Students seeking a hands-on, leading-edge summer research experience are invited to apply to the Armour R&D Summer Research Immersion Program in the global city of Chicago. This unique, competitive program offers students from throughout the country the opportunity to receive engineering course credit for participating in one of a diverse range of engineering research projects with Illinois Tech faculty mentors across all engineering disciplines.
As an Armour R&D Summer Research Immersion Program participant, you’ll attend seminars featuring cutting-edge research from a range of engineering specialties. You’ll learn how to communicate research results in a professional setting, and you will present your research findings to engineering professors and industry representatives from Chicago-area companies at a culminating expo.
In this exciting program, you will spend 20 hours per week conducting research for eight weeks. Students selected to participate will earn three engineering credits upon successful completion of the research program. This program is offered at the standard tuition rates per credit. Students should consult with their faculty advisers to determine if course credits received will apply to their degree programs.
Current Illinois Tech students should contact the instructors to request acceptance into a research section. Students who are not enrolled at the university should email engineering@iit.edu for more information about the registration process.
We recommend you apply by April 15, but applications will be accepted on a rolling basis until sections are full.
Summer 2022 Research Opportunities
ENGR 498-1 Advanced Automotive Projects
Faculty: Francisco Ruiz
Description: This section looks at two main projects: The maglev car, with magnetic levitation replacing the wheels, which will be entering the prototype phase, and the adaptive cycle engine, which will also be entering the prototype phase, starting from a MultiAir engine. Both projects involve computer analysis and the design and fabrication of new parts.
ENGR 498-2 Electric Motors for Electric Vehicles
Faculty: Mahesh Krishnamurthy
Description: Supply chain logistics had become something we took for granted for decades...until 2019. We now know that it is critical for us to reduce our reliance on imported materials, including permanent magnets and copper. This course will explore the design of high-performance, rare-earth material-free electric machines for electric vehicles. A background in Finite Element Analysis (FEA) and power electronics, while not required, would elevate the scope and impact of the project.
ENGR 498-3 Fast Charging in Electric Vehicles
Faculty: Mahesh Krishnamurthy
Description: With a national goal to have at least 50 percent of all cars be electric vehicles, one of the bottlenecks we are still trying to overcome is in the “filling the tank” experience. Most of us would not want to wait for eight hours to continue our trip. This means that fast charging and “extreme fast charging” present a critical opportunity for engineering innovation. This research will explore the role of power electronic control and thermal management for battery packs in electric vehicles. Converter topologies and finite element models will be developed for lithium-ion batteries in EV applications.
ENGR 498-4 Entrepreneurial Innovations in Assistive Technology
Faculty: Mahesh Krishnamurthy
Description: There is a huge opportunity to explore human-centric designs with an entrepreneurial mindset to have a truly global impact. Over the last decade, there have been some revolutionary advancements in most areas, but the development of engineering solutions for people with disabilities has been lagging. Ask yourself—is there something you could design that could improve someone's quality of life? Do you have an idea you have wanted to design, build, and test? This could be in the form of an app, sensor-based solution, or mobility hardware. Students with an interest in using their technology background towards exploring human-centric designs and entrepreneurial initiatives are encouraged.
ENGR 498-6 Research in Internet of Things and Machine Vision System Design
Faculty: Jafar Saniie
Description: Join the research team at Embedded Computing and Signal Processing (ECASP) Research Laboratory and have the opportunity to employ a combination of signal and image processing design tools such as Matlab and OpenCV. Students will be organized into groups to propose solutions to various Internet of Things problems; projects will include machine vision, artificial intelligence, robotics, drone navigation, software-defined radio, wireless health monitoring systems, and audio signal processing using field-programmable gate arrays, Raspberry Pi, and Arduino-embedded computing systems.
ENGR 498-7 Research in Artificial Intelligence and Deep Learning
Faculty: Jafar Saniie
Description: For this course, students join the research team at Embedded Computing and Signal Processing (ECASP) Research Laboratory to employ a combination of signal and image processing design tools such as Matlab, TensorFlow, Python, and OpenCV. Students will be organized into groups to propose solutions to various artificial intelligence and deep learning problems. Students’ projects will include machine vision, robotics, drone navigation, and wireless health monitoring systems using smartphones.
