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Global Risk Management Network, LLC, 757 Warren Rd, Cornell Business & Technology Park, Ithaca, NY 14852-4892
World-Leading Hi-Tech Research Pioneering World-Leading Hi-Tech Digital Transformation PracticesTM:
AI, Algorithms & Machine Learning; Computational Quant Analytics; Cyber Security Risk Engineering; Quantum Computing
.
Who's Who in America®, Who's Who in the World®, Who's Who in Finance & Industry®, Who's Who in Science & Engineering®.
Post-Doc Princeton Quant Trading Presentations: AI & Decision Modeling, Algorithms, Machine Learning; Computational Quant Analytics; Cybersecurity Risk Engineering.
Top-10 PhD IT-Statistics Double Doctorate, MSQF, MSCS, MSNCS, MSAcc, MBAEco, BE, CEng, CISSP, CISA, CEH, CCP-CDP, CPA Education.

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Dr. Yogesh Malhotra
Post-Doc Princeton Quant Trading Presentations: AI & Decision Modeling, Algorithms, Machine Learning; Computational Quant Analytics; Cybersecurity Risk Engineering;
Top-10 PhD IT-Statistics Double Doctorate;
MS Quantitative Finance;
MS Computer Science;
MS Network & Computer Security;
MS Accountancy;
MBA Quantitative Economics;
Bachelor of Engineering with Distinction;
CEng,CISSP,CISA,CEH,CCP/CDP
. 


*

RESEARCH
* ACM-TMIS
* Princeton
* SSRN
* MRM
* GoogleScholar
* Syracuse
* LinkedIn


 

*E-mail: Dr.Yogesh.Malhotra[at]gmail.com *LinkedIn: linkedin.com/in/yogeshmalhotra
Model Risk Management Research Impact among Finance Nobel Laureates such as Black-Scholes & Markowitz.
AI-Algorithms-Machine Learning: Hedge Funds: Model Risk Arbitrage, Cyber-Finance & Insurance Pioneer.
Wall Street Investment Banks-Hedge Funds Quant: Invited Princeton University Quant Trading Presentations.
Global Computational Quant Leaderships: Digital, Computational, Quant, Cyber Risk Management-Analytics:

Wall Street Hedge Funds Quant, Big-3 Banking-Finance and IT-Telecom Firms; Silicon Valley VCs & CxOs;
National Science Foundation; United Nations; US-World Governments, Economies & Defense Agencies.

*2008: AACSB: Model Risk Management Research Impact among Nobel Laureates such as Black-Scholes.
*2015 & 2016 Princeton Quant Trading Conference: Sponsors: Goldman Sachs, Citadel, SIG, KCG Holdings.
*2015 Princeton Quant Trading Conference Invited Research Presentation: Sponsor: Princeton University.
*2016 Princeton Quant Trading Conference Invited Research Presentation: Sponsor: Princeton University.
*2016 New York State Cyber Security Conference Research Presentation: Sponsor: New York State Governor.
*2017: SSRN: 41 Top-10 Rankings: Top 10% Authors: AI-Decision Modeling-Algorithms-Machine Learning.
*2017-2018: ACM-TMIS: Special Issue: FinTech-TechFin Applications: IS Outcomes-Translational Research.
*Publications: 2018 Jrnl. of Operational Risk, 2017 Jrnl. of Computer Sciences, SSRN, MRM, Prior Research.

INTERVIEWS IN WORLDWIDE BUSINESS & TECHNOLOGY PRESS: INSIGHTS & FORESIGHTS LEADING GLOBAL PRACTICES
CIO Magazine CIO Insight Inc. Magazine Fortune Magazine Wall Street Journal Business Standard

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Over 20-Years of Global High Impact Hi-Tech Digital Practices Leadership spans Silicon Valley to Seoul and all continents in between.

AACSB

AACSB logo

Research Impact among Finance & IT Nobel Laureates in AACSB and Scientific Impact Studies.
  
Wall Street Journal
  
Risk Management Tech Ventures leading Computational Quantitative Analytics, Machine Learning, Data Science, Quantitative Finance, & Cybersecurity Practices.
Worldwide Business and IT Editorial Coverage & Interviews in Wall Street Journal, New York Times, Fortune, Fast Company, Forbes, Business Week, CIO, CIO Insight, Computerworld, Information Week, etc.

EXECUTIVE SUMMARY
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Model Risk Management Impact among Finance Nobel Laureates such as Black-Scholes, AACSB.
Post-Doc Princeton Quant Trading Presentations: AI & Modeling, Algorithms, Machine Learning.
Wall Street Hedge Funds Quant: Global Financial Systems Leader, Big-3 Finance-IT firms.

Hands-on Strategic, Operational, Tactical Leader: 
Wall Street Investment Banks-Hedge Funds (Midtown Manhattan): Senior Quants Leader: MDs & PMs: $1 Trillion AUM: JP Morgan. Founder, CxO Computational Quant Risk Analytics Digital Ventures: Clients: Goldman Sachs, Google, Harvard, IBM, Intel, Microsoft: Recommended by Microsoft founder Bill Gates, Big-4 CxOs, US DoD CIOs. Big-3 Finance-IT (US, Hong Kong, India): Bank of America. Advisor: $100 Billion Hi-Tech Firms: Intel, BT (UK), Silicon Valley VCs-CEOs, US & World Governments, UN, NSF.

Post-Doc Computational Quant Research: 
Pioneering AI & Modeling, Algorithms, Machine Learning: Princeton Quant Trading Conference: Sponsors: Goldman Sachs, Citadel: 41 Top-10 SSRN Rankings: Decision Modeling, Uncertainty & Risk Modeling, Mathematical Methods & Programming, Stochastic Models, Econometrics, Operations Research.

Computational Quant Finance-Risk Analytics Projects Leader:
Wall Street investment banks with $1 Trillion AUM such as JP Morgan: Quant Finance, Liquidity Risk, Market Risk, Credit Risk, Financial Econometrics & Programming, Large-Scale Data Modeling, Interest Rate Derivatives, Fixed Income & Equity Portfolio Modeling: SAS, MATLAB, C++, MS-Excel, VBA, Bloomberg.

Post-Doc Princeton Quant Trading Presentations: AI & Modeling, Algorithms, Machine Learning.
Carnegie Mellon, Kellogg: Executive Education Faculty.
Professor: Computer Scientist, Management Scientist, Information Scientist. Chartered Engineer.
Top-10 PhD IT-Statistics Double Doctorate: UPMC-Pitt.
5 Computational Quant Analytics Masters: 2 Computer Science, 3 Quant Finance.

Global CEO, CIO, CFO, CRO Benchmarks: Worldwide Press:
CIO, Wall Street Journal, New York Times, Fortune, Inc...

