RUSSELL W. HANSON

Email: russell.hanson at gmail.com

Tel: +1-617-***-****

Citizenship: U.S.A.

EXPERIENCE

**** – 2020 Chief Scientist, Augustus Intelligence (AI), New York, NY Augustus Intelligence does artificial intelligence (AI) for Fortune 500 companies by leveraging technology in Natural Language Processing (NLP), few-shot learning, fine-grained classification, action recognition, active learning, self-supervised learning, and a host of other state of the art (SOTA) methods. As Chief Scientist my duties are to develop, form, and lead the process of taking academic and prototype systems and technologies and apply them to complex customer business use cases. Augustus Intelligence clients include leading insurance, management consulting, manufacturing, and service companies worldwide. 2018 – 2019 Chief Scientific Officer, Endjinn at ConsenSys, Brooklyn, NY Endjinn does AI and quantitative modeling for Ethereum-based cryptocurrencies. ConsenSys is a multi- billion dollar blockchain/cryptocurrency company with over 900 employees. As Chief Scientific Officer my duties are to develop and refine AI models for cryptocurrencies including Initial Coin Offerings

(ICO’s), stable coins, and other structured and derived blockchain products and assets. 2014 – 2018 Assistant Professor, Institute for Genomics and Multiscale Biology Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, New York, NY My lab and institute work on genomics and multiscale biology at the Icahn Institute at Mount Sinai. Molecular engineering, cancer vaccines, cancer sensors, synthetic biology, molecular sensors, aptamer sensors, imaging, biophysics, nanotechnology, neuroscience, connectome imaging, bioinformatics, genomics, personalized medicine, stratified medicine, and biomarker development. We published in leading journals on topics in Alzheimer’s disease (AD), Traumatic Brain Injury (TBI), neurovasculature, tau disease, and deep learning-based methods in high-throughput neuropathology. 2013 – 2014 Postdoc, Center for Biological Sequence Analysis, Danish Technical University, Copenhagen, Denmark Bioinformatics, computational immunology, cancer informatics, and personalized medicine 2009 – 2013 Harvard University and Harvard Medical School (HMS), Dana Farber, Harvard Partners, Boston, MA Research Associate: Quantitative development and applied statistics; MATLAB, SAS, R, C++ and Java

• Quantitative development in statistics, Bayesian conditional probabilities using MATLAB, R, and Java

• High-throughput genotype/expression cancer research: breast, ovarian, colon, lung, solid tumor types

• Nonparametric, semi-parametric, and parametric statistical tests for informatics of drugs and diseases

• Biostatistics, Cancer Biology, LIMS, epidemiology, bioinformatics, diabetes, diabetic patient

• Hadoop, Pig, Mapreduce, Memcached, TCL/TK, machine learning, statistics, inference, regression 2008 – 2009 Reducible Systems Inc., New York, NY Cambridge, MA Quantitative development for hedge funds, proprietary trading companies in equities, fixed income, derivatives, options, and foreign exchange. C++, C# & Java Development, Complex Event Processing

(CEP).

• Models and algorithms for high frequency trading, market structure

• Developed methods for natural language processing (NLP) clustering of large text corpora

• Developed mathematical model and scoring algorithm for specific data, analyzed efficiency

• C#, C++, SAS, R, Java, StreamBase, OMS/EMS, FIX protocol, Ruby on Rails (RoR), Javascript, Memcached, Google Web Toolkit (GWT), AJAX, mySQL, PostgreSQL, database development front and back ends

2008 IMDS Trading, New York, NY

Proprietary Trading, Hedge Fund, Algorithmic Trading

• Developed high frequency trading strategies for intraday trading

• Managed risk and developed models for trading

• Development in C++/Java, SAS, R, statistics, statistical arbitrage, statistical techniques 2007 The UpDown, Boston, MA

Hedge Fund, Online Investment, and Social Networking

• Social network for investors

• Java, C++, Ruby on Rails, Tomcat, Struts, SQL, mySQL, Apache, JSP, Ant, Eclipse

• Pattern recognition, pattern classification for stock charts and portfolios 2007 – 2008 Massachusetts Institute of Technology (MIT), Boston, MA

• Teaching: Algorithms for Quantum Computation & Quantum Information

• Mathematical Logic (Ramsey Theory, Peano Arithmetic)

• Statistical Physics and Coding Theories

2005 – 2007 GTF/GRA, Boston University Chemistry Department, Boston, MA

• Numerical codes in Java, C++, Perl utilizing methods including transition path sampling, time-series analysis, metadynamics, dual-extended Kalman filtering, expectation-maximization (EM) and hidden- variable algorithms, supersymmetric molecular mechanics, and replica exchange molecular dynamics.

• Developed models for bioinformatics/cheminformatics; analysis of biological networks using flux balance analysis and linear optimization techniques; mathematics of bioinformatics use of machine learning (bagging, boosting, clustering, support vector machines) on bioinformatics problems. 2003 – 2005 GTA & GRA, Georgia Institute of Technology School of Biology, Atlanta, GA

• Full-time development of numerical codes in Java, C++, TCL/TK, Perl with the following applications utilizing adaptive finite difference methods for ODEs and dynamic programming algorithms.

