DSA ADS Course - 2022
Artificial Intelligence, Human Brain, Biodigital Convergence, Human Augmentation
Discuss technical, societal, political, military, legal and ethical aspects of human augmentation and biodigital convergence.
Human Augmentation – The Dawn of a New Paradigm - May, 2021
Abstract
DSA ADS Course - 2022
Artificial Intelligence, Human Brain, Biodigital Convergence, Human Augmentation
Discuss technical, societal, political, military, legal and ethical aspects of human augmentation and biodigital convergence.
Exploring Biodigital Convergence - February, 2020
Abstract
Digital technologies and biological systems are beginning to combine and merge in ways that could be profoundly disruptive to our assumptions about society, the economy, and our bodies. We call this the biodigital convergence.
DSA ADS Course - 2022
Performance of the SARS-CoV-2 RT-PCR test as a tool for detecting SARS-CoV-2 infection in the population
COVID19, Public Policy, Health Policy, SARS-CoV-2, RT-PCR Test, Infectious Potential, Laboratory Quality Assurance, Dr. Kary Mullis, Cycle Threshold Values
DSA ADS Course - 2022
Cost-benefit Analysis, Cost-benefit Fallacy, Public Investment Planning, Forecasting, Resource Allocation, Behavioral Science
Discuss cost-benefit analysis, cost-benefit fallacy, public investment planning, forecasting, resource allocation, welfare economics, behavioral science and behavioral economics.
What if scenario estimates are highly inaccurate and biased? What are potential costs of scenario inaccuracies seriously distorting effective resource allocation?
DSA ADS Course - 2021
Avrim Blum, John Hopcroft, Ravindran Kannan
June, 2016
Introduction:
Computer science as an academic discipline began in the 1960’s. Emphasis was on programming languages, compilers, operating systems, and the mathematical theory that supported these areas. Courses in theoretical computer science covered finite automata, regular expressions, context free languages, and computability.
DSA ADS Course - 2021
Graphical Models, Bayesian Networks, Applied Probability, Probabilistic Causation, Causal Inference
Applied data scientists require high-level understanding of probability theory and specialized techniques to design systems and solve problems in the real world. Graphical model formalism provides a natural framework for the design of new data science systems.
DSA ADS Course - 2021
Probability Theory, Applied Probability, Probabilistic Causation, Causal Inference
Understanding applied probability and accurate assessment of real-world risk is a critical part of high value data science.
DSA ADS Course - 2021
Monte Carlo Tree Search, Markov Chain Monte Carlo, Guided Monte Carlo Tree Search, Monte Carlo Simulations
Discuss Monte Carlo Tree Search, Markov Chains, Upper Confidence Bounds, Upper Confidence Bounds for Trees and Bandit-based methods.
Survey of Monte Carlo Tree Search Methods
DSA ADS Course - 2021
Probabilistic Logic, Probability Theory, Causality, Causal Inference, Applied Probability, Statistics
Discuss applied probability theory and causality.
The Causal Foundations of Applied Probability and Statistics - November, 2020
Abstract