Akanksha Maurya is pursuing an MS in Computer Engineering at UC San Diego with a GPA of 3.73. She received a B.Tech in Instrumentation Engineering from IIT Kharagpur with a GPA of 8.55. Her experience includes internships at Synopsys and IBM as well as research focused on machine learning algorithms for IoT applications. She has publications in time-series clustering for smart grids and hierarchical static low power verification.

1. Akanksha Maurya
http://mauryaakanksha.github.io
amaurya@ucsd.edu | 858.261.8110
EDUCATION
UC SAN DIEGO
MS, COMPUTER ENGINEERING
Expected Mar 2017 | San Diego,CA
GPA: 3.73
IIT KHARAGPUR
B.TECH, INSTRUMENTATION ENGG.
May 2012 | Kharagpur,India
GPA: 8.55
LINKS
Github:// mauryaakanksha
LinkedIn:// akanksha-maurya
COURSEWORK
GRADUATE
Algorithms
Machine Learning
Distributed Systems
Probabilistic Reasoning
Embedded Computing
Internet of Things
Computer Architecture
UNDERGRADUATE
Programming and Data Structures
Operating Systems
Database Management
Artificial Intelligence
Computer Architecture
Embedded Computing
Signals and Networks
TEACHING
UC SAN DIEGO
• Probability and Statistics
• Embedded Computing
• Digital Design
SKILLS
LANGUAGES
• C • C++ • Java • Python • Tcl
• SQL • HTML • CSS • XSD
TECHNOLOGIES
• Boost • Hadoop • OpenCV
• Theano • RapidJSON • QFile
• Jekyll • CTemplate • Docker
• MySQL • Visual Studio • Eclipse
• Android Studio • Git • Perforce
EXPERIENCE
SYNOPSYS | SOFTWARE ENGINEERING INTERN
June 2016 – Sep 2016 | Mountain View, CA
• C++ code generation based on Pimpl design pattern from a XML model.
• Handles serialization and forward-backward database compatibility.
• Generated +35K lines of C++ code from <4K lines of XML code.
SYNOPSYS | SOFTWARE ENGINEER
June 2012 – Aug 2015 | Bangalore, India
• Developed several static verification features in C++ for enhancement projects
with key customers (Apple, Intel, Qualcomm).
• Implemented an algorithm to extract supply connectivity and apply rule based
search for name mapping.
• Designed an abstract data model for hierarchical verification which reduced the
run-time by ~30%.
• Improved the run time of supply order corruption check by ~90%.
• Wrote Tcl and python scripts for reporting the verification results.
IBM | SOFTWARE ENGINEERING INTERN
May 2011 – July 2011 | Bangalore, India
• Implemented an adapter for cyber-security platform to prevent access violation.
RESEARCH
SYSTEM ENERGY EFFICIENCY LAB | RESEARCHER
Sept 2015 – Present | San Diego, CA
Working with Prof Tajana Rosing on machine learning algorithms for Internet of
Things applications. Mainly focusing on time-series clustering and anomaly detection.
PROJECTS
• DISTRIBUTED FILE SYSTEM with support for replication and locking using a
custom Remote Method Invocation library for JVM.
• UNSUPERVISED FACE CLUSTERING with a Haar feature-based classifier
and a stacked auto-encoder using Theano deep learning framework.
• ENERGY EFFICIENT SCHEDULER with sensor interaction based on Earliest
Deadline First algorithm.
• BRANCH PREDICTOR using perceptron and path based neural prediction.
• SMART HOME MONITORING SYSTEM to monitor energy consumption and
control multiple connected appliances with a central dashboard.
PUBLICATIONS
• Time-Series Clustering for Data Analysis in Smart Grid [IEEE SGComm 2016]
• Hierarchical Static Low Power Verification [DAC 2015]
ADDITIONAL EXPERIENCE AND AWARDS
• Individual Excellence Award by Synopsys India for remarkable performance.
• Go Green In the City 2011 Among the top-25 finalists for the international
B-Plan competition by Schneider Electric , Paris.
• Founding member of Synopsys Lending Library, Bangalore, India
• Classical Kathak 7 years dance training under Prayag Sangit Samiti, Allahabad