Kayla
PhD candidate
Expertise
Machine learning, human-robot interaction, mechanical engineering, product development, design thinking, entrepreneurship
Polygence mentors are selected based on their exceptional academic background, teaching experience, and unique ability to inspire the next generation of innovative thinkers and industry leaders.
Machine learning, human-robot interaction, mechanical engineering, product development, design thinking, entrepreneurship
Natural language processing, deep learning, (anti)social computing
ML for software engineering, automatic code generation, interpreting neural networks
Neuroscience, Behavior, Sensory perception, Working memory, Artificial Intelligence
Epilepsy, computational neuroscience, machine learning and causal inference
Networks, neuroscience, artificial intelligence
Robotics, control systems, AI/machine learning
Computer Science - Natural Language Processing
bioengineering, computational biology, computer science, physics, biology
AI, machine learning, deep learning, data science, natural language processing, signal processing, image processing, computational modeling, biophysical modeling, statistics, biomedical engineering, medical devices, neuromodulation, movement disorders
Data Science, Machine Learning, Deep Learning, Computer Vision, Reinforcement learning
Using machine learning and computational tools to solve problems in biology and health; neurodegenerative diseases; psychology (including topics in learning, memory, perception, social psychology, cognitive neuroscience, minds & machines, clinical & abnormal psychology)
Neuroscience of consciousness, applications of machine learning to biomedical research, how do our genetic backgrounds influence our psychology
computational fluid dynamics, computer aided design, artificial intelligence, high performance computing
Data Science, Physics & Statistics
Analyzing and modeling health-related data from wearables or smart devices; machine learning for healthcare
Anything related to data science, machine learning and AI, social sciences, and the arts!
artificial intelligence, machine learning, deep learning, design, ui/ux
Machine Learning, Data Science, Behavioral Modeling, Statistics, Econometrics
Any project involving scientific computing (e.g. simulation, data analysis; can be in a domain I'm familiar with like physics, or otherwise), AI (decision-making, neural networks, etc.), aerospace engineering (related to: orbital dynamics/satellites/space stuff, aeronautics/aircraft), Art (traditional or computer-driven)