For a detailed list of publications, check out my Google Scholar page.
I am super excited to have joined Nvidia in 2022 and to have restarted work on applied AI problems in a company that leads the charge in AI innovation !!!
My latest research on financially quantized VAEs is on arXiv:
Multiresolution Signal Processing of Financial Market Objects *** To appear in 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’23)
In 2008 I moved from IBM into the world of Quantitative Finance. As the financial crisis unfolded over the following years, so did the challenges to traditional quant research. My teams and I worked around the clock on the modeling, implementation, and maintenance of quantitative tools used by traders, structures, strategists, and marketers. Our main focus was on:
- Pricing of vanilla and exotic options
- P&L and Risk Management
- Relative value & historical analysis for alpha generation
- Risk analysis (scenario design, simulations, alternative risk representations)
- Automated data collection, mining, and visualization
Personally, I am greatly interested in applying data science analytics (in particular, methods from other fields like signal/image/geometry processing and machine learning) to solving financial modeling problems.
I am the author of several sell-side and buy-side proprietary papers on topics related to:
- Interest rates volatility modeling for US and LatAm markets
- Valuation of treasury bond options, futures, and futures options
- Risk management of Fixed Income structured products
- System design for the implementation of scalable quant libraries
- Machine learning for finance in the context of discretionary trading strategies
Digital Geometry Processing
Geometry is one of my favorite subjects. I have enjoyed working on geometric proofs since I was a young child. As a computer scientist, I love bringing geometry to life on the computer screen. While at IBM, I worked on algorithms and data representations for the design, analysis, and simulation of 3D shapes. Some of my work on subdivision surfaces done in collaboration with researchers at IBM, NYU, and Dassault Systèmes has been incorporated into CATIA Imagine & Shape.
Detail-Preserving Variational Surface Design with Multiresolution Constraints, IEEE Shape Modeling International 2004, Genova, Italy (with R. Ronfard, F. Bernardini; reprinted in ASME Journal of Computing and Information Science in Engineering, 5(2), 2005, pp. 104-110)
Differentiable Parameterizations of Catmull-Clark Subdivision Surfaces, Symposium on Geometry Processing 2004, Nice, France (with D. Zorin)
Domain Decomposition for Multiresolution Analysis, Symposium on Geometry Processing 2003, Aachen, Germany
Cut-and-Paste Editing of Multiresolution Surfaces, ACM SIGGRAPH 2002, ACM Transactions on Graphics, vol. 21(3), pp. 312-321, 2002 (with H. Biermann, F. Bernardini, D. Zorin)
Sharp Features on Multiresolution Subdivision Surfaces, Journal of Graphical Models, 64(2), 2002, pp. 61-77, (with H. Biermann, D. Zorin, F. Bernardini)
Also in the realm of geometric processing, this work shifts applicability from industrial design to cultural heritage preservation through digital reconstruction. Whereas in the former case new objects come to life on the computer and are subsequently manufactured or engineered, in the latter case the process is exactly the opposite (hence, the term ‘reverse engineering’): real objects are digitized and reconstructed in virtual space. Work done in collaboration with colleagues at IBM has helped art historian Jack Wasserman analyze one of the most beautiful and controversial works of art: Michelangelo’s Florence Pietà.
Reverse Engineering Methods for Digital Restoration Applications, ASME, Journal of Computing and Information Science in Engineering, 6(4), 2006, pp. 364-371 (with H. Rushmeier)
Parameterization of Triangle Meshes over Quadrilateral Domains, Symposium on Geometry Processing 2004, Nice, France (with H. Rushmeier, J. Jin)
Building a Digital Model of Michelangelo’s Florentine Pietà, IEEE Computer Graphics and Applications, 22(1), 2002, pp. 59-67 (with F. Bernardini, H. Rushmeier, J. Mittleman, G. Taubin)
High-Quality Texture Reconstruction from Multiple Scans, IEEE Transactions on Visualization and Computer Graphics, 7(4), 2001 (with F. Bernardini, H. Rushmeier)
Notes and Surveys
Lunches and dinners with friends sometimes turn into technical discussions (“arguments” would be too strong a word :). In response, I like to research and fiddle with code and data. I like quirky titles and literary references which I sometimes add to my papers. Alternatively, I’ve sometimes been invited to offer my point of view on a particular topic or teach a specific subject.
A Short Note on Regression Bias, 2016.
Cassandra’s Twin: What Does the Data Predict?, SSRN, 2016.
A Survey of Subdivision-Based Tools for Surface Modeling, AMS/DIMACS Volume for Computer-Aided Design and Manufacturing, 67, 2005, pp. 1-29 (with D. Zorin, F. Bernardini)
Visualization Viewpoints: Adaptive Graphics, IEEE Computer Graphics and Applications, 2003, pp. 6-10.
Virtual reconstruction is not limited to artistic artifacts. In Biology, visual data typically comes from 2D images, such as those captured with microscopes and X-ray machines. Yet, the organisms they depict are three-dimensional. During my Ph.D. studies, I developed image processing and computational reconstruction methods for generating high-resolution 3D models of viruses from cryo-electron micrographs and X-ray crystallography images.
Computations and Data Visualization for Structure Determination of Spherical Viruses, IEEE Computational Science and Engineering, 5, 1998, pp. 40-52 (with D. C. Marinescu)
Identification of Spherical Virus Particles in Digitized Images of Entire Electron Micrographs, Journal of Structural Biology, 120, 1997, pp.146-157 (with D. C. Marinescu, R. E. Lynch, T. S. Baker)