Bio for Barry Roffman and Dr. David Roffman

About Barry

Hello. I’m Barry S. Roffman, the Mars Correct Project Research Manager. I was born in Philadelphia, PA in May, 1947, graduated from Northeast High there in 1965; and from Temple University in 1969. At the University of Pennsylvania I earned a commission in the U.S. Navy in December 1968. After active duty in the Navy, I taught science (often Earth-Space Science) in Dade and Palm Beach Counties in Florida for 30 years before retiring in 2003. I also spent 10 years in the Navy Reserve and then joined the Coast Guard Reserve in 1983. In 1995 I retired from the military, but was recalled to active duty in March 2003. While on active duty, I wrote defense readiness and disaster response plans at Coast Guard Pacific Area in Alameda, California, and for Coast Guard District 7 in Miami, 13 in Seattle, 14 in Hawaii and 17 in Alaska. I retired again on his 60th birthday in May, 2007. I have been a guest speaker on the History Channel where I discussed his Torah Codes and Ark Code research (which is featured on my ArkCode.Com website). My son and I have also been a guest speakers at the International Mars Society Conventions where we have focused on Martian air pressure since 2010.

MILITARY AWARDS RECEIVED: U.S Coast Guard Meritorious Service Medal, U.S. Coast Guard Commendation Medal, U.S. Coast Guard Achievement Medal, Commandant’s Letter of Commendation Ribbon Bar (gold star in lieu of second), National Defense (double bronze star in lieu of third time), USCG Bicentennial Unit Commendation, Coast Guard Unit Commendation, USCG Humanitarian Service Medal, Armed Forces Reserve Medal (with M and Silver Hour Glass).

A a Reservist I have proudly served aboard the following ships in the Navy: Aircraft Carriers:  USS Lexington; USS Randolph; USS Franklin D. Roosevelt; USS Independence,  USS Kitty Hawk; Amphibious Communications Ship: USS Mount Whitney; Destroyers: USS Barton; USS Lowry; USS Blackwood (a Destroyer Escort); and USS Fox; Frigate: USS Antrim, Coastal Minesweeper: USS Thrush. In the Coast Guard I also served on the  Buoy Tender Ironwood, and the WPB: Aquidneck.

CV for David

Education:

DOCTORATE OF PHILOSOPHY| AUGUST 2016 | UNIVERSITY OF FLORIDA

• Major: Physics

• Specialization: Computational Condensed Matter Theory

• Thesis: “Resonant Surface Scattering on Nanowires.” Explored how to reduce thermal conductance in sprayed lattices with disorder as well as skutterudites (cheap thermoelectric materials). Modeling was done in MATLAB.

MASTER OF SCIENCE | DECEMBER 2013 | UNIVERSITY OF FLORIDA.

• Major: Physics

BACHELOR OF SCIENCE | DECEMBER 2011 | EMBRY-RIDDLE AERONAUTICAL UNIVERSITY

• Major: Space Physics

• Minor: Mathematics

Skills & Abilities

TEACHING UNDERGRADUATE PHYSICS: I have taught over 36 sections of Physics I labs and lectures, with and without calculus. As a graduate teaching assistant the teaching load was typically 3-4 courses per semester (including every summer except 2013).

MATLAB: I have 7 years of experience using this language, and consider myself an expert at using it. Projects completed utilizing this language included: Programming a multilayered Artificial Neural Network for cancer prediction from scratch, PhD thesis involving heat transfer, molecular dynamics simulations, approximating the solutions to ordinary differential equations (ODEs) and partial differential equations (PDEs), and extracting Viking Lander Martian weather data.

C++: I have about 6 months of experience with this language, and have a moderate level of skill. During the few months spent at CERN as part of a fellowship I filtered large data sets containing the energy of muons. After that fellowship ended, I have used this language on occasion to approximate the solutions to ODEs as well as other basic tasks.

