Daniel Scharstein studied Computer Science at the Universität Karlsruhe, Germany, and received his PhD from Cornell University in 1997. His research interests include computer vision, in particular stereo vision, and robotics. He maintains several online computer vision benchmarks at http://vision.middlebury.edu.
Courses offered in the past four years.
▲ indicates offered in the current term
▹ indicates offered in the upcoming term[s]
CSCI 0101 - The Computing Age
The Computing Age
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?" (Seniors by waiver) 3 hr. lect./lab DED
Fall 2011, Fall 2012
CSCI 0150 - Computing for the Sciences ▹
Computing for the Sciences
In this course we will provide an introduction to the field of computer science geared towards students interested in mathematics and the natural sciences. We will study problem-solving approaches and computational techniques utilized in a variety of domains including biology, chemistry, physics, and engineering. Students will learn how to program in Python and other languages, how to extract information from large data sets, and how to utilize a common technique employed in scientific computation. The course has no prerequisites and assumes no prior experience with programming or computer science. (Seniors by waiver) 3 hrs. lect./lab DED
Fall 2014, Fall 2015
CSCI 0201 - 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. (One CSCI course at the 0100-level) 3 hrs. lect./lab DED
Spring 2011, Spring 2012, Spring 2013, Spring 2015
CSCI 0202 - Computer Architecture
A detailed study of the hardware and software that make up a computer system. Topics include assembly language programming, digital logic design, microarchitecture, pipelines, caches, and RISC vs. CISC. The goal of the course is teach students how computers are built, how they work at the lowest level, and how this knowledge can be used to write better programs. (CSCI 0201 previously or concurrently) 3 hrs. lect./lab DED
Fall 2011, Fall 2012
CSCI 0313 - Programming Languages ▲
A systematic approach to concepts and features of programming languages. The course focuses on four major programming paradigms: procedural, object-oriented, functional, and logic programming languages. Students will program in several languages representing the different paradigms. Topics include grammars, data types, control structures, run-time organization, procedure activation, parameter passing, higher-order functions, lambda expressions, and unification. (CSCI 0200 and CSCI 0202) 3 hrs. lect./lab DED
CSCI 0433 - Compiler Design
An introduction to the design and construction of compilers and translators. Topics include context-free grammars, lexical analysis, symbol tables, top-down and bottom-up parsing, parser generators, error recovery, run-time organization, declaration processing, type checking, code generation, and optimization. Through the course of the semester students will implement a complete compiler for a simple programming language. (CSCI 0202 and CSCI 0301) 3 hrs. lect./lab DED
Spring 2011, Fall 2014
CSCI 0453 - Computer Vision
The goal of computer vision is to extract information from digital images and movies. Topics covered in this course include algorithms for edge and motion detection, stereo vision, object recognition, and recovering structure from motion. A range of mathematical techniques will be used to model problems and algorithms. Students will implement, test, and evaluate several computer vision techniques, and will gain experience with analyzing real, noise-contaminated image data. (CSCI 0202 and MATH 0200) 3 hrs. lect./lab DED
CSCI 0461 - Computer Graphics
Computer graphics is the study of how computers represent, manipulate, and ultimately display visual information. In this course we will focus primarily on three-dimensional graphics, touching on topics such as modeling (meshes, hierarchical models, and transformations), rendering (lighting, texturing, rasterization, and clipping), animation, and GPU programming. We will look at the mathematical foundations of these techniques as well as implementation techniques using OpenGL. (CSCI 0202 and MATH 0200) 3 hrs. lect./lab DED
CSCI 0500 - 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.
Spring 2011, Fall 2011, Winter 2012, Spring 2012, Fall 2012, Winter 2013, Spring 2013, Fall 2014, Winter 2015, Spring 2015, Fall 2015, Spring 2016
CSCI 0701 - Senior Seminar ▹
This senior seminar provides a capstone experience for computer science majors at Middlebury College. Through lectures, readings, and a series of two to three week individual and group assignments, we will introduce important concepts in research and experimental methods in computation. Examples will include: reading research papers; identifying research problems; dealing with big data; experimental design, testing and analysis; and technical writing in computer science.
INDE 0800 - Ind Scholar Thesis ▲