CSE Summer 2020 Courses

NOTE: 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.

FULL SUMMER SESSION (5/19/20-8/6/20)

CSE 202 COMPUTER ORGANIZATION AND ARCHITECTURE, MW 4:00-6:50pm, Professor Mark Erle

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.  Credit will not be given for both CSE 201 and CSE 202.


CSE 340 DESIGN AND ANALYSIS OF ALGORITHMS, MTWR 10:00-11:45am, Professor Arielle Carr

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. Credit will not be given for both CSE 340 (MATH 340) and CSE 441 (MATH 441).


SUMMER SESSION I (5/19/20-6/25/20)

CSE 002 FUNDAMENTALS OF PROGRAMMING, MTWR 12:00-1:45, Professor Sharon Kalafut

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


CSE 012 SURVEY OF COMPUTER SCIENCE, MTWR 10:00-11:45, Professor Sharon Kalafut

Course Description: Fundamental concepts of computing and "computational thinking":problem analysis, abstraction, algorithms, digital representation of information, and networks. Applications of computing and communication that have changed the world. Impact of computing on society. Concepts of software development using a scripting language such as Python, Perl, or Ruby. Not available to students who have taken CSE 001.


CSE 017 PROGRAMMING & DATA STRUCTURES, MTWR 12:00-1:45, Professor Arielle Carr

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.


CSE 140 FOUNDATIONS OF DISCRETE STRUCTURES AND ALGORITHMS, MTWR 10:00-11:45, Professor Ahmed Hassan

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.


SUMMER SESSION II (6/29/20-8/6/20)

CSE 017 PROGRAMMING & DATA STRUCTURES, MTWR 10:00-11:45, Professor Corey Montella

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.


CSE 109 SYSTEMS SOFTWARE, MTWR 12:00-1:45, Professor Houria Oudghiri

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.


CSE 298 FOUNDATIONS OF ROBOTICS, TR 4:00-6:50,  Professor Corey Montella
 
Introduces students to the field of robotics, covering foundational mathematics and physics as well as important algorithms and tools. Topics include simulation, kinematics, control, machine learning, and probabilistic inference. The mathematical basis of each area will be covered, followed by practical application to common robotics tasks. This course is designed to be taught remotely using simulated robot platforms and sensors. Pre-requisites:  (CSE 002 and (CSE 001 or CSE 012 or ENGR 010)

 

CSE FALL 2020 COURSES

NOTE: 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.

CSE 003 INTRO. TO PROGRAMMING PART A, MWF 12:10-1:00, Professor Brian Chen

Covers the same material as the first half of CSE 007. Designed to allow more class and laboratory time for each topic. No prior programming experience needed. Cannot be taken by students who have completed CSE 007.


CSE 007 INTRODUCTION TO PROGRAMMING

Problem-solving using the Java programming language. Data types, control flow, methods, arrays, objects, inheritance, breadth of computing. Includes laboratory. If credit is given for CSE 007 then no credit will be given for CSE 003 nor CSE 004.

CSE 007-010, MWF 7:55-9:10, Professor Houria Oudghiri

CSE 00-011, MWF 9:20-10:35, Professor Houria Oudghiri

CSE 007-013, MWF 1:35-2:50, Professor Kallie Ziltz


CSE 012-010 SURVEY OF COMPUTER SCIENCE

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. 

CSE 012-010, TR 10:45-12:00, Professor Sharon Kalafut

CSE 012-011, TR 1:35-2:50, Professor Sharon Kalafut


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.

CSE 017-010, TR 1:35-2:50, Professor Houria Oudghiri

CSE 017-011, TR 3:00-4:15, Professor Arielle Carr

CSE 017-012, TR 7:55-9:10, Professor Houria Oudghiri


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.

CSE 109-011, MWF 10:45-12:00, Professor Mark Erle

CSE 109-012, MWF 3:00-4:15, Professor Mark Erle


CSE 160 INTRO TO DATA SCIENCE, MWF 1:35-2:25, 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.

CSE 216-010, TR 1:35-2:50, Professor William Phillips

CSE 216-011, TR 3:00-4:15, Professor William Phillips


CSE 241 DATABSE SYSTEMS AND APPLICATIONS, MW 7:55-9:10, Professor Sihong Xie

Design of large databases: Integration of databases and applications using SQL and JDBC; transaction processing; performance tuning; data mining and data warehouses. Not available to students who have credit for CSE 341 or IE 224. 


CSE 252 COMPUTERS, INTERNET AND SOCIETY

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).

CSE 252-010, TR 9:50-11:05, Professor Brian Davison

CSE 252-011, MW 11:15-12:30, Professor Eric Baumer


CSE 262 PROGRAMMING LANGUAGES

Use, structure and implementation of several programming languages.

CSE 262-010, MWF 12:10-1:00, Professor Corey Montella

CSE 262-011 MWF 1:35-2:25, Professor Corey Montella


CSE 264 WEB SYSTEMS PROGRAMMING, TR 9:20-10:35, Professor Dominic DiFranzo

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.


CSE 271 PROGRAMMING IN C & THE UNIX ENVIRONMENT, MW 1:35-2:50, Professor Mark Erle

C language syntax and structure. C programming techniques. Emphasis on structured design for medium to large programs. Unix operating system fundamentals. Unix utilities for program development, text processing, and communications.


