BS in Computer Science (CAS) http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised Wed, 25 Apr 2018 00:40:47 -0400 Joomla! - Open Source Content Management en-gb Archived News 2015-2016 http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/380-archived-news-2015-2016 http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/380-archived-news-2015-2016 Lehigh was the host site for the Fourteenth International Semantic Web Conference (ISWC) in October, 2015

Lehigh was awarded its competitive bid to host the Fourteenth International Semantic Web Conference (ISWC) in October, 2015. ISWC is the leading conference in the Semantic Web area, which focuses on the integration and understanding of diverse data, especially data in graph-based formats. Prof. Jeff Heflin, who led the bid team, is intimately familiar with the conference, having served on four ISWC organizing committees over the last decade. ISWC is an annual conference that typically rotates between Europe, North America, and Asia. Previous locations include Sydney, Australia; Boston, MA; Bonn, Germany and Shanghai, China. Lehigh is looking forward to hosting the conference, and showing the international Semantic Web research community the best that Lehigh and Bethlehem has to offer.

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hew207@lehigh.edu (Heidi Wegrzyn) Tue, 27 Mar 2018 14:39:05 -0400
Archived News 2014-2015 http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/379-archived-news-2014-2015 http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/379-archived-news-2014-2015 The NSF Smart Spaces REU Site

The Computer Science and Engineering Department at Lehigh University is proud to be operating the Smart Spaces Research Experience for Undergraduates (REU) Site. This REU Site opened in 2014 and is funded by the National Science Foundation (NSF) Directorate for Computer & Information Science & Engineering (CISE)

2015 NSF Smart Spaces Final Presentations

9 students attended the 2015 summer session of the Smart Spaces REU site.  Check out their final presentations.

Professor Liang Cheng received Best Service Award as the Local Chair of IEEE MASS 2014 (The 11th IEEE International Conference on Mobile Ad hoc and Sensor Systems).

Grace Hopper Celebration of Women in Computing Conference

The CSE Department sent 7 female students to the Grace Hopper Celebration of Women in Computing Conference in Phoenix, AZ in October. Professors Daniel Lopresti, Hank Korth and Mooi Choo Chuah, also attended the conference.

Professor Mooi Choo Chuah elevated to IEEE Fellow effective January 1, 2015 for her contributions to wireless network system and protocol design.

2014-2015 Computer Science Senior Project Awards

Congratulations to Matthew Kilgore on being awarded the 2014-15 Computer Science Outstanding Senior Project Award for “PyRo - The Python Robotics Framework”. Jesse Kurtz and Kyle Moore won Peers' Choice for "KinectForKids".

Best Jobs of 2014

CS-related jobs top U.S. News list of "The Best Jobs of 2014."

Student Awards

CSB student Tae Hong Min recently won awards at both NASA'S SpaceApps Hackathon and HackNY.

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hew207@lehigh.edu (Heidi Wegrzyn) Tue, 27 Mar 2018 14:38:26 -0400
Summer Fall 2018 Course Schedule http://www.cse.lehigh.edu/academics/course-schedule-by-semester http://www.cse.lehigh.edu/academics/course-schedule-by-semester Summer 2018 Courses

 Any issues or questions regarding registration, please contact Heidi Wegrzyn.

Summer Session 1 (May 22nd-June 28th)

CSE 002 FUNDAMENTALS OF PROGRAMMING

Problem-solving and object-oriented programming using Java. Includes laboratory. No prior programming experience needed. Click here for official description.

CSE 002-010, TR 9:00-11:50, Professor Eric Fouh Mbindi

CSE 017 Programming & Data Structures

This course is a programming-intensive exploration of software design concepts and implementation techniques. It builds on the student's existing knowledge of fundamental programming. Topics include object-oriented software design, problem-solving strategies, algorithm development, and classic data structures. Click here for official description.

CSE 017-010, TR 1:00-3:50, Professor Eric Fouh Mbindi

CSE 109 Systems Software

Advanced programming and data structures, including dynamic structures, memory allocation, data organization, symbol tables, hash tables, B-trees, data files. Object-oriented design and implementation of simple assemblers, loaders, interpreters, compilers and translators. Practical methods for implementing medium-scale programs. Click here for official description.

CSE 109-010, MTWR 10:00-12:30, Professor Jason Loew


Fall 2018 Courses

CSE 001 BREADTH OF COMPUTING

Broad overview of computer science, computer systems, and computer applications.  Interactive Web page development.  Includes laboratory.  Not available to students who have taken CSE 12 or ENGR 010. Click here for official description.

CSE 001-010, TR 2:35-3:50, Professor Daniel Lopresti (plan to hold course in Building C)

CSE 001-011, TR 1:10-2:25, Professor James Femister


 

CSE 002 FUNDAMENTALS OF PROGRAMMING

Problem-solving and object-oriented programming using Java. Includes laboratory. No prior programming experience needed. Click here for official description. All sections will offer Guided Study Groups.

CSE 002-110, MW 11:10-12:00 F (lab) 11:10-12:00, Professor Brian Chen

Problem-solving and object-oriented programming using Java. Includes Laboratory. No prior programming experience needed.

CSE 002-210, MW 12:45-2:00, Professor Sharon Kalafut

Problem-solving and object-oriented programming using Java. Includes laboratory. No prior programming experience needed. Laboratory for this section are held during the Thursday lecture time.

CSE 002-310, TR 9:20-10:35, STAFF

Problem-solving and object-oriented programming using Java. Includes laboratory. No prior programming experience needed. Laboratory for this section are held during the Thursday lecture time.

