The Applied Probability Society is a subdivision of the Institute for Operations Research and the Management Sciences (INFORMS). The Society is concerned with the application of probability theory to systems that involve random phenomena, for example, manufacturing, communication network, computer network, service, and financial systems. The Society promotes the development and use of methods for the improvement of evaluation, control, and design of these systems. Such methods include (stochastic) dynamic programming, queueing theory, Markov decision process, discrete event dynamic systems, point processes, large deviations, reliability, and so on. Our members include practitioners, educators, and researchers with backgrounds in business, engineering, statistics, mathematics, economics, computer science, and other applied sciences.

The Applied Probability Society also publishes Stochastic Systems. This open-access journal seeks to publish high-quality papers that substantively contribute to the modeling, analysis, and control of stochastic systems. The contribution may lie in the formulation of new mathematical models, in the development of new mathematical methods, or in the innovative application of existing methods. A partial list of applications domains that are germane to this journal include: service operations; logistics, transportation, and communications networks (including the Internet); computer systems; finance and risk management; manufacturing operations and supply chains; and revenue management.

Latest Discussions

There are no discussions to which you have access

Either the content you're seeking doesn't exist or it requires proper authentication before viewing.

Jobs of Interest to APS

  • Beijing, China, POSITION S Assistant Professor/Associate Professor/ Full Professor in Management Science and Engineering   ABOUT THE ORGANIZATION Tsinghua has the most selective undergraduate program in Mainland China and is among the top 50 universities in the world according to both Times of London and QS rankings. With its Beijing campus inside an expansive former Qing Dynasty garden, the school provides an excellent research environment and the possibility of teaching undergraduate, Master’s (research-oriented, MBA and EMBA) and Ph.D. students. More information about the school can be found at http://www.sem.tsinghua.edu.cn (English version: http://www.sem.tsinghua.edu.cn/portalweb/appmanager/portal/semEN).   POSITIONS SUMMARY The School of Economics and Management (SEM) at Tsinghua University invites applications for faculty positions (Assistant Professor, Associate Professor and Full Professor) in the Department of Management Science and Engineering. The School offers competitive salary, relocation fund, start-up research fund and other fringe benefits. Applicants should hold (or expect to hold before employment) a Ph.D. degree in the field of Information Systems, Operations Management, and related fields. Candidates with a strong methodological background in data analysis and machine learning, optimization, and stochastic methods are preferred. We stress high research potential or achievement. Candidates must be committed to effective teaching, scholarly and professional research, as well as university and community service. Rank and salary will be commensurate with qualifications and experience. No knowledge of Chinese is required, and applicants of all nationalities are encouraged to apply.   APPLICATION To apply, please send an application cover letter, CV (including a list of publications and working papers), three letters of reference (apart from tenured positions), evidence of research and teaching excellence, selected articles or working papers to scholar@sem.tsinghua.edu.cn .   Screening of candidates will start immediately and will continue until the positions are filled.   Information Systems, Operations Management, and related fields. Candidates with a strong methodological background in data analysis and machine learning, optimization, and stochastic methods are preferred. We stress high research potential or achievement. Candidates must be committed to effective teaching, scholarly and professional research, as well as university and community service. 
  • Washington, D.C., Managing Consultant, Guidehouse Inc., Washington, DC. Consult with clients to manage the day-to-day client relationships for domestic and global wholesale power market projects including energy, transmission and capacity. Perform advanced research and analysis in energy markets and technology trends, the macro economic factors influencing those markets over a 30 year time horizon, simulating future scenarios in those markets and perform sensitivities for key contributing factors, and develop forecasts (zonal/nodal). Take the lead in performing energy modeling and forecasting for decades long time horizons. Collect, manipulate and analyze data. Conduct fact-finding, research and analysis, develop analytical models, trends for integrated resource planning & reference case projects. Perform locational marginal pricing (LMP) and production cost simulations using security constrained commitment and dispatch software. Model, analyze, and develop assessments for power markets using stochastic analysis, manage asset valuation, production cost, capacity prices and expansion models, perform transaction due diligence. Program and design these models and conduct competitive market analysis to focus on renewable and emerging electric production technologies. Coordinate project management (scheduling, client updates, budget) and ensuring cost-effectiveness testing at the program and portfolio level on energy projects. Make presentations to senior management within a customer environment & at industry conferences. Technical environment: MS Suite, Excel, Aurora, PROMOD, EPM Simulation model software, C#, Visual Basic, Python. 40 hrs/week, Mon-Fri, 8:30 a.m. - 5:30 p.m. MINIMUM REQUIREMENTS :   Master’s degree or foreign equivalent degree in Engineering, Operations Research, Technology Management or other quantitative field, and 2 years of related work experience in the job offered or as a researcher or consultant. In the alternative, the employer will accept a bachelor’s degree or foreign equivalent in Engineering, Operations Research, Technology Management or other quantitative field plus 5 years of experience in the job offered or as a researcher or consultant. Must have any experience in the following: Client-facing role in wholesale power markets (domestic & global) including energy, transmission and capacity developing analytical energy models, analyzing energy data, trends; Working on integrated resource planning & reference case projects using macroeconomic factors influencing markets over 30 year period, developing 20/30 year forecasts (zonal/nodal), simulating future scenarios using EPM & perform sensitivities for key contributing factors, production cost, capacity prices & expansion models; LMP and production cost simulations using security constrained commitment; Model, analyze, and develop assessments for power markets using stochastic analysis; Perform transaction due diligence for power plants using Aurora; Presenting to senior management and clients. Please apply to: Barbara Homme, Guidehouse Inc., 150 North Riverside Plaza, Suite 2100, Chicago, IL 60606. Please reference Job-ID: DC0005.
