Chief Scientist
CurrentChief Scientist for the Decision Systems Group in the Asymmetric Operations Sector
Please complete the CAPTCHA to continue
@jhuapl.edu
✓
LinkedIn matched
A concise factual answer block for searchers comparing this professional profile.
Philip Graff is listed as Senior Data Scientist at The Johns Hopkins University Applied Physics Laboratory, a with 5538 employees, based in Laurel, Maryland, United States. AeroLeads shows a work email signal at jhuapl.edu and a matched LinkedIn profile for Philip Graff.
Philip Graff previously worked as Chief Scientist at The Johns Hopkins University Applied Physics Laboratory and Data Scientist at The Johns Hopkins University Applied Physics Laboratory. Philip Graff holds Ph.D., Astrophysics from University Of Cambridge.
This section adds company-level context without repeating Philip Graff's masked contact details.
AeroLeads found 1 current-domain work email signal for Philip Graff. Compare company email patterns before reaching out.
Postdoctoral researcher interested in the physics of gravitational waves and their detection. Broader interest in Bayesian data analysis techniques and machine learning.
Listed skills include Physics, Data Analysis, Machine Learning, Astrophysics, and 18 others.
Company context helps verify the profile and gives searchers a useful next step.
A career timeline built from the work history available for this profile.
Laurel, Maryland, United States
Chief Scientist for the Decision Systems Group in the Asymmetric Operations Sector
Laurel, Maryland, United States
Laurel, Maryland, United States
Graph modeling in Java for data mining and pattern discovery.
College Park, Md
I continued my work from my previous position. This includes studies of gravitational wave parameter estimation for massive binary black hole (BBH) systems and spinning BBHs. I am also continuing studies in applying machine learning to astrophysics. Ongoing work includes applying various machine learning methods to Swift data analysis and to LIGO detection pipeline improvement.
My research involved the detection and characterization of gravitational wave signals. I use Bayesian inference techniques to detect and measure the source parameters of gravitational waves in noisy data for the LIGO Scientific Collaboration. This utilizes many waveform models which can be added to real or simulated noise.My research also involves the application of machine learning, specifically artificial neural networks, to astrophysics. This is through the improvement of Bayesian inference as well as using the predictive power of neural networks for direct data analysis and data mining.
Conduct weekly supervisions for students in first-year mathematicsAssign examples, mark work, and review materialFour groups of 2 or 3 students each, meeting one hour per week per group during term
Research student working towards completion of PhD in Astrophysics Group of Department of Physics.
Helped students perform weekly experiments in a first-year physics laboratory classMarked lab reports for 6-10 students per week
Earned my Bachelor of Science degrees (summa cum laude) in Physics and Mathematics while a member of the Honors College.
Developed an improved method for initial lock acquisition of the Michelson interferometers used in the LIGO observatories using pseudo-random noise.MATLAB simulations were used to test concepts; models were planned to be used to test methods on the 40-meter interferometer at Caltech.Work performed with Dr
Other employees you can reach at jhuapl.edu. View company contacts for 5538 employees →
Mary Buzby
Colleague at The Johns Hopkins University Applied Physics LaboratoryWestminster, Maryland, United States
View →
SC
Suhaily Cardona-Romero
Colleague at The Johns Hopkins University Applied Physics LaboratoryEast Lansing, Michigan, United States
View →
RD
Richard Dudley
Colleague at The Johns Hopkins University Applied Physics LaboratoryLaurel, Maryland, United States
View →
ML
Marc Logsdon
Colleague at The Johns Hopkins University Applied Physics LaboratoryPasadena, Maryland, United States
View →
RH
Richard Heisler
Colleague at The Johns Hopkins University Applied Physics LaboratoryMillersville, Maryland, United States
View →
RM
Rudy Miller
Colleague at The Johns Hopkins University Applied Physics LaboratoryWashington Dc-Baltimore Area, United States
View →
RN
Raymond Nosko
Colleague at The Johns Hopkins University Applied Physics LaboratoryLaurel, Maryland, United States
View →
JY
Justin Yonker
Colleague at The Johns Hopkins University Applied Physics LaboratoryGreater Roanoke Area, United States
View →
SL
Samantha Lomuscio
Colleague at The Johns Hopkins University Applied Physics LaboratoryWashington Dc-Baltimore Area, United States
View →
RM
Richard Maurer
Colleague at The Johns Hopkins University Applied Physics LaboratoryLaurel, Maryland, United States
View →
Activities and Societies: Student Government Association, Alpha Epsilon Pi Fraternity, Society of Physics Students, Phi Beta Kappa Honors.
Quick answers generated from the profile data available on this page.
Philip Graff works for The Johns Hopkins University Applied Physics Laboratory.
Philip Graff is listed as Senior Data Scientist at The Johns Hopkins University Applied Physics Laboratory.
AeroLeads has found 1 work email signal at @jhuapl.edu for Philip Graff at The Johns Hopkins University Applied Physics Laboratory.
Philip Graff is based in Laurel, Maryland, United States while working with The Johns Hopkins University Applied Physics Laboratory.
Philip Graff has worked for The Johns Hopkins University Applied Physics Laboratory, University Of Maryland, Nasa Goddard Space Flight Center, University Of Cambridge, and Umbc.
Philip Graff's colleagues at The Johns Hopkins University Applied Physics Laboratory include Mary Buzby, Suhaily Cardona-Romero, Richard Dudley, Marc Logsdon, and Richard Heisler.
You can use AeroLeads to view verified contact signals for Philip Graff at The Johns Hopkins University Applied Physics Laboratory, including work email, phone, and LinkedIn data when available.
Philip Graff holds Ph.D., Astrophysics from University Of Cambridge.
Philip Graff is listed with skills including Physics, Data Analysis, Machine Learning, Astrophysics, Matlab, Research, Statistics, and Mathematical Modeling.
Search by job title, company, industry, location, and seniority. Export verified B2B contact data when you need it.
Start free trial Search contactsCheck these profiles if this is not the Philip Graff you were looking for.
View similar profiles