Events Add an event Speakers Talks Collections
 

Speakers

Sort by
Newest
Trending
1-30 of 104
1-30 of 104
Filter
Davide Venturelli
Artificial Intelligence, Quantum Computing, Physics, Robotics, Entrepreneurship at USRA
algorithm, application software, bayesian inference, brute-force search, cluster analysis, computing, database index, estimation theory, gradient descent, likelihood function, linear programming, machine learning, mathematical optimization, matrix (mathematics), maximum a posteriori estimation, maximum likelihood estimation, mean, quantum computing, quantum superposition, sampling (statistics), software , statistical inference, statistics, support-vector machine, zero-sum game
Shane Milton
Technical Architect at CleanSlate
active directory, algorithm, algorithm selection, api, automated machine learning, automation, azure, bayesian inference, bundle (macos), central processing unit, cloud, cloud conference, command-line interface, computer, computer data storage, computer file, computing, cosmos db, database, devops, ensemble learning, entry point, hard coding, hypertext transfer protocol, input/output, intelligence, internet of things, kaggle, kernel (operating system), linear regression, machine learning, microsoft sql server, microsoft windows, ml.net, multiclass classification, operating system, platform as a service, regression analysis, representational state transfer, server (computing), serverless computing, six feet up, sixfeetup, software as a service, software bug, stack (abstract data type), statistical classification, string (computer science), system call, tensorflow, training, validation, and test sets, unsupervised learning, virtual, virtual conference, web application, world wide web
Beau Coker
PhD student at Harvard University
artificial neural network, attention, bayesian inference, covariance, force, function (mathematics), gas, global positioning system, ground truth, information, integral, logarithm, mathematical optimization, mean, parameter, poisson point process, radial basis function network, smoothness, stationary process, tank, uncertainty, variance, wave, weather, wind
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)
Ioan Gabriel Bucur
Machine Learning Engineer at Radboud University
aldh2, bayesian inference, cardiovascular disease, causal graph, causality, complexity, compound probability distribution, computational complexity theory, confounding, correlation and dependence, function (biology), function (mathematics), genome-wide association study, instrumental variables estimation, laplace's method, likelihood function, marginal likelihood, markov chain, markov chain monte carlo, mathematical optimization, mixture, normal distribution, parameter, risk, shrinkage (statistics)
Xinming Liu
PhD student at MIT Operations Research Center (ORC)
absalom, bayesian inference, bayesian probability, behavior, bit, contract, cornell university, cost, economic system, failure, gambling, human behavior, las vegas, machine, mathematics, meal, memory, negativity bias, paper, probability, rationality, resource, slot machine, tournament, utility
Hanwen Xing
Student at University of Oxford
american broadcasting company, approximate bayesian computation, approximation, aquarium, average, bayesian inference, biopsy, cumulative distribution function, derivative, distortion, equation, function (mathematics), hawaii, inference, letter case, likelihood function, map, paper, parameter, probability, regression analysis, tattoo, truth, weather, weather forecasting
Richard Seiersen
CISO | Co-Founder | Author at Soluble
accuracy and precision, actuary, albert einstein, approximate bayesian computation, bayesian inference, belief, blog, causality, concept, confidence interval, correlation does not imply causation, creativity, cybersecurity, data, density, engineering, error, expected value, expert, false positives and false negatives, fossil, idea, imagination, information, infosec, insurance, likelihood function, monte carlo method, physics, proposition, reality, reason, research, restaurant, return on investment, rsa, rsac, rsaconference, science, security, simulation, statistics, survival analysis, tax, technology, terrorism, type i and type ii errors, uncertainty, understanding, virtual reality, world wide web
Alexander Antony
Sr. Data Scientist at GE Aviation
alexander antony, analytics, analytics & data science, analytics conferences 2021, analytics summit 2021 , autoregressive integrated moving average, autoregressive model, bayesian inference, binary data, covid-19, creativity, data & analytics, data science 2021, dependent and independent variables, dummy variable (statistics), economic data, financial crisis, forecasting, institute for health metrics and evaluation, leadership, moving average, overfitting, planning, prediction, reason, regression analysis, scenario planning, science, scientific method, statistics, structural time series models, tensorflow, time series, university of cincinnati
Martin Hawley
Digital innovation, founder at Winsland and Airspace Unlimited
apple inc., bayesian inference, bayesian network, behavior, complex system, computer security, concept, cyberattack, cybernetics, evidence, food, inference, information, innovation, intuition, mathematical optimization, mathematics, probability, risk, science, security, sense, silence, system, systems theory
Susan Athey
Economics of Technology Professor at Stanford Graduate School of Business