Post-Doctoral Research: Computational Quantitative Analytics: AI & Decision Modeling, Algorithms, Machine Learning, Quantum Computing
40 Top-10 SSRN Research Rankings: Top 10% SSRN Authors; Princeton Quant Trading Conference Presentations;
Professor-Faculty: Computer Scientist, Management Scientist, Information Scientist; Chartered Engineer (C.Eng.)
Top-10 MIS PhD Double Doctorate: IT and Statistics: '45-Cr PhD' Credits in both IT-Quantitative Methods & Statistics-Quantitative Methods: 91 Cr PhD.

- PhD Thesis Field Study: University of Pittsburgh Medical Center (UPMC): Digital Transformation of the UPMC: Quantitative Models.
PRMIA Executive Education: Quantitative Risk Management & Qualitative Risk Management, Kellogg School of Management.
MFE Executive Education: Computational Quant Analytics Financial Engineering C++, Statistics, Maths, University of California Berkeley.
MS* Cybersecurity: Cyber Risk Insurance, Algorithms, Machine Learning, AI & Modeling, Pen Testing Champion.
MS Computer Science: Computational Finance, Algorithms, Machine Learning, AI & Modeling, Cryptography.
MS Quantitative Finance: Derivatives, Stochastics, Securities Pricing, Risk Modeling, Risk Management.
MS* Accountancy: Finance, Auditing, Derivatives, Valuations, Global Financial Crisis: Risk Management.
MBA* Hypermedia Computing, Quant Economics, Advanced Statistics, Econometrics, Quant Modeling Champion.
BE Mechanical Engineering with Distinction: Dynamics of Machines, Electrical Engineering, Electronics,
Fluid Dynamics, Fluid Mechanics, Heat Transfer, Kinematics of Machines, Mechanical Engineering,
Engineering Design, Mechanics, Physics, Statistical Quality Control, Thermal Engineering.
Certifications: C.Eng., CISSP, CISA, CEH, CCP/CDP, CPA-Education,
SAS, MATLAB, SAP-ERP, SAP-CRM, AIB/ABA, Kauffman Foundation.
*Top Rank in Program, Outstanding Student Award, Perfect GPA Award, etc.

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New York State Cybersecurity Conference 2016  US Under Secretary of Defense United States Army United States Navy United States Air Force  penetration-testing-and-ethical-hacking


[Digital Transformation Pioneer] [AI, Algorithms & Machine Learning] [Computational Quant Finance] [FinTech: 'Rethinking Finance'] [CyberSecurity Risk Engineering]
Dr. Yogesh MalhotraRESEARCHWall Street Quant: Big-3 Finance-IT LeaderResearch Impact among Nobel LaureatesPrinceton Quant Trading PresentationsVentures:
[Digital Transformation Pioneer] [AI, Algorithms & Machine Learning] [Computational Quant Finance] [FinTech: 'Rethinking Finance'] [CyberSecurity Risk Engineering]

2015 & 2016 Princeton Quant Trading Conference: Sponsors: Goldman Sachs, Citadel, SIG, KCG Holdings.,
2008: AACSB: Model Risk Management Research Impact among Nobel Laureates such as Black-Scholes.

*Research Impact *Beyond 'Prediction' *Future of Finance *Beyond VaR *Model Risk Management *Future of Risk *Cyber Risk *SSRN *Google Scholar *Publications
*Projects *Goldman Sachs *JP Morgan *Wall Street Hedge Funds *Princeton Presentations *Model Risk Arbitrage *Cyber Finance *Cyber Risk Insurance *Quantum Crypto
*Bayesian vs. VaR *Markov Chain Monte Carlo *Wireless Mobile Trust Models *VoIP Pen Testing Frameworks *Bitcoin Cryptanalytics *NFS Cryptanalytics Algorithms


EXECUTIVE PROFILE
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Advancing on leadership of top Wall Street investment banks and hedge funds and having examined next-generation computational probabilistic modeling of financial econometric signals processing for global financial markets using computer science algorithms and machine learning, Dr. Yogesh Malhotra's computational quantitative risk management focus advanced to include global electromagnetic spectrum networks and global networking and encryption protocols. Spanning deterministic, stochastic, and non-deterministic computational statistical modeling methodologies, his current Computer Science, Computational Quantitative Analytics, &, Cybersecurity-Finance applied research focus is on high-dimensionality complex stochastic problems involving computational time complexity and computational space complexity relevant to emerging Model Risk Arbitrage and Model Risk Management concerns of Wall Street Chief Risk Officers such as the following.

"Recently, such probabilistic, statistical, and numerical methods related concerns are in globally popular press related to cybersecurity controls and compliance. Earlier, similar probabilistic, statistical, and numerical methods related concerns were in the global popular press in the context of the Global Financial Crisis. Future questions focused on the underlying assumptions and logic may focus on related implications for compliance, controls, valuation, risk management, etc. Likewise, recent developments about mathematical entropy measures shedding new light on apparently greater vulnerability of prior encryption mechanisms may offer additional insights for compliance and control experts. For instance, given related mathematical, statistical and numerical frameworks, analysis may also focus on potential implications for pricing, valuation and risk models. The important point is that many such fundamental assumptions and logic underlying widely used probabilistic, statistical, and numerical methods may not as readily meet the eye."

Source: Interview: Bitcoin BlockChain Cryptographic Protocols, Hong Kong Institute of CPAs, January 20, 2014.
Reference: First Research Report on Bitcoin 'Cryptographic Proof' preceding Goldman Sachs
, December 04, 2013.

How applied research shapes worldwide practices - an exemplary illustration in context (Retained Executive Search):

"[T]he approaches to mitigate operating risk associated with the use of models need to evolve to reflect recent trends in the Finance Industry. In particular there are a number of new areas where it is not possible for the "human eye" to necessarily detect material flaws: in the case of models operating over very small time scales in high frequency algorithmic trading, or for portfolio risk measurement models where outputs lack interpretability due to high-dimensionality and complex interactions in inputs, the periodic inspection of predicted versus realized outcomes is unlikely to be an effective risk mitigate. These situations require a holistic validation framework of the system focused on identifying and mitigating potential failures, taking into account the models’ objectives, their implementation including the joint interaction of software and hardware, their response to potential input shocks in real time and the fail-safe mechanisms."

Model Risk Management Managing Director/Executive Director, NYC, Top Wall Street Investment Bank; Interviewed: March 21, 2014.


Department of Defense Directive 8570 (DoDD 8570) Information Security Management & Auditing Certifications:
CISSP (Since 2005): DoDD 8570 - CNDSP Manager, IAM Level III, IAT Level III, IASAE II
CISA (Since 2007): DoDD 8570 - CNDSP Auditor, IAT Level III
CEH (Since 2014): DoDD 8570 - CNDSP Auditor, Incident Responder, & Infrastructure Support

National Science Foundation: 32 National Expert Panels of Cybersecurity & Cyber-computing specialists as judge & referee for allocating multi-million dollar SBIR/STTR innovation grants for US Cybersecurity & Cyber-computing computing technology innovation and commercialization.
Cybersecurity and Risk Management Industrial & Applied Research: 41 SSRN Top-10 Research Rankings (2015-2017).

