounds interact with the genome (effect on gene and protein expression and biomarkers) to shift the onset or outcome of disease. Research projects are centered around: - Milk and dairy-derived bioactive compounds - Plant food botanicals

Texas A&M University

Research Scientist / 20082012

In charge of projects dealing with effects of natural plant extracts to prevent or cure cancer, diabetes, and cardiovascular complications; all these having in common to be the result of inflammation and obesity.

Research Expertise (29)
Food Science
Nutrition
Human Health
Analytical Chemistry
Nutrition and Dietetics
And 24 more
About
Dr. Giuliana Noratto is a senior associate research scientist at Texas A&M AgriLife. She received her Ph.D. in food science and technology from Texas A&M University System, and her M.Sc. in food science and technology from Universidad Nacional Agraria La Molina. She also holds a B.S. in food science and technology from Universidad Nacional Agraria La Molina. Dr. Noratto’s research interests include food safety and quality, sensory science, and food processing.

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Tim Leung

15 Years Experience
Professor of Applied Mathematics, Computational Finance & Risk Management (CFRM) Program
Education

Princeton University

PhD, Operations Research & Financial Engineering

Princeton, New Jersey, United States of America

Cornell University

B.S., Operations Research & Industrial Engineering / May, 2003

Ithaca, New York, United States of America
Experience

University of Washington

Professor / 2016Present

Columbia University

Assistant Professor / 20112016

Johns Hopkins University

Assistant Professor / 20082011

Most Relevant Research Expertise
Risk Management
Statistics, Probability and Uncertainty
Statistics and Probability
Numerical Analysis
Other Research Expertise (18)
Computational Finance
Portfolio Optimization
ETFs
Finance
Applied Mathematics
And 13 more
About
Tim Leung is a professor of operations research and financial engineering at the University of Washington. He holds a PhD from Princeton University and a B.S. from Cornell University. He has held previous positions as an assistant professor at Columbia University and Johns Hopkins University.
Most Relevant Publications (10+)

138 total publications

Stochastic modeling and fair valuation of drawdown insurance

Insurance: Mathematics and Economics / Nov 01, 2013

Zhang, H., Leung, T., & Hadjiliadis, O. (2013). Stochastic modeling and fair valuation of drawdown insurance. Insurance: Mathematics and Economics, 53(3), 840–850. https://doi.org/10.1016/j.insmatheco.2013.10.006

Optimal starting–stopping and switching of a CIR process with fixed costs

Risk and Decision Analysis / Jan 01, 2014

Leung, T., Li, X., & Wang, Z. (2014). Optimal starting–stopping and switching of a CIR process with fixed costs. Risk and Decision Analysis, 5(2–3), 149–161. https://doi.org/10.3233/rda-140107

Timing options for a startup with early termination and competition risks

Risk and Decision Analysis / May 31, 2017

Leung, T., & Li, Z. (2017). Timing options for a startup with early termination and competition risks. Risk and Decision Analysis, 6(2), 151–166. https://doi.org/10.3233/rda-170120

ESO Valuation with Job Termination Risk and Jumps in Stock Price

SIAM Journal on Financial Mathematics / Jan 01, 2015

Leung, T., & Wan, H. (2015). ESO Valuation with Job Termination Risk and Jumps in Stock Price. SIAM Journal on Financial Mathematics, 6(1), 487–516. https://doi.org/10.1137/130937949

Optimal Multiple Trading Times Under the Exponential OU Model with Transaction Costs

Stochastic Models / Jul 16, 2015

Leung, T., Li, X., & Wang, Z. (2015). Optimal Multiple Trading Times Under the Exponential OU Model with Transaction Costs. Stochastic Models, 31(4), 554–587. https://doi.org/10.1080/15326349.2015.1058717

Default swap games driven by spectrally negative Lévy processes

Stochastic Processes and their Applications / Feb 01, 2013

Egami, M., Leung, T., & Yamazaki, K. (2013). Default swap games driven by spectrally negative Lévy processes. Stochastic Processes and Their Applications, 123(2), 347–384. https://doi.org/10.1016/j.spa.2012.09.008

Outperformance portfolio optimization via the equivalence of pure and randomized hypothesis testing

Finance and Stochastics / Aug 27, 2013

Leung, T., Song, Q., & Yang, J. (2013). Outperformance portfolio optimization via the equivalence of pure and randomized hypothesis testing. Finance and Stochastics, 17(4), 839–870. https://doi.org/10.1007/s00780-013-0213-8

Accounting for risk aversion in derivatives purchase timing

Mathematics and Financial Economics / Feb 24, 2012

Leung, T., & Ludkovski, M. (2012). Accounting for risk aversion in derivatives purchase timing. Mathematics and Financial Economics, 6(4), 363–386. https://doi.org/10.1007/s11579-012-0063-8

Forward indifference valuation of American options

Stochastics / Jun 19, 2012

Leung, T., Sircar, R., & Zariphopoulou, T. (2012). Forward indifference valuation of American options. Stochastics, 84(5–6), 741–770. https://doi.org/10.1080/17442508.2012.694438

