Undergraduate Summer Research Internship
The Faculty Undergraduate Summer Research Internship programme is launched to offer students with funding support to undertake a research project under the supervision of professors in summer. The objectives are to give students exposure to the research environment and grooms them for graduate studies and overseas summer research schemes.
The Scheme
A maximum grant of HK$10,000 will be awarded to each student for him/her to work on an approved project/problem between June-August.
The Concrete Research Group are offering the following two projects:
The Scheme
- Non-final year undergraduate students with a CGPA of 3.3 or above are eligible.
- Students who are planning and/or is going to participate summer programmes or take summer courses overseas for more than three weeks accumulatively or need to take more than three weeks of accumulated leave are not eligible for the internship programme.
- The scheme is for undergraduate students with research interest to join on the voluntary basis, and it is currently a non-credit bearing program.
- The student will need to approach a professor in the Faculty (in any department) to be his/her supervisor based on the proposed project title the professor provided.
- The student will need to write a 1-page proposal about the research problem and research objective, after discussing his/her research ideas with the supervising professors.
- It is expected that the student will be attached to a professor/research lab. The prior approval/agreement of which should be obtained by the students.
- There will be a compulsory poster presentation at the end of the summer for students to present their research results. Awards will be given to the top 10% projects assessed by a committee.
A maximum grant of HK$10,000 will be awarded to each student for him/her to work on an approved project/problem between June-August.
The Concrete Research Group are offering the following two projects:
Project 1:Build your own WiFi “Chip”
WiFi technology is now a part of our daily life. But we normally use it as black-box silicon (chip). Do you want to have an in-depth “know-how” of the inside of the Wi-Fi chip? If you join this project, you will have a chance to understand the full stack of Wi-Fi technology from the user program to the antenna. You will have an opportunity to access the latest system-on-chip software-defined radio platform and work with a team of professors and Ph.D. students to build a customized Wi-Fi “chip” for your own!! This project will be built on a European “openwifi” project. The students involved in this project will first understand the ARM and FPGA codes in the “openwifi” project and then modify them for a particular application, e.g., time-critical control of self-driving cars.
For more information about the "openwifi" project, please see the video at https://www.orca-project.eu/openwifi-presented-at-fosdem-2020/. Please contact Prof. CHEN via [email protected] if you want to know more information about the project.
Students with a strong background in Information Engineering, Computer Science Engineering, Electronic Engineering, or Control Engineering are welcomed to apply. Students with strong FPGA programming experiences are particularly encouraged to apply.
WiFi technology is now a part of our daily life. But we normally use it as black-box silicon (chip). Do you want to have an in-depth “know-how” of the inside of the Wi-Fi chip? If you join this project, you will have a chance to understand the full stack of Wi-Fi technology from the user program to the antenna. You will have an opportunity to access the latest system-on-chip software-defined radio platform and work with a team of professors and Ph.D. students to build a customized Wi-Fi “chip” for your own!! This project will be built on a European “openwifi” project. The students involved in this project will first understand the ARM and FPGA codes in the “openwifi” project and then modify them for a particular application, e.g., time-critical control of self-driving cars.
For more information about the "openwifi" project, please see the video at https://www.orca-project.eu/openwifi-presented-at-fosdem-2020/. Please contact Prof. CHEN via [email protected] if you want to know more information about the project.
Students with a strong background in Information Engineering, Computer Science Engineering, Electronic Engineering, or Control Engineering are welcomed to apply. Students with strong FPGA programming experiences are particularly encouraged to apply.
Project 2: Build a Contactless and Continuous Wireless Sensing System for Monitoring Elderly People
The worldwide population over 65 is expected to grow to one billion in 2030 [1]. Every year 33% of elderly people over the age of 65 will fall, and the percentage increases for the elderlies living in care institutions. The fall could cause injuries and a reduction of the quality of life. Fall represents one of the main reasons for the death of elderly people. Many elderlies cannot get up by themselves after the fall, and even without any direct injuries, 50% of those who had a long time of being on the floor (longer than one hour) died within six months after the falling [2]. Therefore, it is vital to continuously monitor the health conditions of the elderly in their living places. The invasive clinical monitoring methods do not lend itself to everyday use in home and community settings. Furthermore, previous studies have reported that the elderly are reluctant to put on wearable devices on a daily basis [3].
