# Ghazaleh Jowkar

> master of Computer Science & Engineering, University of Washington, 2020

**Wikidata**: [Q113667867](https://www.wikidata.org/wiki/Q113667867)  
**Source**: https://4ort.xyz/entity/ghazaleh-jowkar

## Summary
Ghazaleh Jowkar is a computer scientist and engineer known for her research in physiological signal processing. She earned her Master of Computer Science & Engineering from the University of Washington in 2020, where she specialized in electromyography-based movement detection.

## Biography
- **Education**: Master's degree in Computer Science and Computer Engineering, University of Washington (2020)
- **Known for**: Research in electromyography (EMG) based finger movement detection
- **Field(s)**: Computer Science, Computer Engineering

## Contributions
Ghazaleh Jowkar’s primary contribution to the field of computer science is her research into human-computer interaction through physiological signals. In 2020, she authored and published her master's thesis titled "Electromyography (emg) Based Finger Movement Detection" at the University of Washington. 

Working under the guidance of Wei Cheng, Jowkar explored the application of electromyography (EMG)—the recording of electrical activity produced by skeletal muscles—to accurately identify specific finger movements. This work is situated at the intersection of the industrial and service sectors of computer science, focusing on how biological data can be translated into functional digital commands. Her research contributes to the broader understanding of gesture recognition technology, which has applications in assistive devices, robotics, and wearable computing.

## FAQs
### Q: What is Ghazaleh Jowkar's academic background?
A: Ghazaleh Jowkar is a computer scientist who earned a Master of Computer Science & Engineering from the University of Washington in 2020. Her studies focused on the intersection of computer science and computer engineering.

### Q: What was the focus of Ghazaleh Jowkar's research?
A: Her research focused on "Electromyography (emg) Based Finger Movement Detection." This work involves analyzing muscle activity to detect and interpret the movement of fingers for computational use.

### Q: Who was Ghazaleh Jowkar's academic advisor?
A: During her master's program at the University of Washington, Ghazaleh Jowkar was a student of Wei Cheng.

## Why They Matter
Ghazaleh Jowkar’s work is significant for its exploration of electromyography as a viable interface for computer systems. By developing methods for finger movement detection based on EMG signals, her research addresses a critical component of gesture-based computing and neural engineering. Such advancements are essential for creating more intuitive user interfaces and improving the functionality of prosthetic limbs or other assistive technologies. Her academic contributions at the University of Washington have been recognized through her inclusion in the WikiProject PCC Wikidata Pilot, marking her as a notable figure within the university's computer science and engineering records.

## Notable For
*   **Master's Thesis**: Author of "Electromyography (emg) Based Finger Movement Detection" (2020).
*   **Academic Affiliation**: Graduate of the University of Washington's Computer Science & Engineering program.
*   **Research Mentorship**: Conducted specialized research as a student of Wei Cheng.
*   **Data Recognition**: Featured in the WikiProject PCC Wikidata Pilot for the University of Washington.

## Body
### Education and Academic Career
Ghazaleh Jowkar completed her advanced academic training at the University of Washington. In 2020, she received a master's degree with a dual focus on computer science and computer engineering. Her time at the institution was characterized by a focus on the practical application of computer science within the industrial and service sectors.

### Research and Thesis Work
Jowkar's most prominent work is her master's thesis, "Electromyography (emg) Based Finger Movement Detection." This research investigated the use of EMG sensors to capture the electrical signals of muscles to predict or identify finger gestures. This study was supervised by Wei Cheng and contributes to the technical knowledge required for high-precision gesture recognition.

### Professional Identity
As a computer scientist, Jowkar is part of a professional class that practices and studies the application of computational theory. Her specific contributions are documented in academic and structured data repositories, including her role in the WikiProject PCC Wikidata Pilot, which highlights notable academic figures and their contributions to the University of Washington.

## References

1. WorldCat