Category: Graduate Students

From Nanoscale Research to Real-World Impact: Celebrating Dr. Parinaz Eskandari

Dr. Parinaz Eskandari successfully defended her PhD dissertation, “Design, Modeling and Experimental Development of Nanoscale Confinement Structures on Planar Silicon-based Microelectrode Arrays for Single Entity Electrochemical Sensing,” this past April. 

It’s been just a few months since Dr. Parinaz Eskandari graduated with her PhD in Electrical Engineering.

During her time at Michigan Tech, Eskandari tirelessly explored semiconductor devices alongside her advisor, Dr. Paul Bergstrom. She worked on the development of silicon-based platforms for sensitive and reliable detection of biological analytes. In particular, she focused on nanoscale surface engineering, achieving targeted improvements in electrochemical device performance and sensing capabilities.

This research breakthrough did not happen overnight. Over a period of roughly 3 years, Eskandari spent several thousand hours in the lab fabricating and characterizing semiconductor structures. Her intensive workload spanned the entire development process—combining cleanroom microfabrication techniques with electrical and electrochemical analysis, and bridging the gap from initial device design and modeling to testing, data analysis, and interpretation.

Beyond the complex engineering milestones, time in the lab taught Eskandari a deeper set of truths. She took some time out to share what she has learned.

Q: Please describe your path toward your PhD. What twists and turns did it take, and what have you learned from your varied experiences?

A: My path to a PhD was not a straight line. There were unexpected challenges, changes in research direction, and moments of uncertainty that forced me to adapt. Moving to a new country and pursuing advanced research while balancing teaching responsibilities required resilience and flexibility. Looking back, I realize that growth often happens in those difficult moments when things do not go according to plan. I learned that perseverance is not simply about working harder; it is about remaining open to learning, adjusting your approach, and continuing to move forward even when the destination seems unclear.

Q: Do you have any thoughts on patience, motivation, drive, and/or singular focus that you’d like to share?

A: I have learned that patience and persistence are just as important as intelligence. Research rarely provides immediate answers. Experiments fail, manuscripts require revisions, and progress can be slow. Motivation comes and goes, but commitment is what carries you through difficult periods. Rather than waiting to feel inspired every day, I believe in consistently taking small steps forward. Over time, those small efforts accumulate into meaningful accomplishments.

Q: What is your approach to teaching students in the lab?

A: I try to create a learning environment where students feel comfortable asking questions and making mistakes. Laboratories can be intimidating, especially when students are using sophisticated equipment for the first time. I emphasize hands-on learning, encourage curiosity, and guide students through the reasoning behind each procedure instead of simply asking them to follow instructions. My goal is to help students develop confidence and independence as problem-solvers.

Q: What are the most important things you seek to teach?

A: Beyond technical knowledge, I hope to teach students how to think critically, troubleshoot systematically, and communicate effectively. I want them to understand that science and engineering are not about memorizing answers; they are about asking good questions and learning how to approach unfamiliar problems. Integrity, attention to detail, and persistence are qualities that I believe are just as valuable as technical skills.

Q: What do you enjoy most about interacting with students?

A: One of the most rewarding parts of teaching is witnessing the moment when something finally clicks for a student. I enjoy helping students recognize their own potential and gain confidence in abilities they may have doubted. Students often bring fresh perspectives and thoughtful questions that challenge me to think differently as well. Teaching is a two-way learning experience, and I value that exchange greatly.

Q: Any specific career goals now that you have earned your PhD?

A: Looking ahead, I hope to build a career that brings together my interests in semiconductors, photonics, and optoelectronic systems. I am particularly drawn to the process of transforming research concepts into reliable, real-world technologies through product development, testing, and validation. I enjoy the collaborative nature of this work, partnering with multidisciplinary teams to solve complex problems, improve performance, and ensure that innovative ideas can successfully transition from the laboratory to practical applications. Whether contributing to sensing technologies, integrated photonic systems, or next-generation optical devices, I am excited by opportunities to help develop technologies that make a meaningful impact.

Q: If you could create any business/invention, what would it be?

