Computer Science and Engineering


Miaomiao ZhangRoberto Palmieri

As a result of the ongoing Data X Initiative, the CSE Department is pleased to welcome two new assistant professors in 2017-18, Miaomiao Zhang and Roberto Palmieri.

Dr. Zhang's research work focuses on developing novel models at the intersection of statistics, mathematics, and computer engineering in the field of medical and biological imaging. Before joining Lehigh University, Miaomiao completed her Ph.D. degree in the department of Computer Science at University of Utah under the supervision of Dr. Tom Fletcher. After that, she worked with Dr. Polina Golland as a postdoctoral associate at Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. She received the Young Scientist Award 2014 and was a runnerup for Young Scientist Award 2016.

Roberto Palmieri earned his Ph.D. in Computer Engineering from Sapienza University of Rome (Italy). After that, he was a post-doc at Sapienza University and subsequently at Virginia Tech. In 2014 he became a Research Assistant Professor in the Electrical and Computer Engineering department at Virginia Tech. He is interested in system research and distributed computation, spanning from theory to practice. Building fault-tolerant and high performance systems is one of his primary research goals, along with designing protocols for innovative synchronization patterns. Palmieri and his students have published more than 50 papers in the most recognized international conferences and journals of the area.



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.

CSE is also deeply involved in Lehigh's Data X Strategic Initiative, including the development of new courses, new research directions, and an amazing new facility now under development on Lehigh's Mountaintop Campus. For more information on Data X, click here.

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. programs 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, and are regularly recruited by many leading high tech companies.

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.
  • CSE 498 Data Analytics for Smart Cities, TR 4:30-5:45, Prof. Mooi Choo Chuah--With the emergence of powerful smartphones, wearables, and affordable internet of things, much data can be collected about human interactions, traffics, urban dynamics, environment. All such data (sensor data, videos, texts) can be analyzed using deep learning techniques to infer human activities, smart cities infrastructure planning, smart health management or planning autonomous car driving. Deep learning algorithms have proven to be useful for analyzing such big data streams.This course covers some basics of mobile computing, deep learning algorithms followed by discussions of most recent research papers in relevant areas. Students are expected to give presentations of assigned research papers, write summaries of deep learning based approaches taken by researchers to address smart cities related problems. Students will work on a few homework assignments followed by a class project at the end of the semester. Requirements: Graduate students need to be good in C, python (and possilby Java programming) and have some computer system background.

 Courses taught by new faculty 2017-2018:

  • CSE 320/420 Biomedical Image Computing and Modeling, TR 1:10-2:25, Prof. Miaomiao Zhang -This course focuses on an in-depth study of advanced topics and interests in image data analysis. Students will learn about hardcore imaging techniques and gain mathematical fundamentals needed to build their own models for an effective problem solving. Topics of deformable image registration, numerical analysis, probabilistic modeling, data dimensionality reduction, and convolutional neural networks for image segmentation will be covered. The main focus might change from semester to semester. Credit will not be given for both CSE 320 and CSE 420. Prerequisite: (Math 205 or Math 43) and CSE 017, or consent of instructor. Click here for official course description
  • CSE 375/475 Principles and Practice of Parallel Computing, MWF 10:10-11:00, Prof. Roberto Palmieri - It's the era of data, and having knowledge on how to design and develop correct high performance algorithms and applications for computing data is a fundamental requirement for prospective successful software engineers and designers. CSE-375/475 focuses on that, covering both theoretical and practical aspects, providing students with the sufficient knowledge to implement and reason about parallel applications. A particular focus is given to concurrency, which often represents a barrier for many developers given its complexity in providing correct computation due to the presence of simultaneous accesses on shared data. In this regard, the course covers the traditional lock-based programming, and also state-of-the-art (software and hardware) solutions to code concurrent applications without exposing locks to programmer.  Click here for official course description


Prospective students and their parents: if you're planning to visit Lehigh and have interests in Computer Science, Computer Science and Business, or Computer Engineering, please contact us at This email address is being protected from spambots. You need JavaScript enabled to view it. and we'll make sure you have a chance to meet with a faculty member to hear the details of our programs.

Prospective employers: demand for CSE graduates is extremely strong. Our students are aggressively recruited by many of the top companies in the US. If you wish to connect with CSE students at Lehigh, please contact us. We can help disseminate your recruiting materials, and we can also arrange for a room for you to present an overview session and meet with students during a campus visit. Send email to: This email address is being protected from spambots. You need JavaScript enabled to view it. .

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.

 Tapia Group 2016

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.

© 2014-2016 Computer Science and Engineering, P.C. Rossin College of Engineering & Applied Science, Lehigh University, Bethlehem PA 18015.