ENGR 498-8 Fluorescence-guided Surgical Microscope for Cancer Resection
Faculty: Ken Tichauer
Description: Students will work as a team to design and develop a multi-channel fluorescence optical imaging system optimized for identifying fluorescently labeled cancerous tissue in a surgical field. Students will be exposed to modern aspects of molecular imaging in cancer, including an introduction to technological advancements in system development, image reconstruction, and data analysis.
ENGR 498-11 Building Information Modeling (BIM) in Design, Construction, and Operation
Faculty: Julide Bozoglu
Description: This research provides a faculty-mentored immersive research experience as a part of a student team. Building Information Modeling (BIM) is a digital representation of the physical and functional characteristics of a facility. As such it serves as a shared knowledge resource for information about a facility forming a reliable basis for decisions during its life cycle from inception onward. It is clear that BIM is the trend of the future, with increased use documented in the construction industry in the last few years. To sustain the momentum of BIM, effective workforce development that aims to balance the supply-demand equation in the labor market is essential. This opportunity consists of an experiential approach adopted to BIM-enabled learning to investigate collaboration with BIMs. Around many uses of BIM, the researchers select their primary roles, creating a BIM team and exploring the interoperability of selected tools to operate their tasks. In this creative and collaborative process, the researchers gain some skills for BIM capabilities of the integrated design project by using various opportunity materials and software licenses provided for their use in a limited time frame. This methodology allows the researchers to experience the integrated design process in a realistic way and helps them to learn how different tools and methods integrate with each other. The objective of this study is to educate the engineers/architects of the future who will be actively using BIM routinely.
ENGR 498-12 Building Energy Modeling (BEM) in Design and Construction
Faculty: Julide Bozoglu
Description: The energy issue plays an important role in the design and operation of buildings where careful long-term decisions can significantly improve the performance of buildings and thus reduce their consumption of energy. Building Energy Modeling (BEM) is a process in the design phase in which one or more building energy simulation programs use properly adjusted Building Information Models (BIMs) to conduct energy assessments for the current building design. The core goal of BEM is to inspect building energy standard compatibility and seek opportunities to optimize the proposed design to reduce the structure's life cycle costs through saving time and costs by obtaining building and system information automatically from the BIM model instead of inputting data manually, improving building energy prediction accuracy by auto-determining building information such as geometries and volumes precisely from the BIM model, helping with building energy code verification, and optimizing building design for better building performance efficiency and reduce building life-cycle cost. This project presents an experiential approach adopted to BIM-enabled learning to investigate building performance with BIMs. This methodology allows students to experience a BIM learning module, namely the performance and optimization module, and helps them learn how BEM tools and Building Performance Analysis (BPA) methods integrate with each other. The objective of this project is to educate future engineers/architects who will be actively using BIMs in BPA routinely. The main research topics will include building services engineering, sustainable and advanced building materials, energy-efficient design, high-performance-based design, and building codes and social studies. This opportunity consists of an experiential approach to investigate building energy models and use building performance analysis tools and software. This research creates a professional interface between architects and engineers, to prepare the researchers to be capable of acting as interpreters in the complicated and fragmented world of construction. This skill is highly appreciated by industry leaders.
ENGR 498-25 Design with Sensors, FPGA, and Smart Phone
Faculty: Jafar Saniie
Description: Students join the research team at Embedded Computing and Signal Processing (ECASP) Research Laboratory where they will have the opportunity to learn different digital hardware and software design platforms. Students will propose solutions to various design problems including robotics and machine vision, working with computer network laboratory tools, sensor data collection and data management, audio filter design on field-programmable gate arrays, system-on-chip design using Zynq FPGA from Xilinx and ARM platform, body sensor networks, Internet of Things, design for the collection of data from different sensors through a smartphone, and the transmission of data to an online database.
ENGR 498-9 Uncovering the Building Blocks of Turbulence
Faculty: Scott Dawson
Description: This project will focus on studying the properties of turbulence in fluid flows. In particular students will implement algorithms to identify and predict statistical structures in canonical turbulent flows. Students will learn to run computational fluid dynamics codes and apply various data analysis methods. A background and interest in fluid mechanics, mathematics, and programming is desirable.
ENGR 498-17 Wearable Devices
Faculty: Abhinav Bhushan
Description: Did you know that a large number of engineers are hired by medical device companies? Health care remains the fastest-growing sector in the United States. The goal of this class will be to learn about and develop wearable devices. An independent project will be the primary goal of the class, where the student will ideate and design a device. Students will be expected to take the design into workable prototypes.
