 | 2020 Github Repo | Report We introduce SeqCapsGAN, a stylized image captioning framework that combines Generative Adversarial Networks and Capsule Networks to generate human-like captions with sentiment, outperforming baseline models on key evaluation metrics. |
 | 2020 Github Repo | Report We introduce EMG-Caps, a framework for hand gesture classification using Capsule Networks on sEMG signals from the NinaPro DB5 dataset, demonstrating that CapsNets outperform conventional classifiers and other deep learning methods—achieving up to 93.27% accuracy across 53 hand movements. |
 | 2019 Github Repo | Report We performed data acquisition and preprocessing, designed and evaluated classification systems using both conventional and neural network–based pattern recognition methods in TensorFlow and Keras, and implemented a real-time operating 6-DoF robot arm. |
 | 2019 Github Repo We implemented trajectory planning algorithms (RRT/RRT*) in C++, simulated and evaluated their performance in both simple and challenging scenarios, and conducted real-world testing on the NAO robot using ROS. |
 | 2019 Github Repo We developed Hand Gesture Controlled Obstacle Avoiding Robot, implementing embedded programming in C++ on an Atmega328P microcontroller, sensor signal processing with a 6DoF IMU, ultrasonic and IR sensors, actuation control for servos, gear motors, and vibration motors, and a custom communication protocol for a radio transmitter/receiver module. |
 | 2019 Github Repo In this project, we presented a system for predicting opening weekend box office sales from movie trailers by combining metadata (e.g., actors, studio, genre) with audio-visual features (e.g., spectrograms, colors, emotions), and implemented a frontend that enables users to run predictions on arbitrary YouTube trailers. |
 | 2018 Github Repo This thesis introduces CapsGAN, a generative modeling framework that integrates capsule networks into the GAN discriminator to better preserve spatial relationships, evaluates different CapsGAN architectures and routing algorithms, and demonstrates that dynamic routing improves training stability and sample quality compared to standard GAN approaches. |
 | 2018 Github Repo In this project, we develop a deep learning–based learnable filter to enhance the CT image reconstruction pipeline for improved image quality and reconstruction accuracy. |