Published: April 11, 2024 By

Nataliya Nechyporenko, a computer science Ph.D. student advised by Alessandro Roncone in the Human Interaction and Robotics (HIRO) group, has received a PhD fellowship in AI and Machine Learning (AIML) through the Apple Scholars program. The program was created by Apple to recognize the contributions of emerging leaders in computer science and engineering at the graduate and postgraduate level. 

The fellowship provides Nechyporenko support for her research and academic travel for two years, internship opportunities and a two-year mentorship with an Apple researcher. 

Let's learn more about Nechyporenko's research aims and her perspective on the future of robotics research: 

What research do you hope to accomplish through this fellowship?

Think about how you might manually feel around an object to understand its shape, weight, and texture. Or if something is in your way, you'd just push it aside without overthinking it. If you drop something, you'll persistently keep trying to pick it up from different angles until you get it. As you're doing these everyday tasks, you're constantly building up an intuitive sense of your surroundings through trial-and-error. That's the kind of resourceful, flexible, multi-sensory approach I want robots to have when manipulating things – rather than just blindly following a fixed routine. 

The goal is for robotic arms to move and behave with that same kind of curious, improvisational, problem-solving spirit we take for granted as humans. As an Apple AIML scholar, I hope to gain insights into this problem with the help of a fresh network of mentors and collaborators.  

Is this an extension of work you are already doing in your lab? If so, how?

Driven to establish contact-rich planning as a dominant feature in robotics, I focused the first two years of my PhD on analyzing the methods used by state-of-the-art planners and solving the shortcomings leading to the lack of physical robot interaction. 

I have started to extend this work by integrating the empirical formulation of machine learning with model-based algorithmic approaches. I believe this is the path to making robots more adaptable to chaotic human environments. I will continue this work as an Apple scholar. 

What do you think of the current hype around AI and ML? What do you wish people understood about this research area?

The AI and machine learning hype trains have been barreling full steam ahead lately. But robotics? That's an entirely different beast that doesn't follow the overnight disruption narratives. It's a synergy of achievements in areas like materials, manufacturing, sensing, controls theory, and others aligning to reshape the physical world. 

The robotics future will reshape industries and labor concepts, but it will be catalyzed through the patient advancement of many disciplines.

How did you come to study at CU Boulder?

I spent a couple years in the trenches, getting my hands dirty actually building and deploying robots in industry. But after a while, I got this craving -- like there was so much more potential waiting to be unlocked if I could really dive into the deep scientific questions around robotics. That's why I decided to take the plunge back into academia.

What is one of your plans or hopes for the future, either professionally or personally?

I hope to be an expert, a leader, a thinker and a builder. Outside of research endeavors, I aim to be a leader and educator for the robotics and the AI community. Previously, I’ve led volunteering activities, mentored students, and co-organized events that foster discussions around AI. I hope to continue to do so in the future at a larger scale.