In this project, we will develop a comprehensive wireless sensing system, which leverages the current information-carrying RF signals for the contactless and continuous monitoring of the breathing, heart rates, sleeping quality, amounts of exercise (e.g., the time length of standing and sitting), falling of the seniors. Based on these collected big data, we will construct a mathematical model to identify the key reasons for the falling of the elderly or even predict their falling. In doing this, we can provide customized suggestions for individual elderly persons with distinct health conditions to effectively avoid potential falling. This project is featured with wireless signal analysis, activity classification and mathematical modeling, and computer programming. This is a cross-disciplinary project that will involve professors and research students from Information Engineering, and Sports Science and Physical Education.
Students with a strong background in Information/Computer/Electronic/Biomedical Engineering are welcomed to apply. Students with intensive experiences in AI algorithm design and programming are particularly encouraged to apply. Please contact Prof. CHEN via [email protected] if you want to know more information about the project.
[1] Amin, M. G., Zhang, Y. D., Ahmad, F., Ho, K.D.: ‘Radar signal processing for elderly fall detection: The future for in-home monitoring’, IEEE Signal Processing Magazine, 33, (2), 2016, pp.71-80.
[2] A. Khalili, A.-H. Soliman, M. Asaduzzaman, and A. Griffiths, “Wi-Fi Sensing: Applications and challenges,” CoRR, vol. abs/1901.00715, 2019. [Online]. Available: http://arxiv.org/abs/1901.00715.
[3] H Gokalp and M Clarke. Monitoring activities of daily living of the elderly and the potential for its use in telecare and telehealth: a review. Telemedicine journal and e-health: the official journal of the American Telemedicine Association, 19(12):910, 2013.
The worldwide population over 65 is expected to grow to one billion in 2030 [1]. Every year 33% of elderly people over the age of 65 will fall, and the percentage increases for the elderlies living in care institutions. The fall could cause injuries and a reduction of the quality of life. Fall represents one of the main reasons for the death of elderly people. Many elderlies cannot get up by themselves after the fall, and even without any direct injuries, 50% of those who had a long time of being on the floor (longer than one hour) died within six months after the falling [2]. Therefore, it is vital to continuously monitor the health conditions of the elderly in their living places. The invasive clinical monitoring methods do not lend itself to everyday use in home and community settings. Furthermore, previous studies have reported that the elderly are reluctant to put on wearable devices on a daily basis [3].
In this project, we will develop a comprehensive wireless sensing system, which leverages the current information-carrying RF signals for the contactless and continuous monitoring of the breathing, heart rates, sleeping quality, amounts of exercise (e.g., the time length of standing and sitting), falling of the seniors. Based on these collected big data, we will construct a mathematical model to identify the key reasons for the falling of the elderly or even predict their falling. In doing this, we can provide customized suggestions for individual elderly persons with distinct health conditions to effectively avoid potential falling. This project is featured with wireless signal analysis, activity classification and mathematical modeling, and computer programming. This is a cross-disciplinary project that will involve professors and research students from Information Engineering, and Sports Science and Physical Education.
Students with a strong background in Information/Computer/Electronic/Biomedical Engineering are welcomed to apply. Students with intensive experiences in AI algorithm design and programming are particularly encouraged to apply. Please contact Prof. CHEN via [email protected] if you want to know more information about the project.
[1] Amin, M. G., Zhang, Y. D., Ahmad, F., Ho, K.D.: ‘Radar signal processing for elderly fall detection: The future for in-home monitoring’, IEEE Signal Processing Magazine, 33, (2), 2016, pp.71-80.
[2] A. Khalili, A.-H. Soliman, M. Asaduzzaman, and A. Griffiths, “Wi-Fi Sensing: Applications and challenges,” CoRR, vol. abs/1901.00715, 2019. [Online]. Available: http://arxiv.org/abs/1901.00715.
[3] H Gokalp and M Clarke. Monitoring activities of daily living of the elderly and the potential for its use in telecare and telehealth: a review. Telemedicine journal and e-health: the official journal of the American Telemedicine Association, 19(12):910, 2013.