aaai, aaai 20, active learning, ai, analogy, artificial intelligence, artificial neural network, bayes estimator, bayesian inference, bayesian machine learning, behavioral economics, blockchain, causality, city university of new york, cloud computing, cnn, collaborative filtering, competition law, conference, confidence interval, consumer choice, credibility, credit score, deep learning, demand, demand curve, digitization, dimensionality reduction machine learning, discrete choice, econometrics, economics, education, educational technology, effect size, experiment, facebook, field experiment, future, genetic algorithm in machine learning, hypothesis, innovation, insight, institute, instrumental variables estimation, intel, investment, knowledge, likelihood function, logistic function, logistic regression, machine learning, macroeconomics, mathematical model, matrix factorization (recommender systems), maximum likelihood estimation, mergers and acquisitions, microsoft, milken, mind, money, monte carlo method, motivation, multi-armed bandit, nvidia, optimization, p-value, perceptron in machine learning, power (statistics), prediction, price discrimination, price–earnings ratio, privacy, productivity, profit (economics), prototype, python, quasi-experiment, recommender system, regression analysis, regression discontinuity design, reinforcement learning, research, revealed preference, rnn, science, self-driving car, sensitivity analysis, social science, speech recognition, standard deviation, startup company, statistical inference, statistics, tech, training, validation, and test sets, utility, utility maximization problem, valuation (finance), variational bayesian methods
Cheng Zhang
Principal Researcher at Microsoft
bayes estimator, bayesian inference, behavioral economics, consumer choice, credibility, deep learning, demand, economics, experiment, likelihood function, logistic function, machine learning, matrix factorization (recommender systems), maximum likelihood estimation, monte carlo method, quasi-experiment, research, revealed preference, sensitivity analysis, statistical inference, statistics, training, validation, and test sets, utility, utility maximization problem
Elias Bareinboim
Assistant Professor at Columbia University
bayes estimator, bayesian inference, behavioral economics, consumer choice, credibility, deep learning, demand, economics, experiment, likelihood function, logistic function, machine learning, matrix factorization (recommender systems), maximum likelihood estimation, monte carlo method, quasi-experiment, research, revealed preference, sensitivity analysis, statistical inference, statistics, training, validation, and test sets, utility, utility maximization problem
Amit Sharma
Senior Researcher at Microsoft
bayes estimator, bayesian inference, behavioral economics, consumer choice, credibility, deep learning, demand, economics, experiment, likelihood function, logistic function, machine learning, matrix factorization (recommender systems), maximum likelihood estimation, monte carlo method, quasi-experiment, research, revealed preference, sensitivity analysis, statistical inference, statistics, training, validation, and test sets, utility, utility maximization problem
Fabiana Clemente
Founder and Chief Data Officer at YData
artificial neural network, attention, bayesian inference, complexity, computer vision, concept, data analysis, data quality, goal, infrastructure, intelligence, knowledge, learning organization, machine learning, privacy, research, self-awareness, self-driving car, simulation, statistics, time, time series, unsupervised learning, visual perception
Zhenhui (Jessie) Li
Assistant Professor at Pennsylvania State University
acm 2020, artificial intelligence, artificial neural network, astronomy , attention, bayesian inference, case study, color, computer science 2020, computer science event 2020, computer vision, conservation of energy, data conversion, data science, deep learning, design, dog, energy, energy conservation, experiment, eye, face, facial recognition system, function (mathematics), future, gas, heat, human, imagenet, kdd2020, kdd2020 tutorials, knowledge, latitude, learning, letter case, light, machine learning, mass, mathematical optimization, meditation, memory, mother, naruto, neural network, norm (mathematics), parameter, password, physics, prediction, radiation, radioactive decay, reason, reinforcement learning, research, robot, root-mean-square deviation, simulation, solar irradiance, soul, space, stefan–boltzmann law, system, temperature, theory, time, training, validation, and test sets, transfer of learning, truth, water, weather
Vipin Kumar
Regents Professor and William Norris Chair in Large Scale Computing at University of Minnesota
acm 2020, artificial intelligence, artificial neural network, astronomy , attention, bayesian inference, case study, color, computer science 2020, computer science event 2020, computer vision, conservation of energy, data conversion, data science, deep learning, design, dog, energy, energy conservation, experiment, eye, face, facial recognition system, function (mathematics), future, gas, heat, human, imagenet, kdd2020, kdd2020 tutorials, knowledge, latitude, learning, letter case, light, machine learning, mass, mathematical optimization, meditation, memory, mother, naruto, neural network, norm (mathematics), parameter, password, physics, prediction, radiation, radioactive decay, reason, reinforcement learning, research, robot, root-mean-square deviation, simulation, solar irradiance, soul, space, stefan–boltzmann law, system, temperature, theory, time, training, validation, and test sets, transfer of learning, truth, water, weather
Xiaowei Jia
Assistant Professor at University of Pittsburgh