A: If I could create any invention, it would be one that genuinely makes people’s lives easier and improves their quality of life. I am inspired by technologies that solve real-world problems and have a meaningful impact on society. Whether through accessible diagnostic tools, smarter sensing systems, or other innovations that simplify daily challenges, I would want to develop solutions that are practical, affordable, and widely available. To me, the most rewarding aspect of engineering is knowing that something you helped create has the potential to positively affect people’s lives and, in some small way, make the world a better place.

Q: What’s the best advice you can give/have been given?

A: One piece of advice that has stayed with me is: “Do not compare your journey to someone else’s timeline.” Everyone’s path is different. Success is rarely linear, and setbacks do not define your future. Focus on continuous growth, stay true to your values, and trust that persistence will eventually open doors you cannot yet see.

Q: Anything else you’d like to add?

A: I would like to express my sincere gratitude to the mentors, friends, and students who have been part of my journey at Michigan Tech. I am deeply thankful to my advisor, Dr. Paul Bergstrom, for his guidance, encouragement, and support throughout my PhD. During challenging moments, he reminded me not to give up and taught me the importance of resilience and perseverance in both research and life. Those lessons have shaped not only the scientist and educator I have become, but also the person I aspire to be. I am proud of what I have accomplished and excited for the opportunities and challenges that lie ahead.

Course Recommendations for ECE Graduate Students – Fall 2026 

This post outlines the requirements and structures for three primary graduate programs in the ECE Department during the 2026-2027 academic year:

  1. Master of Science in Robotics Engineering (MS ERE)
  2. Master of Science in Electrical and Computer Engineering (MS EECE)
  3. PhD in Electrical and Computer Engineering (PhD ECE)

Program Comparison Summary

Feature MS Robotics (MS ERE) MS ECE (MS EECE) PhD ECE (with MS) PhD ECE (Direct/no MS)
Total Credits 30 30 30 60
EE Course Credits MIN Coursework – 15
Report – 12
Thesis – 10
Coursework – 15
Report – 12
Thesis – 10
9-12 21
3000-level Courses Not permitted  Not permitted  Not permitted  Not permitted 
4000-level MAX Coursework – 12
Report – 12
Thesis – 10
Coursework – 12
Report – 12
Thesis – 10
0-3 6-8
Max Co-op Credits 3 credits (UN 5000-5003) 3 credits (UN 5000-5003) 3 credits (UN 5000-5003) 3 credits (UN 5000-5003)
RCR Requirement 1-3 credits (Report/Thesis) 1-3 credits (Report/Thesis) 1-3 credits 1-3 credits
Typical Duration 1.5 – 2 Years 1.5 – 2 Years 3 – 5 Years 4 – 6 Years

Academic Flexibility & Course Load

Unlike undergraduate degree programs, graduate degrees are more flexible, allowing students to tailor their plan of study to their specific goals and interests. A Master of Science student may select courses of their choosing, provided they conform to the degree requirements. The standard course load for a graduate student is nine (9) credits per semester. Please contact the ECE Graduate Program Director to schedule an advising session.

Online Course Registration Guidelines

Specific regulations govern online enrollment for on-campus graduate students:

  • Dual-Delivery Courses (+OL): Online sections of courses offered concurrently with on-campus sections are unavailable to on-campus students.
  • CPT Exception: On-campus students participating in Curricular Practical Training (CPT) are permitted to enroll in these online course sections.
  • Exclusively Online Courses: Graduate courses that are offered only in an online format (without an equivalent on-campus section) are open to on-campus students.

Fall 2026 Graduate Course Recommendations & Class Descriptions 

To assist with academic planning and elective registration, the active graduate-level courses offered in Fall 2026 are listed below. Courses covering multi-disciplinary domains are cross-listed in all applicable technical areas. The indicator (+OL) identifies courses that offer online enrollment options.

1. Power & Energy

Focus: Power transmission, conversion, machines, and smart-grid integration.