CSE 002-311, TR 10:45-12:00, STAFF

Problem-solving and object-oriented programming using Java. Includes laboratory. No prior programming experience needed. Laboratory for this section are held during the Thursday lecture time.



 

CSE 017 Programming & Data Structures

This course is a programming-intensive exploration of software design concepts and implementation techniques. It builds on the student's existing knowledge of fundamental programming. Topics include object-oriented software design, problem-solving strategies, algorithm development, and classic data structures. Click here for official description.

CSE 017-010, MW 9:10-10:00 F (lab) 9:10-10:00, Professor Eric Fouh Mbindi

CSE 017-010, MW 10:10-11:00 F (lab) 10:10-11:00, Professor Eric Fouh Mbindi

There will be weekly mandatory online quizzes and/or homework. One programming is assigned each week. Programming assignments are presented and discussed in-class during lecture. Each assignment covers one of the major topics in the course. There are two 50-minute exams during the semester, and a comprehensive 2-hour final exam at the end of the course.

CSE 017-012, TR 10:45-12:00, Professor Jeff Heflin

The best way to learn programming is to do it frequently. As such, students will be assigned 10-12 programs to complete throughout the semester. Students are given between 5 and 10 days to finish each assignment, based on the expected difficulty of the task. Before each class, students are expected to read 10-15 pages of the text book, and are evaluated on their comprehension via occasional pop quizzes. There are two 50-minute exams during the semester, and a comprehensive 2-hour final exam at the end of the course.


 

 CSE 109 SYSTEMS SOFTWARE

Advanced programming and data structures, including dynamic structures, memory allocation, data organization, symbol tables, hash tables, B-trees, data files. Object-oriented design and implementation of simple assemblers, loaders, interpreters, compilers and translators. Practical methods for implementing medium-scale programs. Click here for official description.

CSE 109-011, MWF 10:10-11:00 F (lab) 11:10-12:00, Professor Jason Loew

CSE 109-012, MW 12:45-2:00 F (lab) 12:10-1:00, Professor Mark Erle


 

CSE 160-010 INTRO TO DATA SCIENCE, MWF 10:10-11:00, Professor Brian Davison

Interested in understanding the hype about data science, big data, or data analytics? This course introduces you to data science, a fast-growing and interdisciplinary field, focusing on the computational analysis of data to extract knowledge and insight. You will be introduced to the collection, preparation, analysis, modeling, and visualization of data, covering both conceptual and practical issues. Applications of data science across multiple fields are presented, and hands-on use of statistical and data manipulation software is included. The course is open to students from all areas of study; the only prerequisite is some programming experience (automatic if you've taken CSE 1, 2, 12, or BIS 335, or permission of the instructor is available if you can show that you've successfully completed a programming course online, in high school, or elsewhere). 


 

CSE 216 SOFTWARE ENGINEERING

The software life-cycle; life-cycle models; software planning; testing; specification methods; maintenance. Emphasis on team work and large-scale software systems, including oral presentations and written reports. Click here for official description. 

CSE 216-010, TR 1:10-2:25, Professor Liang Cheng

CSE 216-011, TR 9:20-10:35, Professor Liang Cheng


 

CSE 252-010 COMPUTERS, INTERNET AND SOCIETY, TR 9:20-10:35, Professor Brian Davison

An interactive exploration of the current and future role of computers, the Internet, and related technologies in changing the standard of living, work environments, society and its ethical values. Privacy, security, depersonalization, responsibility, and professional ethics; the role of computer and Internet technologies in changing education, business modalities, collaboration mechanisms, and everyday life. (SS). Click here for official description. 


CSE 262 PROGRAMMING LANGUAGES

Use, structure and implementation of several programming languages. Click here for official description.

CSE 262-010, MWF 2:10-3:00, Professor James Femister

CSE 262-011 MWF 11:10-12:00, Professor James Femister


 

CSE 281-010 CAPSTONE PROJECT II, T 10:45-12:00, Professor John Spletzer

Second of a two semester capstone course sequence that involves the design, implementation, and evaluation of a computer science software project; conducted by small student teams working from project definition to final documentation; each student team has a CSE faculty member serving as its advisor; The second semester emphasis is on project implementation, verification & validation, and documentation requirements. It culminates in a public presentation and live demonstration to external judges as well as CSE faculty and students. Prerequisite: Senior standing and CSE 280.


*NEW COURESE FALL 2018* CSE 297-010 BLOCKCHAIN ALGORITHMS & SYSTEMS, MW 11:10-12:25, Professor Hank Korth

Blockchain system concepts, cryptographic algorithms for blockchain security, distributed consensus algorithms for decentralized blockchain control, smart contracts, blockchain databases.


*NEW COURESE FALL 2018* CSE 297-010/397-010 INTRO TO BIOMOLECULAR MODELING AND SIMULATION, MWF11:10-12:25, Professor Wonpil Im

This course is designed to introduce the most basic and key concepts, methods, and tools used in biomolecular modeling and simulation. In particular, this class is a hybrid lecture/hands-on practice style using the lectures and tools in CHARMM-GUI (http://www.charmm-gui.org/lecture). Topics include (but not limited to) UNIX operating system, text editors, Python programming, scientific programming using Python, PDB (Protein Data Bank), molecular mechanics, minimization, molecular dynamics, Monte Carlo simulation. The understanding of these concepts and algorithms as well as their applications to well-defined practical examples involving currently important biological problems will be emphasized.