acm 2020, artificial intelligence, artificial neural network, astronomy , attention, bayesian inference, case study, color, computer science 2020, computer science event 2020, computer vision, conservation of energy, data conversion, data science, deep learning, design, dog, energy, energy conservation, experiment, eye, face, facial recognition system, function (mathematics), future, gas, heat, human, imagenet, kdd2020, kdd2020 tutorials, knowledge, latitude, learning, letter case, light, machine learning, mass, mathematical optimization, meditation, memory, mother, naruto, neural network, norm (mathematics), parameter, password, physics, prediction, radiation, radioactive decay, reason, reinforcement learning, research, robot, root-mean-square deviation, simulation, solar irradiance, soul, space, stefan–boltzmann law, system, temperature, theory, time, training, validation, and test sets, transfer of learning, truth, water, weather
Huaxiu Yao
Postdoctoral Scholar at Stanford University
acm 2020, artificial intelligence, artificial neural network, astronomy , attention, bayesian inference, case study, color, computer science 2020, computer science event 2020, computer vision, conservation of energy, data conversion, data science, deep learning, design, dog, energy, energy conservation, experiment, eye, face, facial recognition system, function (mathematics), future, gas, heat, human, imagenet, kdd2020, kdd2020 tutorials, knowledge, latitude, learning, letter case, light, machine learning, mass, mathematical optimization, meditation, memory, mother, naruto, neural network, norm (mathematics), parameter, password, physics, prediction, radiation, radioactive decay, reason, reinforcement learning, research, robot, root-mean-square deviation, simulation, solar irradiance, soul, space, stefan–boltzmann law, system, temperature, theory, time, training, validation, and test sets, transfer of learning, truth, water, weather
Sriram Sankararaman
Assistant Professor at UCLA Henry Samueli School of Engineering
acm 2020, bayesian inference, bayesian network, computer science 2020, computer science event 2020, covid-19 pandemic, covid-19 pandemic in the united kingdom, deep learning 2020, door, economics, forecasting, future, health day at kdd2020, immunity (medical), kdd2020, machine learning 2020, median, pandemic, parameter, perimeter, politics, prediction, quarantine, reason, science, severe acute respiratory syndrome coronavirus 2, social distancing, social media, statistical model, time, vaccine, virus
Boyang Fu
Ph.D. Student at University of California Los Angeles
acm 2020, bayesian inference, bayesian network, computer science 2020, computer science event 2020, covid-19 pandemic, covid-19 pandemic in the united kingdom, deep learning 2020, door, economics, forecasting, future, health day at kdd2020, immunity (medical), kdd2020, machine learning 2020, median, pandemic, parameter, perimeter, politics, prediction, quarantine, reason, science, severe acute respiratory syndrome coronavirus 2, social distancing, social media, statistical model, time, vaccine, virus
Eran Halperin
Professor of Anesthesiology and Perioperative Medicine, and Computer Science at University of California, Los Angeles
acm 2020, bayesian inference, bayesian network, computer science 2020, computer science event 2020, covid-19 pandemic, covid-19 pandemic in the united kingdom, deep learning 2020, door, economics, forecasting, future, health day at kdd2020, immunity (medical), kdd2020, machine learning 2020, median, pandemic, parameter, perimeter, politics, prediction, quarantine, reason, science, severe acute respiratory syndrome coronavirus 2, social distancing, social media, statistical model, time, vaccine, virus
Nadav Rackocz
Computer Science Ph.D. Student at Department of Computational Medicine University of California Los Angeles
acm 2020, bayesian inference, bayesian network, computer science 2020, computer science event 2020, covid-19 pandemic, covid-19 pandemic in the united kingdom, deep learning 2020, door, economics, forecasting, future, health day at kdd2020, immunity (medical), kdd2020, machine learning 2020, median, pandemic, parameter, perimeter, politics, prediction, quarantine, reason, science, severe acute respiratory syndrome coronavirus 2, social distancing, social media, statistical model, time, vaccine, virus
Nicola Disma
Director of Unit for Research & InnovationConsultant paediatric Anaesthetist at IRCCS Ospedale Pediatrico Giannina Gaslini
analytics, anesthesia, bayesian inference, census, child, decision tree, demography, disability, health care, hospital, information, johns hopkins all children's hospital, learning, machine learning, medical history, music, neurology, patient, pediatrics, perioperative, prediction, predictive modelling, risk, surgery, visual analytics
Walid Habre
Head Anesthesiological Investigations Unit at Université de Genève
analytics, anesthesia, bayesian inference, census, child, decision tree, demography, disability, health care, hospital, information, johns hopkins all children's hospital, learning, machine learning, medical history, music, neurology, patient, pediatrics, perioperative, prediction, predictive modelling, risk, surgery, visual analytics
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
Daniel Lizotte
Assistant Professor at Western University
3d modeling, accuracy and precision, adverse event, bayesian inference, business model, calibration, clinical pharmacology, data, dose (biochemistry), drug, github, hamiltonian monte carlo, likelihood function, map, mass, mass concentration (astronomy), maximum likelihood estimation, monte carlo method, open source, personalized medicine, pharmacokinetics, pharmacology, prediction, simulation, uncertainty
1 2 3 4
1-30 of 104