How does Google Maps find the best route between two locations? How do computers help to decode the human genome? At the heart of these and other complex computer applications are nontrivial algorithms. While algorithms must be specialized to an application, there are some standard ways of approaching algorithmic problems that tend to be useful in many applications. Among other topics, we explore graph algorithms, greedy algorithms, divide-and-conquer, dynamic programming, and network flow.

An introduction to the issues involved in orchestrating the use of computer resources. Topics include operating system evolution, memory management, virtual memory, resource scheduling, multiprogramming, deadlocks, concurrent processes, protection, and design principles. Course emphasis: understanding the implications of OS design on the programs you run and write (i.e., on their security, performance, etc.). This course is programming intensive.

Invertebrates are an incredibly diverse group of organisms that live in nearly all ecosystems across the earth. As ectotherms, invertebrates must develop plastic responses to environmental variation in order to survive. In this course, we will explore these plastic responses in marine invertebrates at all levels of organization -- from cellular to ecosystem scales -- through hands-on activities, projects, and synthesis of primary literature.

How does Neflix learn what movies a person likes? How do computers read handwritten addresses on packages, or detect faces in images? Machine learning is the practice of programming computers to learn and improve through experience, and it is becoming pervasive in technology and science. This course will cover the mathematical underpinnings, algorithms, and practices that enable a computer to learn. Topics will include supervised learning, unsupervised learning, evaluation methodology, and Bayesian probabilistic modeling.

This course will focus on biological systems that push the limits of structural and physiological possibility. For example, midges flap their wings at up to 1000 Hz; bar-headed geese migrate over Mount Everest; deep-sea fish withstand pressures near 300 atmospheres; certain frogs can allow their body temperatures to drop below 0 degrees Celsius. Through readings and discussions we will explore the diverse mechanisms that underlie how organisms reach extreme levels of performance and survive in extreme environments.

Have you ever wondered why Siri or Alexa doesn't understand things you say? Or wondered if actual robots can understand language as well as the ones we see in movies? In this seminar we will learn about social robots and what it takes for robots to converse with humans. We will read research conducted by computer scientists, linguists, and psychologists, as well as investigate representations of social robots in popular media and literature.

In this course, we will take a leap back in time to the origins of life, discuss the evolution of major organismal lineages, and investigate biology processes at different scales, from cellular to ecological. Through the lectures, labs, and in-class discussions, students will be able to explain how scientific knowledge is generated.