Computer Scientist

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Peter J. Schwartz, Ph.D.

https://www.linkedin.com/in/peterjschwartzphd

443-***-**** 93 Old York Court

*****.*****.********@*****.*** North East, MD 21901 Highlights

• Ph.D. in Artificial Intelligence from the University of Michigan

• Exceptional analytical skills for tackling very complex problems

• Experience in Defense and Healthcare industries

Objective

Research and develop advanced computer science and mathematical modeling techniques in order to manage complexity and increase efficiency and scalability when solving computationally challenging problems while contributing to the greater social good. Skills

Subject Matter Expertise: artificial intelligence, mathematical modeling, computational complexity, constraint satisfaction/optimization, Bayesian networks, machine learning Application Domains: model abstraction, network analysis, real-time decision aids, route planning, resource allocation, automated planning/scheduling Languages/Environments: Java, Python, R, C++, Lisp, Eclipse, Visual Studio, Git Non-Technical Experience: business development, technical/proposal writing, oral presentations, project planning/management, team leading, mentoring Education

UNIVERSITY OF MICHIGAN Ann Arbor, MI

Ph.D., Computer Science & Engineering Dec 2007

Intelligent Systems Program

Advisor: Dr. Martha E. Pollack

Dissertation Topic: Managing Complex Scheduling Problems with Dynamic and Hybrid Constraints

UNIVERSITY OF MICHIGAN Ann Arbor, MI

M.S.E., Computer Science & Engineering Dec 2003

UNIVERSITY OF MARYLAND College Park, MD

B.S., Computer Science May 2001

Summa Cum Laude, with Honors

UNIVERSITY OF MARYLAND College Park, MD

B.A., Psychology May 2001

Summa Cum Laude

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Work Experience

PENN MEDICINE Philadelphia, PA

Senior Data Scientist Apr 2015 – present

As a member of both the Data Science Team and the Social Media and Health Innovation Lab, apply Data Science tools and techniques to improve University of Pennsylvania Health System (UPHS) hospital operations and research the relationship between health data and social media. Tease patterns out of electronic health records (EHRs) using machine learning (ML) to model, measure, predict, and optimize patient experiences and health outcomes. Analyze language use on social media using natural language processing (NLP) and compare against health data to monitor and predict health at the individual, hospital, and community level.

ORSA CORPORATION Aberdeen, MD

Senior Mathematician Sep 2007 – Apr 2015

Analyzed complex systems and provided expertise to support decision-makers facing complicated situations, challenging constraints, and competing priorities. Led scientific projects that included theory and methodology R&D, design and analysis of models and algorithms, and software design, implementation, and testing.

• Led a project to support Army Research Laboratory’s (ARL’s) Computational & Information Sciences Directorate (CISD) in the design and optimization of High Performance Computing (HPC) assets deployed in tactical cloudlets.

• Led the Multi-Fidelity Methods (MFM) effort as a Systems Engineering and Technical Advisor (SETA) on the Adaptive Vehicle Make (AVM) program for the Defense Advanced Research Projects Agency (DARPA) Tactical Technology Office (TTO) to increase the scalability of system-level analyses of complex cyber-physical systems (CPS).

• Led a project to support ARL’s Human Research & Engineering Directorate

(HRED) in the development of theory and methodology for large-scale data analysis as applied to Brain-Computer Interaction Technologies (BCIT) in order to detect and predict fatigue induced by monotonous or vigilance type tasks.

• Led a project to support the Defense Threat Reduction Agency (DTRA) in the development of an advanced real-time route planning decision aid to minimize exposure to chemical, biological, radiological, and nuclear (CBRN) hazards.

• Led a project to support Army Research Laboratory’s Human Research & Engineering Directorate (HRED) in the development of a real-time automated task allocation system that optimizes mission performance by recommending allocations of tasks to crew members based on physiometric data and mission context.

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UNIVERSITY OF MICHIGAN Ann Arbor, MI

Graduate Student Research Assistant Sep 2001 – Aug 2007 Studied Automated Search and Constraint Processing techniques in the field of Artificial Intelligence in order to efficiently represent and solve computational problems considered too complex for standard Computer Science techniques. Developed new representations and algorithms for automated scheduling and applied them to air traffic control and traumatic brain injury (TBI) patients with mild cognitive impairment (MCI). Responsible for compiling and organizing cutting-edge research on state-of-the-art systems, integrating this research to evaluate the strengths and limitations of existing theories, and extending it in novel and innovative ways. Developed theoretical concepts, implemented new systems, executed experiments, analyzed data, and reported results. Clearly and concisely communicated novel and complex ideas, presenting written documents and oral presentations in situations ranging from team meetings to international conferences. Served as the lead author of several critically reviewed conference papers, traveling internationally to present them to the larger academic community. US ARMY MATERIEL SYSTEMS ANALYSIS ACTIVITY Aberdeen Proving Ground Student Trainee (Operations Research Analyst) Jun 1994 – Aug 2001 Supported the acquisition of Army materiel by reviewing existing models and simulations, assessing their methodologies, implementing necessary changes, and assisting with Verification, Validation, and Accreditation (VV&A). This work was performed during summer and winter breaks as a high school and undergraduate student. Publications

Schwartz, P., and Pollack, M.E. (2005). Two Approaches to Semi-Dynamic Disjunctive Temporal Problems. International Conference on Automated Planning and Scheduling

(ICAPS) Workshop on Constraint Programming for Planning and Scheduling. Schwartz, P., and Pollack, M.E. (2004). Planning with Disjunctive Temporal Constraints. International Conference on Automated Planning and Scheduling (ICAPS) Workshop on Integrating Planning into Scheduling.

Volunteer Activities

ABERDEEN SCIENCE AND MATH ACADEMY Aberdeen, MD

Mentor Feb 2008 – May 2015

As a mentor at the Science and Math Academy at Aberdeen High School, I guided students through the completion of a Senior Capstone Project. I assisted in developing the goals, scope, and timeline of the project, and I provided supervision and support as the students carried out the research and presented the results. This was a fulfilling way to give back to my community and influence the next generation of research scientists.

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