*NEW COURSE FALL 2018* CSE 298-010 MOBILE APPS (ANDROID), MWF 1:10-2:00, Professor 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, and gyroscope).



CSE 303 OPERATING SYSTEM DESIGN

Process and thread programming models, management, and scheduling. Resource sharing and deadlocks. Memory management, including virtual memory and page replacement strategies. I/O issues in the operating system. File system implementation. Multiprocessing. Computer security as it impacts the operating system. Click here for official description.

CSE 303-010, TR 1:10-2:25, Professor Jason Loew

CSE 303-011, TR 2:35-3:50, Professor Yinzhi Cao

CSE 303-012, TR 9:20-10:35, Professor Jason Loew


 

CSE 307-010/407-010 STRUCTURAL BIOINFORMATICS, MWF 1:10-2:00, Professor Brian Chen

Computational techniques and principles of structural biology used to examine molecular structure, function, and evolution. Topics include: protein structure alignment and prediction; molecular surface analysis; statistical modeling; QSAR; computational drug design; influences on binding specificity; protein-ligand, -protein, and -DNA interactions; molecular simulation, electrostatics. Tutorials on UNIX systems and research software support an interdisciplinary collaborative project in computational structural biology. Click here for official description.


 

CSE 313 COMPUTER GRAPHICS, TR 9:20-10:35, Professor Xiaolei Huang

Computer graphics for animation, visualization, and production of special effects: displays, methods of interaction, images, image processing, color, transformations, modeling (primitives, hierarchies, polygon meshes, curves and surfaces, procedural), animation (keyframing, dynamic simulation), rendering and realism (shading, texturing, shadows, visibility, ray tracing), and programmable graphics hardware. Prerequisite: CSE 109 and (MATH 043 or MATH 205 or MATH 242). Click here for official description.


 

CSE 320-010/420-010 BIOMEDICAL IMAGE COMPUTING, TR 2:35-3:50, Professor Miaomiao Zhang

This course focuses on an in-depth study of advanced topics and interests in image data analysis. Student will learn about hardcore imaging techniques and gain mathematical fundamentals needed to build their own models effective for 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 description.


 

CSE 331-010 USER INTERFACE SYSTEMS & TECHNIQUE, MW 12:45-2:00, Professor Eric Baumer

Principles and practice of creating effective human-computer interfaces. Design and user evaluation of user interfaces; design and use of interface building tools. Programming projects using a variety of interface building tools to construct and evaluate interfaces. Prerequisite: CSE 017 or consent of the instructor. Click here for official description.


 

CSE 334/434-010 SOFTWARE SYSTEM SECURITY, TR 9:20-10:35, Professor Yinzhi Cao

Survey of common software vulnerabilities: buffer overflows, format string attacks, cross-site scripting, and botnets. Discussion of common defense mechanisms: static code analysis, reference monitors, language-based security, secure information flow, and others. The graduate version differs from the undergraduate version by requiring advanced assignments and projects. Credit will not be given for both CSE 334 and CSE 434. Prerequisite: CSE 109 and CSE 262.



CSE 340 DESIGN & ANALYSIS OF ALGORITHMS

Algorithms for searching, sorting, manipulating graphs and trees, finding shortest paths and minimum spanning trees, scheduling tasks, etc.: proofs of their correctness and analysis of their asymptotic runtime and memory demands. Designing algorithms: recursion, divide-and-conquer, greediness, dynamic programming. Limits on algorithm efficiency using elementary NP-completeness theory. Click here for official description.

CSE 340-010, TR 10:45-12:00, Professor Hector Munoz-Avila

CSE 340-011, TR 2:35-3:50, STAFF


 

CSE 341 DATABASE SYSTEMS, ALGORITHMS & APPLICATIONS, MW 8:45-10:00, Professor Hank Korth

Design of large databases; normalization; query languages (including SQL); transaction-processing protocols; query optimization; performance tuning; distributed systems. Not available to students who have credit for CSE 241. Prerequisites: CSE 17



CSE 347-010/447-010 DATA MINING, TR 10:45-12:00, Professor Ting Wang

Overview of modern data mining techniques: data cleaning; attribute and subset selection; model construction, evaluation and application. Fundamental mathematics and algorithms for decision trees, covering algorithms, association mining, statistical modeling, linear models, neural networks, instance-based learning and clustering covered. Practical design, implementation, application and evaluation of data mining techniques in class projects. Click here for official description.


 

CSE 375-010/475-010 PRINCIPLES AND PRACTICE OF PARALLEL COMPUTING, MWF 10:10-11:00, Professor 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 expositing locks to programmer. Click here for official description.


 

*NEW COURSE FALL 2018* CSE 398-013/498-013 NATURAL LANGUAGE PROCESSING, MW 12:45-2:00, Professor 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.



*NEW COURSE FALL 2018* CSE 398-015/498-015 DEEP LEARNING, TR 1:10-2:25, Professor 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 406-010 RESEARCH METHODS, MW 2:35-3:50, Professor Jeff Heflin

Technical writing, reading the literature critically, analyzing and presenting data, conducting research, making effective presentations, and understanding social and ethical responsibilities. Topics drawn from probability and statistics, use of scripting languages, and conducting large-scale experiments. Must have first-year status in either the CS or CompE Ph. D. program.


 

CSE 411-010 ADVANCED PROGRAMING TECHNIQUES, MWF 11:10-12:00, Professor Michael Spear

 Deeper study of programming and software engineering techniques. The majority of assignments involve programming in contemporary programming languages. Topics include memory management, GUI design, testing, refactoring, and writing secure code.