ENGR 498-18 Microfluidics
Faculty: Abhinav Bhushan
Description: The goal of this class is to learn about microfluidics—both design and fabrication. The goal will be to generate advanced microfluidic devices: first by using computer-aided design (CAD) and then by using additive manufacturing for different applications. Students will learn CAD, design, and fabrication techniques such as additive manufacturing and lithography.
ENGR 498-21 Modeling Unsteady Aerodynamic Systems
Faculty: Scott Dawson
Description: This project will study the behavior of unsteady aerodynamic systems, such as wings and fins that can pitch and flap, that might encounter strong gusts and currents. To understand and model these systems, students will combine aspects of classical theory with numerical simulations and experimental data.
ENGR 499-9 Cell-free Protein Synthesis
Faculty: Seok Hoon Hong
Description: Compared to cell-based protein production, cell-free protein synthesis (CFPS) provide engineering flexibility to maximize target protein production yield. Utilizing CFPS platforms, toxic proteins or unnatural proteins can be synthesized without cell-viability concerns. In this project, the optimization of CFPS will be studied to produce novel functional proteins.
ENGR 499-10 Controlling Antibiotic Tolerant Pathogens
Faculty: Seok Hoon Hong
Description: The occurrence of multi-drug resistant bacteria has been a serious threat in our society. Bacteria can survive under conventional antibiotics treatment by developing survival strategies. This project investigates antimicrobial chemicals to see whether the chemicals can be developed as antibiotic alternatives.
ENGR 498-16 Synthetic biology
Faculty: Abhinav Bhushan
Description: The goal of this project-oriented class will be to learn about synthetic biology principles for applications in food and health. Students will learn about cutting-edge biotechnology aspects such as CRISPR and implement them in their work, first as design and then, time permitting, as experiments.
ENGR 499-12 Structural Fatigue Failure Prediction; A Systematic Review
Faculty: Mehdi Modares
Description: Structural systems are susceptible to fracture under cyclic loading; this is known as fatigue failure. In this course, modern design codes, state-of-the-art research, and industry best practices will be used to investigate fatigue failure in structures. This section proposes a research study on the state of the art and shortcomings of predictive models for structural fatigue. The areas identified for investigation include understanding the basic fatigue phenomenon, investigating fatigue models for common structural engineering materials, investigating the techniques used for fatigue life prediction both historically and in current practice, and proposing improvements to current practice.
ENGR 598-1 Research in Artificial Intelligence for Computer Vision
Faculty: Jafar Saniie
Description: Students will have the opportunity to research neural networks and deep learning concepts for machine vision, robotic automation, drone navigation, autonomous vehicles, factory automation, and home/office security. Students will employ software and hardware design tools including Matlab, TensorFlow, Python, OpenCV, FPGA, Raspberry Pi, and smartphones in their design projects. For additional information visit the Embedded Computing and Signal Processing (ECASP) Research Laboratory website.
ENGR 598-2 Electric Machine Design for EVs
Faculty: Mahesh Krishnamurthy
Description: This course will explore the design of high-performance, rare-earth material-free electric machines for electric vehicles. Commercially available software such as Ansys and MagNet will be used to compare machine designs with commercially available motors (such as Prius or Sonata motors) to understand the impact of design and manufacturing variations on the overall performance of the machine.
ENGR 598-3 Fast Charging of Li-ion Batteries
Faculty: Mahesh Krishnamurthy
Description: This research will explore the role of power electronic converters to ensure the safe operation of fast-charged battery packs for electric vehicles. Converter topologies and finite element simulations will be developed for integrating an energy storage system into the grid.
ENGR 598-8 Design with Sensors, FPGA, and Smartphone
Faculty: Jafar Saniie
Description: Students join the research team at Embedded Computing and Signal Processing (ECASP) Research Laboratory to learn different digital hardware and software design platforms. Students will be organized into groups to propose solutions to various design problems including robotics and machine vision, working with computer network laboratory tools, sensor data collection and data management, audio filter design on field-programmable gate arrays (FPGA), system-on-chip design using Zynq FPGA from Xilinx and ARM platform, body sensor networks, Internet of Things, design for the collection of data from different sensors through a smartphone, and the transmission of data to an online database.