CSE 281 CAPSTONE PROJECT II, F 3:00-4:15, Professor Corey Montella

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.


CSE 297 BLOCKCHAIN ALGORITHMS & SYSTEMS, TR 10:45-12:00, Professor Hank Korth

Blockchain system concepts, cryptographic algorithms for blockchain security, distributed consensus algorithms for decentralized blockchain control, smart contracts, blockchain databases. Prerequisites: CSE 109 or CSE 241 or CSE 341 or permission of instructor. CSE 109 can be taken concurrently.


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.

CSE 303-010, MW 1:35-2:25 with M recitation 3:00-3:50, Professor Michael Spear

CSE 303-011, MW 1:35-2:25, with R recitation 12:10-1:00, Professor Michael Spear

CSE 303-012, MW 1:35-2:25, with W recitation 3:00-3:50, Professor Michael Spear

CSE 303-013, MW 1:35-2:25, with R recitation 1:35-2:25 Professor Michael Spear

CSE 303-014, MW 1:35-2:25, with R recitation 3:00-3:50, Professor Michael Spear


CSE 320/420 BIOMEDICAL IMAGE COMPUTING & MODELING, TR 8:25-9:40, Professor Lifang He

Biomedical image modalities, image computing techniques, and imaging informatics systems. Understanding, using, and developing algorithms and software to analyze biomedical image data and extract useful quantitative information: Biomedical image modalities and formats; image processing and analysis; geometric and statistical modeling; image informatics systems in biomedicine. Credit will not be given for both CSE 320 and CSE 420.


CSE 326/426 MACHINE LEARNING, MW 9:20-10:35, Professor Sihong Xie

Bayesian decision theory and the design of parametric and nonparametric classification and regression: linear, quadratic, nearest-neighbors, neural nets. Boosting, bagging. Credit will not be given for both CSE 326 and CSE 426


CSE 331 USER INTERFACE SYSTEMS & TECHNIQUES, TR 2:05-3:20, 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 216 or consent of the instructor.


CSE 336/ECE 336 EMBEDDED SYSTEMS, MW 3:00-4:15, Professor Yahong Zheng

Use of small computers embedded as part of other machines. Limited-resource microcontrollers and state machines from high description language. Embedded hardware: RAM, ROM, flash, timers, UARTs, PWM, A/D, multiplexing, debouncing. Development and debugging tools running on host computers. Real-Time Operating System (RTOS) semaphores, mailboxes, queues. Task priorities and rate monotonic scheduling. Software architectures for embedded systems. 


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.

CSE 340-010, MW 10:45-12:00, Professor Arielle Carr

CSE 340-011, MW 3:00-4:15, Professor Arielle Carr


CSE 360/460-010 INTRODUCTION MOBILE ROBOTICS, TR 2:05-3:20, Professor David Saldana

Algorithms employed in mobile robotics for navigation, sensing, and estimation. Common sensor systems, motion planning, robust estimation, bayesian estimation techniques, Kalman and Particle filters, localization and mapping.


CSE 371/CSE 471 PRINCIPLES OF MOBILE COMPUTING, MW 10:45-12:00, Professor Mooi Choo Chuah

Please see the following link for further information: http://www.cse.lehigh.edu/~chuah/CSE371.html


CSE 375/475 PRINCIPLES & PRACTICE OF PARALLEL COMPUTING, MW 9:50-11:05, 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.


CSE 398/498 BIG DATA ANALYTICS, MW 2:05-3:20, 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.

Beyond the textbook, supplemental readings will provide additional background for each application area. During class, students will take turns helping to lead the discussion. A final project will be required.

Enrollment in this course is limited and requires permission of the instructor. Please note that this is not a basic course on data mining, machine learning, or distributed computing; it assumes you already know something about these topics and/or you can pick up the necessary details on your own. Contact the instructor, Prof. Daniel Lopresti, for details. This course will be taught in Building C.


CSE 401/ECE 401 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 406 RESEARCH METHODS, TR 9:50-11:05, 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 CS program.


CSE 411 ADVANCED PROGRAMING TECHNIQUES, TR 12:40-1:55, STAFF

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.


CSB COURSES – FALL 2020

CSB 304 TECHNOLOGY & SOFTWARE VENTURES, TR 12:10-1:25, Professor Joshua Ehrig

Designed from the perspective of a functional leader, this course provides students with a holistic perspective of developing a successful software venture in an interdisciplinary and experiential environment. Students will develop a software-oriented idea concurrent with module delivery that will contain best practices, case studies, and subject-matter experts. Examination will include business model fundamentals, customer discovery, translating requirements to a minimum viable product, agile development, user acquisition, and traction. Prior programming experience preferred, but, not required. Open to any major.


CSB 313 DESIGN OF INTEGRATED BUSINESS APPLICATIONS II, TR 3:00-4:15,  Professors Sharon Kalafut, George Witmer, and Edwin Yeakel

Integrated Product Development (IPD) Capstone I. Industry-based business information systems design project. Information systems design methodology, user needs analysis, project feasibility analysis of design alternatives, and integrated product development methodology. Formal oral and written presentations to clients. Click here for official description.


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.