 

This listing represents our current plan for the semester in question. Course offerings and class times are occasionally subject to change for reasons beyond our control.

 

PREVIOUS COURSE OFFERINGS

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hew207@lehigh.edu (Heidi Wegrzyn) Mon, 26 Mar 2018 17:56:26 -0400
WiDS http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/377-wids http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/377-wids

 WiDS 2018

Stanford Women in Data Science Conference
Livestream @ Lehigh
Monday, March 5 - Building C Room 115
12:00 noon – 8:00 pm EST

All students, faculty, and staff are invited to attend the Stanford WiDS Livestream at Lehigh. Check out the schedule and pop in and out for the sessions you find interesting. Details can be found in the full program. Register for our Livestream here. A light lunch will be provided starting at 11:30 am, and refreshments will be available throughout the day. If you plan to join us for lunch, send email to jgs2@lehigh.edu.

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jgs2@lehigh.edu (Jeanne Steinberg) Fri, 23 Feb 2018 21:16:21 -0500
CSE Office Moved http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/376-cse-office-moved http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/376-cse-office-moved The CSE Department has moved to Mountaintop Building C effective Friday, January 19, 2018.

CSE Courses held in Building C (all other CSE courses not listed are held on lower campus)


CSE 098 Women in Technology (F 2:10-4:00) held in BC 115
CSE 280 Capstone Project (MW 8:45-10:00) held in BC 210
CSE 343/443 Network Security (MW 12:45-2:00) held in BC 115, second location in EWFM 625 for undergrads with travel constraints.
CSE 398/498 Big Data Analytics (TR1:10-2:25) held in BC 115
CSE 403 Advanced Operating Systems (MW 11:10-12:25) held in BC 115

Lehigh Bus Schedule: http://bus.lehigh.edu/

Building C Location and Parking Map

Faculty and Staff Offices Located in Building C (113 Research Drive)

Eric Baumer

BC 235

Yinzhi Cao

BC 328

Brian Chen

BC 330

Liang Cheng

BC 313

Mooi Choo Chuah

BC 317

Brian Davison

BC 233

Jeff Heflin

BC 232

Xiaolei Huang

BC 332

Daniel Lopresti

BC 215

Hector Munoz-Avila

BC 231

Roberto Palmieri

BC 338

Michael Spear

BC 339

John Spletzer

BC 106

Jeanne Steinberg

BC 214

Ting Wang

BC 327

Heidi Wegrzyn

BC 212

Sihong Xie

BC 326

Miaomiao Zhang

BC 337

 Faculty and Staff Offices Remaining in Packard Lab

James Femister PA 200b
Eric Fouh Mbindi PA 204a
Bryan Hodgson PA 115
Sharon Kalafut PA 200a
Hank Korth PA 414
Jason Loew PA 325

 Computer Engineering Program

Kerry Livermore PA 354

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hew207@lehigh.edu (Heidi Wegrzyn) Tue, 16 Jan 2018 14:22:21 -0500
tmi http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/375-tmi http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/375-tmi
          Data X TMI     
Keynote

Heng Xu
Associate Professor of Information Sciences and Technology
Pennsylvania State University

"Your Privacy Is Your Friend's Privacy: Examining Interdependent Privacy Issues on Online Social Networks"

Monday, November 6, 4:00 PM
STEPS 101

Abstract:   The highly interactive nature of interpersonal communication on online social networks (OSNs) impels us to think about privacy as a communal matter, with users’ private information being revealed by not only their own voluntary disclosures, but also the activities of their social ties. The current privacy literature has identified two types of information disclosures in OSNs: self-disclosure, i.e., the disclosure of an OSN user’s private information by him/herself; and co-disclosure, i.e., the disclosure of the user’s private information by other users. Although co-disclosure has been increasingly identified as a new source of privacy threat inherent to the OSN context, few systematic attempts have been made to provide an empirical understanding on the commonalities and distinctions between self- vs. co-disclosure. To address this gap, we conducted two empirical studies (one theory-driven and the other data-driven) to measure OSN users’ concerns over co-disclosure and potential privacy harms caused by co-disclosure. This research serves as a starting point for theorizing privacy from the non-individualistic perspective and for understanding interdependent privacy issues as a result of interpersonal interaction and social influence.

Bio:  Dr. Heng Xu is Associate Professor of Information Sciences and Technology at the Pennsylvania State University, and leads the Privacy Assurance Lab (PAL). Her research focuses on understanding and assuring information privacy in different contexts, including location based services, social networks, medical practices, and children and adolescent online safety. Her work has been published in premier outlets across various fields such as Business, Law, Computer Science, and Human-Computer Interaction. During 2013-2016, Dr. Xu served as a program director at the U.S. National Science Foundation, and her effort was put into bringing the social, behavioral and economic sciences to studies of major challenges in Big Data, Cybersecurity & Privacy, and Smart Cities.

Panelists

Eric P. S. Baumer is assistant professor of Computer Science and Engineering at Lehigh University. His research examines interactions with algorithms in social computing systems. Recent work includes using computational tools to identify the language of political framing, and studying technology refusal in the context of Facebook. He holds an MS and PhD in Information and Computer Sciences from the University of California, Irvine, completed post-doctoral work at Cornell University, and holds a BS in Computer Science with a minor in Music from the University of Central Florida.

Haiyan Jia is an assistant professor in the Department of Journalism and Communication and the Data X Initiative. Her research explores how communication technology influences individuals and the society. Her work combines theories from information science, computer-mediated communication, social cognition, and developmental psychology to theorize and empirically examine people's privacy management strategies and behaviors on social media.

