https://www.linkedin.com/in/priyanka-dighe-96224928
PRIYANKA DIGHE
9450 Gilman Drive, La Jolla, CA 92092
Contact: +1 (858)-231-6716 | Email: pdighe@eng.ucsd.edu
EDUCATION
University of California, San Diego M.S in Computer Science and Engineering (March 2017)
 GPA: 3.9/4.0
 Teaching Assistant for “Design & Analysis of Algorithms”, “Introduction to Java Programming”
BITS Pilani, K.K Birla Goa Campus, India Bachelor of Engineering in Computer Science (June 2013)
 GPA: 9.05/10.00 | Major GPA: 9.48/10.00
TECHNICAL SKILLS
 Programming Languages: Proficient: C, Java, Python, Spark. Moderate: C++; MySQL, Haskell, HTML; Basic: R, XML/XAML
 Operating System: LINUX, Windows, Android, MacOS
 Software and Technologies: Play Framework, Akka, Maven, Hadoop, PSL, LaTeX, Radian6, Visual Studio, Git
COURSES
 Design & Analysis of Algorithms  Learning Algorithms  Probabilistic Reason & Learning
 Principles of Database Systems  Principles of Programming Languages  Latent Probabilistic Models
 Data Mining and Analytics  Operating Systems (U/G)  Parallel Programming (U/G)
WORK EXPERIENCE
Software Engineer Microsoft India Development Center (July 2013 –June 2015)
Part of Word Blue Team, developing next generation Word Applications for Android/Windows platform:
 Worked on enabling ‘Load and Save’ of basic features of the Word document such as text, pictures and ActiveX objects
 Implemented the proofing experience (Spell Check) for Word documents on new platform, as a part of the team.
 Sole owner of ‘Resume Reading’ feature on Windows Universal Platform.
 Redesigned and implemented rendering of Non-Printable Characters (such as paragraph marks, page breaks, line breaks)
 Worked on enabling printing of Word Documents on new Windows platform.
 Implemented scaling logic for galleries like Color Picker, Font & Shape Styles etc. on small form factors across all office
applications (Word/ Excel/ PowerPoint) for Android platform.
Software Engineer Intern Bloomreach, Inc (June 2016 – August 2016)
Part of a team which builds the platform for data ingestion.
 Implemented a configurable and stateless alerting service for the data integration pipeline using Play Framework and
Akka Library. Design was based on the actor model of concurrency, and micro service architecture.
 The alerting service reduced the redundancy of the current system from 60+ alerts per day to 3 alerts per day.
Intern Hewlett Packard (HP) Labs, Bangalore, India (January 2013-June 2013)
Intern, Crowd Cloud Project: “Prediction using social media”
 Built a preliminary stochastic model predicting revenue of HP products based on related online chatter on Twitter and
historic sales data of similar products.
 Implemented and tested a short term model to predict the revenue of the product with 69.5% accuracy
 Extended this approach for long term prediction models using factors such as the sales data from the previous quarters,
popularity of Twitter, characteristics of user behavior on Twitter, and growth & decay of novelty of a topic on Twitter.
ACADEMIC PROJECTS
“Event Detection for Twitter Data using Collapsed Gibbs Sampling for Dynamic Topic Models” (April 2016)
 Identified temporal topics on Twitter and differentiated them from persistent ones by using Dynamic Topic Models with
logistic normal priors on natural parameters and implemented an efficient inference algorithm for Gibbs sampling.
 Performed a quantitative analysis by comparing our model with Naïve Bayes to verify that it gives more coherent topics.
“Multiple String Pattern Matching Algorithms for Matching DNA Sequences” (December 2012)
 Performed a comparative analysis of various string matching algorithms based on parameters such as time complexity,
space complexity and preprocessing time.
“Implementation of FTP and SSH Client and Server Applications Using Socket Programming” (January 2012)
 Implemented FTP and SSH client and server application with directory hierarchy and authentication features and tested it
for regular directory/file operations and upload/download of files of sizes up to 5GB.