Cyber Security | IT Administration | Networks Administration: Cybersecurity-Risk Management Leader
CISO-Level Cyber Security & Risk Management Leader, Government Administration, State of New York

Under the general direction of the Chief Information Officer (CIO) level executive, IT Administration, the Chief Information Security Officer (CISO) level role serves as a member of the IT Administration senior leadership team and provides domain expertise, direction, and, policy guidance on Cyber Security and IT Administration and Networks Administration. The CISO level role provides direction on information security and privacy across all of enterprise multi-site facilities and programs including all multi-site systems and services affecting 100,000 constituents of the New York State County. This position has broad authority and management responsibility for protecting the privacy, confidentiality, integrity, and availability of enterprise information and services. The CISO level role aligns services responsible for information security, privacy, and security operations to enable enterprise business objectives within acceptable levels of security and privacy risk.

Cybersecurity Technologies Deployment & Cybersecurity Industry Standards & Best Practices Development Leader

Benchmarking & Deploying Cybersecurity Risk Engineering for Leading Cyber Deterrence:

Cyber Security Technologies: Applications, Devices, End Points, Hosts, Networks, O/S, UTMs:
AirWatch, Check Point, Cisco, FireEye, Fortinet, Fortis, Intel, McAfee, Microsoft, Palo Alto, PDQ Deploy, ProofPoint, Qualys, Sophos, Symantec, VMWare, WatchGuard, etc.

Best Practices & Industry Standards:
CERT, Cisco, FBI, FIPS, Fire Eye, Gartner, GIAC, ISACA, Microsoft, NIST, NSA, OWASP, SANS, etc.

Penetration Testing-Ethical Hacking Frameworks & Tools
Metasploit, Nmap, Wireshark, Several Others.

Cybersecurity Leader leading, executing, implementing, and, guiding New York State wide and Enterprise wide IT Administration and Network Administration practices with focused domain expertise in Quant Finance, Cyber Security, Cryptography, Networking-Encryption Protocols, Penetration Testing-Ethical Hacking, Machine Learning Algorithms, Computational Quant Analytics, Risk Analytics.

CISO-Level Cybersecurity-Risk Management Leader reporting to CIO-Level role

CISO-Level Cybersecurity-Risk Management Leader: IT Administration & Networks Administration, Government Administration, State of New York Civil Services, reporting to CIO-Level role.

• Enterprise-wide IT, Telecom Networks, Cybersecurity & Risk Management, Controls & Compliance Policies, Best Practices, Strategies, Technologies, including Enterprise Level Implementations, IT Procurements and Contracts.

• Multi-Factor Authentication & Credentialing; User Access Controls & Group Management Policies for all Users including Authentication, Credentials, Password Policies, BYOD MFA & 2FA Policies, Anti-Malware Botnet and Anti-Ransomware Policies, etc.

• Multi-site Systems Administration including Group Management Policies & Configurations, Cybersecurity Risk Management Controls & Compliance Policies, UAC, and Defense-in-Depth against Advanced Threats & Attacks.

• Multi-site Enterprise-wide Telecom Networks, Hosts, Devices, Applications, OSs, and, IPs Vulnerability and WWW Applications Vulnerability Detection & Remediation leading Risk Mitigation, Network Security, Risk Management, & Compliance Policies, Strategies, &, Implementation, and, WWW Security Standards and Secure Coding Practices.

• Multi-site Enterprise-wide Penetration Testing & Ethical Hacking enabling Pre-emptive and Anticipatory Risk Management and Controls for Cybersecurity Risk mitigation for Networks, Applications, Hosts, Devices, Firmware, Embedded Systems, SCADA, and, Third-Party Services and Infrastructure Providers.

• Multi-site Enterprise-wide development of Zero-Trust UTMs, NGFWs, IPS/IDS, VLANs/VTP/STP, and UAC-ACL Policies and Architectures using Network Segmentation based upon industry-leading Cyber Security, Risk Management, and Compliance Policies.

• Multi-site Enterprise-wide Networks, Operating Systems, Hosts, Applications, and Mobile Device Management Security Controls Risk Management Audit & Threat Analysis including Identification, Elimination, Containment & Mitigation of Critical Risks.

Defense-in-Depth Enterprise Networks and Computer Security & Privacy Leader

Enterprise Networks-Perimeter & Networks Segmentation
Enterprise Networks-Perimeter and multi-layered Network Segmentation hardening against cyber-attacks tracked by newly upgraded Unified Threat Management infrastructure using SQL Server Big Data Analytics, High Frequency Time Series Data Analytics, and, Networks Logs Analysis.

Enterprise Hosts & Server End Point Protection Security
Endpoint (EP) upgrades for Hardening against Cyber Attacks coupled with Attacks and Malware reports analyses. Continuing bench-marking, Procuring and Implementation focus on more robust EP solutions to integrate, simplify, and, economize current EP & MDM infrastructures.

Enterprise User Access Controls, Credentials, Passwords:
Passwords, credentials, user access controls (UAC), and, privilege reviews and upgrades at the Policy, Networks-UTM, Operating Systems, Applications, Host, and Device levels and Policies and Processes for tiered UAC and credentials for various internal and external user groups.

Enterprise Security Content Automation Protocol Implementation:
MS-Windows O/S and Applications hardening based on security, risk, and compliance group policies development and Active Directory-Group Policy implementations ongoing with Security Content Automation Protocol (SCAP) – Security Compliance Manager.

Enterprise Microsoft Network Operating Systems & Applications Security:
MS-Windows Active Directory-Group Policy Network Operating Systems security configurations for hardening Windows Network O/S and Microsoft Windows based MS-Office software applications for mitigation of cybersecurity threats & attacks.

Enterprise Mobile Device Management & Multi-Factor Authentication

Coordinating enterprise wide administration Mobile Device Management for mobile devices toward simplified administration and MFA/2FA while also reviewing latest technologies for integration of MDM with EP.

Zero-Trust Cybersecurity Architectures & Networks Segmentation Leader

Zero-Trust Network Segmentation: Benchmarked-selected top-ranked UTM to replace prior NGFW. Reviewed-audited configuration of 125 UTM Policies and RADIUS-based VPN policies to apply robust networking and encryption protocols for mitigating threats from SMB, NetBios, SNMP, NTLM, and, PPTP.

Security Content Automation Protocol (SCAP): Configured more than 1,000 Group Policies using Security Compliance Manager. Configured, installed, and, implemented active directory (AD) and group policy management (GPM) policies.

Validation & Audit of IP Networks Subnets & VLANs: Identified-eliminated threats and vulnerabilities in Information Gathering, TCP/IP, General Remote Services, Firewall, and Web Server hardening network, servers, hosts, applications, and devices, and, access controls and authentication protocols such as SSL/TLS, IPSec, STP, and VTP.

OWASP Secure Coding Practices: Adoption by Systems, Analysis, and Design teams blocking cyber-attacks such as SQL injection attacks, and, buffer overflow attacks advancing secure PKI authentication and TLS 1.2, IPSec, AES256, and RSA2048.

