Projects

Culture

We strive to build an interdisciplinary team working in the area of natural language processing, medical AI and brain computer interfaces. Our core values are:

  • Experimental: We value scientific rigor, focusing on researching under strong scientific grounds and conducting sound experiments that provide definitive and repeatable findings.
  • Computational: Our scientific nature is to use algorithms, mathematical models, strong theoretical background, and strong coding skills.

Lab Entry

We welcomed students from all disciplines but those with a huge passion for publishing to top-tier conferences/journals or making startup-related product. Make sure you read our graduation criteria here first: research guide. Each year, we TRY not to take more than 10 students a year.

Current Projects

We recommend everyone joining our lab to pursue these continuing projects; we TRY NOT to take any students new topics.

  1. Brain MRI for diagnosis: Fine-tune models to detect multiple diseases through Brain MRI images and deploy as API suite
  2. EEG and mental illnesses: Train models to detect multiple mental illnesses and deploy as an application suite that can diagnose multiple illnesses
  3. Raman Spectroscopy: Develop a portable, continuous glucose monitoring system using Raman Spectroscopy
  4. Voice2Text and Text2Voice: Fine-tune models to support Voice2Text and Text2Voice in Thai and English language and deploy as API suite
  5. Sign2Text: Fine-tune models to support Sign2Text to support deaf people communication and deploy as API suite
  6. Text2Image: Fine-tune LLMs to support Text2Image in Thai and English language for different use case (sales, environment, etc.) and deploy as API suite
  7. Avatar Generation: Develop an API that supports avatar generation + voice over mechanism
  8. Text2Text: Fine-tune LLMs to support Text2Text in Thai and English language for different use cases (sales, environment, research paraphrasing, interviews, tourism, summarization, etc.) and deploy as API suite
  9. Voice2Emotion: Fine-tune models to detect emotion from voice in Thai and English language and deploy as API suite
  10. Face Detection: Train models to detect multiple features of a human and deploy as API suite (e.g., to support driver detection of sleepiness, blood pressure, heart rate, emotion)