Research Tracks

Here are resources for incoming freshman and those who have a desire/interest to develop the skills needed for research. Below are multiple different tracks that explain what they are and contain the recommended classes to help reinforce those topics.

Internet of Things

The Internet of Things (IoT) in university classes involves using smart devices and interconnected systems to enhance learning. Students develop IoT applications, exploring their potential in fields like engineering, computer science, and healthcare. The curriculum includes practical projects to solve real-world problems, providing hands-on experience and preparing students for tech careers by emphasizing connectivity, data analysis, and smart technology integration.
Recommended Classes:

ECEn 426 (Comp. Networks)
ECEn 427 (Embedded Sys.)
Finish electives from these:
- ECEn 526 (Wireless Networking)
- CS 465 (Comp. Security)
- IT&C 548 (Cyber Phys. Sys.)**

Wireless Networking

Wireless networking in university classes focuses on the principles and applications of wireless communication technologies. Students learn about network design, security, and management, exploring their use in various fields like telecommunications and computer science. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in network engineering and related areas by emphasizing connectivity, data transmission, and wireless infrastructure.
Recommended Classes:

ECEn 426 (Comp. Networks)
ECEn 485 (Digital Comm.)
Finish electives from these:
- ECEn 423 (Comp. Organization)
- ECEn 526 (Wireless Networking
- ECEn 471 (Machine Learning)
- CS 470 (AI)
- CS 465 (Computer Security)

Network Security

Network security in university classes centers on protecting computer networks from cyber threats. Students learn about encryption, firewalls, intrusion detection, and security protocols, exploring their application in various fields like cybersecurity and information technology. The curriculum includes practical projects and labs, offering hands-on experience and preparing students for careers in network security and related areas by emphasizing threat detection, risk management, and data protection strategies.
Recommended Classes:

ECEn 426 (Comp. Networks)
CS 465 (Comp. Security)
Finish electives from these:
- ECEn 423 (Comp. Organization)
- ECEn 427 (Embedded Sys.)
- ECEn 471 (Machine Learning)
- IT&C 567 (Cybersecurity & Penetration Testing)
- IT&C 566 (Digital Forensics)**

High Performance Computing

High-performance computing (HPC) in university classes focuses on using powerful computer systems to solve complex problems. Students learn about parallel computing, algorithms, and system architecture, exploring their applications in fields like science, engineering, and data analysis. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in HPC and related areas by emphasizing computational efficiency, large-scale data processing, and advanced problem-solving techniques.
Recommended Classes:

ECEn 423 (Comp. Organization)
ECEn 426 (Comp. Networks)
Finish electives from these:
- CS 312 (Alg. Design & Analysis)
- CS 462 (Dist. Sys. Design)
- ECEn 528 (HP Parallel C)

Robotics

Robotics in university classes focuses on the design, construction, and programming of robots. Students learn about control systems, artificial intelligence, and sensor integration, exploring their applications in fields like manufacturing, healthcare, and automation. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in robotics and related areas by emphasizing innovation, problem-solving, and the integration of hardware and software.
Recommended Classes:

ECEn 433 (Robotics)
ECEn 483 (Feedback Control)
ECEn 471 (Machine Learning)
ECEn 427 (Embedded Sys.)

Robotic Vision/Self-Driving Cars

Robotic vision and self-driving cars in university classes focus on the technologies enabling autonomous vehicles to perceive and navigate the environment. Students learn about computer vision, sensor fusion, machine learning, and control systems, exploring their applications in the automotive and robotics industries. The curriculum includes hands-on projects and labs, offering practical experience and preparing students for careers in autonomous systems and related areas by emphasizing innovation, real-time data processing, and the integration of perception and decision-making algorithms.
Recommended Classes:

ECEn 471 (Machine Learning)
CS 450 (Computer Vision)**
CS 474 (Deep Learning)
Finish electives from these:
- ECEn 483 (Feedback Controls)
- ECEn 426 (Computer Networks)
- ECEn 427 (Embedded Sys.)
- ECEn 433 (Robotics)
- CS 470 (AI)

