Raghav K Subramanian is a graduate student at the University of California, San Diego seeking a Master of Science in Computer Engineering. He has experience in deep learning frameworks like PyTorch and TensorFlow, as well as skills in Python, C++, Java, SQL, and Perl. His academic projects include implementing object detection models for video analysis and designing a social assistant app. He has worked as a teaching assistant at UCSD and interned at Qualcomm on test flow development and as a DFT engineer.

1. RAGHAV K SUBRAMANIAN
rksubram@eng.ucsd.edu raghavsubramanian rksubram 858-247-9839
EDUCATION
University of California, San Diego La Jolla, California
Master of Science in Computer Engineering; GPA: 3.68/4 Sep’18-May ’20
Vellore Institute of Technology Chennai, India
Bachelor of Technology, Electronics and Communication Engineering; GPA: 8.85/10 July ’12-May ’16
KEY SKILLS
○ Languages: Python, C++, Java, SQL, Perl
○ Deep Learning Frameworks: PyTorch, TensorFlow, Keras
○ Packages: Numpy, Scipy, Scikit-learn, Pandas, OpenCV, Pygame, Unity
○ Git for Version control, Comfortable with Unix environments
○ Familiar with using Jupyter Notebooks, Google Colab and Google Cloud Platform
○ Coursework Focus: Algorithms, Artificial Intelligence, Computer Vision and Language, Software
ACADEMIC PROJECTS
Multi-Object Detection using Convolutional Neural nets Python, Pytorch, OpenCV
○ Implemented a Single Shot Detector and a Denoising CNN for a 4k New York walking tour video
○ Identified a 33% increase in precision(mAP) score by cascading SSD and DnCNN architectures
Finalist at Hackmobile - Qualcomm’s Intern Hackathon Python, Android Studio, Java
○ Designed a Social Assistant app to connect people based on common interests for Bose AR glasses
○ Created data pipeline to extract employee records, recommend connections and detect faces
Optimizing AppSAT attacks using modified CNNSAT Neural nets Python, Pytorch, Bash
○ Implemented a modified CNNSAT architecture to optimize Boolean Satisfiability problem solving
○ Wrote scripts to extract data from SAT/UNSAT problems, splicing this for the neural network
Open source contribution to TreeCluster tool Python, Pandas, Numpy, Scipy
○ Contributed a python utility to cluster genetic data using the right phylogenetic distance measure
Ensemble Creation for Adversarial Resilience Python, PyTorch, Scipy
○ Designed a Support Vector Machine(SVM) using image features extracted from a Neural network
○ Implemented multiple clustering and sampling methods to create adversarially resilient ensembles
WORK EXPERIENCE
Teaching Assistant University of California, San Diego Fall ’19
○ Teaching assistant for Machine Learning in Image Processing, for a class of 150 students
Test Flow Development Intern Qualcomm Inc. Summer’19
○ Contributed to production code for memory test flow, with scripts to benchmark tools and tests
DFT Engineer Qualcomm Inc. July’16-June’18
AWARDS AND ACHIEVEMENTS
○ Mini-MBA in Technology management from Rady School of Management, UCSD
○ Institute of Global Entrepreneur fellow for Technology Management and Entrepreneurship, UCSD