Audit of Virtual Private Networks using RADIUS: To bolster credentials authentication by advancing mobile VPN Authentication from PPTP to L2TP and IPSec eliminating reliance upon CHAP thus advancing toward enterprise wide non-reversible encryption.

AD-GPM Default Domain Controllers Policy for Network Security Reconfiguration & Implementation: Advancing toward secure Kerberos authorization and authentication architecture for enterprise wide users.

AD-GPM Default Domain Policy Reconfiguration & Implementation: For securing user credentials advancing upon development of secure host-based user access credentials architecture for enterprise wide users.

AD-GPM Password Security Objects (PSOs) Development & Configuration: To advance development of fine-grained password policies for different privilege levels of enterprise wide internal and external users.

STEM Computer Science-CyberSecurity-Advanced Analytics Professor, Machine Learning-Algos Evangelist

• STEM Computer Science, Cybersecurity, Advanced MS-Excel Analytics Faculty for the State of New York. Developed-taught Cybersecurity Major & CompTIA Security+ for Network Administrators: concluded with its accreditation by the State of New York.

• Applied Research, Teaching, Practice focus on applications of Object-Oriented Programming (OOP) - JavaScript, JQuery Interactive Front-End Web Development; Black Hat Python Pen Testing-Ethical Hacking; Advanced MS-Excel, SQL, Computer Science, Mathematics, and, Statistics & Probability.

• 2015 and 2016 Invited Princeton Quant Trading Conference Presentations at Princeton University sponsored by Princeton University, Goldman Sachs, Citadel, SIG, and KCG Holdings.
- Pioneering Research: Cyber Finance-Insurance: Bayesian Machine Learning Algorithms.
- Ranked in 39 SSRN Top-10 Research Rankings for 2015-2016.

• STEM Faculty Evangelist for teaching Bayesian Inference, Machine Learning, Algorithms, Data Science, Python, R.

• Faculty presentation inspiring STEM Division that counts among alumni first female commander of Space Shuttle USAF Colonel Eileen Collins to lead the Cyber Revolution by focus on Bayesian Inference, Machine Learning, Algorithms, Data Science, Python, R.

• Quant FinTech-Computer Science-Cybersecurity-Algorithms-Machine Learning R&D spanning New York State, national & global industry-university research collaborations advancing post-doc industrial research in Quant FinTech [Applied Mathematics, Statistics, & Econometrics].
- e.g. 2016 European Cooperation in Science & Technology: Switzerland Federal Department of Economic Affairs: Math-Fintech Industrial Research.

• Academy of Management Best Reviewer Award winning Reviewer and Referee for Applied & Industrial Research in Cybersecurity:
- e.g. Journal of Defense Modeling and Simulation (JDMS) (Sage): STIX, TAXII, MCMC, Bayesian Networks, Markov Chain Monte Carlo Models.
- Society for Modeling and Simulation International.

CompTIA Security+ Network Security Instructor for Telecom Network Administrators, State of New York

CompTIA Security+ Network Security Instructor for Telecom Network Administrators, State of New York
• Introduction to Security
• Malware and Social Engineering Attacks
• Application and Networking-Based Attacks
• Host, Application, and Data Security
• Basic Cryptography
• Advanced Cryptography
• Network Security
• Administering a Secure Network
• Wireless Network Security
• Mobile Device Security
• Access Control Fundamentals
• Authentication and Account Management
• Business Continuity
• Risk Mitigation
• Vulnerability Assessment & Review

Hands-On Applied Offensive Cybersecurity Projects Handbooks
• Penetration Testing: A Hands-On Introduction To Hacking
• The Hacker Playbook 2: Practical Guide To Penetration Testing
• Wireshark 101: Essential Skills For Network Analysis
• Metasploit (No Starch Press)
• Nmap Network Scanning: The Official Nmap Project Guide to Network Discovery and Security Scanning
• Violent Python: A Cookbook for Hackers, Forensic Analysts, Penetration Testers and Security Engineers
• Black Hat Python: Python Programming for Hackers and Pentesters

Recent Related Activities and Impact on Global and National Cyber Security and Cyber Finance Practices

• Recent Networks & Computer Security focused Cybersecurity & Risk Management applied R&D project leadership developed as Computational Quantitative subject matter expert to distinguished computer scientists, mathematicians, and, physicists including the US Air Force Research Lab (AFRL) senior scientists such as Executive Director of the New York State’s Cyber Research Institute and former Chief Scientist, Information Directorate, AFRL.

Cybersecurity and Risk Management Innovations and Standards Development, New York State & Princeton University:

2016 New York State Cyber Security Conference, Albany, New York, June 8-9, 2016 
New York State Office of Information Technology Services
Presentation: CyberFinance: Why Cybersecurity Risk Analytics must evolve to Survive 90% of Emerging Cyber Financial Threats, and, What You Can Do About It?
Special Interest Topics: Related to: Finance Sector - Best practices and effective ways to increase the security of financial and personal customer information.

2015 NY Cyber Security & Engineering Technology Association (NYSETA) Conference, RIT, Rochester, NY, Oct 22, 2015
Cybersecurity Networks, Systems & Controls Standards Development
Advancement of Professional Cybersecurity Standards and Practices:
• Full Research Paper Accepted for the NYSETA Conference:
Bridging Networks, Systems, and, Controls Frameworks for Cybersecurity Curricula & Standards Development
Track: Innovative Design and Development Practices
• Rochester Institute of Technology Research Presentation.
- Risk Management and Controls Policy Framework
- Enterprise Risk Management & Governance: Enterprise Risk Management
- Systems & Networks Infrastructure Frameworks
- Systems & Networks Risk Management, Controls, Regulatory Compliance: Model Risk Management
- Networks Protocols and Network Analysis Tools Frameworks
- Cyber-Finance Risk Management, Data at Rest, Data in Motion, Encryption: Cyber Finance Risk Management
- Penetration Testing Execution Standard Applied: Case of VoIP Networks
- Kali Linux, Metasploit, NMap, Wireshark - Ethical Hacking & Penetration Testing
- OWASP, ISACA, SANS, and PCI/DSS Pen Testing & Information Assurance Frameworks

2016 Princeton Quant Trading Conference: Model Risk Arbitrage: Black Hat Hacker Mindset, Apr 16, 2015
- Sponsors: Princeton University, Bendheim Center & ORFE, SIG, Citadel, Goldman Sachs
• Pioneered Cyber-Quant Finance financial innovations including Open Systems Finance, Model Risk Arbitrage, Black Hat Finance, and, Non-Deterministic Methods & Models.
• Black Hat Mindset developed as a Certified Ethical Hacker (CEH, 2014) trained in Black Hat frameworks, methods, models, and techniques advancing upon White Hat frameworks learned as Certified Information Systems Security Professional (CISSP, 2005) applied to development of a new Financial Innovation called Model Risk Arbitrage.
• Essentially, by inter-disciplinary applied understanding of practices across the digital domains of Cybersecurity and Finance, further advanced leading-edge computational quantitative analytics practices to advance both fields of practice.