Machine Learning/AI

Machine learning and AI in university classes focus on developing algorithms and models that enable computers to learn and make decisions. Students learn about data analysis, neural networks, and natural language processing, exploring their applications in various fields like healthcare, finance, and robotics. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in AI and related areas by emphasizing data-driven problem-solving, model development, and the ethical implications of AI technologies.
Recommended Classes:

CS 470 (AI)
ECEn 471 (Machine Learning)
CS 474 (Deep Learning)
Finish electives from these:
- ECEN 427 (Embedded Systems)
- ECEn 483 (Controls)
- ECEn 424 (Computer Systems)
- ECEn 433 (Robotics)

FPGA Design

FPGA design involves creating and implementing hardware systems using a Field-Programmable Gate Array (FPGA), which is a programmable logic device with reconfigurable gate array circuits. Designers typically use hardware description languages (HDLs) like Verilog or VHDL to model the behavior of the design and simulate it before generating a programming file for the FPGA. Unlike processors, FPGAs process logic on dedicated hardware without an operating system.
Recommended Classes:

ECEn 423 (Comp. Organization)
ECEn 426 (Computer Networking)
ECEn 427 (Embedded Sys.)

ASIC Design

ASIC design is a methodology that aims to reduce the cost and size of an electronic circuit, product, or system by integrating individual components and their functionality into a single element—an Application Specific Integrated Circuit (ASIC). Unlike general-purpose integrated circuits (ICs), which consist of interconnected components, ASICs are custom-designed for specific functions, resulting in smaller size, improved reliability, and cost savings. Modern ASICs often combine analog and digital elements, forming system-on-chip (SoC) designs. Examples of ASIC chips can be found in various sectors, including consumer electronics, medical devices, automotive systems, and industrial applications.
Recommended Classes:

ECEn 423 (Comp. Organization)
ECEn 427 (Embedded Sys.)
ECEn 551 (Intro to Digital VLSI)
Still need one credit

Computer System Reliability

Computer system reliability in university classes focuses on ensuring that computer systems operate consistently and correctly. Students learn about fault tolerance, error detection, and system recovery, exploring their applications in fields like aerospace, finance, and healthcare. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in system reliability and related areas by emphasizing robustness, dependability, and strategies to prevent and mitigate system failures.
Recommended Classes:

ECEn 423 (Comp. Organization)
ECEN 427 (Embedded Sys.)
ECEn 523 (Comp. Sys. Reliability)
MATH 431 (Probability Theory)**

Software Engineering

Software engineering in university classes focuses on the principles and practices of designing, developing, and maintaining software systems. Students learn about programming, software design patterns, testing, and project management, exploring their applications in various industries like technology, finance, and healthcare. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in software development by emphasizing problem-solving, collaboration, and the creation of efficient, reliable software solutions.
Recommended Classes:

ECEn 426 (Comp. Networking)
ECEn 471 (Machine Learning)
Finish electives from these:
- CS 462 (Distributed Systems)
- CS 340 (Software Design)
- CS 316 (Algorithms) 312??**
- CS 329 (Testing)**

Embedded Systems Programming

Embedded systems programming in university classes focuses on developing software for specialized computing systems embedded within devices. Students learn about low-level programming, real-time operating systems, and hardware-software integration, exploring their applications in fields like automotive, consumer electronics, and industrial automation. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in embedded systems by emphasizing efficiency, reliability, and the seamless integration of software with hardware.
Recommended Classes:

ECEn 426 (Comp. Networking)
ECEn 427 (Embedded Sys.)
Finish electives from these:
- CS 345 (OS)
- CS 324 (Systems Programming)**
- Recommend CS minor if “Programming”**

Hardware Acceleration and Computer Chip Design

Hardware acceleration and computer chip design in university classes focus on optimizing hardware to improve computational performance. Students learn about digital logic design, VLSI (Very Large Scale Integration), and FPGA (Field-Programmable Gate Array) programming, exploring their applications in areas like AI, gaming, and data centers. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in hardware engineering by emphasizing speed, efficiency, and the creation of custom hardware solutions tailored to specific tasks.
Recommended Classes:

