小黄鸭视频 faculty member Shaun Canavan begins his course by telling students that some problems can鈥檛 be solved 鈥� at least not yet.
鈥淚t might take a computer your entire lifetime to solve it,鈥� says Canavan, describing how he introduces complexity theory in Algorithms Essentials, a fast-paced course in 小黄鸭视频鈥檚 program for adults transitioning into computing or preparing for graduate study.
鈥淭hey have to understand that some problems might take years and years to solve, literally,鈥� he says. But it鈥檚 not about giving up. 鈥淭he question becomes: how do we think differently about the problem?鈥�
鈥淭his is math and computer science at their finest,鈥� he says. 鈥淎nd it opens doors for what鈥檚 next.鈥�
From Math Major to Emotional AI Researcher
As a kid, Canavan wanted to be a scientist and conduct research. But he loved math.
鈥淚 always excelled in math and it was my favorite subject. I liked solving problems. I started college as a math major but soon realized that I wanted to apply mathematics to issues and not simply solve math problems.鈥�
He thought about changing his major. He was curious about human behavior. Psychology fascinated him but he didn鈥檛 want a degree in it.
After earning his bachelor鈥檚 and master鈥檚 degrees from Youngstown State University and a PhD in computer science from Binghamton University, Canavan joined 小黄鸭视频 in 2017.
And he built a career at the intersection of psychology, math, and computer science 鈥� and teaching.
Teaching in the Pathway to Computing Program
He teaches Algorithm Essentials in the PTC program. 鈥淚t鈥檚 one of the most important classes for anyone thinking about a master鈥檚 degree in computer science,鈥� he says. 鈥淎 lot of what they鈥檒l encounter in interviews or in graduate coursework comes from this course.鈥�
The course covers key material such as data structures, graph algorithms, and classic design strategies like dynamic programming and divide-and-conquer techniques. Students also work with Big-O notation to evaluate algorithm efficiency and correctness, and more. And while it鈥檚 rigorous 鈥� packed into a fast-moving, eight-week term 鈥� Canavan emphasizes that students can succeed if they commit.
鈥淚鈥檝e had students who struggled in the beginning, then buckled down and finished strong,鈥� he says. 鈥淚t鈥檚 hard, it鈥檚 fast, but it鈥檚 doable.鈥�
Making Complexity Real
To make these concepts real, Canavan gives students problems that are technically solvable 鈥� but would take a computer thousands of years to process. He simulates the challenge.
鈥淚鈥檒l run a small program and say, 鈥楲et鈥檚 see if it finishes before class ends.鈥� It never does 鈥� and that鈥檚 the point.鈥� By grounding these abstract concepts in visual, hands-on learning, he helps students bridge the gap between theory and application 鈥� and builds the confidence they鈥檒l need in future computing roles.
Empathy, Ethics, and What Comes Next
Outside the classroom, Canavan continues his work on research with far-reaching potential. He鈥檚 collaborated with colleagues in 小黄鸭视频 Health, the School of Social Work, and the College of Education, working on projects that apply affective computing to detect signs of PTSD in teens and diagnose autism in children earlier. One project is already published; another is under review.
His work explores how machines interpret human emotion and behavior: facial expressions, stress signals, and patterns of empathy and interaction.
鈥淲e still don鈥檛 fully understand what emotion is,鈥� he says. 鈥淎nd yet we鈥檙e trying to define it 鈥� in machines.鈥� He points to empathetic AI chatbots as one example: 鈥淚f you鈥檙e on a mental health site, you want a chatbot that shows empathy.鈥�
He鈥檚 also deeply interested in the ethics of AI, particularly how large datasets can introduce bias based on culture, age, or other human factors.
鈥淯nintended biases in AI come into play, too,鈥� he adds. 鈥淭hat鈥檚 my top interest: how demographics and data shape AI.鈥�
That balance of logic and emotion, structure, and social good drives both his research and his teaching.
A Springboard for Career Changers
Canavan sees the Pathway to Computing program as a springboard for students ready to pivot into something new. For many, it鈥檚 their first serious dive into technical learning. For others, it鈥檚 a return to school after years in another field.
His advice? Come in with an open mind. Be ready to learn.
鈥淭here鈥檚 a lot of new material, but you鈥檒l see just how cool and powerful computing can be.鈥�
And that, he says, is what teaching 鈥� and computing 鈥� is all about.
鈥淲e鈥檙e not just solving problems. We鈥檙e solving the right ones. And that starts with helping people think in new ways.鈥