Optimal Timing to Purchase Options

SIAM Journal on Financial Mathematics / Jan 01, 2011

Leung, T., & Ludkovski, M. (2011). Optimal Timing to Purchase Options. SIAM Journal on Financial Mathematics, 2(1), 768–793. https://doi.org/10.1137/100809386

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Osaye Fadekemi, PhD

4 Years Experience
Assistant Professor of Mathematics at Alabama State University with expertise in Graph Theory and Network Modeling
Education

University of Johannesburg

Doctor of Philosophy, Department of Pure and Applied Mathematics / July, 2019

Auckland Park

University of KwaZulu-Natal

Master of Science, School of Mathematics, Statistics and Computer Science / March, 2015

Durban

African Institute For Mathematical Sciences Ghana

Master of Science, Mathematical Sciences / June, 2013

Biriwa
Experience

Auburn University Auburn

Visiting Asisitant Professor / August, 2019May, 2021

Alabama State University

Assistant Professor / June, 2021Present

Most Relevant Research Expertise
Disease Modeling
Other Research Expertise (11)
Graph Theory
Network Modeling
Discrete Mathematics and Combinatorics
Theoretical Computer Science
Applied Mathematics
And 6 more
About
Dr Fadekemi Janet Osaye is a mathematician whose primary research interest is in graph theory and network modeling. In particular, she is interested in distance measures in graphs and their applications to solving many real-world problems. Her interest in discrete mathematics was inspired by her research project carried out at AIMS Ghana. She has published several articles in reputable journals and has presented in several conferences across the globe. In 2019, she became the first black female to be awarded a PhD in Mathematics by the University of Johannesburg, South Africa, in its 116 years of its existence. Since June 2021, she has been an Assistant Professor of Mathematics at Alabama State University and was previously a Visiting Assistant Professor at Auburn University. She is the founder of GirlsMatics Foundation, a STEM non-governmental organisation for girls in Nigeria which was motivated by her involvement with AIMS Ghana’s outreach programs for high school students in Biriwa, Ghana. She is also the co-founder of FadNna Partners, an analytics and management firm based in Lagos, Nigeria.

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Sicun Fan

Georgia
12 Years Experience
Metagenomics, NGS, and Biotechnology Expert with extensive experience in foodborne pathogens, probiotics research, and related domains.
Education

North Carolina State University

PhD, major, Food Science / October, 2022

Raleigh, North Carolina, United States of America

North Carolina State University

PhD, minor, Biotechnology / October, 2022

Raleigh, North Carolina, United States of America
Experience

USDA

Postdoctoral Fellow / October, 2022December, 2024

1.Evaluation of the bacterial metagenome in retail poultry to improve pathogen control strategies. 2.Quantification of Salmonella and Campylobacter during poultry processing.

Bristol Myers Squibb

Upstream Process Development Intern / May, 2022August, 2022

Developed a MinION sequencing platform to identify integration hotspots in CHO cells.

North Carolina State University

Teaching Assistant / August, 2020May, 2022

Supervised 60 students in: (1)Virus Biotechnology and (2) Core Technologies in Molecular & Cellular Biology.

Most Relevant Research Expertise
data analysis
statistics
Other Research Expertise (9)
metagenomics
NGS
biotechnology
molecular biology
food safety
And 4 more
About
I bring **years of experience in experimental design, wet lab, data analysis, and problem-solving** across both **academic** and **industry settings**. My expertise extends to **project planning and budget management**, ensuring efficient execution of research and development initiatives. I am passionate about **leveraging cutting-edge technologies** to address complex challenges in **microbiology, food safety, and health sciences**. Please feel free to connect to discuss how my skills in **molecular biology, biotechnology, and food safety** can contribute to driving innovation and success in your organization!

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Panos Ipeirotis

19 Years Experience
Professor at New York University
Education

Columbia University

PhD, Computer Science / August, 2004

New York, New York, United States of America

University of Patras

Diploma in Engineering, Computer Engineering and Informatics / July, 1999

Patras
Experience

New York University Stern School of Business

Professor / September, 2004Present

Compass

Distinguished Scientist / April, 2019May, 2022

Google Inc

Visiting Scientist / February, 2013September, 2014

Most Relevant Research Expertise
Statistics, Probability and Uncertainty
Statistics and Probability
Other Research Expertise (23)
Crowdsourcing
Data Quality
Economics and Econometrics
Applied Psychology
Computational Theory and Mathematics
And 18 more
About
Crowdsourcing,machine learning, databases,Online Labor Markets,Social Media Analytics,Data Mining,Information Retrieval
Most Relevant Publications (2+)

97 total publications

Statistical considerations for crowdsourced perceptual ratings of human speech productions

Journal of Applied Statistics / Nov 14, 2018

Fernández, D., Harel, D., Ipeirotis, P., & McAllister, T. (2018). Statistical considerations for crowdsourced perceptual ratings of human speech productions. Journal of Applied Statistics, 46(8), 1364–1384. https://doi.org/10.1080/02664763.2018.1547692

Introduction to the Special Issue on EC’12

ACM Transactions on Economics and Computation / Mar 27, 2015

Leyton-Brown, K., & Ipeirotis, P. (Eds.). (2015). Introduction to the Special Issue on EC’12. ACM Transactions on Economics and Computation, 3(1), 1–2. https://doi.org/10.1145/2742678

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