Manan Lalit
Machine Learning Researcher at HHMI Janelia Research Campus
Ashburn, Virginia, United States
Summary
👤
Senior🎓
Top SchoolManan Lalit is a machine learning researcher with eight years of experience applying deep learning to bioimage analysis, currently developing methods for segmentation, cell tracking, and lineage tracing of volumetric microscopy at HHMI Janelia. He combines a PhD-level foundation in mathematical modeling and differential equations with hands-on expertise in 3D+t embryonic datasets from his time at MPI-CBG, enabling robust, physics-aware approaches to noisy biological imagery. Earlier work in fluid dynamics and acoustics — including engine exhaust and silencer performance at Scania — gives him an unusual edge in modeling complex spatiotemporal systems and engineering practical solutions. Based in Ashburn, VA, he bridges computational science and developmental biology, translating algorithmic advances into tools that reveal dynamic embryonic processes.
8 years of coding experience
4 years of employment as a software developer
Indian Institute of Technology KanpurDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Technische Universität DresdenMaster of Science, Automotive Engineering, Master of Science, Automotive Engineering at Chalmers University of Technology
Hindi, English, French, Swedish
Stackoverflow
31reputation
4kreached
0answers
1question
Github Skills (65)
deep-learning10
instance-segmentation10
shape-context10
multidimensional10
image-synthesis9
computer-vision8
pipeline8
jupyter-widget8
python8
diffusion-models8
ui-components8
tracking-algorithm8
machine-learning8
gradio-interface7
clustering7
Programming languages (6)
Github contributions (5)
juglab/PPN2V
Dec 2019 - Jan 2021
Parametric, Probabilistic Noise2Void
Contributions:12 commits, 4 PRs, 11 pushes in 1 year 1 month
parametricnoise2voidprobabilistic
funkelab/cellulus
Aug 2023 - Apr 2024
Unsupervised Instance Segmentation in Microscopy
Contributions:8 PRs, 97 pushes, 20 branches in 7 months
instance-segmentation
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