Jaydeep Rade

Jaydeep Rade

Ph.D. Candidate (2024), 3D Deep Learning | Computer Vision, Iowa State University, Ames, Iowa, USA

About me

I am currently a Ph.D. candidate in the Electrical Engineering department at Iowa State University (ISU), under the guidance of Dr. Adarsh Krishnamurthy and Dr. Anwesha Sarkar. My PhD work primarily focuses on developing deep learning models for generating high-resolution 3D structures across various engineering domains, including structural engineering and computational biology. My current project involves the 3D reconstruction of protein structures from AFM images, leveraging diffusion models and Neural Radiance Fields (NeRFs).

  • Research interests: Deep Learning, Computer Vision, Diffusion Models, Object Detection, 3D Reconstruction, Vision-Language Models, Agentic AI

Before pursuing my Ph.D., I obtained M.S. in 2021 from Iowa State University, with my thesis titled “Deep Learning Frameworks for Structural Topology Optimization”link, supervised by Dr. Adarsh Krishnamurthy and Dr. Soumik Sarkar. In 2018, I graduated with a Bachelor of Technology(B.Tech.) in Electronics Engineering from the Veermata Jijabai Technological Institute (VJTI) in Mumbai, India.

Apart from academics, I have gained industry experience through internships at Bayer Crop Science, where I worked as a Computer Vision Intern, and at ANSYS, where I was a Machine Learning Intern.

Apart from research, I enjoy playing FPS games like CS or Valorant. In my free time I usually watch movies, TV shows. In pleasant weather I love to go for long drives to explore the water bodies or hike on trails. My go to stress buster is cooking and hanging out with friends.

You can find my CV here!

News

  • Won a Graduate Research Excellence Award at Iowa State University, May 2024.

  • Presented a poster at the Biomedical Engineering Society (BMES) 2024 conference, Baltimore, Maryland, USA.

  • Presented a poster at CVPR 2024 Workshop on Deep Learning for Geometric Computing (DLGC), Seattle, Washington, USA.

  • Presented a poster at the 17th U.S. National Congress on Computational Mechanics (USNCCM 2023), Albuquerque, New Mexico, USA.

  • Presented a poster at NeurIPS 2022 Workshop on Machine Learning for Structural Biology (MLSB), New Orleans, Louisiana, USA.