Hongmin Wu

I am a PhD. Candidate in robotics. The primary goal of my research is to enable personal robots to be deployed in the home and workplace with minimal intervention by robotics experts. With this in mind, we equip robots with a set of abilities that allows them to assess the quality of sensory data, internal modals, used the Bayesian Nonparametric methods, LSTM, Seq2Seq, and Variational Autoencoder for learning dynamical models for multimodal time series with complex and uncertain behavior patterns. Thus, my work draws roughly equally from both machine learning and robotics, including learning from demonstration, movement representation, robot introspection (anomaly detection, classification, recovery), human-robot interaction, and deep learning.

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Anomaly Classification (1)
Anomaly Detection (2)
Anomaly Recovery (1)
Fundamentals of Machine Learning (1)
Gassian Process (1)
HDP-HMM (1)
Human-robot Collabration (1)
Interests Objective (1)
Introspection (1)
Introspection Models Construction (1)
LSTM (1)
Multimodal Feature Engineering (1)
RO-MAN (1)
Recovery (1)
Seq2Seq (1)
Synthetic Multivariate Time Series Argumentation (1)
Task Representation (1)
Tutorial (1)

Anomaly Classification

Anomaly Detection

Anomaly Recovery

Fundamentals of Machine Learning

Gassian Process

HDP-HMM

Human-robot Collabration

Interests Objective

Introspection

Introspection Models Construction

LSTM

Multimodal Feature Engineering

RO-MAN

Recovery

Seq2Seq

Synthetic Multivariate Time Series Argumentation

Task Representation

Tutorial