Vansh Vig

Phone: +1-646-***-**** Email

Newark, NJ LinkedIn

EDUCATION:

• Master of Science (MS), Computer Science (09/2023 – 05/2025) New Jersey Institute of Technology.

• Bachelor of Technology (B. Tech), Computer Science and Engineering (08/2018 – 06/2022) Chandigarh Engineering College, affiliated with Punjab Technical University. SKILLS

• PROGRAMMING/SCRIPTING LANGUAGES and FRAMEWORKS: Python, R, SQL, Scala, Tensorflow, PyTorch, Linux, Java, Javascript, C++, Git, React.

• CLOUD STACK: Databricks, Power BI, Snowflake, AWS Sagemaker, Tableau, Hadoop.

• TOOLS: Jira, Jupyter notebook, Google Colab, Spark, Anaconda, MySQL, Eclipse, Pickle, R Studio, Matlab. WORK EXPERIENCE:

Event Technical Manager at New Jersey Institute of Technology (USA) (10/2023 - Present)

• Led a ticket sales team for a concert show, surpassing the sales figures of the previous year through strategic planning and marketing. Filled up over 90% of the seats.

• Ensured proper functioning of multimedia presentation and speaker systems for a PhD conference. Coordinated pre- event checks and troubleshooting for any issues.

• Managed the installation of MATLAB and OpenCV for a workshop on 10 + computers for a Image Processing and Engineeing workshop.

Software Engineering Intern at Goodera I.T. Pvt. Ltd. (10/2021 – 05/2022)

• Conducted thorough testing of Software products and processes to identify errors / defects and resolved them (React, Jest, Enzyme, Python, PyTest and Flask). Used Pickle to exchange data between different networks and 2 different webpages stored on the python files.

• Engineered test cases as issues on Jira for testing. Managed the test cases scripts using Git Version Control. Reported 10 + issues and bugs in the code to software developers in order to improve the software.

• Deployed 2 web applications on local host and connected to MySQL via JDBC. Controlled the web applications using Javascript. Created a database on MySQL and executed complex queries to fetch complex patterns.

• Developed test plans, test cases and test reports to track testing progress. Worked closely with developers, product managers and other team members to understand requirements. Generated an SLA for building 2 web applications.

• Configured an ODBC connection to extract data from Snowflake (1 million+ rows) and used for analysis in Tableau. Generated 5 dashboards for visualizing and reporting. PROJECTS:

Activity Recognition using Accelerometer Sensor Data

• Worked on a Multivariate Timeseries classification model. Engineered 8 features based on timestamps namely

“Hour”, “Minute”, “Second”, “Millisecond”, “Time elapsed”, “Lag Time”, “Cumulative time” (aggregation of activity time) and “Binned Time”. Engineered the model using Databricks workbook, Python and PySpark.

• Visualized timeseries plots to visualize behavior of features over a series of time steps.

• Implemented LSTM and RNN to predict the target class using LeakyReLU and ReLU activation functions and early stopping. Used Cross Entropy loss as the loss function. House price prediction system

• Implemented SVRegressor and Decision Tree Regressor to predict the house prices based on 31 features. Preprocessed, extracted features and computed feature importance using correlation (r > 0.5) and random forest.

• Merged few features to generate new features. Reduced 31 features to 22.

• Obtained 9% better r squared error on SVR, 4% on Decision Tree and 10% on KNN. Twitter Streaming Sentiment Analysis (Natural Language Processing)

• Achieved 91% accuracy for classification of tweets (NLP, RNN, CNN). Defined pipelines to extract twitter data.

• Conducted exploratory data analysis and data modeling on datasets (1.6 million rows). CERTIFICATIONS:

• Python with Machine Learning, Next Algorithms (No Expiry).

• Programming for everybody (Python), University of Michigan (No Expiry).

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