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.

To keep up-to-date with all the latest developments in the Applied Probability Society community, INFORMS members should make sure to subscribe for real-time or digest correspondence through INFORMS Connect. For INFORMS members outside of the Society or for community members outside of INFORMS who would like to receive updates as well, register here to receive select Applied Probability Society communication directly.

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

  • Houston, Texas, The Department of Health Services Research at The University of Texas MDAnderson Cancer Center has an opening for two postdoctoral fellowships. Under the mentorship of Dr. Iakovos Toumazis , these postdoctoral fellowships will provide highly motivated individuals with the opportunity to contribute to the design, implementation, analysis, and publication of high-impact studies focusing on public health policy, decision analytics, mathematical modeling and microsimulation modeling. The first position focuses on the development and application of decision analytical models to optimize sequential decision-making under uncertainty for lung cancer screening (OR-focused position). The second position focuses on the development and application of computer simulation-based modeling to simulate the lung cancer disease progression and assess the impact of alternative interventions on cancer incidence and mortality (microsimulation-focused position). Job Responsibilities: OR-focused position: Develop optimization models to optimize sequential medical decision making under uncertainty. Assess the effectiveness and cost-effectiveness of optimal policies to inform public health policy. Microsimulation-focused position: Develop microsimulation models for decision analysis and cost-effectiveness analysis. Calibrate and validate microsimulation models to observed outcomes from clinical trials and/or cancer registries. Both positions: In coordination with the principal investigator, lead the research team in writing manuscripts, disseminating findings at scientific meetings, and preparing grant applications. Qualifications: OR-focused position: Expertise in Markov decision process (MDP)/partially observable MDP (POMDP) is required. Prior experience in data analytics, applications of operations research to public health and medical decision making is highly desired, but not required. Microsimulation-focused position: Expertise in stochastic simulation modeling and Monte Carlo methods is required. Prior experience with model validation and calibration is highly desired but not required. Experience in survival analysis, parameter estimation, and data analytics will be considered a plus. Both positions: Good understanding of mathematical modeling and hands-on experience of general-purpose programming languages such as Julia, R, Python, or MATLAB is required. Strong writing and verbal communication skills are required. Education: Qualified candidates should have or be close to completion of a Doctorate Degree in industrial engineering, operations research, computer science, health services research, epidemiology, health-outcomes research, biostatistics, data science or a related quantitative field. Terms : The two fellowships are for one-year, full-time commitment, renewable upon mutual consent with competitive salary and benefits. Opportunities for the fellows to write and submit their individual career development grants (e.g. NIH career development award) would be provided and strongly supported by the PI and the institution. Institution: MD Anderson consistently tops U.S. News & World Report’s list for cancer care (“America’s Best Hospitals”) and is located in the Texas Medical Center (TMC), the world’s largest. The proximity of the TMC to Rice University and the Museum District, light rail connections to world-class performing arts and professional sporting venues, a short drive from Galveston and the Texas coast, and a diverse population of Houston are a few features of this uniquely cosmopolitan and affordable city. Contact Information: To apply, interested candidates should submit a brief cover letter personalizing one’s interest in the position(s), with information about research experience and interests, and their CV with the names and contact information for references to Dr. Iakovos Toumazis, IToumazis@mdanderson.org with subject: “ Postdoctoral Fellowship – OR ” or Apply via Slate for the OR-focused position or with subject “ Postdoctoral Fellowship – Microsimulation ” or Apply via Slate for the microsimulation-focused position. Review of applications will begin immediately and continue until both positions are filled.   Sincerely, Iakovos Toumazis, PhD Assistant Professor Department of Health Services Research Division of Cancer Prevention & Population Sciences IToumazis@mdanderson.org T 713-792-4420 F   713-563-0059
  • Fargo, North Dakota, Position Description and Responsibilities: The Industrial and Manufacturing Engineering (IME) Department at North Dakota State University (NDSU) invites applications for a (tenure-track) Assistant Professor position.  The successful candidate will be expected to: 1) establish a program of externally-funded research with an excellent record of scholarly publication, 2) teach undergraduate and graduate courses and supervise MS and PhD students, and 3) provide service to the university and its units, to the state and regional community, and to the appropriate professional organizations. We invite candidates in all areas of IME to apply, with preference given to candidates with:  at least one degree in industrial or manufacturing engineering, prior teaching experience, experience in operational research, machine learning, artificial intelligence, stochastic methods, statistics, systems modeling, and/or advanced analytical methods will be considered. Department:  The IME department has seven full-time faculty and over 170 students in programs leading to bachelor’s, master’s, and doctoral degrees.  The programs leading to the Bachelor of Science in Industrial Engineering and Management and the Bachelor of Science in Manufacturing Engineering degrees are accredited by the Engineering Accreditation Commission of ABET.  For more information regarding our department and programs see the department’s website:  https://www.ndsu.edu/ime/        University: NDSU has a land-grant mission of teaching, research, and service.  NDSU is an EEO/AA-MF/ Vet/ Disability employer, an ADVANCE institution, and a Carnegie Very High Research Activity Institution.   Qualifications: Earned a Ph.D. or be expected to complete their degree in industrial or manufacturing engineering or closely related discipline.  Must have excellent oral and written communication skills in English, have strong interest and potential to develop and conduct a sponsored research program, have credentials to teach a variety of courses in industrial and manufacturing engineering at both the undergraduate and graduate levels.  An interest and an ability to interact and collaborate effectively with a diversity of staff, colleagues and students and provide exceptional service to faculty, staff, students, and guests by fostering a professional and collaborative work environment is also required.
  • Slater, Iowa, About Syngenta   Syngenta is a global leader in agriculture; rooted in science and dedicated to bringing plant potential to life. Each of our 28,000 employees in more than 90 countries work together to solve one of humanity’s most pressing challenges: growing more food with fewer resources. A diverse workforce and an inclusive workplace environment are enablers of our ambition to be the most collaborative and trusted team in agriculture. Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. Join us and help shape the future of agriculture.   About Us   Syngenta Digital is changing the agriculture industry and we want you to be part of that. Digital innovations, data and new technologies will transform the way that crops are managed in the future and enable farmers and agronomists to enhance efficiency and sustainable food production. You will help to develop solutions that turns data into meaningful information and ultimately helps to grow more food with fewer resources.   The Syngenta Analytics and Data Sciences team is seeking a Biostatistician with a passion for utilizing their statistical and applied mathematical skills to help transform our Seeds product development pipeline, through enhanced experimental designs and analytics. As a Biostatistician you will work collaboratively on the design, analysis, and implementation of industry-leading experimental designs and biometric capabilities to improve decision making for Syngenta Seeds Research and Development.   You will help transform digital agriculture by: Working collaboratively on the design, analysis, and implementation of industry-leading experimental designs and the biometric capabilities to improve decision making for Syngenta Seeds Research and Development. