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Siyang Li, a PhD student in MCLab, obtained an intern offer from Google. Congratulations! We have an interview with her about internship hunting.

What is the normal intern hiring procedure and how did you prepare for it?

For internship in big tech companies, usually we can apply online or through internal referral. If the resume review goes well, we can proceed to phone interviews, solving some programming problems. That definitely requires a lot of practice. I spent several months on it last year. After passing the phone interviews, there are team matching interviews and we need to find out the most suitable team to work with. Good communication skills would help. Sometimes, you have to go through several matching interviews before getting an offer.
I did an intern last year at Google and this year I get a returning offer, which is a lot easier as long as one performs well in previous interns.

How was it like working at Google?

My colleagues were quite helpful. My host was always happy to answer any question and I did ask a lot. The working environment was also quite relaxing. You can get free meals and snacks every day. There are also gyms and video game rooms. Now those facilities become a standard in software industry but I think it was Google who started it.

Any suggestions for your fellows?

I think PhD students should be careful about team matching when searching interns. Working on a project closely related the research topic would be an ideal situation; otherwise, it is better to think twice before accepting an offer. Of course, this strategy increases the risk of not getting an offer, so I would suggest starting intern hunting early. Starting early means more [...]

In spring 2016, MCL welcomes a new lab member, Chen Liang. We had an short interview with her.

1. Could you briefly introduce yourself? (Previous research experience, project experience, research interest and expertise)
I am an undergraduate student at USC studying Electrical Engineering at Viterbi school of Engineering and Game animation at School of Cinematic Art. I joined MCL in January 2016.

2. What’s your first impression of USC and MCL?
Every group member is ambitious and passionate about what he or she is doing. MCL is recently researching on a state of art topic in image processing — CNN.
This topic is newly rising and has a lot to explore; Therefore, MCL members are all curiously exploring the potential possibilities by using this method and striving to get new insight into it.

3. What’s your future expectation for MCL?
I expect more academic communications among group members.

In spring 2016, MCL has a new PhD student, Ronald Salloum. We welcomed him and had an interview with him.

1. Could you briefly introduce yourself? (Previous research experience, project experience, research interest and expertise)

I received a B.S. degree in Electrical Engineering from California State Polytechnic University, Pomona. After receiving my B.S. degree, I worked for a few years in the industry as a systems engineer. I am currently pursuing a PhD degree in Electrical Engineering at USC, under Professor Kuo’s supervision. My research interests include machine learning, biometrics, medical imaging, and computer vision.

2. What’s your first impression of USC and MCL?

I was very impressed by how Professor Kuo is able to supervise such a large group of students. He is very enthusiastic about his students’ research work and does an excellent job in motivating the group. Also, I was impressed by how organized and systematic MCL is.

3. What’s your future expectation for MCL?

I am very excited to be joining MCL and look forward to collaborating with other students in the group, enhancing my skills, and broadening my knowledge of various fields, including machine learning, biometrics, and computer vision.

Sachin Chachada, a MCL member, has passed his defense on Jan 14, 2016. Congratulations!
His dissertation title is “Classification and Retrieval of Environmental Sounds”. Speech and music signals have been extensively studied for several decades. Need for Environmental Sound Recognition (ESR) system has picked up the pace in recent years. Environmental sounds are quotidian sounds, both natural and artificial, i.e. sounds one encounters in daily life other than speech and music. In this thesis, Narrow Band Time Frequency features are proposed which characterize a signal using TF representation of its band limited filtered signal. In order to further improve the performance, use of a novel multi-classifier approach, Para-Boost (PB) model, is proposed. It takes the advantages of all the features and improves the overall performance of ESR system. Finally, considering the exponential growing environmental sound data on the Internet, the thesis tackles the problem of a good content based retrieval system. A two stage content based environmental sound retrieval system is proposed. This query-by-example retrieval system assumes that the database is partially labeled. In Stage I, a broad categorization of environmental sounds based on their signal-characteristic is done. For each category, a classifier is trained to predict labels for unlabeled data in the database and also narrow search range for a query by assigning it multiple, yet limited, class labels. In Stage II, a novel feature and a scoring scheme to do local matching and ranking is proposed. An audio signal is first segmented in an unsupervised manner using Mean Shift algorithm and each segment is represented by its point of convergence in the feature space. The audio signal is finally represented by its energy distribution over each segment thereby capturing the temporal variations [...]

Longguang (William) Song, a USC graduate, recently obtained a full-time offer from Google. Congratulations!

William obtained his MS and BS degree from USC and Beijing University of Posts and Telecommunications in 2015 and 2013, respectively. During his study at USC, he conducted directed research on video/image quality assessment at MCL.

1. How did your graduate study at USC and DR experiences at MCL help you? (technically and psychologically)

The experiences of studying at USC and joining MCL change the way I think of everything. I have learnt a lot from Professor Kuo’s class as well as his insightful talks, which are really eye opening. Another great thing is that I have met lots of smart and friendly people here. Some of them become my best friends.

2. What was the hardest time during job hunting and how did you overcome it?

Looking for a job is tough, at least for me. The worst thing I have is that I didn’t get a single interview for almost three months, I was really frustrated. Thanks to my friends, they gave me lots of support so that I can keep going. So be nice to your friends.

3. Suggestions to current graduate students? (e.g. interview strategy and preparation, etc.)

I suggest students who want to find a job here start preparing as soon as possible. It will be helpful if you can gain some research and internship experience. In addition, interview is a communication process. Be sure to practice how to talk clearly about yourself and you ideas.

I hope all of you can enjoy your life here.