ENGR 598-24 Millimeter-wave Technology for Wireless Networking, Sensing, and Applications
Faculty: Jafar Saniie
Description: Students will learn topics in artificial intelligence, and deep learning using hardware-software co-design by joining the research team at the Embedded Computing and Signal Processing (ECASP) Research Laboratory. to This course focuses on practical applications in computer vision and deep learning utilizing Xilinx PYNQ (Python productivity for ZYNQ) Development Board. Students will work on top of Xilinx’s Python ecosystem and Jupyter notebooks environment.
ENGR 598-25 Research in Digital Signal Processing and Embedded Computing
Faculty: Jafar Saniie
Description: Students in this course join the research team at the Embedded Computing and Signal Processing (ECASP) Research Laboratory where they will have the opportunity to learn topics in artificial intelligence and deep learning for ultrasonic imaging with both medical and industrial applications. This course focuses on practical applications in deep learning utilizing PYNQ (Python productivity for ZYNQ) and Jetson Nano Development Boards. Students will work on top of Python and Jupyter notebooks environment.
ENGR 598-26 BIM (Building Information Modeling) in Design, Construction and Operation
Faculty: Julide Bozoglu
Description: This research provides a faculty-mentored immersive research experience as a part of a student team. Research topics are determined by the instructor in the area of research, which is Building Information Modeling (BIM) in this case. The objective of this study is to educate the engineers/architects of the future who will be actively using BIM routinely.
ENGR 598-27 Building Energy Modeling (BEM) in Design and Construction
Faculty: Julide Bozoglu
Description: The objective of this study is to educate future engineers/architects who will be actively using Building Information Models (BIM) in Building Performance Analysis (BPA) routinely. The main research topics will include building services engineering, sustainable and advanced building materials, energy-efficient design, high-performance-based design, and building codes and social studies. This opportunity consists of an experiential approach to investigate building energy models and use building performance analysis tools and software.
ENGR 598-9 Uncovering the Building Blocks of Turbulence
Faculty: Scott Dawson
Description: This project will focus on studying the properties of turbulence in fluid flows. In particular, students will implement algorithms to identify and predict statistical structures in canonical turbulent flows. Students will learn to run computational fluid dynamics codes and apply various data analysis methods. A background and interest in fluid mechanics, mathematics, and programming is desirable.
ENGR 598-17 Wearable devices
Faculty: Abhinav Bhushan
Description: Did you know that a large number of engineers are hired by medical device companies? Healthcare remains the fastest-growing sector in the United States. The goal of this class will be to learn about and develop wearable devices. An independent project will be the primary goal of the class where the student will ideate and design the device. Students will be expected to take the design into workable prototypes.
ENGR 598-18 Microfluidics
Faculty: Abhinav Bhushan
Description: The goal of this class is to learn about microfluidics—both design and fabrication. Students will generate advanced microfluidic devices first using computer-aided design (CAD) and then using additive manufacturing for different applications. Students will learn CAD, design, and fabrication techniques such as additive manufacturing and lithography.
ENGR 598-21 Modeling Unsteady Aerodynamic Systems
Faculty: Scott Dawson
Description: This project will study the behavior of unsteady aerodynamic systems, such as wings and fins that can pitch and flap, which might encounter strong gusts and currents. To understand and model these systems, we will combine aspects of classical theory with numerical simulations and experimental data.
ENGR 598-16 Synthetic Biology
Faculty: Abhinav Bhushan
Description: The goal of this project-oriented class will be to learn about synthetic biology principles for applications in food and health. Students will learn about cutting-edge biotechnology aspects such as CRISPR and implement them in their work, first as design and then, time permitting, as experiments.
ENGR 198-25 Research in Internet of Things and Machine Vision System Design
Faculty: Jafar Saniie
Description: join the research team at Embedded Computing and Signal Processing (ECASP) Research Laboratory and have the opportunity to employ a combination of signal and image processing design tools such as Matlab and OpenCV. Students will be organized into groups to propose solutions to various Internet of Things problems. Students’ projects will include machine vision, artificial intelligence, robotics, drone navigation, software-defined radio, wireless health monitoring systems, and audio signal processing using field-programmable gate arrays, Raspberry Pi, and Arduino Embedded Computing Systems.
