Computer Science and Engineering
Computer Science and Engineering is at the core of the information age. To prepare our students for the tremendous opportunities in the field, the CSE Department is strongly committed to excellence in both education and research. We conduct ground-breaking work in artificial intelligence, bioinformatics, data mining, robotics, software security, computer networking, software systems, biomedical image processing, computer vision, mobile healthcare, and the WWW. Our faculty includes five NSF CAREER award winners, one of the most prestigious awards available to young researchers in CSE.
Lehigh undergraduates benefit from the personal attention typical of a small college, yet have exposure to state-of-the-art technologies available only at a research university. To provide flexibility, we offer a variety of different undergraduate degree programs, including B.S. degrees in the College of Engineering, and a B.S. and a B.A. degree in the College of Arts and Sciences. All of our B.S. degrees are fully accredited. In addition, we offer a unique B.S. in Computer Science and Business which is accredited both in computer science and in business. Beyond their courses, students often work one-on-one with faculty, and can even become involved in their research projects. Internships provide real-world experience.
Our majors are designed to provide a strong foundation in the core areas of Computer Science and Engineering, from the hardware/software interface up through systems software, programming languages, software engineering, and the mathematical foundations of computing. Electives include topics in artificial intelligence, computer networking, parallel and distributed computing, security, robotics, bioinformatics, data mining, web and mobile application development, and databases. As a result, our graduates are in high demand.
Our vibrant graduate programs prepare students for positions in industry and academia. Our faculty have research funded by competitive sources including NSF, DARPA, NIH, and other federal and state agencies, as well as leading companies in the field.
For a list of major employers who have hired our graduates in the recent past, click here.
For a listing of planned CSE courses for Summer/Fall 2017, click here
New course for Summer 2017 (Session 1):
- CSE 298 Mobile Apps (Android), MTWR 11:00-12:35, Prof. Eric Fouh Mbindi-- This is a project-oriented course that explores the concepts and technologies pertaining to application development for mobile devices. This course uses Android as the platform. Topics covered include mobile software architecture, user interface design, graphics, multimedia, Location-aware software development, network-centric software development, software development for mobile device sensors (such as cameras, recorders, accelerometer, gyroscope). Prerequisite: CSE 017.
New and special topic courses for Fall 2017:
- CSE 160 Data Science, MWF 10:10-11:00, Prof. Brian Davison -- learn about the collection, preparation, analysis and visualization of data, covering both conceptual and practical issues.
- CSE 398/498 Natural Language Processing, TR 1:10-2:25, Prof. Sihong Xie--Wondering how Google translates English into Chinese, how IBM Watson beat humans in Jeopardy and how Grammarly correct your essays?
This course introduces you to natural language processing (NLP) that empowers many fascinating applications like the above. The course will study, in both depth and detail, the fundamental statistical models and their computational implementations in NLP. You will learn how to model texts on the level of word, sentence, and paragraph using tools such as trees, graphs, and automata.
The following techniques will be covered: text normalization, language model, part-of-speech tagging, hidden Markov model, syntactic and dependency parsing, semantics and word sense,reference resolution, dialog agent, machine translation.
Two class projects to design, implement and evaluate classic NLP models will enable the students to have hands-on NLP experience. Programming experience (CSE 17) and probability and statistics (MATH 231 or ECO 045) will be required. Credit will not be given for both CSE 398 and CSE 498.
- CSE 398/498 Deep Learning, TR 1:10-2:25, Prof. Xiaolei Huang-- In this course, we will learn the core principles behind neural networks and deep learning. We will start with simple neural networks with a handful of layers, and then move on to study deep neural networks with tens or even hundreds of layers. We will learn about and compare different neural network architectures including Convolutional Neural Networks, Generative Adversarial Networks, and Recurrent Neural Works. For applications, we will look at handwritten digit recognition, object recognition, computer-aided diagnosis, and natural language understanding. Prerequisites: For undergraduate students, CSE 109 and MATH 231; For graduate students, no prerequisite for CSE MS or PhD students; for all other students, permission by department/instructor required.
- CSE 398/498 Seminar in Data-Systems Research, MW 8;45-10:00, Prof. Hank Korth--Discussion of a recent research paper in most class meetings. Everyone reads the paper in advance, students rotate roles in leading discussion. The papers relate to systems aspects of database system internals (i.e. not applications) chosen from recent operating system and database research conferences.
New students often ask whether it is possible to take one of majors if they have had no programming experience in high school. Yes! Many of our majors first started their study of CSE at Lehigh with no previous background. We provide the appropriate introductory courses for students to succeed in CSE with or without past experience.
Lehigh CSB student Bruke Mammo (left) and Professor of Practice Eric Fouh Mbindi (right) with Professor Richard Tapia of Rice University (center) at the 2016 ACM Richard Tapia Celebration of Diversity in Computing, Austin, TX.