ECEn 423 (Comp. Organization)
ECEN 427 (Embedded Sys)
Finish electives from these:
- ECEn 471 (Machine Learning)
- CS 474 (Deep Learning)
- ECEn 551 (Intro to Digital VLSI)

Work For Tesla

Working for Tesla involves contributing to cutting-edge innovations in electric vehicles, energy solutions, and autonomous technology. Employees at Tesla engage in roles that span engineering, software development, design, and manufacturing, with a focus on sustainability and pushing the boundaries of technology. The experience is dynamic and fast-paced, offering the opportunity to work on pioneering projects that shape the future of transportation and energy, while emphasizing innovation, collaboration, and a commitment to excellence in a rapidly evolving industry.
Recommended Classes:

ECEn 423 (Comp. Organization)
ECEn 426 (Comp. Networks)
ECEn 427 (Embedded Sys.)
ECEn 446 (Power Electronics)
ECEn 433 (Robotics)
Take a business class
WRTG 316

Optical Engineering

Optical engineering in university classes focuses on the design and application of systems that use light, such as lenses, lasers, and fiber optics. Students learn about optics, photonics, and image processing, exploring their applications in fields like telecommunications, medical devices, and aerospace. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in optical engineering by emphasizing precision, innovation, and the development of advanced optical technologies.
Recommended Classes:

ECEn 462 (Emag Rad. and Prop.)
ECEn 466 (Intro to Optical Eng.)
ECEn 4XX/5XX (4 credit class)
Finish electives from these:
- PHSCS 451 (Quantum Mech.)**
- PHSCS 452 (Apps of Quantum Mech.)**
- PHSCS 471 (Optics)**
- ECEn 562 (Silicon Photonics)

Electric Vehicles

Electric vehicles in university classes focus on the design, development, and technology behind battery-powered transportation. Students learn about electric drivetrains, battery management systems, and sustainable energy integration, exploring their applications in the automotive industry and beyond. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in electric vehicle engineering by emphasizing innovation, sustainability, and the future of clean transportation.
Recommended Classes:

ECEn 446 (Power Electronics)
ECEn 483 (Feedback Control)
Finish electives from these:
- ECEn 433 (Robotics)
- ECEn 445 (Mixed Sig. VLSI)
- ECEn 427 (Embedded Sys.)
- ECEn 487 (DSP)

Renewable Energy

Renewable energy in university classes focuses on the development and implementation of sustainable energy sources like solar, wind, and hydroelectric power. Students learn about energy conversion, storage systems, and grid integration, exploring their applications in reducing carbon emissions and combating climate change. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in renewable energy by emphasizing sustainability, innovation, and the transition to cleaner energy solutions.
Recommended Classes:

ECEn 446 (Power Electronics)
Finish electives from these:
- ECEn 445 (Mixed Sig. VLSI)
- ECEn 483 (Feedback Control)
- ECEn 426 (Comp. Networks)
- ECEn 427 (Embedded Sys.)

Secure and/or Digital Communications

Secure and digital communications in university classes focus on the principles and technologies that protect and transmit information over digital networks. Students learn about encryption, cryptography, network security, and communication protocols, exploring their applications in areas like cybersecurity, telecommunications, and finance. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in secure communications by emphasizing data protection, privacy, and the development of robust communication systems.
Recommended Classes:

ECEn 485 (Digital Comm.)
ECEn 487 (DSP)
Finish electives from these:
- MATH 341 (Real Analysis)
- MATH 352 (Complex Analysis)
- MATH 355 (Graph Theory)
- MATH 371 (Abstract Algebra)
- MATH 487 (Number Theory)
- IT&C 585 (Encryption Implementation)**
- MATH 431 (Probability Theory)**
- MATH 485 (Cryptography)**

