Teaching

Spring 2025

1.873 Mathematical Modeling of Ecological Systems

Understanding the conditions leading to the emergence and persistence of ecological systems is paramount to understand the sustainability of biodiversity. Systems ecology has been established as a holistic approach to understand the context-dependent behavior of ecological systems using formal procedures of systems thinking, synthesis, and modeling. This course centers on theoretical understanding of ecological dynamics from one to multispecies systems across environmental contexts. Lectures address phenomenological and mechanistic understanding through graphical, analytical, and numerical analysis. Grading is based on psets and presentations.

Lecture: Tuesdays and Thursdays 10.30am-12pm Room 1-277

Fall 2024

1.010A Probability: Concepts and Applications (1sr half of term)

Introduces probability with an emphasis on probabilistic systems analysis. Readings about conceptual and mathematical background are given in advanced of each class. Classes revise background and are centered on developing problem-solving skills. The course is exam-based and focused on the analysis of probabilistic outcomes, estimating what can happen under uncertain environments. Topics include random events and their probability, combinatorial analysis, conditional analysis, random vectors, functions of random vectors, propagation of uncertainty, and prediction analysis.

Lecture: Tuesdays and Thursdays 3.30pm-5pm Room 1-242

Recitations: Wednesday 2.30pm-3.30pm Room 1-242

1.010B Causal Inference for Data Analysis (2nd half of term)

Introduces causal inference with an emphasis on probabilistic systems analysis. Readings about conceptual and mathematical background are given in advanced of each class. Class is focused on understanding theory based on real-world applications. The course is project-based and focused on cause-effect relationships, understanding why probabilistic outcomes happen. Topics include correlation analysis, Reichenbach's principle, Simpson's paradox, structural causal models and graphs, interventions, do-calculus, average causal effects, dealing with missing information, mediation, and hypothesis testing.

Lecture: Tuesdays and Thursdays 3.30pm-5pm Room 1-242

Recitations: Wednesday 2.30pm-3.30pm Room 1-242

Spring 2024 1.873 Mathematical Modeling of Ecological Systems

Fall 2023         1.010B Causal Inference for Data Analysis

Fall 2023         1.010A Probability: Concepts and Applications

Spring 2023 1.873 Systems Ecology in Theory

Fall 2022         1.010 Probability and Causal Inference

Spring 2022    1.873 Ecological Dynamics and Modeling

Fall 2021          1.010 Probability and Causal Inference

Spring 2021    1.873 Ecological Dynamics and Modeling

Fall 2020         1.010 Probability and Causal Inference

Spring 2020    1.873 Ecological Dynamics and Modeling

Fall 2019         1.010 Probability and Causal Inference

Spring 2019    1.873 Ecological Dynamics and Modeling

Fall 2018         1.010 Introduction to Probability and Statistics

Spring 2018    1.087/1.873 Fundamentals of Network and  Community Ecology

Fall 2017         1.010 Uncertainty in Engineering

Spring 2017    1.S977 Fundamentals of Network and  Community Ecology

Fall 2016         1.010 Uncertainty in Engineering