Experts and Thought Leaders in Statistics

Yseult Héjja-Brichard, Ph.D.

Baltimore, Maryland, United States of America

Postdoctoral researcher in Biological Sciences at University of Maryland Baltimore County

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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Ryan Howell

San Francisco , California, United States of America

Professor of Psychology, Department of Psychology, San Francisco State University

Most Relevant Research Interests

Cognitive Neuroscience

Health Informatics

Other Research Interests (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+)

66 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

Most Relevant Research Interests

Statistics

Statistics, Probability and Uncertainty

Statistics and Probability

Analysis

Health Informatics

Other Research Interests (39)

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

Professor of Biostatistics and Ecology & Evolutionary Biology

Most Relevant Research Interests

Health Informatics

Statistics and Probability

Other Research Interests (51)

Evolutionary Genomics

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

Food Scientist PhD and Registered Dietician - Texas A&M University

Research Interests (29)

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

Professor of Applied Mathematics, Computational Finance & Risk Management (CFRM) Program

Most Relevant Research Interests

Risk Management

Statistics, Probability and Uncertainty

Statistics and Probability

Numerical Analysis

Other Research Interests (18)

Computational Finance

Portfolio Optimization

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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Mengying Li

Assistant Professor at The Hong Kong Polytechnic University

Research Interests (23)

Electrical and Electronic Engineering

Instrumentation

Renewable Energy, Sustainability and the Environment

Computer Science Applications

Control and Systems Engineering

And 18 more

About

Mengying Li is an Assistant Professor at The Hong Kong Polytechnic University. She received her Ph.D. in Mechanical Engineering from University of California, San Diego in 2018. Her research interests include predictive modeling, design optimization, and machine learning. She is also an expert in passive cooling devices.

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Osaye Fadekemi, PhD

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

Most Relevant Research Interests

Disease Modeling

Other Research Interests (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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Panos Ipeirotis

Professor at New York University

Most Relevant Research Interests

Statistics, Probability and Uncertainty

Statistics and Probability

Other Research Interests (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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