Biomedical Engineering

Biomedical engineering in university classes focuses on applying engineering principles to healthcare and medical technologies. Students learn about medical device design, biomaterials, and tissue engineering, exploring their applications in areas like diagnostics, prosthetics, and rehabilitation. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in biomedical engineering by emphasizing innovation, patient care, and the development of cutting-edge medical solutions.
Recommended Classes:

ECEn 462 (Emag Rad and Prop)
ECEn 487 (DSP)
ECEn 471 (Machine Learning)
ECEn 521 (Algorithm Design)
Need 3 more credits

Aerial Robotics

Aerial robotics in university classes focuses on the design and operation of drones and other flying robots. Students learn about aerodynamics, control systems, and autonomous navigation, exploring their applications in fields like agriculture, surveillance, and disaster response. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in aerial robotics by emphasizing innovation, real-time problem-solving, and the integration of hardware and software for flight control and automation.
Recommended Classes:

ECEn 483 (Feedback Control)
ECEn 534 (Flight Dynamics & Cont.)
Finish electives from these:
- ECEn 471 (Machine Learning)
- ECEn 433 (Robotics)
- ME 415 (Flight Vehicle Design)**
- ME 515 (Aerodynamics)**
- ME 537 (Robotics manipulators)**
- ME 575 (Optimization)**
- CS 240 (Adv Programming)
- CS 412 (Lin. Prog. & Convex Optim.)**
- CS 470 (AI)
- MATH 341/342 (Analysis)

Quantum Engineering

Quantum engineering in university classes focuses on harnessing the principles of quantum mechanics to develop advanced technologies. Students learn about quantum computing, quantum communication, and quantum sensing, exploring their applications in fields like cryptography, material science, and complex problem-solving. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in quantum engineering by emphasizing cutting-edge research, technological innovation, and the development of next-generation quantum systems.
Recommended Classes:

ECEn 450 (Intro to Semicond. Devices)
ECEn 452 (Experiments in IC Dev.)
ECEn 462 (Emag Rad & Prop.)
ECEn 562 (Integrated Photonics)
Finish electives from these:
- ECEn 471 (Machine Learning)
- CS 470 (Intro to AI)
- CS 474 (Intro to Deep Learning)
- Math 411 (Numerical Methods)
- PHSCS 451 (Quantum I) **
- PHSCS 452 (Quantum II) **
- Math 485 (Mathematical Cryptography) **

Wireless Communications

Wireless communications in university classes focuses on the technologies and principles behind transmitting information without physical connections. Students learn about radio frequency (RF) engineering, signal processing, and network protocols, exploring their applications in mobile networks, satellite communications, and IoT systems. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in wireless communications by emphasizing innovation, signal clarity, and the development of efficient communication networks.
Recommended Classes:

ECEn 462 (Emag Rad & Prop)
ECEn 464 (Wireless Comm. Circuits)
Take at least one of these:
- ECEn 423 (Comp. Organization)
- ECEn 426 (Comp. Networking)
- ECEn 427 (Embedded Sys.)
Take at least one of these:
- ECEn 485 (Digital Comm.)
- ECEn 487 (DSP)

Array Signal Processing

Array signal processing in university classes focuses on techniques for analyzing and interpreting signals received from multiple sensors or antennas. Students learn about array configurations, beamforming, and spatial filtering, exploring their applications in fields like radar, communications, and audio processing. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in signal processing by emphasizing signal enhancement, spatial resolution, and advanced data analysis techniques.
Recommended Classes:

ECEn 487 (DSP)
Finish electives from these:
- ECEn 462 (Emag Rad & Prop)
- ECEn 485 (Digital Comm.)
- ECEn 426 (Comp. Networking)
- ECEn 427 (Embedded Sys.)
- MATH 355 (Graph Theory)
- CS 462 (Large scale distributed system design)
- CS 474 (Deep learning)
- MATH 431 (Probability Theory)**

