About Anton Treskunov, Ph.D.

Professional Summary

I am a seasoned Research Engineer with over 20 years of experience spanning virtual reality, human-computer interaction, and computer vision. My career has been driven by a passion for innovation and solving complex problems across various technological domains.

Recently, I've developed a keen interest in AI and large language models. This new focus allows me to leverage my diverse background in exciting new ways, potentially contributing fresh perspectives to these cutting-edge fields.

Current AI Interests

1. Multi-modal AI Systems

I'm fascinated by the potential of integrating different types of data (text, images, audio, 3D) into unified AI models. My background in computer vision and 3D data processing could bring unique insights to this area, potentially enhancing language models with spatial and visual understanding. I'm excited about:

  • Developing architectures that can process and generate multi-modal data efficiently
  • Exploring ways to transfer knowledge between different modalities
  • Investigating how multi-modal understanding can improve the overall capabilities and robustness of AI systems

2. Human-AI Interaction

My experience in HCI and VR has made me deeply interested in creating more intuitive and effective interfaces between humans and AI systems. In the context of large language models, I'm particularly intrigued by:

  • Adaptive communication styles that can adjust based on user preferences and context
  • Developing more natural and engaging interaction paradigms for complex AI systems
  • Exploring how to leverage multi-modal inputs and outputs to enhance human-AI communication
  • Investigating ways to align AI behavior with human expectations and values during interactions

3. Interpretability and Explainable AI

Given the increasing complexity of AI models, I'm keenly interested in research that aims to make these models more interpretable and their decision-making processes more transparent. For large language models, I'm particularly interested in:

  • Developing techniques to visualize and understand the internal representations and decision processes of neural networks
  • Creating methods for generating human-understandable explanations of model outputs
  • Exploring the relationship between model interpretability and alignment
  • Investigating how improved interpretability can contribute to the development of safer and more reliable AI systems

Key Expertise

  • Computer Vision and Image Processing
  • Virtual and Mixed Reality
  • Human-Computer Interaction
  • Research and Development of Complex Systems
  • Interdisciplinary Problem-Solving
  • Artificial Intelligence and Machine Learning

Recent Interests

  • Exploring advancements in neural network architectures for language models
  • Investigating human-AI interaction, including adaptive communication and emotional response in AI systems
  • Advancing techniques for processing and analyzing complex, high-dimensional data for perception tasks
  • Examining the potential intersections of AI with VR and HCI

Career Highlights

Education

Professional Philosophy

Throughout my career, I've consistently sought to push technological boundaries and create innovative solutions that improve people's lives. My diverse background allows me to approach problems from multiple angles, often leading to novel solutions. As I focus more on AI and machine learning, I'm excited about the potential to contribute to the development of artificial general intelligence in a way that benefits all of humanity.