In this year’s AGM, we made a major change. And it went quite smoothly, thanks again (and again) to my efficient society members. So let’s see who are the new faces as our CS excos for the next term, during CS Log Off Night. All of you MUST attend ya
Project # 1
Emotion conveys our cognitive state, guides our behavior, and influences our motivation. Users of psychoactive drugs (e.g., amphetamine, cannabis, and opioid) usually show some emotional impairment as a result of brain damages caused by these illicit drugs. In Malaysia, ketum has been widely used as psychoactive natural substance for its medical and euphoric effects. Although the use of ketum is reported to cause unpleasant psychological withdrawal symptoms in regular ketum users, to date, information on emotional impairment among ketum users has not been explored and scientifically investigated.
In general, there are different methods that are used for detecting the emotional impairment such as EEG, fMRI, and EMG. However, all of these equipment are costly, require constant expert monitoring, and more importantly, obstrusive. Prior studies demonstrated that gaze movements could reveal how people process emotional cues such as facial expressions. Hence, this project aims at exploring an alternative automatic seamless and unobtrusive measuring tool based on analyzing the gaze movements of ketum users. Advances in deep machine learning is going to be utilized to detect, track and analyze ketum users and non-users to establish an automatic and reliable model to detect the emotional impairment in ketum-users.
This project will be performed in close collaboration with drug center experts and postgraduate researchers. The applicant would be required to review the recent studies about emotion processing in psychology and emotion detection in computer science, collect data from ketum users, implement techniques for gaze detection and publishing.
Project Duration: 1 year
Starting: Jan 2016 (but can already start with literature review)
Project # 2
Cyanobacteria or the blue green algae are known for their capability to produce toxic secondary metabolites termed cyanotoxins. These toxins are responsible for human health problems and animal poisonings worldwide, ranging from skin irritation to more harmful effects such as organ failure. Cyanobacteria can be confused with true algae or water weeds and this confusion may have obscured early detection of its toxic bloom. Early detection of toxic bloom requires rapid identification of cyanobacteria in water resources. By far, phenotypic evaluation is the simplest approach proven to be useful for instant detection of the presence of toxic cyanobacteria. However, lack of knowledge in cyanobacteria taxonomy, as well as locally available expertise, and lack of samples to be identified often led to the misidentification of this type of algae. This warrants for a method to automatically identify of cyanobacteria using an array of available but limited features.
This interesting project will be carried out under the collaboration with the School of Biological Sciences. The candidate will have a field supervision from an algae expert.
The student is to explore image processing and deep learning and develop a classification system of Cyanobacteria – that would tell Cyanobacteria from other true algae. Only offline modelling is expected, and not online testing (real-time testing). Data will be provided.
JAN 17- SEPT 17 (the prospective candidate can already start before that, if he/she is ready)
I am looking for two more candidates for Internship in Spain. You will be attached the the oldest technical University in Spain.
Same as the previous requirements plus CGPA should be 3.4 . Interns that love programming and development work is strongly encouraged to apply.
The area of work would be in Emotional Speech Synthesis. The period of stay is from Jan (3rd week) – July 2017.
Interested? Then email me at syaheerah AT usm DOT my before 17th October (Monday),
Salam and hi all,
I am looking to have a MSc./PhD Students by research for a project under Affective Computing, and a collaborative project with a University in Spain. Specifically it is on analysing emotion of viewers while watching a video clip/TV ads. The study involves expression recognition from a multimodal perspective: multiple cues such as facial, speech, audiovisual features (music etc.). The selected student will be sent for a 5-6-month fully sponsored research stay starting Jan 2017 in Universidad Politecnica de Madrid, Spain. However, for the Masters/PhD tenure, the student will not be sponsored, until a sponsorship is obtained (via MyBrain, grants etc.).
Candidate with the background of CS or EE is preferred.
Interested prospective candidates can check my website www.syaheerah.com to get some ideas on the area of research, email me @ syaheerah AT usm DOT my.
I was flooded with questions such as “Can I apply if my CGPA is lower than 3.0”? Well, I have decided to bring it down to 2.6 So please go head and apply! However, coding and CRITICAL THINKING should be your passion!
Also please check out these Fact Sheets about UPM Madrid. Note that although it is stated you would need around 700EUR per month, personally I think that is only if you are staying in an apartment on your own. On a sharing accommodation basis, it should be lower.
Calling all MALAYSIANS to participate in our project! Have a peek at:
Salam dan selamat sejahtera Here you’ll find two simple files for the weka tutorial that we’ll be using:
Weka download here. Pre req is Java VM. Please get the whole pack if you do not have Java installed in your PC.
You can also find my lecture note here: