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Engineering Software Engineer

Location:
Mountain View, CA
Posted:
February 11, 2014

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Resume:

Guru Raghavendra Gorantla

Ph: 217-***-**** accmtz@r.postjobfree.com

summary

• Java, MATLAB & Datawarehousing programmer, with one year prior experience as SWE.

• Experience working on Machine Learning, Computer Vision models such as Facial recognition, Deep learn-

ing models, Text mining etc for academic research & industrial applications.

Education

University of California, San Diego, San Diego, CA. 2012-Present

M.S., Electrical and Computer Engineering.

Thesis: Efficient algorithms for Bayesian Inference using Optimal Transportation approach.

Advisor: Prof. Todd Coleman

National Institute of Technology Karnataka, Suratkal, India.

B.Tech., Electrical Engineering 2007-2011

Thesis: Energy aware routing in Wireless Sensor networks

Advisor: Prof. Ashvini Chaturvedi

Computing Skills

Sometimes: Python, Hadoop, C/C++

Regular: Java, R, MATLAB, Unix, PL/SQL, IBM Data stage;

Experience

Summer Intern, FaceData.com, San Diego, CA, July - Sep 2013

- Facial Feature Extraction: Development & performance analytics of automated facial feature extraction

methods and commercial applications to finding look-alikes and algorithmic evaluation of attractiveness.

- Implemented a novel edge detection algorithm which improved performance of face detection algorithms.

- Resulted in a patent and yet to be released press statement.

- Digital Image processing; Edge recognition; Feature Engineering; Face contour and efficient face component

identification.

- Graduate Researcher, Neural Interaction Lab, UCSD Advisor: Prof. Todd Coleman

- Efficient Bayesian Inference Systems: Research on designing a computationally faster algorithm for

Bayesian inference using Optimal transportation techniques.

- Stochastic gradient descent, L1 regularization, Optimal transportation maps,

- Research Intern, Inst of Neural Computation, UCSD Mentor: Srinjoy Das Aug - Sep 2013

- Feature Extraction with Deep Belief Networks : Implemented Deep Learning models (conditional RBMs

and auto encoders) to extract features for sequence prediction in a gaming system.

- Conditional RBM, stacked auto encoders, Recurrent Neural Networks, connect 4 sequence game, (Python,

Matlab)

- Software Engineer, Mphasis, A HP company Bangalore, India June ’11 - Aug 2012

- Application development that involve handling databases (PL/SQL/IBM Data stage) and interactive UI.

- Teaching Assistant, University of California San Diego La Jolla, CA

- Advanced Data Structures, Engineering Computation.

- Undergraduate Research Intern, University of Illinois Urbana Champaign Urbana, IL

- Built a Brain Machine interface module to control a video game using just the human brain signals.

- P300 Linear classifier, Recording neural activity (EEG signals), Motor Imagery,

Guru Raghavendra Gorantla (2 of 2)

Selected Projects

Machine Learning & Data Mining:

- Sparse Classification Models for Genomics Application

Worked on Genome data set for the prediction of whether a person is suffering from disease or not based on the

SNP dataset provided.

Implemented and performance evaluation of Linear Regression, Subset Selection Methods, Shrinkage Methods

(L1, L2, Partial Least Squares), Principle Component Regression, Logistic Classification, SVMs with Linear &

Nonlinear Separating hyperplanes

- Hand Digit Classification for MNIST dataset

Implemented and analyzed performance of classification models: Linear Classifier, Logistic Classificaiton, K-

Nearest Neighbors, Gaussian Classifier, SVMs, PCA + linear classifier, Regularized linear classifiers (L1, L2).

- Sentiment Analysis with Text Mining over a large Movie review dataset

Used a Bag of words feature representation, with tf-idf over feature vectors and performed Logistic classification

& SVM over the feature set.

- Topic Classification Models for Document Classification (R)

Trained Latent Dirchilet Alloctation model to classify documents into different classes.

- Collabarative Filtering Algorithm for Movie rating prediction

- A statistical analysis of data from a hypothetical anaphor study. (Linguistics)

- Feature Extraction with Deep Belief Networks (Matlab, Python)

Computer Vision & Signal Processing

- Traffic Signal Detection and Rear Lamp detection (Matlab)

- Red Eye detection and Rectification (Matlab)

Programming

- Shopping website (HTML, JSP, JavaScript, AJAX and PostgreSQL)

Created a website allowing customers to browse, purchase products and owners to add/update products, cate-

gories, and observe live sales analytics.

- Boggle Word Game Implementation (C++)

Game was designed to allow player enter words formed by using adjacent letters on the board and each word

checked with the dictionary for a match.

Other:

- Energy aware routing in Wireless Sensor networks

- Application Of Brain Computer Interface to Video gaming

Relevant Course Work

ECE 175 Pattern Recognition & Machine ECE 175A Fundamentals of Image Processing

Learning

CSE 255 Data mining & predictive analysis CSE 151 Digital Signal Processing

ECE 273 Convex Optimization ECE 255 Information Theory

CSE 135 Server-side web applications ECE 251C Filter banks & Wavelets

CSE 100 Advanced data structures LING 251 Probabilistic Methods in Linguistics

Distinctions

• One the 23 research interns selected across the globe for the Information Trust Institute (ITI) Program at

University of Illinois, Urbana Champaign.

• Secured State 1007 Rank among 150,000 students in States Engineering Entrance Exam EAMCET 2007.

• Secured All India Rank 3684 among 550,000 students in All India Engineering Entrance Exam AIEEE 2007.

• Secured All India Rank 3208 among 300,000 students in IIT- Joint Entrance Exam IIT-JEE 2007.

• Ranked among top 10 students at the Electrical Engineering Dept., National Inst. of Technology, Suratkal .



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