About
- Head of Data Science at Xsell Technologies, Chicago, IL, with 10+ years of industry…
Experience
Education
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Illinois Institute of Technology
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Activities and Societies: Bridges International, Circle K. International
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Activities and Societies: Event Organizer , Extra-curriculars
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Licenses & Certifications
Volunteer Experience
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Student Volunteer
Circle K International
- Present 8 years
Social Services
Provide Volunteer service to serve Friday dinner to homeless at St, Teresa of Avila parish.
Courses
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Advanced Data Mining
CS 522
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Advanced Database Organization
CS 525
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Big Data
CS 595
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Computer Networks
CS542
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Data Mining
CS422
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Data Preparation & Analysis
CSP 571
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Natural Language Processing
CS 585
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Online Social Network Analysis
CS579
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Science of Programming
CS 536
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Software Project Management
CS 587
Projects
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Auto Summarization of Text using Lexical Chains (Python, NLP)
Takes a text file as input and outputs the set of lexical chains in the text. Using the lexical chains it automatically creates a summary of the input article.
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Sentiment Analysis and Recommendation System (Python)
Built a text classifier to determine whether a movie review is expressing positive or negative sentiment. The data came from the website
IMDB.com. After that implemented a content based recommendation-algorithm using list of genres for a movie as the content. -
Document Clustering using different topic modelling techniques( Python )
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Document clustering or text clustering is an application of cluster analysis to textual documents. Using this clustering mechanism and its different implementations we will focus on modelling topics and clustering the documents based on these topics. The main aim of this project is to provide an overview of some widely-used document clustering techniques. We will compare three different techniques viz. Latent Dirichlet Allocation (LDA), Latent Semantic Analysis (LSA) and Word2Vec and, analyze…
Document clustering or text clustering is an application of cluster analysis to textual documents. Using this clustering mechanism and its different implementations we will focus on modelling topics and clustering the documents based on these topics. The main aim of this project is to provide an overview of some widely-used document clustering techniques. We will compare three different techniques viz. Latent Dirichlet Allocation (LDA), Latent Semantic Analysis (LSA) and Word2Vec and, analyze our results to learn which technique is better. For better analysis, we will be working over 2 datasets: Enron Email Dataset and Yelp Dataset, to carry out experiment on multiple different topics.
Other creators -
Real Time Data Analysis using Github Data in Python.
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Using Python fetched real time data for top 10 most popular users from Github using GitHub API to perform community detection and create recommendation system using Python. The aim is to recommend new repositories to a user that he/she can mark as star per their interest. Four scripts were created to implement this: Data collection, Clustering data, Recommendation system, and Summary.
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Collecting a Political Social Network using Twitter API in Python
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Used Twitter API to construct a social network for 4 U.S. presidential candidates using their account information. Fetched interesting information such as their friends/followers/following to construct a better network using own analysis. Used libraries such as Networkx, Matplotlib to plot the links between them and print some stats of resulting graph.
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Pharmaceutical and Life Sciences (P&LS) industry
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As the core of solution implementation, this project utilized multiple facets of advanced analytics (i.e., predictive modeling, statistical algorithms, data-driven segmentation, real-time scoring, etc.) to dramatically change the way our customer conducted their sales and marketing efforts. I was an integral part of – both in solution development as well as application maintenance), Software Group (Analytics product support for IBM SPSS suite of products) and IBM Cloud Services (Infrastructure…
As the core of solution implementation, this project utilized multiple facets of advanced analytics (i.e., predictive modeling, statistical algorithms, data-driven segmentation, real-time scoring, etc.) to dramatically change the way our customer conducted their sales and marketing efforts. I was an integral part of – both in solution development as well as application maintenance), Software Group (Analytics product support for IBM SPSS suite of products) and IBM Cloud Services (Infrastructure provision and management of the platform, on which the entire solution implementation was hosted). Managed enormous data bases along with managing incremental periodical data load on top of history. I was involved in the analysis of the source system data, Designing and restructuring of the systems and jobs to incorporate the new data and development of the new code.
Honors & Awards
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Manager's Choice Award
IBM India Pvt. Ltd.
Honored with Manager's Choice Award thrice during my tenure in IBM. Twice for the practice “Put the client First” and once for the practice “Show personal interest”
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Deep Skills Award for Inforsphere Datastage.
IBM India Pvt. Ltd.
Languages
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English
Full professional proficiency
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