  • EE 4221 – Power System Analysis 1 (+OL) Covers power transmission line parameters and applications, symmetrical components, transformer and load representations, system faults and protection, and the per-unit system.
  • EE 4227 – Power Electronics (+OL) Fundamentals of circuits for electrical energy processing. Covers switching converter principles for dc-dc, ac-dc, and dc-ac power conversion. Other topics include harmonics, pulse-width modulation, feedback control, magnetic components, and power semiconductors.
  • EE 5200 – Advanced Methods in Power Systems (+OL) Advanced analysis and simulation methods for load flow, symmetrical components, short-circuit studies, optimal system operation, stability, and transient analysis. Application of commonly used software reinforces concepts and provides practical insights.
  • EE 5230 – Power System Operations (+OL) Study of advanced engineering and economic algorithms and analysis techniques for the planning, operation, and control of the electric power system from generation through transmission to distribution.
  • EE 5900 – Modern Power System Dynamics (+OL) Focuses on the dynamic behavior, stability analysis, modeling, and transient control of modern interconnected electrical networks.
  • EE 5900 – High Voltage Engineering (+OL) Examines insulation engineering, breakdown mechanisms in solids, liquids, and gases, overvoltages, testing methods, and high-voltage safety procedures.

2. Signals & Systems

Focus: Processing, analysis, systems modeling, and communications engineering.

  • EE 4252 – Digital SP and Applications Digital signal processing techniques with emphasis on applications. Includes sampling, the Z-transform, digital filters, and discrete Fourier transforms. Emphasizes techniques for design and analysis of digital filters. Special topics may include the FFT, windowing techniques, quantization effects, physical limitations, image processing basics, image enhancement, image restoration, and image coding.
  • EE 5500 – Prob & Stoch Processes (+OL) Theory of probability, random variables, and stochastic processes, with applications in electrical and computer engineering. Probability measure and probability spaces. Random variables, distributions, expectations. Random vectors and sequences. Stochastic processes, including Gaussian and Poisson processes. Stochastic processes in linear systems. Markov chains and related topics.
  • EE 5715 – Linear Systems Theory & Design (+OL) Overview of linear algebra, Modern Control: state-space based design of linear systems, observability, controllability, pole placement, observer design, stability theory of linear time-varying systems, Lyapunov stability, optimal control, Linear Quadratic regulator, Kalman filter, Introduction to robust control.
  • ME 4775 – Control Sys Analysis & Design (+OL) This course covers topics of control systems design. Course includes a review for modeling of dynamical systems, stability, and root locus design. Also covers control systems design in the frequency domain, fundamentals of digital control and nonlinear systems.
  • ME 5670 – Experimental Design in Engg (+OL) Review of basic statistical concepts. Models for testing significance of one or many factors. Reducing experimental effort by incomplete blocks and Latin squares. Factorial and fractional factorial designs. Response surface analysis for optimal response.

3. ElectroPhysics

Focus: Physical systems, devices, electromagnetic fields, and semiconductor material processing.

  • EE 4490 – Laser Systems and Applications Survey of laser types and analysis of common physical and engineering principles, including energy states, inversion, gain, and broadening mechanisms, from a quantum-mechanical perspective. Laser applications and laser properties are explored in the laboratory portion.
  • EE 5330 – Chip Fabrication This course provides an advanced introduction to the science and engineering involved in semiconductor device fabrication associated with microelectronic chips through lecture and laboratory exercises.

4. Computer Engineering

Focus: Processing hardware, algorithms, networking, and automotive computer systems.

  • EE 4173 – Comp Sys Engineering & Perform Covers the principles and practices of modern computer architecture. Emphasizes quantitative performance evaluation of: memory hierarchies, from cache through virtual memory; pipelined processors with advanced hazard management; and combined processor/memory systems. Introduces RAID, superscalars, parallel processing, cache coherence, and performance simulation software.
  • EE 4271 – VLSI Design Design of VLSI circuits using CAD tools. Analysis of physical factors affecting performance. Exhibit content learning through a course project demonstration.
  • EE 4272 – Computer Networks Computer network architectures and protocols; design and implementation of datalink, network, and transport layer functions. Introduction to the Internet protocol suite (TCP, UDP, IP), domain name service and protocols, file sharing protocols, wireless networks, and network security.
  • EE 5271 – VLSI Design Design of VLSI circuits using CAD tools. Analysis of physical factors affecting performance. Exhibit content learning through a course project demonstration.
  • EE 5455 – Cybersecurity Indust Ctrl Sys (+OL Only) General introduction to cybersecurity of industrial control systems and critical infrastructures. Topics include NIST and DHS publications, threat analysis, vulnerability analysis, red teaming, intrusion detection systems, industrial networks, industrial malware, and selected case studies.

5. Robotics

Focus: Industrial automation, autonomous perception, intelligence algorithms, control design, and embedded architectures.