Daniel Lopresti is Professor and Chair of Lehigh's Department of Computer Science and Engineering, as well as Director of the university's Data X Initiative. He conducts research examining fundamental algorithmic and systems-related questions in pattern recognition, document analysis, and computer security, and has been frequently quoted as an expert on electronic voting security. He has held leadership roles in most of the major international conferences on document analysis over the past 10 years and is co-editor-in-chief of the International Journal on Document Analysis and Recognition. He chairs the Conferences & Meetings Committee of the International Association of Pattern Recognition. He also serves on the Computing Community Consortium Council of the Computing Research Association (CRA), whose mission is to catalyze the computing research community and enable the pursuit of innovative, high-impact research. He received his bachelor's degree in math from Dartmouth, and his Ph.D. in computer science from Princeton.

Rebecca Wang is an assistant professor of Marketing and the Data X Initiative at Lehigh University. Her research focuses on customer engagement in the contexts of digital channels. By collaborating with industry partners and analyzing large datasets, she uses causal inference and statistical methods to answer questions related to direct marketing with new and mobile media. Prior to her academic career, she worked in industry as a consultant and a data engineer for six years. She holds an A.B. in Engineering Sciences from Dartmouth College, and a Ph.D. in Marketing from Northwestern University.

Gaia Bernstein is the Michael J. Zimmer Professor of Law, Director of the Institute of Privacy Protection and Co-Director of the Gibbons Institute for Law, Science and Technology at Seton Hall University School of Law. Professor Bernstein specializes in law and technology, information privacy, health privacy, intellectual property, law and genetics and reproductive technologies. Her scholarship examines the role of users in the adoption of new technologies. She is currently working on a book titled "The Over-Users: Technology Addiction and the Power of Awareness".

Najarian (Jari) Peters is an attorney and privacy compliance professional with over ten years of experience in academic, healthcare, and private organizations. Prior to joining Seton Hall faculty, she was the Senior Healthcare Compliance Manager for the Health and Wellness Business Unit of Panasonic North America. She has also served as Chief Compliance/Privacy Officer and Risk Manager Counsel for National Healthcare Associates and as Senior Compliance, Ethics Liaison, and HIPAA Privacy Officer for the Rutgers Office of Ethics Compliance and Corporate Integrity. After graduating law school, Ms. Peters joined Weill Cornell Medical School's Office of Research Compliance and Sponsored Programs. She earned her undergraduate degree in Political Science from Xavier University of Louisiana and her Juris Doctorate from Notre Dame Law School. Her research interests include voter privacy, algorithmic bias and accountability, and local broadband movements.

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jgs2@lehigh.edu (Jeanne Steinberg) Tue, 31 Oct 2017 18:34:36 -0400
Spring 2018: Course for skill area http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/374-spring-2018-course-for-skill-area http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/374-spring-2018-course-for-skill-area
  • Theory Skills
    1. CSE 409 Theory of Computation
    2. CSE 426 Pattern Recognition
    3. CSE 498 Advanced Algorithms
  • Applied Theory Skills
    1. CSE 426 Pattern Recognition
    2. CSE 498 Advanced Algorithms
    3. CSE 498 Principles and Implementation of Information Privacy
  • Advanced application skills
    1. CSE 498 Big Data Analytics
    1. Knowledge-Based Systems Skills
      1. CSE 498 Big Data Analytics
    2. Computer Hardware, Systems & Networks
      1. CSE 401 Advanced Computer Architecture
      2. CSE 403 Advanced Operating Systems
      3. CSE 443 Network Security
    3. Security in Computational Environments
      1. CSE 443 Network Security
      2. CSE 498 Principles and Implementation of Information Privacy
    1. Software & Programming Skills
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    hew207@lehigh.edu (Heidi Wegrzyn) Wed, 25 Oct 2017 18:18:32 -0400
    Spring 2018 Course Offering http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/373-spring-2018-course-offering http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/373-spring-2018-course-offering Spring 2018 Courses

    CSE 002 FUNDAMENTALS OF PROGRAMMING

    Problem-solving and object-oriented programming using Java. Includes laboratory. No prior programming experience needed. Click here for official description. All sections will offer Guided Study Groups.

    CSE 002-110, MW 3:10-4:00 F (lab) 3:10-4:00, Professor James Femister

    CSE 002-210, MW 11:10-12:00 F (lab) 11:10-12:00, Professor Brian Chen

    CSE 002-211, MW 11:10-12:00 F (lab), 12:10-1:00 Professor Brian Chen


    CSE 012-010 SURVEY OF COMPUTER SCIENCE, MWF 1:10-2:00, Professor Eric Fouh Mbindi

    This course provides a project-based exploration of fundamental concepts in computing and "computational thinking." Topics include but are not limited to networks, data visualization, information storage and retrieval, and the popular Python programming language. Each project presents applications of computing in solving real life problems. In this course you will learn to write Python code to visualize data from different sources. You will learn how information is transferred across networks and how to store and retrieve data from relational database management systems. Optional Structured Study Groups will be provided for students who express interest. Click here for official description. Guided Study Groups will be offered in this course.


    CSE 017 DATA STRUCTURES & PROGRAMMING

    This course is a programming-intensive exploration of software design concepts and implementation techniques. It builds on the student's existing knowledge of fundamental programming. Topics include object-oriented software design, problem-solving strategies, algorithm development, and classic data structures. Click here for official description.