2015 Princeton Quant Trading Conference: Future of Finance: Cyber Finance, Apr 4, 2015
- Sponsors: Princeton University Bendheim Center & ORFE, Citadel, KCG Holdings.
• Pioneered Computational Quantitative Analytics industrial research in Cyber Finance & Cyber Risk Insurance Modeling in collaboration with the committee of distinguished research scientists from AFRL/NYS-CRI.
• Cyber Finance: Future of Finance Beyond 'Flash Boys': Tail Risks & Systemic Risks:
• Risk Modeling for Managing Uncertainty in an Increasingly Non-Deterministic Cyber World.
• Advanced Risk Modeling Statistical Techniques: Econometrics & Time Series Models, Bayesian Inference, Markov Chain Monte Carlo, Capital Markets, Derivatives, Portfolio Construction & Optimization Models, Volatility Models, VaR, ARCH, GARCH, Multifactor Pricing Models, Market Risk, Credit Risk, Liquidity Risk, Cyber Risk Insurance.

• Invited Risk Management Keynotes: State Street Bank world HQ, MA, and, National CROs/CSOs Summit, VA.
• Invited Risk Management Advice: MDs-Teams of Risk Management firms and Wall Street firms.


Post-Doc Network & Computer Security Research Pioneering Cybersecurity Risk Insurance Modeling leading global industry standards and frameworks for the Cybersecurity and Risk Management industry. Advisors: Executive Director, New York State Cyber Research Institute, Prior Chief Scientist, Air Force Research Lab / Information Directorate; Program Manager & Principal Computer Engineer, Information Directorate, Air Force Research Laboratory / Information Directorate.

2013-2015 Cyber Risk Insurance Industry Quant Risk Analytics Standards Development
• Averted the impending national Cyber risk and Cyber-insurance disaster based upon large-scale commercial reliance upon quantitative models with inherent model risks, tail risks, and systemic risks.
• Developed the first known Cyber-Finance-Trust™ framework for Cyber insurance modeling to analyze how finance risk entangled with Cyber risk further exacerbates the systemic, interdependent, and correlated character of Cyber risks.
• Developed the first known model risk management framework for Cyber insurance modeling as model risk management has received sparse attention in Cyber risk assessment and Cyber insurance modeling.
• Review of quantitative models in Cyber risk and Cyber insurance modeling developed the first known analysis establishing significant and extreme model risks, tail risks, and, systemic risks related to predominant models in use.
• Developed an empirical study of VaR and Bayesian statistical inference methodologies with specific guidance for containing model risks by applying multiple simple and advanced models for cross-checking the reliability of VaR.
• Developed an analysis of the Markov Chain Monte Carlo Models, Gibbs Sampling and Metropolis-Hastings statistical computing algorithms for enabling Bayesian statistical inference methodologies to minimize model risk in Cyber risk and Cyber insurance risk modeling for the specific context of cybersecurity.
• Developed the first known portfolio theory based framework for Cyber insurance modeling with guidance to minimize model risks, tail risks, and systemic risks inherent in models in commercial Cyber insurance modeling.
• Given increasing role of uncertainty in cyber (and financial) risk modeling and management, developed framework for enabling Knightian uncertainty management relating it to model risk management.

2013-2016 CompTIA Security+ Network Security & Pen Testing-Ethical Hacking Programs Development
• Developed and Delivered Applied Experiential Learning Penetration Testing and Ethical Hacking Program and CompTIA Security+ Network Security Certification Program for Telecom & Networking Professionals via SUNY system.
• Developed and delivered experiential learning in Penetration and Ethical Hacking Frameworks, Tools, Techniques, and, Methods including Metasploit, NMap, and Wireshark, and, Black Hat Penetration Testing via SUNY system.
• EC-Council Certified Ethical Hacker (CEH) and ISC2 Certified Information Systems Security Professional (CISSP) having logged over 2,000-hour professional experience in Penetration Testing & Ethical Hacking in Authorized Darknets as top-ranked ethical hacker in SUNY institutional competitions.

• Top-10 PhD IT Information Systems (Pittsburgh), MS Network & Computer Security (SUNY), MS Computer Science (SUNY), IT Information Systems Professor (Syracuse), Computer Science-Cybersecurity-CompTIA Security+ Professor (SUNY system); MS Quant Finance (Fordham), MS Accountancy (SUNY), MBA (UNLV), BE (Delhi) Chartered Engineer.
• EC-Council Certification: Penetration Testing & Countermeasures. SUNY System: Ethical Hacking & Pen Testing Instructor.

• 20+ years global R&D leadership advancing Cybersecurity, Risk Management, and Computational Risk Analytics Best Practices for developing, testing, and implementing Complex Systems: globally adopted and recommended by top CEOs such as Microsoft founder Bill Gates; and US DoD, CIOs of NASA, US Air Force, Army, Navy and Marine Corps.
• Portfolio of Global Research & Practice Leadership includes Wall Street investment banks such as JP Morgan and Goldman Sachs; Hi-Tech Firms such as Google, IBM, Intel and Microsoft; Brand Intelligence firms such as Ogilvy.
• Executive advisor on IT strategies to global firms such as Intel Corp., British Telecom (UK) and Philips (Netherlands).

• Recent Risk Management project leaderships for Wall Street investment banks with $1 Trillion AUM such as JP Morgan while reporting to JP Morgan Global Head of Quantitative Research and Analytics (Midtown Manhattan, New York).
• Prior Project Leader on Big-3 IT and Global Financial Systems, USA & Hong Kong, Bank of America, Crédit Agricole CIB.

• Associate Professor/Assistant Professor of Quantitative Methods, IT & Operations Research, Syracuse University, Developed Quantitative Models of Risk Management and Compliance applied by NASA and Big Banks; Research ranked and recognized for real world impact among others such as Nobel laureates; IT Research Editorial Review Panels for 40+ journals & publishers including ACM and IEEE. Academy of Management: Best Reviewer Award for IT/IS Research.
• Interviews & Editorial Coverage: CIO, Computerworld, Information Week, Wall Street Journal, New York Times, etc.
• Global and national CxO Keynotes, Expert Panels: Silicon Valley, Conference Board, US & World Governments, UN.

• Algorithms & Computational Finance: C++, SAS, Java, Machine Learning, Signal Processing
• Cybersecurity, Financial Protocols & Networks Protocols Analysis, and, Penetration Testing

Algorithms & Computational Finance: SAS, MATLAB, C++, C++11, Machine Learning, Signal Processing

C++ Design Patterns, Monte Carlo Models, Black-Scholes Model, C++11 Multithreading and Concurrency, SAS Applied Data Science, SAS Advanced Data Mining Models, Uncertainty Modeling, Machine Learning, Computer Algorithms, Mathematical Computation, Computational Cryptography, Artificial Intelligence & Modeling, Machine Learning, Soft Computing, Multivalent Logic, Fuzzy Systems, Computational Complexity, Computational Economics, Graph Theory, Social Networks Analysis, Game Theory, Bayesian Models, Automata, Computability, Formal Languages

Algorithms & Mathematical Models of Computing Machines

Complexity theory, Computability theory, Automata theory, Regular Languages, Finite Automata, Nondeterminism, Regular Expressions, Nonregular Languages, Pumping Lemma, Context-Free Languages, Context-Free Grammars, Pushdown Automata, Non-Context-Free Languages, Church-Turing Thesis, Turing Machines, Variants of Turing Machines, Hilbert’s Problems, Decidable Languages, Undecidability, Undecidable Problems from Language Theory, Computation Histories, Mapping Reducibility, Time Complexity, Measuring Complexity, Class P, Class NP, P versus NP, Cook-Levin Theorem, NP-complete Problems.