  • EE 4235 – Sensing/Processing in Robotics Sensing and signal processing for robotics applications in manufacturing and autonomous navigation. Heavy emphasis on developing, testing, and evaluating algorithms. MATLAB programming required.
  • EE 5715 – Linear Systems Theory & Design (+OL) Overview of linear algebra, Modern Control: state-space based design of linear systems, observability, controllability, pole placement, observer design, stability theory of linear time-varying systems, Lyapunov stability, optimal control, Linear Quadratic regulator, Kalman filter, Introduction to robust control.
  • EE 5821 – Computational Intelligence This course covers the four main paradigms of Computational Intelligence, viz., fuzzy systems, artificial neural networks, evolutionary computing, and swarm intelligence, and their integration to develop hybrid systems. Applications of Computational Intelligence include classification, regression, clustering, controls, robotics, etc.
  • EE 5900 – Machine Learning for Robotics Introduces foundational machine learning paradigms and algorithms, deep neural network designs, and training procedures tailored for robot control, vision, and autonomous decision-making processes.
  • ME 4707 – Autonomous Systems The main concepts of autonomous systems will be introduced including motion control, navigation, and intelligent path planning and perception. This is a hands-on project based course. Students will have the opportunity to work with mobile robotics platforms. Having a foundational understanding of programming is recommended to make the most of this course.

6. Automotive

Focus: Powertrains, hybrid architecture, electric vehicles, vehicle modeling, and dynamic system optimization.

  • EE 4295 – Intro Propulsion Sys for HEV (+OL) Hybrid electric drive vehicle analysis will be developed and applied to examine the operation, integration, and design of powertrain components. Model based simulation and design is applied to determine vehicle performance measures in comparison to vehicle technical specifications. Power flows, losses, energy usage, and drive quality are examined over drive-cycles via application of these tools.
  • EE 5811 – Automotive Systems (+OL) Automotive systems for light-duty vehicles are examined from the perspectives of requirements, design, technical, and economic analyses to meet advanced mobility needs. This course links the content for the automotive systems graduate certificate in controls, powertrain, vehicle dynamics, and connected and autonomous vehicles.
  • ME 4775 – Control Sys Analysis & Design (+OL) This course covers topics of control systems design. Course includes a review for modeling of dynamical systems, stability, and root locus design. Also covers control systems design in the frequency domain, fundamentals of digital control and nonlinear systems.
  • ME 5680 – Optimization I Provides introductory concepts to optimization methods and theory. Covers the fundamentals of optimization, which is central to any problem involving engineering decision making. Provides the tools to select the best alternative for specific objectives.

Michigan Tech at SPIE Defense and Commercial Sensing 2024

Tim Havens (CS/ICC/GLRC) and Steve Senczyszyn (GLRC) attended and presented at the SPIE Defense and Commercial Sensing conference, held April 21–25 in National Harbor, Maryland.

Senczyszyn presented “Comparing performance of robot operating system (ROS) mapping algorithms in the presence of degraded or obscured depth sensors.” His co-authors include Havens; Tony Pinar (ECE); Adam Webb (MTRI); ECE undergraduate Mohamed Salem; ECE graduates Elizabeth Donoghue, Shelby Wills and Moira Broestl; and U.S. Army engineer Stanton Price.

Havens presented “Synthetic augmentation methods for object detection in infrared overhead imagery.” His co-authors include Ashley Olson (MTRI) and Jonathan Christian and Jason Summers of ARiA.

Dylan Kangas (ECE) presented “Developing robust unmanned surface vehicles with ROS.” His co-authors include Havens, Senczyszyn, Pinar, Keven Li (ME-EM), ECE undergraduates Salem and Tyler Ryynanen, U.S. Army engineers Steven Price and Stanton Price, and Stephen Taylor and Timothy Murphy of the U.S. Navy’s Naval Surface Warfare Center.

Havens and Olsen are also co-authors of a presentation by Summers and Christian of ARiA titled “Generative EO/IR multi-scale vision transformer for improved object detection.”

Bos Group on Testing of Lidar for Autonomous Vehicles

Colorful lidar image of an outdoor area in one image, with a near vertical green line in the second image.
(a) The reference point cloud scan (gray) overlayed with point clouds collected by each of the DUT lidars (colors). (b) Side view of an initial alignment between the reference point cloud (green) and point clouds from the DUT lidars for the 10 m target. Notice that the target is tilted toward the test origin. See the open source article link below.

