Links
The following links host my updated Resume and CV.
Technical Skills
I am experienced with:
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Data analysis, in particular big data, statistics, deconvolution, modeling & simulation
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Python, C, C++ programming
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Machine learning (PyTorch, scikit-learn, TensorFlow)
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Scientific computing (NumPy, SciPy, pandas, PyOpenCL)
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Distributed and parallel computing (AWS, SLURM, PBS, HTCondor)
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Data visualization (matplotlib, Plotly Dash, PyOpenGL)
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Version control systems (Git, SVN)
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Public speaking, mentoring, and leadership roles
Education
PhD, Physics
University of Wisconsin—Madison
BS, Chemical Physics
Rice University
Languages Spoken
English, Español (Native)
Français (Working Proficiency),
Ελληνικα (ενα λιγο, i.e. basic)
Selected Articles
“DeepFake Detection Challenge Part II”
IQT, In-Q-Tel, 7 July, 2021, Article link
“DeepFake Detection Challenge”
IQT, In-Q-Tel, 21 June, 2021, Article link
“What AI Can and Cannot Do for the Intelligence Community”
Defense One, Defense One, 5 Jan., 2021, Article link
“Why IQT made the COVID-19 Diagnostic Accuracy Dash App.”
Modern Data, Modern.Data, 27 August, 2020, Article link
“Learning to Run a Power Network Challenge.”
Gab41, IQT Labs, 4 May, 2020, Article link
Selected Presentations
“Approaches for Multi-modal Synthetic Media Detection”
Invited talk at Applied Imagery Pattern Recognition, 49th IEEE AIPR 2020.
Online info
“Operationalize COVID-19 Statistics with Dash - Featuring IQT’s COVID-19 Diagnostic Accuary Tool”
Invited Webinar Talk for Plotly Dash.
Webinar link
“PyUnfold: the Python Package for Iterative Unfolding”
Talk at IIHE, ULB, Bruxelles, Belgium.
Slides
“Overview of Semi-Supervised Classification with GCNs”
Invited talk at ML6, Ghent, Belgium.
Slides
“Introduction to Machine Learning Workshop”
Lecture & Keras Workshop at IIHE, ULB, Bruxelles, Belgium.
Slides
Honors and Awards
BAEF and WBI Postdoctoral Fellowships
NSF Graduate Research Fellowship
Fulbright Research Fellowship
See my
blogpost
regarding my Fulbright research experience.
MMUF Undergraduate Fellowship
Selected Publications
Below is a list of the publications for which I am a major contributor.
Localizing Radio Frequency Targets Using Reinforcement Learning
2021 IEEE ROSE Conference, 2021. IEEE Publication
Multimodal Approach for DeepFake Detection
49th Annual IEEE AIPR 2020. IEEE Proceeding
L2RPN: Learning to Run a Power Network in a Sustainable World
NeurIPS 2020 White Paper. ChaLearn
Cosmic Ray Observations at the TeV Scale with the HAWC Observatory
I.e. my PhD thesis.
Observation of Anisotropy of TeV Cosmic Rays with Two Years of HAWC
Astrophys. J. 865, 57 (2018). arXiv:1805.01847
Official press release
PyUnfold: A Python Package for Iterative Unfolding
Journal of Open Source Software 3(26), 741 (2018). arXiv:1806.03350
Constraining the \(\bar{p}/p\) Ratio in TeV Cosmic Rays with the Moon Shadow
Phys. Rev. D 97, 102005 (2018). arXiv:1802.08913
The All Particle Cosmic Ray Energy Spectrum Measured by the HAWC Experiment from 10 to 500 TeV
Phys. Rev. D 96, 122001 (2017). (Editor’s Suggestion) arXiv:1710.00890
Official press release
All-Particle and Light-Component Cosmic Ray Energy Spectrum Measured by the HAWC Experiment
PoS: Proceedings of the 35th ICRC (Busan), 2017. arXiv:1801.05526
Towards a Measurement of the \(e^{+}e^{-}\) Flux Above 1 TeV with HAWC
PoS: Proceedings of the 34th ICRC (The Hague), 2015. arXiv:1508.03466