Page Not Found
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Page not found. Your pixels are in another canvas.
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Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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About me
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About me
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Archive Layout with Content
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Mandira Sawkar
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Markdown
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This is a page not in th emain menu
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Page Archive
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Portfolio
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Projects
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Publications
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Posts by Tags
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Talk map
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Talks and presentations
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Teaching
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Terms and Privacy Policy
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Blog posts
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Jupyter notebook markdown generator
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Posts
Future Blog Post
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This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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Blog Post number 3
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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Blog Post number 2
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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Blog Post number 1
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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projects
getPaid
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Created a SparkML RandomForest model to predict total employee compensation. Queried data with SparkSQL, ran PySpark scripts to run EDA, pre-process data, and train model achieving with 0.98 R2 score.
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Cancer Detection as a Microservice
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Trained a Voting Classifier to predict cancer type with the Wisconsin Breast Cancer Dataset. Hosted the model as a Flask-based microservice running within a Docker container.
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Product Shipping Status Classifier
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Created a RandomForest model to predict issues in the product supplychain which might delay product shipment to customers. Employed PCA and LDA optimization for visualization and dimension reduction. RandomForest model achieved accuracy of 97% (with PCA) and 92% (with LDA).
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Interpretable Parking Ticket Location Classifier
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Built a SparkML RandomForest classifier to predict the police-precinct of ticketed vehicles using the NYC parking-ticket dataset. Used PySpark for parallel computation. Achieved 98% accuracy, and identified police precincts with anomalous ticketing practices.
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AI Alignment in Criminal Justice - Fair Jury Selection and Deliberation
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Created a theoretical hybrid model for fair jury selection and intra-jury deliberation using optimization and game theory with a novel extension to nash equilibrium.
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LLM-as-a-SupremeCourt-Judge
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Developed an AI framework with LLMs (GPT API, fine-tuning, chain-of-thought reasoning) to evaluate 200+ Supreme Court cases, revealing how factors such as panel size, prompting strategies, and ideology personas influence alignment between LLM reasoning and human judges.
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Detecting Deception: Intelligent Systems for Fighting Misinformation
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Designed a logic-gated fact-checking system integrating RoBERTa classifiers with contradiction detection, validated on 7,200+ claims. Improved explainability and reliability by maintaining 83% accuracy while enabling selective overrides for low-confidence predictions.
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Beyond Hallucinations: A Multi-Agent Approach To Fact-Checked AI Knowledge
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Developed a theoretical framework consisting of multiple LLM agents producing verifiable responses through debate and consensus.
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Two Centuries of Sexism in British Parliament: A Computational Analysis of Women’s Representation in the Hansard Corpus
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Built an LLM-as-judge pipeline to mine 6.7M UK parliamentary speeches for suffrage debates, achieving stance-classification agreement with human experts (k=0.71) that exceeded inter-annotator agreement itself (k=0.64). Designed a psychology-grounded sexism taxonomy and applied it at corpus scale, quantifying that anti-suffrage speeches were 2.6x more likely to contain sexist rhetoric (54% vs. 21%) and revealing a century-long shift from hostile to benevolent sexism..
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