Jeremy Bos (ECE) was quoted and PhD student Zach Jeffries (electrical engineering) and Akhil Kurup ’22 (PhD, computer engineering) were mentioned by SPIEGreen Car CongressTech XploreBioengineering.org and SCIENMAG in a story about a three-year effort to develop tests and performance standards for lidars used in autonomous vehicles and advanced driver assistance systems.

Bos led the testing through its first year, with Jeffries’ assistance. The team’s findings are detailed in an open-access paper published this month in Optical Engineering.

Zach D. JeffriesJeremy P. BosPaul F. McManamon, Charles Kershner, Akhil M. Kurup
Optical Engineering, Vol. 62, Issue 3, 031211 (January 2023). https://doi.org/10.1117/1.OE.62.3.031211

Extract

This paper describes the initial results from the first of 3 years of planned testing aimed at developing methods, metrics, and targets necessary to develop standardized tests for these instruments. Here, we evaluate range error accuracy and precision for eight automotive grade lidars; a survey grade lidar is used as a reference. These lidars are tasked with detecting a static, child-sized, target at ranges between 5 and 200 m.

Our purpose in this work is to motivate the development of test standards in this area and highlight variations in performance between lidars when stated specifications are similar.

Proposed additions to the testing include more complex targets, dynamic targets, placing corner cubes, or identical lidars on the test range, and weather effects.

Maurer, Brock, and Hilliker Present at Defense Manufacturing Conference

The Defense Manufacturing Conference (DMC 2022), was held in Tampa, Florida, on December 5–8. DMC is the nation’s annual forum for enhancing and leveraging the efforts of engineers, managers, technology leaders, scientists, and policy makers across the defense manufacturing industrial base.

Developing Disruptive and Transformational Solutions

Three electrical and computing engineering students presenting their research were:

Michael Maurer (PhD Candidate)
Presentation Title: Periodically Poled Polymers as an Entangled Photon Source

Giard Brock (Undergraduate)
Presentation Title: Ultra-violet Liquid Crystal Display Resin Printer Exposure Method for Rapid Prototyping of Printed Circuit Boards

Austin Hilliker (Undergraduate)
Presentation Title: Utilization of a Commercial Off the Shelf Laser Engraver for Rapid Production of Printed Circuit Boards

Three students check in for the conference.
Giard Brock, Michael Maurer, and Austin Hilliker

Lucas and Whitaker Place in Computing[MTU] Showcase Poster Session

Evan Lucas
Evan Lucas
Steven Whitaker
Steven Whitaker

The Institute of Computing and Cybersystems has announced the winners of the first Computing[MTU] Showcase Poster Session. Among the winners were electrical and computer engineering graduate students Evan Lucas and Steven Whitaker for “Active learning with binary feedback on multiclass problems,” who were tied for second place with Suresh Pokharel of Computer Science.

Active learning with binary feedback on multiclass problems

An active learning approach is often used for multiclass classification problems, where predictions are made on new data and a human user is used to determine if the predictions are correct. Typical approaches may ask a human to select the correct class if the prediction is incorrect. This work attempts to use a binary feedback on the predicted classes to save time and allow maximal use of a negative prediction on a partly trained model.

Ranit Karmakar Wins Best Overall Venture Award

Husky Innovate Students Win Top Prizes in New Venture Online Competition

Pitch screenshot on eye banks from the Focus presentation.

For the 11th year running, Central Michigan University and Michigan Tech collaborated to offer Tech students a chance to compete at CMU’s New Venture Competition. 2021 marked the second year the pitch competition was held online as the New Venture Online Competition (NVOC).

Despite the challenges of a pandemic and a virtual platform, our students persevered, honed their pitches and won top prizes. This year’s NVOC winners were also winners at the 2021 Bob Mark Business Model Pitch Competition held at Tech in January. All of their hard work and effort paid off!

Congratulations to this year’s MTU winners:

Read more in the NVOC 2021 Booklet.

By Husky Innovate.