• Biomolecular electrostatics using the Adaptive Poisson-Boltzmann Solver (APBS), DelPhi; hybrid and multi-layer quantum mechanics and molecular mechanics (QM/MM) simulation; density functional theory (DFT) methods; grand-canonical (μVT) Monte Carlo; and statistical mechanics. SKILLS

Programming: Python, Java, C/C++, R, SAS, SPSS, C#, MATLAB, LISP, Perl scripting for automation and data analysis, Fortran, Assembly, Data Structures and Algorithms, Parallel, Grid, High-performance and multi-processing

(MPI & OpenMP), SQL/mySQL, PostgreSQL, Oracle, OpenGL, DirectX, LabVIEW, Processing Math/Theory: Machine learning, statistical learning, recommendation engines, regression, Support Vector Machines

(SVM), parametric/nonparametric statistics, recursion theory, optimization, math logic Operating systems: Windows, Linux, Unix, MacOS

Security: Network traffic analysis and profiling, firewalls, buffer overflows, pen testing, fuzzing, application security, intrusion detection (IDS), sniffing

Natural language: Natural Language Processing (NLP), Computational Linguistics, Text Corpora Analysis, Twitter SERVICE

Board of Advisors, Ligandal, Inc.; Organization for Human Brain Mapping; Founding Partner, Brain Backups, LLC; Board of Advisors, Cloud GenomiX; Chairman, Committee on Advanced Technology, The Cure is Now, 501(c)(3)

EDUCATION

2013 – present Ph.D. Bioinformatics(tbd), Danish Technical University, Copenhagen, Denmark Cancer bioinformatics, personalized medicine, drug sensitivity predictions, immunology, cancer immunology

2005 – 2007 Ph.D. Computational Chemistry(abd/loa), Boston University, Boston, MA Medicinal Chemistry, Molecular Quantum Mechanics, Energy and Conformational Sampling Algorithms, Applied Stochastic Modeling, Applied Probability, Ab Initio 2003 – 2005 M.S. Biology, Georgia Tech School of Biology, Atlanta, GA Mathematical Biology and Computational Biophysics

1999 – 2003 B.A. Physics, Reed College, Portland, OR Thesis topic: Fast Fourier Transform Analysis of DNA Sequences Fall 2001 Massachusetts Institute of Technology (MIT) Media Lab, Cambridge, MA Special Student in Physics and Media

RESEARCH AND PUBLICATIONS

https://scholar.google.com/citations?hl=en&user=sotDQUkAAAAJ TITLE

CITED

BY

Low-level blast exposure disrupts gliovascular and neurovascular connections and induces a chronic vascular pathology in rat brain

MAG Sosa, R De Gasperi, GSP Garcia, GM Perez, C Searcy, D Vargas, ... Acta neuropathologica communications 7 (1), 1-20

8

Artificial intelligence in neuropathology: deep learning-based assessment of tauopathy M Signaevsky, M Prastawa, K Farrell, N Tabish, E Baldwin, N Han, ... Laboratory Investigation 99 (7), 1019

6

MACHINE LEARNING-BASED HISTOPATHOLOGICAL APPROACH TO TAU PATHOLOGY M Signaevski, KW Farrell, N Tabish, E Baldwin, M Prastawa, J Koll, ... TITLE

CITED

BY

Alzheimer's & Dementia: The Journal of the Alzheimer's Association 14 (7), P1596 Using synthetic biology to interface with physical micro and nano-sized sensors (Conference Presentation) R Hanson, J Fuller, A Cheng

Micro-and Nanotechnology Sensors, Systems, and Applications IX 10194, 1019417 The aptabot: an inducibly affinity-switching, minimally invasive in vivo contrast agent E Heffern, J Fuller, R Hanson

bioRxiv, 043950

In silico prediction of tumor antigens derived from functional missense mutations of the cancer gene census JS Khalili, RW Hanson, Z Szallasi

Oncoimmunology 1 (8), 1281-1289

28

Hacking the Genome-Designer Proteins, Elite Organisms, and You R Hanson

Presentation at the 21st Chaos Communication Congress December, 27-29 2

Fast fourier transform analysis of DNA sequences

RW Hanson

Reed College

4

Developing Human-Level Artificial Specific Intelligences R Hanson

DFCI–April 24, 2009

R Hanson

https://www.researchgate.net/profile/Russell_Hanson/research AI can Significantly Benefit Small Businesses

Preprint

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• February 2020

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Russell Hanson

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Trust in AI

Preprint

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• October 2019

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Russell Hanson

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Developing Human-Level Artificial Specific Intelligences Preprint

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• July 2019

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Russell Hanson

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Artificial intelligence in neuropathology: deep learning-based assessment of tauopathy Article

Full-text available

• February 2019

• Laboratory Investigation

•

Maxim Signaevsky

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Marcel Prastawa

•

Kurt W Farrell

•

•

John Crary

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MACHINE LEARNING-BASED HISTOPATHOLOGICAL APPROACH TO TAU PATHOLOGY Article

• July 2018

• Alzheimer's and Dementia

•

Maxim Signaevski

•

Kurt W Farrell

•

Nabil Tabish

•

•

John Crary

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Using synthetic biology to interface with physical micro and nano-sized sensors (Conference Presentation) Conference Paper

• June 2017

• SPIE Defense + Security

•

Russell Hanson

•

Jason Fuller

•

Andrew Cheng

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The aptabot: an inducibly affinity-switching, minimally invasive in vivo contrast agent Article

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• March 2016

•

Russell Hanson

•

Elleard Heffern

•

Jason Fuller

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The fractal network information systems theory of molecular biology Article

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• November 2014

•

Bion Howard

•

Russell Hanson

•

Zihai Li

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In silico prediction of tumor antigens derived from functional missense mutations of the cancer gene census Article

Full-text available

• November 2012

• OncoImmunology

•

Jahan S Khalili

•

Russell Hanson

•

Zoltan Szallasi

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