Algorithms & Computational Complexity

Big-O and Small-O, Primality Testing, Euclid's Algorithm, Fermat's Little Theorem, Recurrence Relations, Divide-and-Conquer Algorithms, Fast Fourier Transform, Undirected Graphs, Depth-First Search, Directed Graphs, Directed Acyclic Graphs (DAGs), Breadth-First Search, Dijkstra's Algorithm, Shortest Path Algorithms, Bellman-Ford Algorithm, Greedy Algorithms, Minimum Spanning Trees, Kruskal's Algorithm, Prim's Algorithm, Huffman Encoding, Horn Formulas, Dynamic Programming, Topological Ordering, Knapsack Problem, Floyd-Warshall Algorithm, Traveling Salesman Problem, Linear Programming, Duality, Complexity Reductions, Network Flows, Max-Flow Minimum Cut Algorithm, Bipartite Matching, Simplex Algorithm, NP-Completeness, Satisfiability (SAT), Integer Linear Programming, Vertex Cover, Clique, NP-Complete Reductions.

Algorithms, Cyber Networks & Computational Economics

Graph Theory, Social Networks Analysis, Network Strength, Network Structure, Graph Partitioning, Homophily, Structural Balance, Game Theory, Dominant Strategies, Nash Equilibria, Mixed Strategies, Evolutionarily Stable Strategies, Braess's Paradox, Auctions and Pricing, Auction Formats, Bidding Strategies, Matching Markets, Bipartite Graphs, Market-Clearing Prices, Equilibria in Trading Networks, Power in Social Networks, Nash Bargaining Solution, Modeling Network Exchange, Information Networks, WWW Link Analysis, PageRank, Spectral Analysis, VCG Principle, VCG Prices, Bayes' Rule, Information Cascades, Network Effects, Negative Externalities, Power Laws, Rich-Get-Richer Models, Long Tail, Information Cascades, Decentralized Search, Epidemic Models, Wisdom of Crowds Models, Asymmetric Information, Reputation Systems, Voting Systems.

Algorithms, Cryptography, Cryptology & Cyber Security

Shannon's Information Theory, Modular Arithmetic, Number Theory, Symmetric Cryptography, Data Security, Stream Ciphers, Linear Feedback Shift Registers (LFSR), Data Encryption Standard (DES), Triple DES (3 DES), Galois Fields, Advanced Encryption Standard (AES), Block Ciphers (ECB, CBC, OFB, CFB, CTR, GCM), Public-Key Cryptography, RSA Cryptosystem, Public-Key Cryptosystems, Discrete Logarithm Problem, Diffie-Hellman Key Exchange, Elgamal Encryption Scheme, Elliptic Curve Cryptosystems, Digital Signatures, RSA Signature Scheme, Elgamal Signature Scheme, Digital Signature Algorithm, Elliptic Curve Digital Signature Algorithm, Hash Functions, Hash Algorithms, Message Authentication Codes (MACs, HMAC, CBC-MAC, GMAC), Key Establishment (Symmetric and Asymmetric), Key Derivation.

C++ Mathematical Finance, Risk, Design Patterns & Derivatives Pricing Models

C++ Software Engineering Design Patterns: C++ Algorithms, Creational patterns, Virtual Copy Constructor, Factory Pattern, Singleton Pattern, Structural patterns, Adapter Pattern, Bridge Pattern, Decorator Pattern, Behavioral patterns, Strategy Pattern, Template Pattern, Iterator; C++ Computational Finance Options and Derivatives Pricing Applications: Monte Carlo Model, Black Scholes Model, Monte Carlo Call Option Pricer, Encapsulation, Open Closed Principle, Inheritance, Virtual Functions, Virtual Constructor, Bridge Pattern, Statistics Gatherer,  Wrappers, Convergence Table, Decorator Pattern, Random Number Generators, Linear Congruential Generator, Anti-Thetic Sampling, Exotics Engine, Template Pattern, Black Scholes Path Generation Engine, Asian Option, Tree Class, Pricing On Trees, Solvers, Templates, Implied Volatilities, Function Objects, Bisections, Newton Raphson Method, Smart Pointers, Exceptions.

C++11 Multithreading & Concurrency Standard Extensions and Operating Systems

Threads, Lambda Expressions, Thread Execution Modes, Thread Termination Modes, References in Multi-threading Mode, Exception Management for Threads, Resource Acquisition is Initialization (RAII), Thread Execution and Document Management, Parameter Passing in Threads, Object References in Threads, std::thread Standard Thread Library, C++ smart pointers, Inter-Thread Execution Transfer, Hardware Concurrency for Multi-Threading, Thread IDs, Preventing Broken Invariants, Mutexes and Race Conditions, Runtime Functions and Arguments Passing, Stack-Related Interface Issues and Race Conditions, std::lock Standard Thread Library, Preventing Deadlocks in Multi-threading, std::lock_guard Standard Thread Library, std::unique Standard Thread Library, std::defer Standard Thread Library, Mutex Ownership Transfers, Efficient Locking of Mutexes, compare vs. swap, Data Initialization and Race Conditions, Initialization of Static Variables, Single Writer & Multiple Readers.

Machine Learning, Signal Processing, Uncertainty & Risk Modeling, Econometric Modeling

Multivalent Logic, Uncertainty Modeling, Interval Arithmetic, Multi-Level Interval Numbers, Fuzzy Numbers, Fuzzy Arithmetic, Fuzzy Sets, Fuzzy Operations, Fuzzy Relations, Many-Valued Logic, ANFIS (Adaptive Neuro-Fuzzy Inference System) Models, MATLAB, Java Neural Network Models, C, Approximate Reasoning, Algorithms, Data Mining, Machine Learning, Supervised Learning, Unsupervised Learning, Semi-supervised Learning, Dimensionality Reduction, Pattern Recognition, Classification, Clustering, Overfitting, Underfitting, K-Means Clustering Algorithms, K-Nearest-Neighbor Algorithms, Feature Selection, Nearest Neighbor Classifiers, Naive Bayes Classifier, Bayesian Classifiers, Differential Misclassification, Bootstrap Aggregating (Bagging), Boosting, Single Link Clustering, Complete Link Clustering, Novelty Detection, Receiver Operating Characteristic (ROC), Decision Trees, Genetic Algorithms, Neural Networks, Wrappers vs. Filters, ID3 Algorithms, C4.5 Algorithms, C5.0 Algorithms, Entropy Estimation.

