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 Spring 2017, click here
New and special topic courses for Spring 2017:
- CSE 198 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 198 Intro to Internet of Things, T 7:10-9:00pm, Prof. Darryl Jones -- This 2-credit course will give an end to end introduction to the Internet of Things (IoT) from both a technical and business perspective. It will cover technical solutions, data and analytics, as well as business implications and overall economic impacts. At the end of the course, students will have an understanding of the current state and trends within IoT, the market opportunities available, and the emerging technologies that make IoT possible. Students will also have first hand experience converting IoT data into consumable Insights that drive business value.
Areas introduced will include IoT Hardware and Devices, Interoperability and Compatibility, IoT Big Data Architecture, Data Science in IoT, Monetization Strategies, Business Models, Vertical Industry Disruption, and User Experience. Note that this is an evening course and some kind of programming experience is pre-requisite (CSE 002 or CSE 012 or BIS 335).
- CSE 350/450 Mobile Computing, MW 12:45-2:00, Prof. Mooi Choo Chuah -- This is a combined lecture/seminar course where emphasis will be placed on reading research papers on recent developments in mobile computing. This includes how to use sensors within smartphones or WiFi signals to build useful apps for our lives e.g. measuing our sleeping patterns, heart rate monitoring and how to design scalable mobile data systems e.g. offloading functions to mobile cloudlets, designing energy efficient apps for image retrieval. Last but not least, we will also address security and privacy issues for mobile sensing. A course project is expected. Android-based mobile devices will be used. Prerequisite: CSE 109 or equivalent.
- CSE 398 Robot Operating Systems (ROS), TR TR 1:10-2:25, Prof. John Spletzer--Robot Operating System (ROS) is a software framework for writing robotics applications (http://www.ros.org/). It is the de facto industry standard, seeing widespread use in not only academic research, but also industrial applications and everything in between. In this course, we will explore the ROS framework, tools, and numerous packages of interest (e.g., PCL). In doing so, we will leverage the VADER laboratory's ROSCAR vehicles as our development platform (http://vader.cse.lehigh.edu/roscar/). The course is project based, and students will be partitioned into small groups of 2-3 students where they will implement autonomous behaviors to accomplish a higher level task (e.g., simultaneous localization and mapping). There are no exams in this course. Pre-Requisites: ROS is written in C++, so knowledge of the language is required. CSE360 or instructor approval is also required. Familiarity with Ubuntu/Linux is also desirable (but not required).
- CSE 398/498 Services Computing, MWF 11:10-12:00, Prof. Liang Cheng--Principles and practice of services computing. SOA (service oriented architecture), middleware, services computing management, P2P (peer-to-peer) service systems, cloud computing, ubiquitous computing, and services computing performance, security and privacy. Case studies include Google service platforms (GSP), Amazon web services (AWS), and Blockchain/Bitcoin. Prerequisite: CSE 303 or 202 previously or concurrently, or consent of the instructor.
- CSE 398/498 Big Data Analytics, T 2:35-3:50, Prof. Daniel Lopresti--In this 2-credit project course, we will gain a practical working knowledge of large- scale data analysis using the popular open source Apache Spark framework. Spark provides a powerful model for distributing programs across clusters of machines and elegantly supports patterns that are commonly employed in big data analytics, including classification, collaborative filtering, and anomaly detection, among others.
Working from the course textbook, we will study and program solutions for problems including: music recommender systems; predicting forest cover with decision trees; anomaly detection in network traffic with K-means clustering; understanding Wikipedia with Latent Semantic Analysis; analyzing co-occurrence networks with GraphX; geospatial and temporal data analysis on the New York City Taxi Trips data; estimating financial risk through Monte Carlo simulation; analyzing genomics data and the BDG project; and analyzing neuroimaging data with PySpark and Thunder.
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.