VLDB 2026 Research / reviewers in the wild / expert
Parmida Ghahremani
dblp:247/3995
· DBLP profile ↗
4ranked-venue papers
3as first author
3since 2021 · last 2023
0000-0002-6935-817XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 4 · 3 first-author · 3 since 2021Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
2 papers |
Medical and health informatics · 67% Bioinformatics and computational biology · 33% | |
| Computer graphics and multimedia
2 papers |
Virtual and augmented reality · 45% Visualization and visual analytics · 34% Rendering · 21% | |
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 100% |
Topics — the 7 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics
computational pathology |
0.6 | 1 | 2022 | DeepLIIF: An Online Platform for Quantification of Clinical Pathology Slides · CVPR 2022 |
Medical and health informatics › medical imaging
medical image analysis |
0.6 | 1 | 2022 | DeepLIIF: An Online Platform for Quantification of Clinical Pathology Slides · CVPR 2022 |
Bioinformatics and computational biology › neuroscience
neuroinformatics |
0.6 | 1 | 2022 | NeuroConstruct: 3D Reconstruction and Visualization of Neurites in Optical Microscopy Brain Images · IEEE Trans. Vis. Comput. Graph. 2022 |
Virtual and augmented reality › navigation
immersive navigation |
0.4 | 1 | 2019 | Exploration of Large Omnidirectional Images in Immersive Environments · VR 2019 |
Immersive interaction › virtual reality locomotion
teleportation |
0.4 | 1 | 2019 | Exploration of Large Omnidirectional Images in Immersive Environments · VR 2019 |
Rendering
hybrid rendering |
0.2 | 1 | 2022 | NeuroConstruct: 3D Reconstruction and Visualization of Neurites in Optical Microscopy Brain Images · IEEE Trans. Vis. Comput. Graph. 2022 |
Visualization and visual analytics
volume visualization |
0.2 | 1 | 2022 | NeuroConstruct: 3D Reconstruction and Visualization of Neurites in Optical Microscopy Brain Images · IEEE Trans. Vis. Comput. Graph. 2022 |
Methods — techniques the papers use, named apart from their topics
image registration · 1.1convolutional neural network · 1.1user study · 0.8peek then warp · 0.8auto-scaling · 0.8multiplex immunofluorescence · 0.6isosurface rendering · 0.6iso-surface rendering · 0.6deep learning · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment
Parmida Ghahremani, Joseph Marino, Juan Hernandez-Prera, Janis V. de la Iglesia, Robbert J. C. Slebos, Christine H. Chung, Saad Nadeem |
MICCAI (6) | 1 |
| 2022 | DeepLIIF: An Online Platform for Quantification of Clinical Pathology SlidesabstractIn the clinic, resected tissue samples are stained with Hematoxylin-and-Eosin (H&E) and/or Immunhistochemistry (IHC) stains and presented to the pathologists on glass slides or as digital scans for diagnosis and assessment of disease progression. Cell-level quantification, e.g. in IHC protein expression scoring, can be extremely inefficient and subjective. We present DeepLIIF (https://deepliif.org), a first free online platform for efficient and reproducible IHC scoring. DeepLIIF outperforms current state-of-the-art approaches (relying on manual error-prone annotations) by virtually restaining clinical IHC slides with more informative multiplex immunofluorescence staining. Our DeepLIIF cloud-native platform supports (1) more than 150 proprietary/non-proprietary input formats via the Bio-Formats standard, (2) interactive adjustment, visualization, and downloading of the IHC quantification results and the accompanying restained images, (3) consumption of an exposed workflow API programmatically or through interactive plugins for open source whole slide image viewers such as QuPath/ImageJ, and (4) auto scaling to efficiently scale GPU resources based on user demand. Parmida Ghahremani, Joseph Marino, Ricardo Dodds, Saad Nadeem |
CVPR | 1 |
| 2022 | NeuroConstruct: 3D Reconstruction and Visualization of Neurites in Optical Microscopy Brain ImagesabstractWe introduce NeuroConstruct, a novel end-to-end application for the segmentation, registration, and visualization of brain volumes imaged using wide-field microscopy. NeuroConstruct offers a Segmentation Toolbox with various annotation helper functions that aid experts to effectively and precisely annotate micrometer resolution neurites. It also offers an automatic neurites segmentation using convolutional neuronal networks (CNN) trained by the Toolbox annotations and somas segmentation using thresholding. To visualize neurites in a given volume, NeuroConstruct offers a hybrid rendering by combining iso-surface rendering of high-confidence classified neurites, along with real-time rendering of raw volume using a 2D transfer function for voxel classification score versus voxel intensity value. For a complete reconstruction of the 3D neurites, we introduce a Registration Toolbox that provides automatic coarse-to-fine alignment of serially sectioned samples. The quantitative and qualitative analysis show that NeuroConstruct outperforms the state-of-the-art in all design aspects. NeuroConstruct was developed as a collaboration between computer scientists and neuroscientists, with an application to the study of cholinergic neurons, which are severely affected in Alzheimer's disease. Parmida Ghahremani, Saeed Boorboor, Pooya Mirhosseini, Chetan Gudisagar, Mala Ananth 0001, David Talmage, Lorna Role, Arie E. Kaufman |
IEEE Trans. Vis. Comput. Graph. | 1 |
| 2019 | Exploration of Large Omnidirectional Images in Immersive EnvironmentsabstractNavigation is a major challenge in exploring data within immersive environments, especially of large omnidirectional spherical images. We propose a method of auto-scaling to allow users to navigate using teleportation within the safe boundary of their physical environment with different levels of focus. Our method combines physical navigation with virtual teleportation. We also propose a “peek then warp” behavior when using a zoom lens and evaluate our system in conjunction with different teleportation transitions, including a proposed transition for exploration of omnidirectional and 360-degree panoramic imagery, termed Envelop, wherein the destination view expands out from the zoom lens to completely envelop the user. In this work, we focus on visualizing and navigating large omnidirectional or panoramic images with application to GIS visualization as an inside-out omnidirectional image of the earth. We conducted two user studies to evaluate our techniques over a search and comparison task. Our results illustrate the advantages of our techniques for navigation and exploration of omnidirectional images in an immersive environment. Seyedkoosha Mirhosseini, Parmida Ghahremani, Sushant Ojal, Joseph Marino, Arie Kaufrnan |
VR | 2 |