PriyankaDighe_Resume_new

  • 1.
    https://www.linkedin.com/in/priyanka-dighe-96224928 PRIYANKA DIGHE 9450 GilmanDrive, La Jolla, CA 92092 Contact: +1 (858)-231-6716 | Email: pdighe@eng.ucsd.edu EDUCATION University of California, San Diego M.S in Computer Science and Engineering (March 2017)  GPA: 3.9/4.0  Teaching Assistant for “Design & Analysis of Algorithms”, “Introduction to Java Programming” BITS Pilani, K.K Birla Goa Campus, India Bachelor of Engineering in Computer Science (June 2013)  GPA: 9.05/10.00 | Major GPA: 9.48/10.00 TECHNICAL SKILLS  Programming Languages: Proficient: C, Java, Python, Spark. Moderate: C++; MySQL, Haskell, HTML; Basic: R, XML/XAML  Operating System: LINUX, Windows, Android, MacOS  Software and Technologies: Play Framework, Akka, Maven, Hadoop, PSL, LaTeX, Radian6, Visual Studio, Git COURSES  Design & Analysis of Algorithms  Learning Algorithms  Probabilistic Reason & Learning  Principles of Database Systems  Principles of Programming Languages  Latent Probabilistic Models  Data Mining and Analytics  Operating Systems (U/G)  Parallel Programming (U/G) WORK EXPERIENCE Software Engineer Microsoft India Development Center (July 2013 –June 2015) Part of Word Blue Team, developing next generation Word Applications for Android/Windows platform:  Worked on enabling ‘Load and Save’ of basic features of the Word document such as text, pictures and ActiveX objects  Implemented the proofing experience (Spell Check) for Word documents on new platform, as a part of the team.  Sole owner of ‘Resume Reading’ feature on Windows Universal Platform.  Redesigned and implemented rendering of Non-Printable Characters (such as paragraph marks, page breaks, line breaks)  Worked on enabling printing of Word Documents on new Windows platform.  Implemented scaling logic for galleries like Color Picker, Font & Shape Styles etc. on small form factors across all office applications (Word/ Excel/ PowerPoint) for Android platform. Software Engineer Intern Bloomreach, Inc (June 2016 – August 2016) Part of a team which builds the platform for data ingestion.  Implemented a configurable and stateless alerting service for the data integration pipeline using Play Framework and Akka Library. Design was based on the actor model of concurrency, and micro service architecture.  The alerting service reduced the redundancy of the current system from 60+ alerts per day to 3 alerts per day. Intern Hewlett Packard (HP) Labs, Bangalore, India (January 2013-June 2013) Intern, Crowd Cloud Project: “Prediction using social media”  Built a preliminary stochastic model predicting revenue of HP products based on related online chatter on Twitter and historic sales data of similar products.  Implemented and tested a short term model to predict the revenue of the product with 69.5% accuracy  Extended this approach for long term prediction models using factors such as the sales data from the previous quarters, popularity of Twitter, characteristics of user behavior on Twitter, and growth & decay of novelty of a topic on Twitter. ACADEMIC PROJECTS “Event Detection for Twitter Data using Collapsed Gibbs Sampling for Dynamic Topic Models” (April 2016)  Identified temporal topics on Twitter and differentiated them from persistent ones by using Dynamic Topic Models with logistic normal priors on natural parameters and implemented an efficient inference algorithm for Gibbs sampling.  Performed a quantitative analysis by comparing our model with Naïve Bayes to verify that it gives more coherent topics. “Multiple String Pattern Matching Algorithms for Matching DNA Sequences” (December 2012)  Performed a comparative analysis of various string matching algorithms based on parameters such as time complexity, space complexity and preprocessing time. “Implementation of FTP and SSH Client and Server Applications Using Socket Programming” (January 2012)  Implemented FTP and SSH client and server application with directory hierarchy and authentication features and tested it for regular directory/file operations and upload/download of files of sizes up to 5GB.