Soft Community Detection

Sakineh “Audrey” Yazdanparast (ECE), Timothy C. Havens (CC), and Mohsen Jamalabdollahi have authored “Soft Overlapping Community Detection in Large-Scale Networks via Fast Fuzzy Modularity Maximization,” which is available under the “Early Access” area on IEEE Xplore.

Extract

Soft overlapping clustering is one of the notable problems of community detection. Extensive research has been conducted to develop efficient methods for non-overlapping and crisp-overlapping community detection in large-scale networks. In this paper, Fast Fuzzy Modularity Maximization (FFMM) for soft overlapping community detection is proposed. FFMM exploits novel iterative equations to calculate the modularity gain associated with changing the fuzzy membership values of network vertices. The simplicity of the proposed scheme enables efficient modifications, reducing computational complexity to a linear function of the network size and the number of communities.

Citation

S. Yazdanparast, T. C. Havens and M. Jamalabdollahi, “Soft Overlapping Community Detection in Large-Scale Networks via Fast Fuzzy Modularity Maximization,” in IEEE Transactions on Fuzzy Systems.

DOI: 10.1109/TFUZZ.2020.2980502

Kunle Olutomilayo Leads Outreach on True African Story

Kunle Olutomilayo
Kunle Olutomilayo

On May 15, 2019, eight students from the African Students Organization (ASO) chapter of Michigan Tech went to Dollar Bay High School to share a perspective of African history and culture that is often misrepresented or ignored by Western media.

Meeting a class of middle and high school students, Kunle Olutomilayo (PhD student, ECE), president of ASO, opened the floor with introductory remarks. Highlighting the historical significance of Africa to human existence. ASO’s interaction with the Dollar Bay School involved an exposition of West African naming practices, a telling of Asante folklore, a video showing different places in all 54 African countries, and a lesson on some facts about the African continent that are rarely pointed out.

Tolu Odebunmi (PhD student, Humanities) explained how the pronunciation of names worked in Yoruba, one of several languages in Nigeria. By referring to the tonal nature of Yoruba pronunciation, Tolu explained how names were significant in most African cultures. Of particular interest was the meanings attached to names and how the circumstances surrounding the birth of a child could dictate the name that was given to a child. For example, some ethnic groups in Ghana name their children based on the day of the week that a child is born.

While the video served as a means to retell the African story, the lesson led by Alfred Owusu-Ansah (PhD student, Humanities) highlighted rarely mentioned issues; Alfred pointed out how the world’s oldest university was established in 859 C.E. in Morocco by a woman. He also pointed out other firsts, like the first successful heart transplant was achieved in South Africa. In encouraging the students to explore the rich diversity of Africa, he suggested that they could read Nobel Laureates like Wole Soyinka of Nigeria or Nadine Gordimer of South Africa; or follow great scientists like Sameera Moussa (a renowned nuclear scientist) of Egypt, and Philip Emeagwali of Nigeria, who built the fastest computer of the time in 1989.

After the lesson students were invited to ask questions. This led to what was perhaps the climax of the day when a very bright student asked: “We hear that Africans are corrupt, how true is that?” Alfred pointed out that corruption does exist at different levels in the different countries in Africa; the same way that corruption exists at different levels in all countries in the world. Alfred highlighted the importance of checks and balances in any system of governance that seeks to minimize corrupt practices, which is as true for Africa as it is for North America. This led to a conversation on the cultural differences between African countries and the United States of America. It was clear that both Africans and Americans had a lot of respect for each other and were eager to learn new things. Ending the interaction with a song, the president of ASO sees this interaction as one of many that can help both Africans and the people of the great Upper Peninsula understand each other better.

by Bello Adesoji | African Student Organization.

Chaofeng Wang is the 2018 Matt Wolfe Award Recipient

Chaofeng Wang
Chaofeng Wang

Graduate students in Electrical and Computer Engineering were recognized for their outstanding achievements in a banquet held earlier this month.

Chaofeng Wang was awarded the 2018 Matt Wolfe Award for his remarkable research achievement as a graduate research assistant. His research included the development of intelligent and secure underwater acoustic communication networks and machine learning techniques. The Matt Wolfe Award is awarded each year to an outstanding research assistant and was established in memory of Matt Wolfe by his family. Wolfe was a 1992 BSEE graduate and MSEE candidate. Wang was nominated by his advisor, Zhaohui Wang (ECE).