SAS Applied Data Science & Advanced Data Mining Models

SAS Programming Advanced Techniques and Efficiencies: User-Defined Functions, Controlling I/O Processing and Memory, Accessing Observations, Using DATA Step Arrays, Using DATA Step Hash and Hiter Objects, Combining Data Horizontally; SAS SQL: SQL Queries, Displaying Query Results, SQL Joins, Subqueries, Set Operators, Creating Tables and Views, Advanced PROC SQL Features; SAS Macros: Macro Variables, Macro Definitions, DATA Step and SQL Interfaces, Macro Programs; SAS Data Manipulation Techniques: Controlling Input and Output, Summarizing Data, Reading Raw Data Files, Data Transformations, Debugging Techniques, Processing Data Iteratively, Restructuring a Data Set, Combining SAS Data Sets, Creating and Maintaining Permanent Formats; SAS Programming: SAS Programs, Accessing Data, Producing Detail Reports, Formatting Data Values, Reading SAS Data Sets, Reading Spreadsheet and Database Data, Reading Raw Data Files, Manipulating Data, Combining SAS Data Sets, Creating Summary Reports.

Technologies of Computational Quantitative Modeling, Quantitative Finance & Risk Management

Algorithms: Graph Theory, Dynamic & Linear Programming, Computational Complexity
Algorithms: Social Networks Analysis, Game Theory, Nash Equilibrium, Financial Markets
Algorithms: Mathematical Models of Automata, Computability & Formal Languages
Algorithms: Computational Mathematical Models of Cryptography & Encryption Protocols
Advanced Statistical Models & Machine Learning Numerical Methods for Large Data Frameworks
Bayesian Inference & Markov Chain Monte Carlo Models for High-Dimensional Stochastics
C++11 Concurrency & Multi-threading, Machine Learning, & Java Neural Network Models
C++ Mathematical Finance Derivatives Pricing & Software Engineering Algorithms
C++ Design Patterns Financial Programming for Derivatives & Options Pricing
C++ Financial Programming for Quantitative Finance Models & Applications
C++ Programming for Financial Engineers Course, University of California Berkeley
Cybersecurity-Signal Processing: Cryptography, Finance Protocols, Information Assurance
Network Penetration Testing & Protocols Analyses: Metasploit Pro, Nmap, Wireshark, etc.
Network Security: CCNA Security, ICND1, ICND2; Network Intrusion Detection & Prevention
Statistics for Financial Engineers Course, University of California Berkeley
Math Foundations for Financial Engineers Course, University of California Berkeley
MATLAB Advanced Financial Econometrics Markov Chain & Monte Carlo Models
MATLAB Market Risk, Credit Risk, Volatility, VaR, ARCH, GARCH, EVT, ES Models
MATLAB/MS-Excel/C++ Credit Risk Management & Credit Risk Derivatives Models
MATLAB Stocks and Equity Portfolio Management & Equity Derivatives Models
MATLAB Continuous Time Interest Rates, Yield Curve, Fixed Income Derivatives Models
MATLAB Stochastic Numerical Methods & Mathematics for Quantitative Finance
MATLAB Artificial Intelligence-Machine Learning-Fuzzy Logic-Chaotic Time Series Models
MATLAB Advanced Statistical, Financial Econometrics & Optimization Models
MATLAB Advanced Finance Portfolio Theory, CAPM & APT Matrix Algebra Models
MS-Excel Market Risk, Credit Risk, Volatility, VaR, ARCH, GARCH, EVT, ES Models
MS-Excel/VBA Hedge Fund Statistical Risk/Returns, Asset Pricing, Market Risk Models
MS-Excel/VBA Fixed Income Portfolio Management & Fixed Income Derivatives Models
MS-Excel/VBA Advanced Quantitative Models of Utility Theory & Portfolio Management
MS-Excel/VBA Advanced Statistical, Financial Econometrics & Optimization Models
MS-Excel/VBA/ACL Advanced Financial Accounting & Financial Auditing Models
MS-Excel/VBA/Solver/Macros for Operations Research & Network Programming Models
MS-Excel/VBA/Solver/Macros for Finance, Investments, Accounting Decision Models
SAS Advanced Programming, SAS SQL Processing & SAS Macro Programming Courses
SAS Large Scale Data Models of High-Frequency Econometrics & Market Microstructure
SAS Advanced Quantitative Models of Macroeconomics & Microeconomics Analysis
SAS/SPSS Statistical Analysis of Variance (ANOVA) & Co-Variance (ANCOVA) Models
SAS/SPSS Applied Multivariate Analysis & Applied Regression Analysis Models
SAS/SPSS Correlation, Multivariate Regression & Inferential Statistics Models
SAS/SPSS Quantitative Statistical Structural Equation Models in Behavioral Science
SAS/SPSS Quantitative Statistical Methods in IT, Organizations & Social Sciences
Quantitative Structural Equation Models of Risk Management, Controls & Compliance
Statistical Multivariate Regression Models of Risk Management, Controls & Compliance
Qualitative Survey Research Methods in Organizational Controls & Compliance Analysis.


PROJECTS PORTFOLIO
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2015-2017: 41 SSRN Top-10 Research Rankings: Top-10% SSRN Authors:
AI & Decision Modeling; Algorithms & Machine Learning:
SSRN Top-10 Research Ranking Categories:
• Capital Markets,
• Cognition in Mathematics, Science, & Technology,
• Computational Biology,
• Computational Techniques,
• Computing Technologies,
• Corporate Governance: Disclosure, Internal Control, & Risk-Management,
• Cyberlaw,
• Decision-Making under Risk & Uncertainty,
• Econometric & Statistical Methods,
• Econometric Modeling,
• Econometrics,
• Hedging & Derivatives,
• Information Systems & Economics,
• Interorganizational Networks & Organizational Behavior,
• Mathematical Methods & Programming,
• Microeconomics,
• Operations Research,
• Risk Management,
• Risk Management Controls,
• Risk Modeling,
• Social Network Analysis,
• Stochastic Models,
• Systemic Risk,
• Telecommunications & Network Models,
• Uncertainty & Risk Modeling,
• VaR Value-at-Risk.
Other Categories:
• Banking & Insurance
• Cultural Anthropology,
• Economics of Networks,
• Innovation Law & Policy,
• Mutual Funds, Hedge Funds, & Investment Industry,
• Sociology of Innovation

