Demo Data from EDBT 2026 / reviewers in the wild / expert
Christopher S. Chen
dblp:134/9704
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0003-2445-8449ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1 · 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.
| Artificial intelligence
1 paper |
Robot manipulation · 50% Video understanding and tracking · 50% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Video understanding and tracking › object tracking › 3d object tracking
depth-based object tracking |
0.2 | 1 | 2013 | Three-dimensional, automated magnetic biomanipulation with subcellular resolution · ICRA 2013 |
Robotics › Robot manipulation › micromanipulation
magnetic manipulation |
0.2 | 1 | 2013 | Three-dimensional, automated magnetic biomanipulation with subcellular resolution · ICRA 2013 |
Methods — techniques the papers use, named apart from their topics
depth tracking algorithm · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Sarc-Graph: Automated segmentation, tracking, and analysis of sarcomeres in hiPSC-derived cardiomyocytesabstractA better fundamental understanding of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) has the potential to advance applications ranging from drug discovery to cardiac repair. Automated quantitative analysis of beating hiPSC-CMs is an important and fast developing component of the hiPSC-CM research pipeline. Here we introduce "Sarc-Graph," a computational framework to segment, track, and analyze sarcomeres in fluorescently tagged hiPSC-CMs. Our framework includes functions to segment z-discs and sarcomeres, track z-discs and sarcomeres in beating cells, and perform automated spatiotemporal analysis and data visualization. In addition to reporting good performance for sarcomere segmentation and tracking with little to no parameter tuning and a short runtime, we introduce two novel analysis approaches. First, we construct spatial graphs where z-discs correspond to nodes and sarcomeres correspond to edges. This makes measuring the network distance between each sarcomere (i.e., the number of connecting sarcomeres separating each sarcomere pair) straightforward. Second, we treat tracked and segmented components as fiducial markers and use them to compute the approximate deformation gradient of the entire tracked population. This represents a new quantitative descriptor of hiPSC-CM function. We showcase and validate our approach with both synthetic and experimental movies of beating hiPSC-CMs. By publishing Sarc-Graph, we aim to make automated quantitative analysis of hiPSC-CM behavior more accessible to the broader research community. Bill Zhao, Christopher S. Chen, Emma Lejeune |
PLoS Comput. Biol. | 3 |
| 2013 | Three-dimensional, automated magnetic biomanipulation with subcellular resolutionabstractIn our previous work we introduced the inverted MiniMag, a magnetic manipulation system capable of 5 degree-of-freedom (5-DOF) wireless control of micro- and nano structures. In this work, we implement a depth tracking algorithm to provide feedback on the z-position of manipulated particles in the absence of a side camera. We demonstrate 3D closed-loop servoing of magnetic microbeads along predefined trajectories. We successfully position magnetic microbeads functionalized with antibodies in close proximity to macrophages with sub-cellular resolution and record the phagocytosis of the beads. We also show that the system can be used for 3D targeted microtissue manipulation inside microfabricated devices. Simone Schürle, Mahmut Selman Sakar, Alessandro Meo, Jens Möller, Bradley Kratochvil, Christopher S. Chen, Viola Vogel, Bradley J. Nelson |
ICRA | 6 |