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Frederick Cheung
CTO at Dressipi
algorithm, array data structure, attention, augustine of hippo, bayes' theorem, bit, brand, c (programming language), database, email, evaluation, experiment, facebook, garbage collection (computer science), gas, hash function, intelligence quotient, json, justice, landing page, mathematics, measurement, medication, memory, memory management, p-value, paper, prediction, probability, probability distribution, programming, race condition, reason, recommender system, reputation, ruby, ruby (programming language), rubyconf, runtime system, sample (statistics), sample size determination, statistical hypothesis testing, statistical significance, string (computer science), symbol, time, twitter, uncertainty, understanding, variance, wheel
San Gultekin
Ph.D., Research Scientist at Verizon Media
air pollution, algorithm, bomb, car, child, concentration, constitution of texas, earth, experiment, exponentiation, facebook, function (mathematics), hypothesis, inner product space, learning, likelihood function, mcdonald's, ratio, research, risk, sample size determination, solution, summation, texas, triangle
Peiyuan Zhu
Student at The University of British Columbia Department of Statistics
action film, bayesian inference, cluster analysis, data, database, determinism, experiment, infection, likelihood function, logarithm, markov chain monte carlo, mathematics, negative binomial distribution, number, observation, prediction, sample size determination, sampler (musical instrument), science, sequence, solid modeling, statistical inference, temperature, theory, truncation (statistics)
Sorawit Saengkyongam
Doctoral Researcher at Copenhagen Causality Lab
bed, beyoncé, blood, blood pressure, correlation and dependence, data, definition, expected value, experiment, hot rod, information, kentucky, kidney, lumbar puncture, paper, parameter, prediction, pressure, prom, question, randomized controlled trial, sample size determination, scanning electron microscope, statistics, united states
Jakob Runge
Researcher at German Aerospace Agency
attention, autocorrelation, causality, data, exercise, experiment, eye, false positives and false negatives, graph (discrete mathematics), information, intersectionality, london, moon, mutual information, polymerase chain reaction, power of a test, reliability (statistics), sample size determination, sepsis, statistic, statistical significance, test statistic, time series, truth, type i and type ii errors
Arnab Mondal
Ph.D. Scholar at IIT Delhi
air pollution, algorithm, causal graph, causality, correlation and dependence, data, diamond, dog, earth, efficacy, entropy (information theory), escambia county, florida, experiment, ice, information, joint probability distribution, mathematics, mean, minimax, mutual information, pearson correlation coefficient, rain, random variable, regression analysis, saipan, sample size determination, science, toyota prius
Jan-Christian Huetter
Postdoctoral researcher at Broad Institute of MIT and Harvard
causal model, causality, equation, estimator, experiment, infidelity, lasso (statistics), likelihood function, linearity, logarithm, mathematical optimization, matrix (mathematics), maximum likelihood estimation, mean, minimax, minimax estimator, normal distribution, observation, random variable, sample size determination, sparse matrix, structural equation modeling, the matrix, universe, variable (mathematics)
Matt Brems
Data Scientist at Betavector
confidence interval, data analysis, decision tree learning, deductive reasoning, deviation (statistics), errors and residuals, ethics, forecasting, imputation (statistics), inference, linear regression, logic, mean, median, missing data, mode (statistics), opinion poll, p-value, prediction, random forest, regression analysis, sample size determination, standard deviation, statistical classification, statistical hypothesis testing
Jing Gao
Associate Professor at University at Buffalo, USA
acm 2020, artificial intelligence, big data, causal inference, causality, computer science 2020, computer science event 2020, computer vision, correlation and dependence, counterfactual conditional, covariance, data science, deep learning 2020, dependent and independent variables, experiment, hypothesis, kdd2020, knowledge, linear regression, logistic regression, machine learning, machine learning 2020, pearson correlation coefficient, placebo, prediction, recommender system, regression analysis, risk, sample size determination, science, statistical classification, statistical inference, truth
Zhixuan Chu
PhD student at University of Georgia, USA
acm 2020, artificial intelligence, big data, causal inference, causality, computer science 2020, computer science event 2020, computer vision, correlation and dependence, counterfactual conditional, covariance, data science, deep learning 2020, dependent and independent variables, experiment, hypothesis, kdd2020, knowledge, linear regression, logistic regression, machine learning, machine learning 2020, pearson correlation coefficient, placebo, prediction, recommender system, regression analysis, risk, sample size determination, science, statistical classification, statistical inference, truth
Liuyi Yao
PhD student at University at Buffalo, USA
acm 2020, artificial intelligence, big data, causal inference, causality, computer science 2020, computer science event 2020, computer vision, correlation and dependence, counterfactual conditional, covariance, data science, deep learning 2020, dependent and independent variables, experiment, hypothesis, kdd2020, knowledge, linear regression, logistic regression, machine learning, machine learning 2020, pearson correlation coefficient, placebo, prediction, recommender system, regression analysis, risk, sample size determination, science, statistical classification, statistical inference, truth