Recent Research Presentations and Research Reports
*Princeton University Presentations on the Future of Finance: 'Rethinking Finance' for Era of Global Networked Digital Finance.
*2016 Princeton Quant Trading Conference Invited Research Presentation: Beyond Stochastic Models to Non-Deterministic Methods.
*2015 Princeton Quant Trading Conference Invited Research Presentation: Beyond Risk Modeling to Knightian Uncertainty Management.
*Beyond 'Bayesian vs. VaR' Dilemma to Empirical Model Risk Management: How to Manage Risk (After Risk Management Has Failed).
*Markov Chain Monte Carlo Models, Gibbs Sampling, & Metropolis Algorithm for High-Dimensionality Complex Stochastic Problems.
*Risk, Uncertainty, and Profit for the Cyber Era: 'Knight Reconsidered': Model Risk Management of Cyber Risk Insurance Models.
*Cybersecurity & Cyber-Finance Risk Management: Strategies, Tactics, Operations, &, Intelligence: ERM to Model Risk Management.
*Number Field Sieve Cryptanalysis Algorithms for Most Efficient Prime Factorization on Composites: Beyond Shannon's Maxim.
* Bitcoin Protocol & Bitcoin Block Chain: Model of 'Cryptographic Proof' Based Global Crypto-Currency & Electronic Payments System.
*2015-2016 40 SSRN Top-10 Research Rankings for Computational Quantitative & Risk Analytics Algorithms Machine Learning Research.
* 2008 AACSB International Impact of Research Report: Named among Black-Scholes, Markowitz, Sharpe, Modigliani & Miller

Top Wall Street Investment Banks Quantitative Finance Projects & FinTech Ventures
Princeton: Future of Finance: 'Rethinking Finance' for Era of Global Networked Digital Finance
2016 Princeton Quant Trading Conference: Invited Research Presentation: Model Risk Arbitrage
2015 Princeton Quant Trading Conference: Invited Research Presentations: Future of Finance
Quantitative Finance Risk Analytics Modeling Wall Street Investment Banks & VC Projects
Model Risk Management: Risk Management Analytics from 'Prediction' to 'Anticipation of Risk'
Quantitative Finance Risk Analytics, Econometric Analytics, Numerical Programming Models
Quantitative Finance Model Risk Management for Systemic-Tail Risks in Cyber Risk Insurance
JP Morgan Portfolio Optimization, VaR & Stress Testing: 17-Asset Class Portfolio
JP Morgan Portfolio Liquidity Risk Modeling Framework for $500-600Bn Portfolio
Bayesian VaR Beyond Value-At-Risk (VaR) Model Risks Exposed by Global Financial Crisis
Goldman Sachs Alumnus Asset Manager Large-Scale Data High Freq Econometric Models
Quantitative Finance, Risk Modeling, Econometric Modeling, Numerical Programming
Technologies of Computational Quantitative Finance & Risk Analytics and Risk Management
Algorithms & Computational Finance: C++, SAS, Java, Machine Learning, Signal Processing
Cybersecurity, Financial Protocols & Networks Protocols Analysis, and, Penetration Testing
Quantitative Finance, Quantitative Risk Analytics & Risk Management Projects Impact
Digital Social Enterprise Ventures Creating Trillion $ Practices for Hundreds of Millions

Named among FinTech Finance & IT Nobel laureates for Real World Impact of Research
FinTech Innovations: Model Risk Arbitrage, Open Systems Finance, Cyber Finance, Cyber Insurance
AACSB International Reports Impact of Research among Black-Scholes, Markowitz, Sharpe
Research Impact Recognized among Finance & Information Technology Nobel laureates
40 SSRN Top-10 Rankings: Computational Quant Analytics: Algorithms, Methods & Models
FinTech Innovations: Model Risk Arbitrage, Cyber Finance, Cyber Risk Insurance Modeling
Computational Quantitative Finance Modeling & Risk Management Research Publications
Model Risk Management of Cyber Risk Insurance Models & Quantitative Finance Analytics
Thesis on Ongoing Convergence of Financial Risk Management & Cyber Risk Management
U.S. Federal Reserve & Office of the Comptroller of the Currency Model Risk Guidance
Bayesian VaR Beyond Value-At-Risk (VaR) Model Risks Exposed by Global Financial Crisis
Markov Chain Monte Carlo Models & Algorithms to Enable Bayesian Inference Modeling
OCC Notes Cybersecurity Risk & Cyber Attacks as Key Contributor to Banks' Financial Risk
Future of Bitcoin & Statistical Probabilistic Quantitative Methods: Global Financial Regulation
Models Validation Expert Panels: IT, Operations Research, Economics, Computer Science

Global, National, & Enterprise CxO Level FinTech-Cyber-Risk Analytics Ventures
CxO Think Tank that pioneered 'Digital' Management of Risk, Uncertainty, & Complexity
CxO Consulting: Global, National & Corporate Risk Management Practices Leadership
CxO Guidance: Cyber Defense & Finance-IT-Risk Management: Uncertainty & Risk
CxO Keynotes: Conference Board, Silicon Valley, UN, World Economy: Uncertainty & Risk
The Future of Finance Project Leading Quantitative Finance Practices at Elite Conferences
The Griffiss Cyberspace Cybersecurity Venture Spans Wall Street and Hi-Tech Research
UN Quantitative Economics Expert Paper & Keynote on Global Economists Expert Panel
National Science Foundation Cybersecurity & Cybercomputing National Expert Panels
Digital Social Enterprise Innovation Ventures Pioneering the Future of Risk and Quant
Global Footprint of Worldwide World-Leading CxO Risk Management Ventures & Practices


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FinTech: Wall Street & IT: Goldman Sachs, Google, HP, IBM, Intel, Microsoft, Ogilvy, Wells Fargo
Consulting Firms
: Accenture, Ernst & Young, McKinsey, PricewaterhouseCoopers
Business Schools: Harvard, MIT, Princeton, Stanford, UC Berkeley, Wharton
Associations
: AACSB, ABA, ACM, AICPA, AOM, APICS, ASTD, ISACA, IEEE, INFORMS
World Governments: Australia, Canada, European Union, United Kingdom, United States
U.S. Defense
: AFRL, Air Force, Army, CCRP, Comptroller, DISA, DoD, Marines, NASA, Navy
World Defense: Australia (Air Force), Canada (Defence R&D), UK (Ministry of Defence)
World Health: World Health Organization (WHO), U.S. Department of Health & Human Services,
European Health Management Association, U.K. Department of Health, UNESCO, UNDP
Larger Sample

British Telecom UK Cisco Systems IBM Intel Corp. Microsoft

U.S. DoD DISA US Air Force Royal Australian Air Force Government of UK, Ministry of Defence Canadian Department of National Defence

Harvard Business School Stanford Graduate School of Business Wharton School Princeton University UC Berkeley Haas School of Business

MIT Sloan School of Management MIT PressHarvard UniversityStanford School of Medicine

Stanford UniversityMIT 50 K Entrepreneurship CompetitionMIT LibrariesYale Law Journal NASA

Fortune Inc. Business WeekNew York TimesWall Street Journal

Forbes Fast CompanyHarvard Business Press Publishing Computer World Information Week InfoWorld CIO Magazine

ForbesBusiness Week San Jose Mercury NewsInfoWorld American Institute of Certified Public Accountants (AICPA) AACSB International

ACM IEEE AACSB International American Society for Training and Development American Bar Association

And Elsewhere...