Christopher Asakiewicz

Teaching Professor

School: School of Business

Building: Babbio Center

Room: 427

Phone: (201) 216-8012

Fax: (201) 216-5385

Email: casakiew@stevens.edu

Website

Research

Collaborative Research and Discovery
IT-Enabled Business Process Innovation
Knowledge Mining and Visualization
Healthcare Analytics
Cognitive Systems
Artificial Intelligence

General Information

Publications and Speaking Engagements:

Journal Articles:
Building a Cognitive Application using Watson DeepQA, Accepted for Publication July/August 2017, IEEE IT Professional Magazine.

Translational Research 2.0 – A Framework for Accelerating Collaborative Discovery, May 2014, Journal of Personalized Medicine, Volume 11, Number 3, pp 351-358.

Business Investments in IT: Managing Integration Risk, July/August 2011, IEEE IT Professional Magazine.

Conference Proceedings:
Accelerating Translational Research by Leveraging AI and Machine Learning, PhUSE 2020 US Connect Conference, Orlando, Florida, at: https://www.phusewiki.org/docs/2020%20US%20Connect%20Florida/Presentations/ML/Final%20Papers/ML04%20pdf.pdf

The Impact of Data and Knowledge Integration on Biobanking and Collaborative Discovery, 2010, International Conference on Management Science and Information Engineering (ICMSIE)

Semantic Discovery in Biomedical Research: Grants, Patents, and Publications, 2010, International Conference on Cellular, Molecular Biology, Biophysics and Bioengineering (CMBB)

Doubling IT Innovation Spending: Laying the Foundation for IT-Enabled Business Process, Supply Chain, and Service Innovation in the Pharmaceutical Industry, 2009, International Conference on Management and Service Science, Beijing, China, IEEE Catalog Number: CFP0941H-CDR, ISBN: 978-1-4244-4639-1

White Papers:
Cognitive Analytics for Making Better Evidence-based Decisions, 2017, SSRN Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2965767.

The Intelligent Enterprise: Scenario Analysis for Better Decision Making in Pharmaceutical, Diagnostic, and Medical Device New Product Development, 2015

Translational Research 2.0 – Searching for Answers in a World of Big Data, SSRN 2013

Translational Research 2.0, 2012

Integrated Research Systems – Accelerating Medical and Healthcare Research, 2011.

Research Monograph:

Enterprise Systems Value-Based R&D Portfolio Analytics: Methods, Processes, and Tools, 2014, A013 – Final Technical Report , Systems Engineering Research Center, SERC-2014-RT-041-1

Keynote/Major Speaker Engagements:

Accelerating Translational Research by Leveraging AI and Machine Learning, PhUSE 2020 US Connect Conference, Orlando, Florida, at: https://www.youtube.com/watch?v=7Vurg4_CvvM&list=PLS6XDiRNQo00BYx8nyJkll8BRfjPP3zSR&index=4&t=0s

Industry Academic Partnership (Genesis Research and Stevens School of Business), PhUSE Conference “Artificial Intelligence and the Digital Transformation of Healthcare” Keynote Presentation and Conference Chair, July 2019

Cognitive Analytics for Enhanced Data Analysis and Decision Making, PhUSE Conference “Artificial Intelligence and Data Automation – Game Changer on Data Analysis and Decision Making” Invited Presentation, May 2018

Cognitive Analytics for Making Better Evidence-based Decisions, PhUSE Conference “The Future is Now – Harnessing Big Data!” Invited Presentation, August 2017

The Language of Business in Pharmaceutical and Life Science Research, Pfizer Worldwide Research and Development “The Business of Science” Invited Lecture, August 2016

High Velocity Organizations, HSATM Roundtable, July 2015

The Intelligent Enterprise: Scenario Analysis for Better Decision Making, HSATM Research Forum, November 2014

Translational Research 2.0, Cambridge Health Technology Web Symposium, September 2012

Integrated Research Systems – Accelerating Medical and Healthcare Research, Research Informatics Web Conference, August, 2011

The Impact of Data and Knowledge Integration on Biobanking and Collaborative Discovery, International Society of Biological and Environmental Repositories (ISBER) 2010 Annual Meeting, May 11th – May 14th, 2010 Rotterdam, Netherlands

