Charalambos Poullis, Concordia University

Research

appearance modeling and rendering large-scale urban reconstruction LiDAR processing urban feature classification/semantic segmentation generative models geospatial computer vision road extraction semantic segmentation

Latest papers

From data to action in flood forecasting leveraging graph neural networks and digital twin visualization.
Scientific reports · 2024 · senior author
Transductive meta-learning with enhanced feature ensemble for few-shot semantic segmentation.
Scientific reports · 2024 · senior author
Author Correction: Motion estimation for large displacements and deformations.
Scientific reports · 2022 · senior author

All 4 publications

Latest funding

IASO: Enhancing Surgical Precision with Advanced Camera Systems and Artificial Intelligence
NSERC · 2024 · Principal investigator
$117,500
Semantic Segmentation in Geospatial Computer Vision
NSERC · 2021 · Principal investigator
$116,000
PHOENIX: Generative models and Deep Reinforcement Learning for Geospatial Computer Vision
NSERC · 2021 · Principal investigator
$240,000

All 8 grants and awards

4 publications.

01

From data to action in flood forecasting leveraging graph neural networks and digital twin visualization.

Roudbari NS, Punekar SR, Patterson Z, Eicker U, Poullis C

Scientific reports2024Senior author

DOI: 10.1038/s41598-024-68857-y PMID: 39127785

02

Transductive meta-learning with enhanced feature ensemble for few-shot semantic segmentation.

Karimi A, Poullis C

Scientific reports2024Senior author

DOI: 10.1038/s41598-024-54640-6 PMID: 38369571

03

Author Correction: Motion estimation for large displacements and deformations.

Chen Q, Poullis C

Scientific reports2022Senior author

DOI: 10.1038/s41598-022-26246-3 PMID: 36517657

04

Motion estimation for large displacements and deformations.

Chen Q, Poullis C

Scientific reports2022Senior author

DOI: 10.1038/s41598-022-21987-7 PMID: 36385172

IASO: Enhancing Surgical Precision with Advanced Camera Systems and Artificial Intelligence

Principal investigatorNSERC2024Alliance Grants

Principal investigators: Poullis, Charalambos C

Keywords: 3d reconstruction; artificial intelligence; computer-assisted surgical tools; computer vision; multi-sensor fusion; real-time calibration

$117,500

Semantic Segmentation in Geospatial Computer Vision

Principal investigatorNSERC2021Discovery Grants Program - Individual

Principal investigators: Poullis, Charalambos

Keywords: large-scale urban reconstruction; urban feature classification/semantic segmentation; lidar processing; appearance modeling and rendering

$116,000

PHOENIX: Generative models and Deep Reinforcement Learning for Geospatial Computer Vision

Principal investigatorNSERC2021Alliance Grants

Principal investigators: Poullis, Charalambos C

Keywords: generative models; geospatial computer vision; road extraction; semantic segmentation

$240,000

ACESO: Computer Vision Algorithms for Computer-Assisted Surgical Systems

Principal investigatorNSERC2021Alliance Grants

Principal investigators: Poullis, Charalambos C

Keywords: Anomaly detection; Calibration; Evaluation metrics; Reconstruction; Tracking

$120,000

DEADALUS: Massive-scale urban reconstuction, classification, and rendering from remote sensor imagery

Principal investigatorNSERC2017Department of National Defence / NSERC Research Partnership

Principal investigators: POULLIS, CHARALAMBOS

$389,802

Rapid and Automatic Reconstruction of Large-scale Areas

Principal investigatorNSERC2016Discovery Grants Program - Individual

Principal investigators: Poullis, Charalambos

$110,000

Elastic 3D space research workshop exchange

Co-investigatorSSHRC2015Connection Grants

Principal investigators: Sujir, Leila R.

Keywords: stereoscopic 3D; embodied interaction; 3D graphics; expanded drawing practices; art-science collaboration; architectural projections; built environment; media arts inquiry

$25,000

Exploring elastic 3D spaces: bodies and belonging

Co-investigatorSSHRC2015Partnership Development Grants

Principal investigators: Sujir, Leila R.

Keywords: sculptural video art installations; stereographic 3D (S3D); spatialized narratives; gesture based interfaces; 3D drawing; migration; displacement; immigration; narratives; documents; fictions; mythologies

$169,850

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

Frequent collaborators

Computer Science and Software Engineering
Buildings, Civil and Environmental Engineering
Concordia Institute for Information Systems Engineering (CIISE)

Co-authors at Concordia University, colored by department. Thicker lines mean more shared papers; select anyone to open their profile and their own map.

Ursula Eicker

Buildings, Civil and Environmental Engineering

1 shared papers, latest 2024

Zachary Patterson

Concordia Institute for Information Systems Engineering (CIISE)

1 shared papers, latest 2024

Write to this professor

A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.

Applying for

Paper to mentionMention their NSERC grant from 2024

Subject: Prospective PhD student: appearance modeling and rendering Dear Professor Poullis, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. I read your paper "From data to action in flood forecasting leveraging graph neural networks and digital twin visualization." (2024), and it connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your NSERC-funded project "IASO: Enhancing Surgical Precision with Advanced Camera Systems and Artificial Intelligence" (2024), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]