Opportunities

Position Overview

The Data Science Research Center (DSRC) at Duke Kunshan University (DKU) is seeking a Research Fellow in Biomedical Data Acquisition and Annotation with expertise in autism diagnose and treatment as well as biomedical data annotation, to engage in research projects at the Speech and Multimodal Intelligent Information Processing (SMIIP) Lab.

DKU is a partnership of Duke University, Wuhan University and the Municipality of Kunshan, China. The campus is located 37 miles west of Shanghai in Kunshan, which is connected to Shanghai via a 20-minute high-speed train. DKU currently offers graduate and undergraduate programs. For more info, visit http://www.dukekunshan.edu.cn.

DSRC is an interdisciplinary research-dedicated unit that engages a broad spectrum of investigators across disciplines. The center is now aggressively pursuing interdisciplinary research on big data analytics over a broad range of applications including autonomous driving, advanced manufacturing, digital arts, human computer interaction, healthcare, etc.

This research fellow will perform research and development works on research projects supervised by Dr. Ming Li.

How to Apply: Please directly apply this position via DKU official website. It is also highly recommended submit formal English resume and cover letter to ming.li369@dukekunshan.edu.cn.

Reports to

Prof. Ming Li, Associate Professor of Electrical and Computer Engineering

Essential Duties

• Maintain delivered ASD assisted diagnose system and 3D scanning system and ensure they are working in normal condition in the Third Affiliated Hospital of Sun Yat-sen University.
• To demonstrate and train people who are going to use these prototype systems for research in the Third Affiliated Hospital of Sun Yat-sen University.
• Assist doctors in collecting ASD related behavior data by using our delivered systems.
• Analyze the data that collected by the doctors and send feedback to the doctors.
• Digitize the collected data (e.g. assessment results, demographic information of children with ASD, etc.) in the hospital.
• Annotate the behavior audio-visual data in required protocols.
• Other data processing and annotation works as assigned (e.g. labeling the laryngoscope data).
• Other data processing related duties as assigned by the project PI.
• University employees’ job responsibilities will continue to expand in scope and depth as the University grows in size and complexity.

Required Qualifications

• Solid understanding about ASD diagnoses and treatments.
• Solid experience with clinical assessment tools (such as, ADOS, PEP-3, ADI, etc.)
• Solid child development assessment skills.
• Solid experience with data annotation, such as Praat, Auditory etc.
• Publications in the field of computer science or psychology related to autism is a plus.

Education

• Bachelor’s degree in psychology, clinical medicine, pharmacy, child health, rehabilitation, speech therapy or related major.

Years of Related Working Experience

• 3+ years’ experience in Autism related research.

Position Overview

With the rapid 5G, IoT, and social network applications, billions of intelligent devices (e.g., mobile phones and IoT devices) and massive data have been ubiquitous in our lives. These data provide valuable information for many attractive real-world applications, such as smart homes, smart retail, smart manufacturing, and autonomous driving. However, in enabling these intelligent services, traditional data-driven AI technologies require collecting and centralizing the training data in the data-center (cloud), raising severe data privacy concerns (e.g., data misuse and leakage). 

To tackle the above challenge, federated learning (FL) has emerged as an attractive distributed AI paradigm, which enables many distributed clients to collaboratively train a shared machine learning model while keeping their raw data private. FL has great potential in privacy-sensitive data applications, such as IoT (wearable gadgets), healthcare (medical information protection), finance (fraudulent loans), and advertising (personalized recommendations).

Here are some research topics that Prof. Luo is currently working on:    

1. Effectiveness and Efficiency: How to enable low-cost FL deployment in future resource-constrained (storage, computation, and communication) mobile and IoT devices. 
2. Incentive Mechanism: How to design incentive mechanisms to stimulate data owners to participate in FL, and how to evaluate their contributions. 
3. Fairness and Bias: How to mitigate data/model bias for achieving a good balance between accuracy and fairness due to social-economic factors.
4. Security and Privacy: How to detect and defend malicious attackers in FL systems and ensure robustness.  

Reports to

Dr. Bing Luo

Essential Duties

• Effectiveness and Efficiency: conduct research on how to enable low-cost FL deployment in future resource-constrained (storage, computation, and communication) mobile and IoT devices. 
• Incentive Mechanism: conduct research on how to design incentive mechanisms to stimulate data owners to participate in FL, and how to evaluate their contributions. 
• Fairness and Bias: conduct research on how to mitigate data/model bias for achieving a good balance between accuracy and fairness due to social-economic factors.
• Security and Privacy: conduct research on how to detect and defend malicious attackers in FL systems and ensure robustness.  

Required Qualifications

• Enrolled in applied-math/data/computer science and passed major courses with A grades or above.
• Strong mathematical and machine learning backgrounds.
• Strong self-learning and problem solving abilities, Highly self-motivated.