Letter of recommedation for CS EE related programs
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July 10, 2022 at 5:57 pm
Dear Admission Committee,
It’s with great pleasure that I recommend Mr. Z to your internship program in KUT. In viewing of my direct contact and fruitful collaboration with him, I am confident that Mr. Z would be an excellent applicant.
The primary quality of Mr. Z is his astute insight and understanding. When Mr. Z first contacted me in his early junior year to do researches, I introduced him to the subject of visible-infrared paired dataset for low-light vision(LLVIP). It’s a rather novel topic which concerns image recognition, fusion dataset and Generative adversarial network. Mr. Z grasped the gist of the concepts and algorithms quickly. He was soon able to clearly explain and discuss different approaches, so I assigned him the task of applying SpikingJelly framework in MNIST image recognition. He implemented the algorithms with VGG and ResNet network smoothly and replicated similar outcome as that of the original paper.
In addition, Mr. Z is also diligent. He completed labeling of 400 pictures within one day, even though he was previously unfamiliar with the process. In the Spring semester of 2022, he attended my class named” Theory and Practice of Deep Learning”. Not only did he kept attending class and participating class discussions, but he also submitted his assignments with flying colors. He did more reports than I required, despite his heavy workload of other lessons. In his experiment report, he coherently described the whole experimental process and related theories. For instance, in his experiment on fusion GAN, he compared the results between with and without image preprocessing, and also differences of output due to dataset. In another assignment on Convolution Neural Network, he compared prediction result given different sets of learning rate, number of epochs and VGG configurations. He visualized the training and testing outcome, and added fully connected layers thereby increasing the prediction accuracy on testing CIFAR data to almost 0.91. A student with such devotion would surly become a valuable asset for your academic research.
Another aspect I admire about Mr. Z is his initiative and commitment to academic research. In the middle of this spring semester, he came to me to discuss neuron models and their application in neural networks. He did a comprehensive review on current neuron models ,their simulation and hardware implementation, especially on Hodgkin–Huxley neurons. His review is obviously written meticulously, and as a professor with academic background in electronic hardware and AI algorithms, I am delighted to see that he developed his idea eloquently. Since Hodgkin–Huxley neurons is computationally complicated, it’s really impressive that he came up with his ideas on possible simplifications.
I hold genuine faith in Mr. K Z’s proficiency and academic prospect, and I offer him my highest recommendation. Your positive consideration will be highly appreciated. Should you have questions on Mr. Z’s detailed information, please don’t hesitate to contact me.
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