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Data Science, Machine Learning, Data Analytics, Programming

Boston, Massachusetts, United States
February 26, 2018

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Boston, MA ***** 617-***-****

Available from May 2018


Northeastern University, Boston, MA May 2018

Candidate for a Master of Science in Computer Science (GPA: 3.5) Courses: AI, Machine Learning, Information Retrieval, Robotic Systems, Parallel Data Processing Amity University, Noida, India June 2014

Bachelor of Technology in Aerospace Engineering


Languages: Java, Python, R Programming, C#, Racket, ACL2s, Shell Scripting, MATLAB, Scala Web Technology Stack: HTML, CSS, Bootstrap, JavaScript, Swing (Java), MySQL Tools: Apache Hadoop, Spark, AWS, Google Cloud Platform, Univa Grid Engine Engineering Software: ANSYS Fluent, Abaqus CAE, CATIA, SolidWorks, AutoCAD, Star-CCM+ WORK EXPERIENCE

Scientific Computing Co-op June 2017 – December 2017 Novartis Institutes for Biomedical Research, Cambridge

• Developed Unsupervised learning techniques for systematic behavior mapping on biological datasets using MATLAB and Python

• Developed Deep Learning Network models such as CNN and RNN for identifying binding signatures in RNA-RBP using Keras and Tensorflow

• Classified jobs submitted on the cluster based on their profile using unsupervised machine learning techniques and performed data visualization using TensorBoard

• Performed image analysis using additive histogram equalization with openCV and basic clustering techniques on multiple cross-sectional images of muscle tissue

• Ran most of the project work in an HPC environment using UGE/SGE Graduate Teaching Assistant (Logic and Computation, Northeastern University) January 2017 – April 2017

• Conducted weekly comprehensive lab sessions for a class of 360 students, assisting students with queries regarding the course and ACL2s programming, and grade their assignments and exams. Graduate Research Assistant (Software Verification, Northeastern University) June 2016 – December 2016

• Implemented an algorithm based on binary search for a SAT Solver tool that finds satisfying assignment for a given propositional expression using Python and improved its performance by more than 60 percent

• Performed unit testing using Bash shell scripts on a Unix-based platform on various polynomial inequalities


Google Cloud and YouTube-8M Video Understanding Challenge January 2017 – April 2017

• Analyzed data using visualization techniques and performed multiclass classification on IPython Notebook

• Developed classifiers (Logistic, Recurrent Neural Network) for predicting the top 5 labels a given video can have on Google Cloud Platform

Information Retrieval Engine December 2016 – January 2017

• Developed a retrieval model using Python consisting of a focused crawler that reads in a corpus, and generates a web index. The results are ranked based on document ranking models such as BM25 and PageRank

ACADEMIC PROJECTS (Northeastern University)

Climate Analysis in MapReduce (Hadoop, Spark, Scala)

• Worked with GHCN weather data to compute average minimum and maximum temperature for a given year at a given station using the MapReduce framework

• Implemented various design patterns such as Combiner, In-Mapper combining and Secondary Sort and compared performances.

Software Development: DBLP Search Engine January 2017 – April 2017

• Created a search engine as an agile project within a team of 4, that enabled browsing for authors based on use cases such as area of expertise, journal/conference name etc. using Java(Backend), Swing(UI), MySQL(Database), Jenkins(Integration)

Robotics: Path Planning on 6-link Robot along with object localization September 2016 – December 2016

• Implemented planning algorithms PRM and RRT for computing path in a non-trivial obstacle environment using MATLAB for a PUMA 560 robot from randomly selected start and goal configurations

• Performed object localization and shape fitting given a point cloud data using Random Sample Consensus Artificial Intelligence: Ms. PacMan Vs. Ghosts January 2016 – April 2016

• Utilized the Ms Pacman-vs-Ghosts Competition Framework in Java to test the AI algorithms

• Implemented the major AI algorithms (primarily, localized search optimization and pathfinding algorithms) that controlled Ms Pacman’s motion


• Founding member and Vice-President of NU Grad Women Coders, a technology-based group at Northeastern

• Passionate about data science, machine learning and its applications in software, healthcare, aviation and education domains

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