Malhar Mangtani

Dynamic AI/ML Research Intern with proven expertise at Laurentian University, specializing in deep learning models for medical imaging. Achieved high precision in nuclei segmentation using TensorFlow. Strong analytical skills complemented by effective collaboration in team environments, driving impactful contributions to AI-driven solutions in education at USICAMM, Mexico.

• Awarded Best Presentation and published research paper “Malaria Parasite Detection in Thin Blood Smear Images Using ConvNeXt with Explanations” in the Explainable AI for Computational Intelligence session at ICETCI 2025.
• Participated in the International Experience Program (Canada).
• Worked as AI Research Intern at USICAMM, Mexico, contributing to an AI-driven teacher management platform.

🔹 American Sign Language Recognition System

• Built a real-time sign language recognition model using CNNs & LSTMs.
• Enabled gesture-to-text translation for improved communication accessibility.

🔹 Real-Time Face and Hand Recognition with Finger Count

• Implemented a recognition system integrating facial features and hand gestures.
• Built finger-counting module for real-time human-computer interaction.

🔹 Emotion Detection using Deep Learning Algorithms

• Designed an EfficientNet-based model for real-time webcam emotion recognition.
• Achieved high accuracy on a 6-class dataset with confusion matrix & reports.

🔹 Malaria Parasite Detection in Thin Blood Smear Images (Research Paper)

• Proposed ConvNeXt-based model with Grad-CAM++ for explainable malaria detection.
• Research paper accepted at ICETCI 2025, Hyderabad, awarded Best Presentation.

🔹Synthetic CT Generation from MRI using GAN for Radiotherapy Applications (Ongoing)

• Developing a 3D GAN-based pipeline for MRI-to-CT synthesis.
• Evaluating results with SSIM, PSNR, MAE, aiming for radiotherapy treatment planning.