Fernando Gonzalez Del Cueto Email & Phone Number
@quantlab.com
3 phones found area 713
LinkedIn matched
Who is Fernando Gonzalez Del Cueto? Overview
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Fernando Gonzalez Del Cueto is listed as Computational and Applied Mathematician at PathCision Medicine, a with 6 employees, based in Denver Metropolitan Area, United States. AeroLeads shows a work email signal at quantlab.com, phone signal with area code 713, and a matched LinkedIn profile for Fernando Gonzalez Del Cueto.
Fernando Gonzalez Del Cueto previously worked as Chief Technology Officer at Lumos Imaging and Chief Research Scientist at Lumos Imaging. Fernando Gonzalez Del Cueto holds Phd, Computational And Applied Mathematics from Rice University.
Email format at PathCision Medicine
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AeroLeads found 1 current-domain work email signal for Fernando Gonzalez Del Cueto. Compare company email patterns before reaching out.
About Fernando Gonzalez Del Cueto
I've navigated my career through various industries with a broad skill set in optimization, imaging science, computer vision, mathematical modeling, and the evolving areas of machine learning and deep learning. I enjoy the challenge of prototyping, using the appropriate tools and methods to solve interesting problems. This practical approach has led to meaningful contributions across computational imaging, finance, and geophysical exploration, among other fields.
Listed skills include Applied Mathematics, Inverse Problems, Numerical Analysis, Mathematical Modeling, and 43 others.
Fernando Gonzalez Del Cueto's current company
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Fernando Gonzalez Del Cueto work experience
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Chief Technology Officer
CurrentTransitioned into a leadership role to further our technological strategy and adapting to the unique challenges of our compact start-up environment, emphasizing innovation with limited resources.Spearheaded our R&D efforts, personally contributing to and advancing research projects, pushing the boundaries of our technology. Oversaw experimental lab operations, managing collaboration with industry partners to ensure the delivery of project goals and milestones. Key achievements and contributions:* Engineered a specialized deep neural network tailored to the unique structure of our signals unlocking new technological potential. Achieved vast speed improvements over traditional methods.* Innovatively designed and implemented cost-effective software solutions, enhancing efficiency across multiple workflow aspects from data storage to experimental automation, demonstrating adaptability and resourcefulness under resource constraints.* Authored and secured NASA's 2022 SBIR project `S11.04-2107'. Conceptualized a novel application for our technology, led proposal writing, and actively contributed to its technical workload. Co-authored project deliverables, navigating stringent deadlines and project challenges.
Chief Research Scientist
Onboarded as a consultant at Lumos Imaging and progressively transitioned to a more pivotal role in developing our novel imaging technology for spatial and spectral information recovery. My focus was on enhancing image reconstruction algorithms, confronting the complexities of this highly ill-posed challenge, and diligently working to achieve our quality objectives.Key achievements:* Updated the core algorithmic framework with state-of-the-art optimization methods, markedly improving processing speed and enhancing image quality. This involved a comprehensive redesign of the numerical optimization solver and strategic reformulations of the underlying mathematical problem.* Implemented some critical functions in CUDA/ArrayFire, achieving a 3x increase in processing speed and efficiency.
Quantitative Research Scientist
As a pivotal member of the R&D team at Quantlab Financial, I was tasked with the development of algorithmic trading strategies for stock options. My tenure, though brief due to family relocation, was marked by notable contributions to both data management and the discovery of trading insights. Leveraging my expertise in data structuring, pattern recognition, statistics, and machine learning, I significantly enhanced our strategy development processes.Key Achievements:* Worked on identifying trading opportunities through statistical analysis and machine learning techniques.* Overhauled the data storage framework, employing relational structures and optimized data types to quadruple query performance.* Advanced our analysis capabilities by integrating Python, SQL, and multi-core parallel processing, facilitating rapid data analysis and effective prototyping.
Research Geophysicist
Joined the novel technologies for exploration research group. Specialized in mathematical modeling, parameter estimation, and optimization across multiple research domains, with the ultimate goal of creating technologies for de-risking oil exploration. Key contributions:* Pioneered proprietary methods in target detection algorithms for hyperspectral data.* Employed SOTA convex optimization techniques and integrated expert insights into mathematical models, creating a solver for advection-dominated transport problems. This innovation significantly reduced scenario analysis time.* Streamlined data processing and visualization workflows by implementing and integrating solutions with geospatial software, achieving substantial time savings for explorationists.* Technical collaboration in joint research efforts with MIT (LIDS) and U. of Utah, funded by Shell.* Directed summer intern research projects for two years.
Summer Intern
During my two-month internship at Shell, I focused on pioneering research in algorithms for geolocation and depth estimation, specifically aimed at identifying gravitational anomalies from gravimetry data. Using spectral methods, I lead to the creation of the "Bathogram" — a method that became part of the company's exploration capabilities. This innovation was recognized for its originality and was subsequently trademarked.My ability to drive this project to success with minimal supervision not only demonstrated my independence and dedication but also impressed my supervisor, culminating in a job offer upon completion of my PhD. This experience underscored my proficiency in Matlab and my expertise in constrained smooth optimization, marking the beginning of my career in geophysical research and technology innovation.
Web Developer
Developed an automated quoting system, significantly reducing human preparation time from hours to minutes and integrating real-time pricing by connecting to the inventory system's database.
Fernando Gonzalez Del Cueto education
Phd, Computational And Applied Mathematics
Ma, Computational And Applied Mathematics
Ba Applied Mathematics, Applied Mathematics
High School
Frequently asked questions about Fernando Gonzalez Del Cueto
Quick answers generated from the profile data available on this page.
What company does Fernando Gonzalez Del Cueto work for?
Fernando Gonzalez Del Cueto works for PathCision Medicine.
What is Fernando Gonzalez Del Cueto's role at PathCision Medicine?
Fernando Gonzalez Del Cueto is listed as Computational and Applied Mathematician at PathCision Medicine.
What is Fernando Gonzalez Del Cueto's email address?
AeroLeads has found 1 work email signal at @quantlab.com for Fernando Gonzalez Del Cueto at PathCision Medicine.
What is Fernando Gonzalez Del Cueto's phone number?
AeroLeads has found 3 phone signal(s) with area code 713 for Fernando Gonzalez Del Cueto at PathCision Medicine.
Where is Fernando Gonzalez Del Cueto based?
Fernando Gonzalez Del Cueto is based in Denver Metropolitan Area, United States while working with PathCision Medicine.
What companies has Fernando Gonzalez Del Cueto worked for?
Fernando Gonzalez Del Cueto has worked for Pathcision Medicine, Lumos Imaging, Quantlab Financial, Llc, Shell Oil Company, and Grupo Siasa.
How can I contact Fernando Gonzalez Del Cueto?
You can use AeroLeads to view verified contact signals for Fernando Gonzalez Del Cueto at PathCision Medicine, including work email, phone, and LinkedIn data when available.
What schools did Fernando Gonzalez Del Cueto attend?
Fernando Gonzalez Del Cueto holds Phd, Computational And Applied Mathematics from Rice University.
What skills is Fernando Gonzalez Del Cueto known for?
Fernando Gonzalez Del Cueto is listed with skills including Applied Mathematics, Inverse Problems, Numerical Analysis, Mathematical Modeling, Inversion, Research, Data Analysis, and Scientific Computing.
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