Laura Biester
she/her
Assistant Professor of Computer Science
- Office
- 75 Shannon Room 214
- Tel
- (802) 443-4217
- lbiester@middlebury.edu
- Office Hours
- Spring 2025: Tuesday 2-3, Wednesday 10-11, Thursday 2-3, and by appointment
Courses Taught
CSCI 0145
Current
Introduction to Computing
Course Description
Introduction to Computing
In this course we will provide a broad introductory overview of the discipline of computer science, with no prerequisites or assumed prior knowledge of computers or programming. A significant component of the course is an introduction to algorithmic concepts and to programming using Python; programming assignments will explore algorithmic strategies such as selection, iteration, divide-and-conquer, and recursion, as well as introducing the Python programming language. Additional topics will include: the structure and organization of computers, the Internet and World Wide Web, abstraction as a means of managing complexity, social and ethical computing issues, and the question "What is computation?" (Juniors and Seniors by waiver) (formerly CSCI 0101) 3 hr. lect./1 hr. lab
Terms Taught
Requirements
CSCI 0201
Upcoming
Data Structures
Course Description
Data Structures
In this course we will study the ideas and structures helpful in designing algorithms and writing programs for solving large, complex problems. The Java programming language and object-oriented paradigm are introduced in the context of important abstract data types (ADTs) such as stacks, queues, trees, and graphs. We will study efficient implementations of these ADTs, and learn classic algorithms to manipulate these structures for tasks such as sorting and searching. Prior programming experience is expected, but prior familiarity with the Java programming language is not assumed. (CSCI 0145 or CSCI 0146 or CSCI 0150) (Juniors and Seniors by waiver) 3 hrs. lect./lab
Terms Taught
Requirements
CSCI 0312
Software Development
Course Description
Software Development
This course examines the process of developing larger-scale software systems. Laboratory assignments emphasize sound programming practices, tools that facilitate the development process, and teamwork. (CSCI 0200 and CSCI 0201) 3 hrs. lect./lab
Terms Taught
CSCI 0457
Current
Natural Language Processing
Course Description
Natural Language Processing
In this course we will explore computational models for processing natural (human) language. We will introduce statistical and algorithmic techniques that are used to classify, generate, and understand language at the syntactic and semantic levels. We will explore applications such as parsing, information extraction, language modeling, and sentiment analysis. Assignments will involve constructing and modifying systems and will incorporate a variety of large corpora. We will also discuss the ethical concerns associated with current methods for collecting and labeling large corpora, and how language technologies might reflect and reinforce social hierarchies. This course fulfills the Responsible Computing requirement for the Computer Science major. (CSCI 0102 OR CSCI 0200 AND CSCI 0201)
Terms Taught
Requirements
CSCI 0500
Current
Upcoming
Advanced Study
Course Description
Advanced Study
Individual study for qualified students in more advanced topics in computer science theory, systems, or application areas. Particularly suited for students who enter with advanced standing. (Approval required) 3 hrs. lect.
Terms Taught
CSCI 0702
Upcoming
Senior Thesis
Course Description
Senior Thesis
The senior thesis is recommended for students interested in pursuing graduate study in Computer Science. Students will spend the semester researching and writing, and developing and experimenting as appropriate for their topic. All students will be expected to report on their work in the form of a written thesis, a poster, and an oral presentation at the end of the semester. In addition, throughout the semester, students will meet as a group to discuss research and writing, and will be expected to attend talks in the Computer Science lecture series. Before approval to join the class is granted, students are expected to have chosen a thesis adviser from the CSCI faculty, and determined a thesis topic with the guidance and approval of that adviser. (Approval required) 3 hrs. lect./disc.
Terms Taught
Areas of Interest
- Natural Language Processing
- Computational Social Science