HTML/JAVASCRIPT: Approximately 2 months of experience with using these languages. I only have a basic understanding of them as this knowledge was acquired for personal amusement rather than academic or work reasons.

MACHINE LEARNING (ARTIFICIAL NEURAL NETWORKS) AND BIG DATA: As a postdoc at Yale, I needed to be able to create a multi-parameterized model for tumor specific cancer prediction. The result was me learning how to program artificial neural networks from scratch. They have varied in between 1-5 layers with an arbitrary number of neurons per layer with the relevant bias terms. Sample sizes used in my studies were over 500,000 people. Already there are very promising results for some specific cancer types.

MICROSOFT WORD, EXCEL, POWERPOINT: Reports were always written in Word until I learned Latex; now I select the appropriate software for the task. I was required to teach students how to use Excel as part of my lab instructor duties. It was also used to maintain gradebooks, calculate the sunrise and sunset times for a specific location on Mars, and for storing the CDC data I use in my research as a postdoctoral associate. I have used PowerPoint to make presentations for classes, my PhD dissertation, and at International Mars Society Conventions (Speaker 2010 and 2011).

LATEX: I have 2 years of experience in producing pdf documents using this software, and am almost an expert at using it. My PhD thesis document was written in Latex.

EPIC: This program is commonly used to store electronic medical records. I have basic knowledge of how to use it in a read-only manner. This was done with the relevant approval in the context of cancer research. I am very familiar with the HIPPA requirements.

CLASS 3B LASERS: Used one of these and a Fabry-Perot for spectroscopy for 1 month in a senior physics lab. Work was with one partner without supervision of the professor. I know the safety protocols and dangers (risk of blindness) associated with this class of laser.

LEADERSHIP: Elected to the Graduate Student Advisory Council in the University of Florida physics department. When the graduate coordinator tried to impose the new requirement of a mandatory course for all existing students, I fought back because it would have taken away from research time and extended time required to finish degree programs. We came to compromise in which each student’s adviser could sign a waiver for this new course.

WEBSITE ADMIN: I maintain my own website davidaroffman.com with topics that vary from Martian meteorology to breakthrough propulsion physics to my dissertation work.

Experience

POSTDOCTORAL ASSOCIATE | YALE | DECEMBER 2016-OCTOBER 2017

• Research involved using big data and machine learning to construct a multi-parameterized model to predict cancer risk and then recommend the appropriate screening methods. Other duties include collaboration with masters’ students, postgraduate researchers, other postdocs, research scientists, professors, and medical doctors to achieve optimal results. Teamwork is essential to success.

GRADUATE TEACHING ASSISTANT | UNIVERSITY OF FLORIDA | AUGUST 2012-AUGUST 2016

IHEPA FELLOWSHIP AT CERN | UNIVERSITY OF FLORIDA | MAY 2013-AUGUST 2013: I was sent to work at CERN and lived in Switzerland for the summer of 2013 as part of a fellowship I was awarded. Work done was primarily filtering large data sets of muons based on their energies. A software package called ROOT as well as C++ and Linux were used during the course of my work.

Publications:

(1) Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network

(2) Development and Validation of a Multiparameterized Artificial Neural Network for Prostate Cancer Risk Prediction and Stratification

(3) A multi-parameterized artificial neural network for lung cancer risk prediction.

(4) Scoring colorectal cancer risk with an artificial neural network based on self-reportable personal health data

(5) Meteorological Implications: Evidence of Life on Mars?

(6) MARS CORRECT: A Critique Of All NASA Mars Weather Data

(7) First Annual Update to Mars Correct: Critque of all NASA Mars Weather Data

Professional Memberships and Conferences:

American Association of Physicists in Medicine (AAPM) Junior Member | March 2017-Present

AAPM conference in Denver 2017 | July 30th – August 3rd 2017

Multi-Parameterized Models for Prostate Cancer Prediction.  E-Poster Presentation made on August 1st.

 

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