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Projects

Sentence-Level Bias Detection preview

Sentence-Level Bias Detection

Detects sentence-level media bias in news by separating emotion-driven bias from framing-driven bias. Compares sentiment (tone) vs TF-IDF (framing) and uses RoBERTa + classical ML to flag sentences biased through framing even when tone is neutral.

PythonNLPMLTF-IDFSVMRoBERTa

AI Travel Agent

Full-stack travel planning app with a Gemini-powered chat agent. Collects preferences, searches flights and hotels (Booking.com), food and museums (TripAdvisor), and builds an itinerary; sessions and suggestions stored in SQLite.

Prompt engineeringAgentic workflowsLLM orchestration
CartPole DeepRL Benchmark Suite preview

CartPole DeepRL Benchmark Suite

Unified benchmark of deep RL algorithms on CartPole-v1: value-based (DQN), policy-gradient (REINFORCE, Actor–Critic, A2C), and PPO. Each method in its own module with training scripts; shared networks and plotting in PyTorch + Gymnasium.

Deep RLDQNREINFORCEActor-CriticA2CPPO
Network Motif Detection preview

Network Motif Detection

Python implementation of RAND-ESU for sampling connected induced subgraphs (motifs) in large networks. Includes ESA baseline with bias correction, parallel execution, and significance testing with edge-swap ensembles.

RAND-ESUESAMotif samplingParallel execCPython
VAE-GAN-RNN-arithmetic preview

VAE-GAN-RNN-arithmetic

Image generation with VAEs and GANs (CelebA), plus sequence-to-sequence models for arithmetic: text-to-text, image-to-text, and text-to-image (MNIST). Includes latent interpolation and recurrent encoder–decoder experiments.

VAEGANRNNSeq2SeqMNISTCelebA

Surrogate-model-eval

Surrogate model evaluation and model comparison: surrogate_model, IPL, LCCV, and vertical model evaluator for pipeline experiments. Includes comparison scripts and example runners.

AutoMLModel selectionSurrogate modelsPython

Data Mining (ADM)

Advanced Data Mining course project: Python-based data analysis and experimentation with a written report. Covers core data mining concepts and applied analysis.

PythonData analysisResearch
Flappy RL Benchmarks preview

Flappy RL Benchmarks

Procedural Flappy Bird environment with dynamic themes (day, night, hell, space) and RL agents: PPO, DQN, DDQN, SAC. Built in Python with pygame; supports manual play and agent play for evaluating adaptation across difficulty and visuals.

RLPPODQNDDQNSACPython
Pacman Rangers preview

Pacman Rangers

Group project: Python3 Pacman Capture the Flag (UC Berkeley CS 188 style). Design agents for two-team CTF in a Pacman arena—defend your food, steal the opponent’s, use power capsules and limited observations. Custom team logic, tournaments, and MCTS/planning.

Multi-agentSearchStrategyPython
Terrain-Adaptive House Generator preview

Terrain-Adaptive House Generator

Automated pipeline extending GDPC: analyzes a 100×100 terrain slice, selects the flattest build site, and procedurally generates a garden plus a rustic cottage with randomized decorations and terrain visualizations in Minecraft.

Procedural generationTerrain analysisGDPCPython