Circuits

Circuits in university classes focus on the design and analysis of electrical circuits and systems. Students learn about circuit components, network analysis, and electronic devices, exploring their applications in various fields like consumer electronics, telecommunications, and power systems. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in circuit design and engineering by emphasizing problem-solving, innovation, and the creation of efficient and reliable electronic systems.
Recommended Classes:

ECEn 445 (Intro to Mixed Sig. VLSI)
ECEn 446 (Power Electronics)
ECEn 450 (Intro to Semiconductor Dev.)
ECEn 464 (Wireless Comm. Circuits)
ECEn 551 (Intro to Dig. VLSI Circuits)

3D Printing and Microfluidics

3D printing and microfluids in university classes focus on additive manufacturing techniques and the manipulation of tiny fluid volumes. Students learn about 3D printing technologies, material properties, and microfluidic design, exploring their applications in areas like prototyping, medical devices, and chemical analysis. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in these fields by emphasizing precision, innovation, and the integration of printing and fluid manipulation technologies.
Recommended Classes:

ECEn 462 (Emag Rad & Prop)
ECEn 466 (Optical Eng.)
Finish electives from these:
- ECEn 427 (Embedded Sys.)
- ECEn 567 (Physical Optics)
- ECEn 471 (Machine Learning)
- CS 450 (Computer Vision)**
- CS 474 (Intro to Deep Learning)
- ChEn 374 (Fluid Mechanics)**
- MeEn 312 (Fluid Mechanics)**
- MeEn 330 (Mechatronics)**
- PHSCS 471 (Optics)**
- MfgEn 572 (Design for Additive Manufacturing)**

Materials

Materials science in university classes focuses on the properties and applications of various materials, including metals, polymers, ceramics, and composites. Students learn about material behavior, processing techniques, and performance evaluation, exploring their applications in industries like aerospace, automotive, and electronics. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in materials engineering by emphasizing material selection, innovation, and the development of new materials for diverse applications.
Recommended Classes:

ECEn 450 (Intro to Semicond. Dev.)
5 more credits of EE electives
Finish electives from these (none on approved list at this point): **
- ChEn 376 (Heat and Mass Transfer)
- MeEn 250 (Science of Engineering Materials)
- MeEn 450 (Engineering Materials)
- MeEn 456 (Composite Material Design)
- Chem 285 (Intro bio-organic Chemistry)
- Chem 351/352 (Organic Chemistry)
- PHSCS 451/452 (Quantum Mechanics)
- MfgEn 355 (Plastics)
- MfgEn 456 (Composites)

Optoelectronics

Optoelectronics in university classes focuses on the integration of optical and electronic systems. Students learn about devices that convert electrical signals into optical signals and vice versa, such as LEDs, lasers, and photodetectors, exploring their applications in telecommunications, imaging, and sensing. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in optoelectronics by emphasizing device performance, optical signal processing, and the development of advanced optical-electronic systems.[brief description]
Recommended Classes:

ECEn 450 (Intro to Semicond. Dev.)
ECEn 452 (IC lab)
ECEn 462 (Emag Rad & Prop)
ECEn 466 (Optical Eng.)
ECEn 555 (Optoelectronic Devices)
Finish electives from these:
- ECEn 562 (Integrated Photonics)
- PHSCS 451 (Quantum I)**

Semiconductors

Semiconductors in university classes focus on the materials and technologies used to control electrical conductivity in electronic devices. Students learn about semiconductor physics, fabrication processes, and device applications, exploring their roles in transistors, diodes, and integrated circuits. The curriculum includes hands-on projects and labs, providing practical experience and preparing students for careers in semiconductor engineering by emphasizing material properties, circuit design, and the development of cutting-edge electronic components.
Recommended Classes:

ECEn 450 (Intro to Semicond. Dev.)
ECEn 452 (IC lab)
Finish electives from these:
- STAT 240 **
- STAT 340 **
- STAT420 **
- STAT421 **
- CHEM 467 **
- PHSCS 451 (Quantum I) **
- ECEn555
- ECEn550

Contact an Advisor