  • Baltimore, Maryland,   General Summary The Healthcare Data Scientist position will join our Advanced Analytics group at the University of Maryland Medical System (UMMS) in support of its strategic priority to become a data-driven and outcomes-oriented organization. The successful candidate will have 3+ years of experience with Machine Learning, Predictive Modeling, Statistical Analysis, Mathematical Optimization, Algorithm Development and a passion for working with healthcare data. Previous experience with various computational approaches along with an ability to demonstrate a portfolio of relevant prior projects is essential. This position will report to the UMMS Vice President for Enterprise Data and Analytics (ED&A).   Principal Responsibilities and Tasks Develops and manages predictive (machine learning and deep learning) and prescriptive (mathematical optimization and simulation) analytic models in support of the organization’s clinical, operations and business initiatives and priorities. Deploys solutions so that they provide actionable insights to the organization and are embedded or integrated with application systems Supports and drives analytic efforts designed around organization’s strategic priorities and clinical/business problems Works in a team to drive disruptive innovation, which may translate into improved quality of care, clinical outcomes, reduced costs, temporal efficiencies and process improvements. Builds and extends our analytics portfolio supported by robust documentation Works with autonomy to find solutions to complex problems using open source tools and in-house development Stays abreast of state-of-the-art literature in the fields of operations research, statistical modeling, statistical process control and mathematical optimization Creates and communicates project plans and other required project documentation and provides updates to leadership as necessary Develops and maintains relationships with business, IT and clinical leaders and stakeholders across the enterprise to facilitate collaboration and effective communication Works with the analytics team and clinical/business stakeholders to develop pilots so that they may be tested and validated in pilot/incubator settings Performs analysis to evaluate primary and secondary objectives from such pilots Assists leadership with strategies for scaling successful projects across the organization and enhances the analytics applications based on feedback from end-users and clinical/business consumers Assists leadership with dissemination of success stories (and failures) in an effort to increase analytics literacy and adoption across the organization. Knowledge, Skills and Abilities Ability to develop (from scratch) machine learning and/or deep learning approaches to solving clinical and business (including operations, supply chain, human resources, finance) problems. Knowledge of databases, data structures, data processing and data mining. Ability to perform independent/unsupervised exploratory data analysis. Ability to develop complex process models using discrete-event-simulation. Ability to program independently in Python (intermediate skills); ability to participate in software platform and web application development. Proven communications skills – Effective at working independently and in collaboration with other staff members. Capable of artful storytelling and clearly presenting findings in oral and written format and through graphics. Proven analytical skills – Able to compare, contrast, and validate work with keen attention to detail. Skilled in working with “real world” data including scrubbing, transformation, and imputation. Proven problem solving skills – Able to plan work, set clear direction, and coordinate own tasks in a fast-paced multidisciplinary environment. Expert at triaging issues, identifying data anomalies, and debugging software. Design and prototype new application functionality for our products. Change oriented – actively generates process improvements; supports and drives change, and confronts difficult circumstances in creative ways Effective communicator and change agent Ability to prioritize the tasks of the project timeline to achieve the desired results Strong analytic and problem solving skills Ability to cooperatively and effectively work with people from various organization levels Education and Experience Master’s or higher degree (may be substituted by relevant work experience) in applied mathematics, engineering, operations research, physics, computer science, statistics or a related field. PhD degree preferred. Background in computer science, operations research, statistics or a physical engineering discipline. 3+ years of Machine Learning/Predictive Analytics and Mathematical Optimization experience (to include time in graduate program for applicants with PhD degrees). Prior experience with Python and R is a must (experience with tools such as WEKA, RapidMiner, or other open source tools are strongly preferred). Ability to develop and apply computational algorithms and statistical methods to healthcare data (including, but not limited to data from electronic medical record, financial management, human resource, quality and supply chain) Ability to develop and deploy healthcare-relevant predictive and prescriptive models. Ability to perform standard statistical analysis. Ability to formulate and solve mathematical (deterministic and stochastic) optimization problems and simulation; prior experience in Arena, FlexSim or similar environments. Experience with discrete-event-simulation strongly preferred. Robust experience with SQL Intermediate development skills in Python. Ability to combine analytic methods and advanced data visualizations. Experience with Big Data technologies, including Hadoop. Expert ability to break down and clearly define problems. Experience with text mining and Natural Language Processing (NLP) desirable. Incentive Plan Offered. Competitive medical, dental and retirement benefits.

Stochastic Systems Articles

Recent Shared Files

No Data Found

Either the content you're seeking doesn't exist or it requires proper authentication before viewing.


Log in to see this information