Sheng Li
Assistant Professor at Computer Science at University of Georgia
acm 2020, artificial intelligence, big data, causal inference, causality, computer science 2020, computer science event 2020, computer vision, correlation and dependence, counterfactual conditional, covariance, data science, deep learning 2020, dependent and independent variables, experiment, hypothesis, kdd2020, knowledge, linear regression, logistic regression, machine learning, machine learning 2020, pearson correlation coefficient, placebo, prediction, recommender system, regression analysis, risk, sample size determination, science, statistical classification, statistical inference, truth
Zheyan Shen
PhD Candidate at Tsinghua University
acm 2020, artificial intelligence, big data, causal inference, causality, computer science 2020, computer science event 2020, computer vision, correlation and dependence, counterfactual conditional, covariance, data science, deep learning 2020, dependent and independent variables, experiment, hypothesis, kdd2020, knowledge, linear regression, logistic regression, machine learning, machine learning 2020, pearson correlation coefficient, placebo, prediction, recommender system, regression analysis, risk, sample size determination, science, statistical classification, statistical inference, truth
Peng Cui
Associate Professor at Tsinghua University
acm 2020, artificial intelligence, big data, causal inference, causality, computer science 2020, computer science event 2020, computer vision, correlation and dependence, counterfactual conditional, covariance, data science, deep learning 2020, dependent and independent variables, experiment, hypothesis, kdd2020, knowledge, linear regression, logistic regression, machine learning, machine learning 2020, pearson correlation coefficient, placebo, prediction, recommender system, regression analysis, risk, sample size determination, science, statistical classification, statistical inference, truth
Lee Rhodes
Distinguished Architect at Verizon Media
acm 2020, artificial intelligence, association for computing machinery, big data, computer science, computer science event 2020, computer vision 2020, confidence interval, cumulative distribution function, deep learning, differential privacy, dimensionality reduction, estimation theory, hyperloglog, kdd2020, likelihood function, loss function, machine learning, mean, mode (statistics), numerical analysis, online and offline, probability distribution, quantile, quantization (signal processing), regression analysis, robust statistics, sample size determination, sampling (statistics), selection algorithm, singular value decomposition, sorting algorithm, support-vector machine
Jonathan Malkin
Distinguished Architect at Verizon Media
acm 2020, artificial intelligence, association for computing machinery, big data, computer science, computer science event 2020, computer vision 2020, confidence interval, cumulative distribution function, deep learning, differential privacy, dimensionality reduction, estimation theory, hyperloglog, kdd2020, likelihood function, loss function, machine learning, mean, mode (statistics), numerical analysis, online and offline, probability distribution, quantile, quantization (signal processing), regression analysis, robust statistics, sample size determination, sampling (statistics), selection algorithm, singular value decomposition, sorting algorithm, support-vector machine
Daniel Ting
Staff Research Scientist at Tableau
acm 2020, artificial intelligence, association for computing machinery, big data, computer science, computer science event 2020, computer vision 2020, confidence interval, cumulative distribution function, deep learning, differential privacy, dimensionality reduction, estimation theory, hyperloglog, kdd2020, likelihood function, loss function, machine learning, mean, mode (statistics), numerical analysis, online and offline, probability distribution, quantile, quantization (signal processing), regression analysis, robust statistics, sample size determination, sampling (statistics), selection algorithm, singular value decomposition, sorting algorithm, support-vector machine
Brittany Casey
Pediatric Hospital Medicine Fellow at Johns Hopkins All Children’s Hospital
attention, breathing, communication, deep learning, electronic health record, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical record, neural network, patient, pediatrics, point of care, positive and negative predictive values, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, truth
Paola Dees
Physician at Johns Hopkins All Children's Hospital
attention, breathing, communication, deep learning, electronic health record, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical record, neural network, patient, pediatrics, point of care, positive and negative predictive values, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, truth
John Morrison
Assistant Professor of Pediatrics at The Johns Hopkins University School of Medicine
attention, breathing, communication, deep learning, electronic health record, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical record, neural network, patient, pediatrics, point of care, positive and negative predictive values, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, truth
Mohamed Rehman
Eric Kobren Professor of Applied Health Informatics at The Johns Hopkins University School of Medicine