    CSE 017-012, MWF 11:10-12:00, Professor James Femister

    CSE 017-010, MWF 10:10-11:00, Professor Eric Fouh Mbindi

     There will be weekly mandatory online quizzes and/or homework. One programming is assigned each week. Programming assignments are presented and discussed in-class during lecture. Each assignment covers one of the major topics in the course. There are two 50-minute exams during the semester, and a comprehensive 2-hour final exam at the end of the course.

    CSE 017-011, MWF 9:10-10:00, Professor Eric Fouh Mbindi

     There will be weekly mandatory online quizzes and/or homework. One programming is assigned each week. Programming assignments are presented and discussed in-class during lecture. Each assignment covers one of the major topics in the course. There are two 50-minute exams during the semester, and a comprehensive 2-hour final exam at the end of the course.


    ** NEW COURSE FOR 2017-2018** CSE 098 WOMEN IN TECHNOLOGY, F 2:10-4:00, Professor Daniel Lopresti (Course runs only first half of semester)


    The technology industry has been the engine of growth for the US economy for the past four decades. Emergent tech companies have shaped all of our lives, and created significant professional and financial opportunities for the leaders of these high growth ventures. Despite the many clear opportunities, women hold a minority of the leadership positions in the tech industry. Why? What can be done to change this? How can the next generation of female tech industry leaders succeed? Prerequisite: permission of instructor.


    ** NEW COURSE FOR 2017-2018** CSE 098/CSB 098 SOFTWARE PRODUCT MANAGMENT, F 2:10-4:00, Professor Daniel Lopresti (Course runs only second half of semester)

    Managing the product life cycle Writing great software is only half the challenge. Successful companies are built on top of product/market fit - having the right capabilities at the right time in the market. Product management is key to establishing product/market fit. This class will cover the various elements of product management including: Product definition - writing PRDs and MRDs, Competitive analysis, Pricing, Go-to-market channel strategies, Promotion and demand generation. Prerequisite: permission of instructor


    CSE 109 SYSTEMS SOFTWARE

    Advanced programming and data structures, including dynamic structures, memory allocation, data organization, symbol tables, hash tables, B-trees, data files. Object-oriented design and implementation of simple assemblers, loaders, interpreters, compilers and translators. Practical methods for implementing medium-scale programs. Click here for official description.

    CSE 109-010, MWF 1:10-2:00 F (lab) 12:10-1:00, Professor Jason Loew

    CSE 109-011, MWF 10:10-11:00 F (lab) 11:10-12:00, Professor Jason Loew


    CSE 160-010 INTRO TO DATA SCIENCE, MWF 10:10-11:00, Professor Brian Davison

     

    Interested in understanding the hype about data science, big data, or data analytics? This course introduces you to data science, a fast-growing and interdisciplinary field, focusing on the computational analysis of data to extract knowledge and insight. You will be introduced to the collection, preparation, analysis, modeling, and visualization of data, covering both conceptual and practical issues. Applications of data science across multiple fields are presented, and hands-on use of statistical and data manipulation software is included. The course is open to students from all areas of study; the only prerequisite is some programming experience (automatic if you've taken CSE 2, 12, or BIS 335, or permission of the instructor is available if you can show that you've successfully completed a programming course online, in high school, or elsewhere). 


    ** THIS COURSE REPLACES CSE 261**

    CSE 198 FOUNDATIONS OF DISCRETE STRUCTURES AND ALGORITHMS

    Basic representations used in algorithms: propositional and predicate logic, set operations and functions, relations and their representations, matrices and their representations, graphs and their representations, trees and their representations. Basic formalizations for proving algorithm correctness: logical consequences, induction, structural induction. Basic formalizations for algorithm analysis: counting, pigeonhole principle, permutations. Prerequisite: (Math 021 or Math 031 or Math 51 or Math 76) and (CSE 001 or CSE 002 or CSE 012)

    CSE 198-012, TR 10:45-12:00, Professor Ting Wang

    CSE 198-013, TR 1:10-2:25, Professor Xiaolei Huang


     CSE 202 COMPUTER ORGANIZATION AND ARCHITECTURE

    Interaction between low-level computer architectural properties and high-level program behaviors: instruction set design; digital logics and assembly language; processor organization; the memory hierarchy; multicore and GPU architectures; and processor interrupt/exception models. Click here for official description.

    CSE 202-010, TR 9:20-10:35, Professor Jason Loew

    CSE 202-011, MW 12:45-2:00, Professor Mark Erle


    CSE 216-010 SOFTWARE ENGINEERING, MW 11:10-12:25, Professor Michael Spear

    The software life-cycle; life-cycle models; software planning; testing; specification methods; maintenance. Emphasis on team work and large-scale software systems, including oral presentations and written reports. Click here for official description.


    CSE 241-010 DATABASE SYSTEMS

    Design of large databases: Integration of databases and applications using SQL and JDBC; transaction processing; performance tuning; data mining and data warehouses. Click here for official description.

    CSE 241-010, TR 10:45-12:00, Professor Hank Korth

    CSE 241-011, TR 2:35-3:50, Professor Sihong Xie


    CSE 252-010 COMPUTERS, INTERNET AND SOCIETY, TR 2:35-3:50, Professor Eric Baumer

    An interactive exploration of the current and future role of computers, the Internet, and related technologies in changing the standard of living, work environments, society and its ethical values. Privacy, security, depersonalization, responsibility, and professional ethics; the role of computer and Internet technologies in changing education, business modalities, collaboration mechanisms, and everyday life. (SS) Click here for official description.


