ELEE 4011/2: Senior Design Capstone Project — I (full-instructor)
Spring 2023:
ELEE 4032: Senior Design Capstone Project — II
ELEE 5940-1: Digital Communications
This course is a graduate-level introduction to the basic principles that underline the analysis and design of digital communication systems. Digital communication systems involve the transmission of information (in digital form) from a source that generates the information to one or more destinations. Course topics include introduction to digital communication; digital signaling and detection techniques; probability of error analysis and optimal receivers for AWGN and other channels; matched filter and correlators; signal space representations; digital passband modulation with coherent receivers, including different forms of amplitude shift keying (ASK), phase shift keying (PSK), quadrature amplitude & phase modulation (QAM), and frequency shift keying (FSK); non-coherent detection techniques. Other topics such as synchronization, coding and information theory, transmission over Bandlimited channels, adaptive equalization, spread spectrum, and fading channels, will be briefly discussed.
Fall 2022:
ELEE 4012: Senior Design Capstone Project — I (co-instructor) A capstone design course which integrates materials from many sub-disciplines of Electrical & Computer and Robotics Engineering. This course provides a comprehensive engineering design experience comparable to that encountered in industry. Students have an opportunity to participate in a creative and realistic design effort that, in addition to the technical aspect, requires written, oral, and visual communication skills, as well as teamwork and planning. Course and Lab sessions target (i) technical and theoretical topics related to the developed product, (ii) reliability, safety, and engineering ethics and practices, among other topics, as well as (iii) actual implementation of algorithms and hardware including prototype development, testing, and final product development. Distinction between course and lab sessions in terms of delivered material and task assignment is reserved for instructors to decide.
ELEE 5750: Deep Learning
This course is an introduction to “Deep Learning”, a branch of machine learning concerned with development and application of large deep neural networks. In a nutshell, the course covers various deep learning algorithms which extract higher-level layered representations of the data to maximize the performance on a given task. The course also covers topics like backward/forward propagation methods, practical aspects of deep learning, optimization methods for neural networks, as well as advanced topics such as convolutional neural networks and generative adversarial models. A semester-long project in which students implement a practical application of deep learning algorithms into various domains, such as image classification, facial or speech recognition, autonomous driving, privacy and algorithmic fairness, is required to successfully complete the class.
Spring 2022:
ELEE 5940-1: Digital CommunicationsELEE 4880/5880: Digital Signal Processing
This course provides a comprehensive treatment of the theory, design, and implementation of digital signal processing algorithms. It introduces students to fundamental concepts of digital signal processing including sampling and reconstruction, the Z-transform,
discrete-time Fourier transforms (DFT) and their implementation, digital filter design including Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) digital filtering, Fast Fourier Transform (FFT), and Adaptive Filtering. Advanced-level treatment of topics will be achieved by research-based term projects and final presentations (by graduate students).
ELEE 4800/5800: Computer Organization and Architecture
Computer architecture is the science of selecting and interconnecting hardware components to create a computer that meets functional, performance and cost goals. This course qualitatively and quantitatively examines computer design trade-offs and teaches the fundamentals of computer architecture and organization, including CPU, memory, registers, arithmetic & control units, and input/output components. Topics include data representation; machine architecture with coverage of basic digital logic circuits; machine language and assembler language programming; memory types and hierarchies; Input/Output and storage devices; organization of the processor data-path and control: parallelism, multi-core, multiprocessor, and clusters. All topics/concepts are demonstrated using MIPS architecture (Microprocessor without Interlocked Pipelined Stages). Graduate students are required to study and present more advanced topics such as Assemblers, linkers, the SPIM simulator; Graphics and Computing GPUs.
Fall 2021:
ELEE 5750: Deep LearningELEE 5940-2: Information Theory
This course is a graduate-level introduction to information theory, an elegant mathematical theory which provides an understanding for the fundamental limits of information compression and communication, e.g., to what size can we compress an image with or without distortion? how fast can we communicate a message “reliably” over an unreliable channel? The concepts of information theory extend far beyond communication theory and have influenced diverse fields from machine learning to computer science to biology and physics. This course, intended primarily for advanced undergraduates and beginning graduate students, offers a broad introduction to information theory and its applications: Entropy and mutual information; lossless data compression; communication in the presence of noise, channel capacity and channel coding; lossy compression and rate-distortion theory; Kolmogorov complexity. The course will also touch on the applications of information theory to machine learning (inference), security and privacy, and distributed information storage and retrieval systems.
Spring 2021:
ELEE 4800/5800: Computer Organization and ArchitectureELEE 2650: Digital Logic Circuits Laboratory
This course provides an introduction to logic circuit design and analysis. Topics include logic simulation using Multisim and Xilinx tools; combinatorial logic circuit design; TTL SSI integrated circuits to implement simple combinatorial logic circuit designs; latches, flip flops, and clocking; counters; sequential circuit design and a design project.
Fall 2020:
ELEE 5750: Deep LearningELEE 4680/5680: Computer Networks
This course provides an introduction to the design and analysis of computer communication networks. Topics include OSI layered model; application layer protocols; Internet addressing; network interfaces, topologies, architectures, and implementation; local and wide area networks; wireless networks; bridging and routing. The course will consist of a reading/lecture/discussion component and a project component. The class will also include about 5-6 research presentations on various aspects of computer networking performed by the graduate students as a semester-long class project: Specific topics include queuing theory; multiple access protocol, caching techniques; network security, wireless ad-hoc networks, vehicular ad-hoc networks, and cloud computing.
Penn State University:
Guest Lecturer
Fall 2018: EE 560: Probability, random variables & stochastic processes
Spring 2018: EE 561: Information theory
Spring 2014: EE 360: Communication systems
Teaching Assistant
Fall 2018: EE 560: Probability, random variables & stochastic processes
Spring 2014: EE 353: Discrete and continuous signals & systems EE 360: Communication systems