Openings

Full-time Research Assistant position in Xiao Lab at American University, Washington DC.  

Staring date September 1st, 2023 or soon after. 

Application deadline: August 15th, 2023. 

In-Person Full time 

Position Overview

The Xiao Computational Perception Lab in the Department of Computer Science at American University is seeking a full-time Research Assistant (RA) / Lab Programmer for an NIH-funded project on human material perception. The main goal is to build computational models to simulate, predict, and explain human material perception and recognition in immersive and natural environments.  To achieve this,  we use a combination of human psychophysics, deep learning, VR/AR,  and SOTA generative AI technique (e.g. GAN and  Neural Radiance Field) to create immersive environments and measure human material perception with various tasks. In addition, we also wish to measure neural signals of material perception using EEG.  These projects have both real-world applications (e.g. user-in-the-loop image editing) and contributions to neuroscience. 

Job Description  

The RA iis working in a collaborative environment under close supervision of the PI. The RA is to pursue research projects of his/her own as well as provide support for research carried out in the Xiao lab. Possible duties include:  

• Building VR/AR experimental interfaces with Unity3D

• Python coding for behavioral data analysis

• Collecting data for psychophysical experiments

• Training machine learning models

This is an ideal position for someone interested in gaining research experience in perception science and computational modeling before applying to graduate school. The position comes with a salary and full benefits. This position is initially for a one-year contract but have the possibility to extension. Starting date is September 1st, 2023, or soon after.

Position Requirements:

• The ideal candidate should have a Bachelor's degree in quantitative psychology, computer science, engineering, neuroscience, cognitive science, or a related field. 

• The candidate should have solid programming skills in Python or Matlab. Having experience with deep learning library such as PyTorch is a plus.  

• Experience with statistical methods (linear models, multivariate analysis, etc.).

• Experience with psychophysics is not required but would be useful. 

The Lab and Facility

Xiao Lab studies both human and computer vision with an emphasis on material perception and recognition. The lab currently has a few ongoing research projects:  

• Learning latent representation of human perception of material properties (NIH R15, PI)

• Prediction of clinical trial outcomes with human experts and machine learning models  (NSF SBE Core, PI)

• Material and object perception in infants and children  (Internal funded by American University, collaborating with Dr.Laurie Bayet). 

• Volumetric Capture Studio (NSF MRI Co-PI)

• Uncertainty estimation in few-shot learning in text classification (collaborating with C.T. Lu at Virginia Tech)

The Xiao Lab is located in a state-of-the-art technology building, which is home to computer science, physics, math, and a design and build lab. The lab has high-performing GPU workstations, haptic phantom devices, VR headsets, and 3D printers. We also have access to a new NSF-funded Volumetric Capture Studio.

Washington, DC, is the US capital and has a vibrant scene of computational cognition and computer vision research (e.g., NIH, NIST, Johns Hopkins University, George Washington University, George Mason University, Georgetown University, and the University of Maryland). 

How to apply

Please submit your application, including a CV,  and a cover letter describing your background, computational skills, experience, and motivation - preferably in PDF format, and the names of two references that have agreed to be contacted. Please submit the application no later than July 20th, 2023, to Prof. Bei Xiao at bxiao@american.edu. Dr. Xiao will also be attending VSS (May 18-22) and SFN conference. Interested candidates can arrange a time to meet the PI. 

Representative Recent Publications：  

1. Liao, C, Sawayama, M, Xiao, B.  (2023) Unsupervised learning reveals interpretable latent representations for translucency perception. PLOS Computational Biology. Feb 8, 2023. PDF. 

2. Liao, C, Sawayama, M, Xiao, B.  (2022) Crystal or Jelly? Effect of Color on the Perception of Translucent Materials with Photographs of Real-world Objects. Journal of Vision. PDF.

3. He, J. Zhang, X., Shuo L. Wang, S, Huang, Q., Lu, C-T, Xiao, B. (2022) Semantic Editing On Segmentation Map Via Multi-Expansion Loss. Neurocomputing. 501,306-317. PDF.

Fully-funded PhD fellowship in Neuroscience at American University, Washington DC.  

Application deadline: December 1, 2023

The Xiao lab currently has an opening for a NIH-funded PhD fellowship in Neuroscience (Application deadline Dec 1, 2023). The main topic of this PhD studentship is to understand human  material perception using deep learning, multi-modal human psychophysics, VR/AR.  A parallel goal is to develop algorithms that can simulate, predict and explain human behavior. The candidate also has opportunity to study visual development of material perception through collaborating with Laurie Bayet in psychology to investigate material perception in infancy and early childhood.  Xiao lab also collaborates with researchers in Virginia Tech, NIH, and University of Tokoy. 

Xiao lab uses a combination of visual psychophysics, computer vision, deep learning, and graphics techniques. Beyond basic human vision research, ongoing projects in the lab includes human-in-the-loop text-to-image manipulation, predicting clinical trial outcome using NLP (NSF funded), uncertainty estimation in text classification with few-shot learning (through collaboration).

Qualification:  The ideal candidate should have a Bachelor's degree in computer science, engineering, neuroscience, cognitive science, or a related field. 

The candidate will pursue PhD degree in an interdisciplinary brain and cognitive science program. The ideal candidate is expected to have strong technical background and have experience in at least one of the following methods: machine learning, computer vision, image processing, computational neuroscience, human psychophysics, computer graphics, and human cognition. Solid programming skills is a plus. Prospective graduate student should contact me directly and are required to apply to the graduate program Behavior, Cognition, & Neuroscience Graduate Program at AU.

Projects:

Xiao Lab studies both human and computer vision with an emphasis on material perception and recognition. The lab currently has a few ongoing research projects:  

• Learning latent representation of human perception of material properties (NIH R15, PI)

• Prediction of clinical trial outcomes with human experts and machine learning models  (NSF SBE Core, PI)

• Material and object perception in infants and children  (Internal funded by American University, collaborating with Dr.Laurie Bayet). 

• Volumetric Capture Studio (NSF MRI Co-PI).  This can capture 3D images of moving humans and objects. 

• Uncertainty estimation in few-shot learning in text classification (collaborating with C.T. Lu at Virginia Tech)

How to apply: 

Please submit your application, including a CV,  and a cover letter describing your background, computational skills, experience, and motivation - preferably in PDF format, and the names of two references that have agreed to be contacted. Please submit the application no later than July 20th, 2023, to Prof. Bei Xiao at bxiao@american.edu.  Bei will also be attending VSS (May 18-22) and SFN conference. Interested candidates can arrange a time to meet the PI. 

Applications should be sent apply at BCCN website:

https://www.american.edu/cas/psychology/behavioral/requirements.cfm

More details about Xiao lab: https://sites.google.com/site/beixiao/