    CSE 264-010 WEB APPLICATIONS, TR 2:35-3:50, Professor James Femister

    Practical experience in designing and implementing modern Web applications. Concepts, tools, and techniques, including: HTTP, HTML, CSS, DOM, JavaScript, Ajax, PHP, graphic design principles, mobile web development. Not available to students who have credit for IE 275. Click here for official description.


    CSE 280-010 CAPSTONE PROJECT I, MW 8:45-10:00, Professor John Spletzer

     First of a two semester capstone course sequence that involves the design, implementation, and evaluation of a computer science software project. Conducted by small student teams working from project definition to final documentation. Each student team has a CSE faculty member serving as its advisor. The first semester emphasis is on project definition, planning and implementation. Communication skills such as technical writing, oral presentations, and use of visual aids are also emphasized. Project work is supplemented by weekly seminars. Prerequisite: junior standing and CSE 216.


    ** NEW COURSE FOR 2017-2018** CSE 298/FIN 298 BLOCKCHAIN, MW 12:45-2:00, Professor Hank Korth

    Blockchain is the technology underlying Bitcoin, along with other digital currencies, and a technology applicable broadly in finance, accounting, and "smart" contracts. It offers the ability to decentralize financial transactions, automate record keeping, and increase privacy, but it remains controversial. Some describe it as "the most important invention since the Internet", yet others, including the CEO of a leading financial firm, have described Bitcoin as a "fraud" and that CEO has threatened to fire anyone in the firm caught trading it.

    This course will provide an introduction to the technology underlying blockchain, the current and potential applications of blockchain in business, and the resulting policy issues. The course is designed for students with either some business-course background, some computer-science background, or both. Prerequisite: permission of instructor.


    CSE 318-010 INTRODUCTION TO THE THEORY OF COMPUTATION, TR 10:45-12:00, Professor Hector Munoz-Avila

    Formal study of theoretical computational models: finite automata, pushdown automata, and Turing machines. Study of formal languages: regular, context-free, and decidable languages. Click here for official description.


    CSE 326/426 FOUNDATIONS OF MACHINE LEARNING, MW 2:35-3:50, Professor Miaomiao Zhang

    ** NEW FACULTY MEMBER FOR 2017-2018**

    An introductory course offers a broad overview of the main techniques in machine learning.  Students will study the basic concepts of advanced machine learning methods as well as their theoretical background. Topics of learning theory (bias/variance tradeoffs; VC theory); supervised learning parametric/nonparametric methods, Bayesian models, support vector machines, neural networks); unsupervised learning (dimensionality reduction, kernel tricks, clustering) and reinforcement learning will be covered.  Also note that this course is a prerequisite for CSE 347 Data Mining.   Click here for official description.


    CSE 327-011 ARTIFICIAL INTELLIGENCE OF THEORY AND PRACTICE, TR 1:10-2:25, Professor Jeff Heflin

    Introduction to the field of artificial intelligence: Problem solving, knowledge representation, reasoning, planning and machine learning. Use of AI systems or languages. Advanced topics such as natural language processing, vision, robotics, and uncertainty. Click here for official description.


    CSE 343-010/443-010 NETWORK SECURITY, MW 12:45-2:00, Professor Mooi Choo Chuah

    Overview of network security threats and vulnerabilities. Techniques and tools for detecting, responding to and recovering from security incidents. Fundamentals of cryptography. Hands-on experience with programming techniques for security protocols. Click here for official description.


    **NEW COURSE for 2017-2018** CSE 398/498-014 PRINCIPLES AND IMPLEMENTATION OF INFORMATION PRIVACY, TR 9:20-10:35, Professor 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 information systems that respect individuals' data privacy while still enabling high-quality services. 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. CSE 398 prerequisite: CSE 347/447, for CSE 498: permission of instructor.


    **NEW COURSE for 2017-2018** CSE 398/498-010 BIG DATA ANALYTICS, R 1:10-2:25, Professor Daniel Lopresti

     In this 3-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.

    The Tuesday meeting time is tentative and if needed students will meet with the instructor separately each week at a mutually convenient time, either individually or in small groups.

    Enrollment in this course is limited and requires permission of the instructor. Please note that this is not a basic course on data mining, cluster computing, or programming in Scala; it assumes you already know something about these topics and/or you can learn them quickly on your own. Contact the instructor, Prof. Dan Lopresti, for details. This course will be taught using one of the new classrooms in Building C.


    CSE 401-010 ADVANCED COMPUTER ARCHITECTURE, TR 10:45-12:00, Professor Xiaochen Guo

    Design, analysis and performance of computer architectures; high-speed memory systems; cache design and analysis; modeling cache performance; principle of pipeline processing, performance of pipelined computers; scheduling and control of a pipeline; classification of parallel architectures; systolic and data flow architectures; multiprocessor performance; multiprocessor interconnections and cache coherence.


    CSE 403-010 ADVANCED OPERATING SYSTEMS, MW 11:10-12:25, Professor Roberto Palmieri

     ** NEW FACULTY MEMBER FOR 2017-2018**

    Principles of operating systems with emphasis on hardware and software requirements and design methodologies for multi-programming systems. Global topics include the related areas of process management, resource management, and file systems.


    CSE 409-010 THEORY OF COMPUTATION, TR 10:45-12:00, Professor Hector Munoz-Avila

    Finite automata. Pushdown automata, Relationship to definition and parsing of formal grammars. Credit will not be given for both CSE 318 and CSE 409.


