Hariprasad Ravishankar is a Masters student in Electrical Engineering at USC expected to graduate in May 2017. He has work experience in image processing and deep learning at NinePoint Medical and Philips Research. His technical skills include Python, C++, MATLAB, OpenCV, TensorFlow and deep learning frameworks. Some of his projects include implementing LeNet-5 for handwritten digit classification achieving 99.05% accuracy, bag of words object detection using SIFT features, and texture classification using Laws' filter.

1. HARIPRASAD RAVISHANKAR
hravisha@usc.edu • Greater Boston, MA 01821 • (213) 268-3102
EDUCATION __________________________________________________________________________________________________________________________
University of Southern California Expected Graduation: May’ 17
Masters in Electrical Engineering, GPA 3.84/4.0
Coursework: Speech Recognition, Image Processing, Multimedia Systems Design, Pattern Recognition, Digital Signal Processing, Linear Algebra
VIT University, Vellore, India Jul’ 11 – May’ 15
Bachelors in Electronics and Instrumentation Engineering, CGPA 9.13/10
Two-time Awardee of University Merit Scholarship for Academic Excellence
Coursework: Biomedical Instrumentation, Neural Networks and Fuzzy Control, VLSI Design, Process Control, Process Automation
Coursera: Machine Learning by Stanford University on Coursera. Certificate earned on November 8, 2016
SKILLS ________________________________________________________________________________________________________________________________
C++, Python, C, MATLAB, OpenCV, Torch, Lua, Caffe, DIGITS by NVIDIA, Lasagne-Theano package, Linux, TensorFlow, Simulink
WORK EXPERIENCE ___________________________________________________________________________________________________________________
Image Processing Co-op, NinePoint Medical, Inc., Bedford, MA Jan’17 - Present
 Developing a Deep Learning Architecture for efficient segmentation of clinical features in OCT images using Tensorflow
 Designing a custom network based on well-known architectures such as U-Net, Fully Convolutional Net for image segmentation
 Tuning hyper parameter settings to increase efficiency, minimize inference time and memory
 Developing verification scripts and post processing algorithms for offline deployment
Summer Research Intern, Philips Research, Bangalore, India Jun’16 – Jul’16
 Worked on a Deep Learning Approach for Nucleus Segmentation in Cervical Cancer Images
 Implemented Segmentation by Classification and Segmentation using Deconvolution techniques using DIGITS by NVIDIA
 Designed and trained an architecture based on AlexNet and a 2 stage Deconvolution network for segmentation
 The model was successful in detecting and segmenting unseen nuclei with a PPV of 91% and Jaccard Score of 95%, making it a viable technique
for commercial deployment for cancer identification
TECHNICAL PROJECTS ________________________________________________________________________________________________________________
Handwritten Digits Classification and Analysis of LeNet-5 CNN Architecture | Torch | Lua Nov’16
 Constructed the LeNet-5 Architecture using Torch to classify the MNIST dataset
 Performed extensive parameter analysis of different weight initialization schemes, non-linear activation functions, minimization algorithms
 Achieved a top accuracy of 99.05% and a mean Average Precision of 0.993
 Engineered modified LeNet-5 to be robust to Negative MNIST, translated MNIST, and MNIST with complex backgrounds
Bag of Words based Object Detection using SIFT Descriptors | OpenCV | C++ Oct’16
 Extracted SIFT KeyPoints and descriptors of multiple images and clustered to 8 groups using K-means Clustering
 Generated the Bag of Words histogram with 8 bins for each image by computing the intra-group KeyPoint count
 Designed a Nearest Neighbor classifier to classify a new image
Texture Classification and Segmentation | C++ | OpenCV Oct’16
 Implemented the Law’s Filter based Texture Classification algorithm using OpenCV C++ on USC SIPI Texture dataset
 Extracted features based on average energy of filters, and performed dimensionality reduction using PCA
 Unsupervised Classification was performed using K-Means Clustering and accuracy of 100% was achieved
Analysis of Egocentric Videos | Python | OpenCV Mar’ 16 – May’ 16
 Developed an Audio-Video player with functionalities such as pause, play, fast forward and rewind in Python
 Implemented an algorithm to auto-generate a 90 second summary of important moments of video
 Implemented a novel algorithm to render context specific subsection of video for a given photograph input
Pattern Recognition System for Predicting Readmission of Diabetes Patients | MATLAB Apr’16
 Implemented and contrasted Parametric and Non-Parametric classification methods such as Naïve Bayes, Multi-class all-pairs, K Nearest
Neighbors, Minimum Distance to class means etc. to predict the chances of readmission
 Performed detailed data cleaning and feature selection methods such as PCA to identify most relevant features
JPEG and JPEG2000 Standard Implementation| Visual Studio C++ Feb’ 16
 Implemented the DCT-based JPEG compression and Wavelet decomposition-based JPEG 2000 compression in C++
 Analyzed qualitative difference between the two State-of-the-Art techniques through step-wise reduction of Compression ratios
Low Cost Gesture Detector Using Neural Networks| Energia |MATLAB Oct’13 – Jan’ 14
 Designed and developed an award winning Low Cost Gesture Detector prototype
 Implemented the Learning Vector Quantization algorithm in MATLAB for model training and developed the hardware architecture of the device
 Design published in IEEE Xplore and awarded Finalist at the Texas Instruments India Educator’s Conference 2014 amongst 300 teams in India
NOTABLE POSITIONS__________________________________________________________________________________________________________________
 Senator of Ming Hsieh Department of Electrical Engineering at USC representing the Viterbi Graduate Student Association Aug’15 – Dec’15
 English Teacher at Make a Difference, an NGO to impart quality English education to the underprivileged children Aug’14 – Dec’14
linkedin.com/in/hariprasadravi