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, 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 information systems. 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 2016, click here
New CSE courses for Spring 2016:
- 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 350/450 Privacy Aware Data Analytics, TR 2:35-3:50, Prof. Ting Wang -- With the tremendous success of data-driven services and applications (e.g., personalized recommendation, customized news, targeted ads) follows their immense threat to the privacy of people's sensitive information. This course discusses how to design and implement data analytical methods and systems that respect individuals' data privacy while still enabling high-quality analysis results. Main topics covered in the course include: privacy-aware data publishing, privacy-aware data mining, privacy-aware mobile services, privacy-aware web services, and secure multiparty computation. The course will be a combination of lectures and paper presentations by the students. Students will also pursue a course research project. The final outputs of the project include a presentation and a short report. Prerequisite: CSE 347/447 or consent of instructor.
- CSE 350/450 Mobile Computing, TR 10:45-12:00, 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 398/498 Big Data Analytics, Tu 10:45 – 12:00, 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. Supplemental readings will provide additional background for each application area, but most of the work in the course will involve implementing, studying, and enhancing the programming examples from the textbook. During class, students will take turns presenting their own solutions and helping to lead the discussion. A final project will be required. Contact the instructor, Prof. Dan Lopresti, for details.
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.
Chang Sun, Casey Caruso, Rachel Okun, Elise Cross, Tamara Hass, April Xu and Qing Yi at the 2015 Grace Hopper Celebration of Women in Computing, Houston, TX.