Hi! I am a fifth-year Ph.D. student at the Computer Science Department at University of Maryland College Park, advised by Prof. Heng Huang. Previously, I was a Ph.D. student at ECE Department at University of Pittsburgh before our group moving to UMD.

My research interests are generative modeling and making deep neural networks efficient and deployable in real-world applications. I am also interested in automated medical image analysis.

I spent Summer 2023 as a research scientist intern at Adobe Research, Seattle, where I worked on architectural efficiency of diffusion models and was fortunate to have Yan Kang, Yuchen Liu, Richard Zhang, and Zhe Lin as my mentors. I was also a Deep Learning Intern at Enlitic in Summer 2021.

I got my Bachelor of Science (B.Sc) from University of Tehran, working with Dr. Reshad Hosseini on 3D Reconstruction of Symmetric Structures where I was a member of Computational Audio-Vision Lab.

News

  • [Nov. 2023] Our paper, “Compressing Image-to-Image Translation GANs Using Local Density Structures on Their Learned Manifold” got accepted to AAAI 2024.
  • [May. 2023] I started my internship as a research scientist intern at Adobe Research.
  • [Nov. 2022] Our paper, “EffConv: Efficient Learning of Kernel Sizes for Convolution Layers of CNNs” got accepted to AAAI 2023.
  • [Jun. 2022] Our paper “Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps” got accepted to ECCV 2022.

Selected Publications

    Alireza Ganjdanesh, Shangqian Gao, Hirad Alipanah, Heng Huang
    The Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024.

    Alireza Ganjdanesh, Shangqian Gao, Heng Huang
    The Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023.

    Alireza Ganjdanesh, Shangqian Gao, Heng Huang
    European Conference on Computer Vision ECCV 2022.

Professional Services

Conference Reviewer: KDD 2020, CIKM 2021, ICLR 2023, CVPR 2023, ICCV 2023, AAAI 2023 Journal Reviewer: TNNLS 2023, American Journal of Human Genetics (AJHC) 2020.