    **THIS COURSE REPLACES CSE 441**

    CSE 498-010 ADVANCED ALGORITHMS, TR 2:35-3:50, Professor Hector Munoz-Avila

    Average-case runtime analysis of algorithms. Randomized algorithms and probabilistic analysis of their performance. Analysis of data structures including hash tables, augmented data structures with order statistics. Amortized analysis. Elementary computational geometry. Limits on algorithm space efficiency using PSPACE-completeness theory. Prerequisite: CSE 340 or MATH 340 or permission of instructor.


    This listing represents our current plan for the semester in question. Course offerings and class times are occasionally subject to change for reasons beyond our control.


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    hew207@lehigh.edu (Heidi Wegrzyn) Wed, 11 Oct 2017 18:22:14 -0400
    Hittinger http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/372-hittinger http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/372-hittinger
              Hittinger      Data X Seminar Series

    Jeffrey Hittinger


    Computational Scientist
    Center for Applied Scientific Computing
    Lawrence Livermore National Laboratory

    "Making Every Bit Count: Variable Precision?"

    Thursday, October 19, 4:00 PM
    Packard Lab 466

    Abstract:   Decades ago, when memory was a scarce resource, computational scientists routinely worked in single precision and were more sophisticated in dealing with the pitfalls finite-precision arithmetic. Today, however, we typically compute and store results in 64-bit double precision by default even when very few significant digits are required. Many of these bits are representing errors – truncation, iteration, roundoff – instead of useful information about the solution. This over-allocation of resources is wasteful of power, bandwidth, storage, and FLOPs; we communicate and compute on many meaningless bits and do not take full advantage of the computer hardware we purchase.

    Because of the growing disparity of FLOPs to memory bandwidth in modern computer systems and the rise of General-Purpose GPU computing – which has better peak performance in single precision – there has been renewed interest in mixed precision computing, where tasks are identified that can be accomplished in single precision in conjunction with double precision. Such static optimizations reduce data movement and FLOPs, but their implementations are time consuming and difficult to maintain, particularly across computing platforms. Task-based mixed-precision would be more common if there were tools to simplify development, maintenance, and debugging. But why stop there? We often adapt mesh size, order, and models when simulating to focus the greatest effort only where needed. Why not do the same with precision?

    At LLNL, we are developing the methods and tools that will enable the routine use of dynamically adjustable precision at a per-bit level depending on the needs of the task at hand. Just as adaptive mesh resolution frameworks adapt spatial grid resolution to the needs of the underlying solution, our goal is to provide more or less precision as needed locally. Acceptance from the community will require that we address three concerns: that we can ensure accuracy, ensure efficiency, and ensure ease of use in development, debugging, and application. In this talk, I will discuss the benefits and the challenges of variable precision computing, highlighting aspects of our ongoing research in data representations, numerical algorithms, and testing and development tools.

    Bio:   Dr. Jeffrey Hittinger is a computational scientist in the Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory, where he currently serves as Acting Deputy Director of CASC and leader of the Scientific Computing Group. At Livermore, he also leads a large interdisciplinary Strategic Initiative project on Variable Precision Computing. Dr. Hittinger has been actively involved in the Department of Energy (DOE) planning for exascale computing and co-chaired the working group that produced the Applied Mathematics Research for Exascale Computing community report for the DOE Office of Science Advanced Scientific Computing Research program. His current research interests include high-order numerical methods for hyperbolic systems, computational plasma physics, high-performance parallel computing, a posteriori error estimation, and code and solution verification. Dr. Hittinger earned his Ph.D. in Aerospace Engineering and Scientific Computing from the University of Michigan, where he also earned master's degrees in Applied Mathematics and in Aerospace Engineering. He is a graduate of Lehigh University, with a bachelor's degree in Mechanical Engineering.

    This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

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    jgs2@lehigh.edu (Jeanne Steinberg) Mon, 09 Oct 2017 19:11:10 -0400
    Computer Science Electives http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/371-computer-science-electives http://www.cse.lehigh.edu/academics/undergraduate-computer-science/in-the-college-of-arts-and-sciences/2-uncategorised/371-computer-science-electives COMPUTER SCIENCE ELECTIVE CHOICES

    Students are required to take 12 credits of Computer Science electives from the following list:

    CSE 202 Computer Organization and Architecture

    CSE 241 Data Base Systems and Applications

    CSE 264 Web Systems Programming (3)

    CSE 265 System and Network Administration (3)

    CSE 271 Programming in the C and Unix Environment (3)

    CSE 303 Operating Sytem Design (3)

    CSE 313  Computer Graphics (3)

    CSE 318  Automata and Formal Grammars (3)

    CSE 319 Image Analysis and Graphics (3)

    CSE 326 Foundations of Machine Learning (3)

    CSE 327 Artificial Intelligence Theory and Practice (3)

    CSE 331  User Interface Systems and Techniques (3)

    CSE 334 Software System Security (3)

    CSE 335  Topics on Intelligent Decision Support Systems (3)

    CSE 336  Embedded Systems (3)

    CSE 337 Reinforcement Learning (3)

    CSE 341 Database Systems, Algorithms, and Applications (3)

    CSE 342  Fundamentals of Internetworking (4)

    CSE 343  Network Security (3)

    CSE 345  WWW Search Engines (3)

    CSE 347 Data Mining (3)

    CSE 348  AI Game Programming (3)

    CSE 360  Introduction to Mobile Robotics (3)

    CSE 363 Network System Design (3)

    CSE 375  Hardware & Software Topics in Parallel Computing (3)

    Or other courses as approved by the CSE Department Chair.

    ]]>
    hew207@lehigh.edu (Heidi Wegrzyn) Mon, 09 Oct 2017 17:12:22 -0400