Meet the Faculty - Junaed Sattar
Tell us about your journey to the University of Minnesota. How did you become interested in computer science and your specific field?
Growing up in Bangladesh, access to computing resources was quite limited. After high school, my immediate dream was to become a professional cricket player, but my mother gently steered me toward a more practical career path. My father then introduced me to a local company that was doing desktop publishing, one of the few places utilizing computers at the time. Exploring those early systems fascinated me, and that spark ultimately inspired me to pursue computer science.
During graduate school, I crossed paths with several researchers from the University of Minnesota’s robotics division, a program I had long admired. The prospect of working alongside them someday seemed incredibly exciting. About 12 years ago, while presenting my research at a marine robotics conference, a UMN faculty member happened to be in the audience. A few weeks later, he reached out via email, saying, “Hey, your presentation was excellent, and we would love to have you here. We are hiring, so if you are open to a transition, please apply.”
At the time, I was a very new faculty member at another institution and wasn’t actively looking to move. However, out of immense respect for this mentor, I decided to submit an application, though I had little expectation of what might come of it. Ten years later, I am proud to be a member of the faculty here at the University of Minnesota. In hindsight, it was one of the defining and most rewarding milestones of my career.
Tell us more about your current research.
My primary research focus is on field robotics with humans in the loop, which involves deploying autonomous systems into unpredictable, real-world environments — specifically the underwater domain. There are numerous critical applications for marine robotics, and our work centers on improving how these systems perceive their surroundings through vision and acoustics. Crucially, we focus on human-robot collaboration, ensuring that robots are fully aware of and responsive to the divers working alongside them, accurately interpreting their intentions and commands.
A major pillar of our current work involves environmental preservation and water sustainability. Through a grant from the Institute on the Environment, we are developing autonomous robots and matching docking infrastructure to conduct long-term water quality monitoring across Minnesota’s lakes. When a robot runs low on power, it autonomously navigates to a dock to recharge and seamlessly transfer environmental data back to scientists. We are looking forward to deploying these systems this summer.
Another initiative, launched this past January and funded by the Minnesota Invasive Species Research Center (MAISRC), addresses aquatic invasive species. We are utilizing robots equipped with cameras and sonar sensors to identify and map invasive snail populations, providing conservationists with precise maps to target and manage infestations.
Additionally, we hold a National Science Foundation (NSF) grant focused on underwater object detection and data scarcity. Training traditional artificial intelligence (AI) models requires massive datasets, which are incredibly difficult to collect underwater due to visibility and operational constraints. Our research addresses this challenge by developing innovative AI models that achieve high-performance detection and environmental awareness despite having limited data to learn from.
Which courses do you typically teach? What can people expect to get out of those courses?
Most recently, my teaching has focused on the intersection of robotics, AI, and computer vision. I teach CSCI 4551 - Introduction to Computational Robotics, a brand-new undergraduate course I designed and launched last fall, which I will be teaching this fall term again. Because robotics is highly interdisciplinary, this class is structured to give computer science undergraduates a computing-centric framework for how software and algorithms give physical machines their intelligence. This course is a spin-off of CSCI 5551 - Introduction to Intelligent Robotic Systems, a graduate-level class I taught for six years.
Over the last few years, I have also taught CSCI 5561 - Computer Vision, which I will be offering in the spring of 2027, as well as CSCI 8980 - Special Advanced Topics in Computer Science, a seminar course exploring the latest breakthroughs in field robotics. On the foundational side, I enjoy teaching introductory tracks, including CSCI 1113 - Introduction to C/C++ Programming for Scientists and Engineers and CSCI 1133 - Introduction to Computing and Programming Concepts.
What do you do outside of the classroom for fun?
I have a deep appreciation for the outdoors and love spending time hiking and camping. Exploring Minnesota's North Shore is easily one of my favorite getaways. Beyond outdoor recreation, I am an avid photographer and a passionate motorsports fan. I follow Formula 1 closely and have been fortunate enough to attend several races live when I lived in Montreal.
Do you have a favorite spot on campus or in the Twin Cities?
On campus, I love walking across the Washington Avenue Bridge. On a clear day, it’s the perfect vantage point to pause and take in the view of the Mississippi River below.
Narrowing down a favorite spot in the Twin Cities is tough because I am drawn to the region's waterfronts. I frequent spots along the river like Boom Island Park in Minneapolis and Raspberry Island in St. Paul. I also love the architecture and energy of the Guthrie Theater, as well as the vibrant historic district encompassing the Stone Arch Bridge and Gold Medal Park.
Is there anything else you would like students to know?
There is understandably a lot of anxiety right now surrounding the rapid evolution of AI, with students wondering if a computer science degree remains relevant if AI can write code. My answer to that is an emphatic yes. In fact, computer science is more critical now than it has ever been.
I want to emphasize that there is absolutely no substitute for strong, fundamental foundational knowledge. While AI is transforming our efficiency, largely in very positive ways, highly skilled human minds are indispensable for guiding, evolving, and ensuring these systems remain safe, ethical, and humane. The mindset shouldn't be one of fear that a tool will replace us, but rather excitement for how we can build it. Focusing heavily on core scientific principles right now is what will prepare our students for long, flourishing, and resilient careers.