Semantic Discovery in Biospecimen Science, 3rd Annual Biospecimen Research Network (BRN) March 24th – March 25th, 2010. Bethesda, Maryland

Keynote: IT-Enabled Process Integration Risk Management and its Impact on Biomedical Research, Bio IT World Expo Europe: October 6th – October 9th, 2009 – Hannover, Germany

Keynote: Doubling IT Innovation Spending: Laying the Foundation for IT-Enabled Business Process, Supply Chain, and Service Innovation in the Pharmaceutical Industry, Bridging IT and Pharma Conference: September 30th – October 2nd, 2007 - Hyatt Harborside - Boston, MA

Keynote: Maximizing the Business Value of IT, Wharton Technology Conference, Philadelphia, PA, 2004

e-Seminar: Knowledge Mining: Fast and Effective Analysis of Clinical Research Results, ClearForest e-Seminar Series, 2004

Colloquia: Implementing IT Governance, Carnegie Mellon University, Tepper School of Business, 2004

Experience

A senior management professional with strategic background in Business Technology Management, Information Technology, Consulting and Education with a 21-year history as a Vice President of Global Business Technology at Pfizer. Chris has done pioneering work in the areas of Knowledge Mining and its application within Life Sciences, most notably as a means of accelerating Translational Research. His research and teaching interests include: Cognitive Systems; Healthcare Analytics; Enterprise-level Application; Information; and Business Process Rationalization; as well as Talent, Skill, and Capability Development.

Institutional Service
  • Graduate Curriculum Committee Member
  • BI&A Advisory Board Chair
  • BI&A Curriculum Committee Chair
  • Institute Curriculum Committee Member
  • Corporate Friendly Committee Member
Consulting Service

Chris’ current IT strategy and management consulting engagements have been with major life sciences firms, healthcare organizations, and disease foundations, helping them in integrating major IT-enabled business processes, assessing and managing the risks associated with major change efforts (ERP, CRM, and SCM), and assisting in the establishment of a biobank and collaborative environment to support rare disease research.

Professional Societies
  • PhUSE – Global Pharmaceutical User Group for Data Management, Biostatistics, and Statistical Programming Member
  • ACM – Association for Computing Machinery Member
  • IEEE – Institute for Electrical and Electronics Engineers Senior member
Grants, Contracts, and Funds

Funded Research:

Proposed Research Funding for Document Driven Programming & Quality Control in Statistical Analysis, 2020-2021, with support from Merck Pharmaceuticals, Funding of $248K (over 2 years). In collaboration with Dr. Rong Liu and Dr. David Belanger.


Research Funding for the following research projects: Research Network Analysis Project for Wiley, a Cybersecurity - Web Log Mining Project for the I.E.E.E., a Transportation Optimization Modeling Project for Pfizer, and a Machine Learning project for J.P. Morgan Chase, 2018, and Natural Language Processing for Data Identification and Extraction from Pooled Healthcare Research Data for Genesis Research, 2019.


Research Funding for Value-Based R&D Portfolio Analytics: Methods, Processes, and Tools, 2014, with support from the Department of Defense, U.S. Army Armament Research, Development, and Engineering Center (ARDEC) Office of Strategic Business Development.


Research Funding for the Establishment of a Biobank for Rare Disease Research in Neurofibromatosis (NF), 2010, with support from the Department of Defense, Office of Congressionally Directed Medical Research Programs (CDMRP) and the Children’s Tumor Foundation (CTF).


Selected Publications
Journal Article
  1. Asakiewicz, C.; Stohr, E.; Mahajan, S.; Pandey, L. (2017). Building a Cognitive Application Using Watson DeepQA. IT Professional (4 ed., vol. 19, pp. 36-44).
    https://api.elsevier.com/content/abstract/scopus_id/85028750734.
Review, Journal
  1. Asakiewicz, C. (2014). Translational Research 2.0: A framework for accelerating collaborative discovery. Personalized Medicine (3 ed., vol. 11, pp. 351-358).
    https://api.elsevier.com/content/abstract/scopus_id/84902593187.