Projects by Manas Acharya
Featured Projects
A mix of production systems, machine-learning research, and full-stack tools — built across coursework, internships, and side projects.
JobFlow
AI-powered resume tailoring for every application
Intelligent job application tool with 8-step AI pipeline that generates ATS-optimized resumes and personalized cover letters from any job posting URL.
8-step pipeline with keyword matching, relevance scoring, and ATS optimization
Hilton Invoice Code Finder
Offline invoice classification web app
Pro bono offline-first web app for a Hilton corporate manager. Matches free-text invoice descriptions to 93 GL codes across 10 departments using TF-IDF + cosine similarity in the browser. iPhone-optimized UI; localStorage persistence for use in the field.
DALL-E + SAM Image Editing
Generative pipeline: text → image → mask → inpaint
Three-stage generative-image pipeline combining OpenAI DALL-E 3 for generation, Meta's Segment Anything Model for region selection, and DALL-E's edit endpoint for mask-based inpainting. Demonstrated on a fashion design concept.
1024×1024 generation + SAM segmentation + 3-variant inpainting
Time-Series Retail Sales Forecasting
Daily retail sales forecasting + descriptive analytics
End-to-end pipeline on a year of daily POS data for a small retail client. Compared naive, seasonal-naive, ARIMA, Random Forest, and Gradient Boosting; explored the global-pool approach from Montero-Manso & Hyndman (2021). Paired with a descriptive sales report (day-of-week, seasonal, by-department) delivered to the client.
Gradient Boosting: MAE $494, sMAPE 13.0% — 24% MAE reduction vs ARIMA
La Liga Ranking
Team ranking from match-result averaging
Ranked all 20 teams of the 2020-21 La Liga season from 760 match records. Encoded wins/draws/losses (1, 0.5, 0), pivoted into a team-vs-team matrix, and computed per-opponent average performance. Team project with Jenisha Shrestha and Bipin Bisural.
Top 4 (Atlético, Real Madrid, Barcelona, Sevilla) — exact match to actual 2020-21 standings
Heart Disease Prediction
Clinical prediction model
Cardiovascular risk assessment on the UCI Heart Disease dataset. Team project with Jenisha Shrestha; compared multiple classifiers, with Logistic Regression emerging as the most promising.
0.152 misclassification rate (Logistic Regression)