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Luis Ahumada
ДолжностьDirector Center for Pediatric Data Science and Analytic Methodology at Johns Hopkins All Children's Hospital
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Ali Jalali
Senior Data Scientist at Biofourmis
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Hannah Lonsdale
Clinical Research Associate at The Johns Hopkins University
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Tom Haskell
Global Head of Data Analytics at Kantar Health
agnosticism, artificial neural network, bit, data, data fusion, database, denmark, diabetes, disease, genocide, health, information, insurance, islam, linkedin, methodology, neural network, patient, patient-reported outcome, prediction, sample size determination, server (computing), statistical model, terrorism, type 2 diabetes
Lulu Lee
Vice President, Health Outcomes, Real World Evidence at Kantar Health
agnosticism, artificial neural network, bit, data, data fusion, database, denmark, diabetes, disease, genocide, health, information, insurance, islam, linkedin, methodology, neural network, patient, patient-reported outcome, prediction, sample size determination, server (computing), statistical model, terrorism, type 2 diabetes
Srikesh Arunajadai
Vice President of Data Science at Kantar Health
agnosticism, artificial neural network, bit, data, data fusion, database, denmark, diabetes, disease, genocide, health, information, insurance, islam, linkedin, methodology, neural network, patient, patient-reported outcome, prediction, sample size determination, server (computing), statistical model, terrorism, type 2 diabetes
Karim Varela
CEO & Founder at Civilized Software
advertising, amazon web services, analytics, attribution (marketing), brand, cloud computing, confidence interval, credit card, data, experian, general data protection regulation, kubernetes , mathematics, online advertising, online and offline, personal data, publish–subscribe pattern, sales, sample size determination, smart tv, sponsor (commercial), sponsorships , standard deviation, statistics, student's t-test, twitter, visa inc.
Vern Rabe
Data Architect at International Medical Corps
algorithm, array data structure, average, bit, code, computer, control flow, correlation and dependence, database, database index, decimal, estimator, experiment, hash table, histogram, microsoft sql server, null (sql), parameter, query optimization, sample size determination, sql, statistics, stored procedure, subroutine, table (database), unit price
Eric Ma
Investigator II (Data Science & Statistical Learning) at Novartis Institutes for BioMedical Research (NIBR)
adjacency matrix, anonymous function, apis, artificial neural network, automatic differentiation, bayes' theorem, bayesian, bayesian inference, bayesian network, bayesian statistics, behavior, belief, bernoulli process, beta distribution, betweenness centrality, bias of an estimator, binomial distribution, bipartite graph, bootstrapping (statistics), breadth-first search, calculus, call stack, cauchy distribution, central limit theorem, centrality, clique (graph theory), coding, comma-separated values, compiler, component (graph theory), confidence interval, consumer behaviour, cross entropy, cross-validation (statistics), cut, copy, and paste, data science, data visualization , debugging, deep learning, degrees of freedom (statistics), density, depth-first search, derivative, ecology, effect size, electric power transmission, empirical bayes method, engineering, eric ma, errors and residuals, estimation theory, experience, exponential distribution, fan fiction, feed forward (control), for loop, function (mathematics), gender, generalized linear model, generative model, gif, gradient, gradient descent, graduate school, graph (discrete mathematics), histogram, imputation (statistics), integral, interquartile range, joint probability distribution, knowledge, language, learning, likelihood function, limit of a function, linear map, logarithm, logistic function, logistic regression, loss function, machine learning, marginal distribution, mathematical optimization, mathematics, matrix (mathematics), matrix multiplication, maxima and minima, maximum likelihood estimation, mean squared error, median, mentorship, metadata, microsoft excel, mixture distribution, mixture model, mode (statistics), negative binomial distribution, network analysis, network science, normal distribution, nothing, null (sql), numpy, outcome (probability), outlier, p-value, parameter, parameter (computer programming), pathfinding, pdf, poisson distribution, postdoctoral researcher, prediction, prior probability, probabilistic programming, probability distribution, probability mass function, productivity, programmer, project jupyter, pycon, pyjanitpr, python, python (programming language), random variable, random walk, reality, reason, regression analysis, resampling (statistics), research, reserved word, row and column vectors, sample size determination, scalar (mathematics), science, scipy, shortest path problem, simulation, slope, software bug, source lines of code, stack (abstract data type), standard deviation, statistical hypothesis testing, statistical inference, statistical model, statistics, student's t-distribution, student's t-test, symmetric matrix, table (database), time series, transpose, travelling salesman problem, tree (graph theory), tutorial, twitter, type system, uncertainty, value (economics), variance, vector space, visualization (graphics), worldview
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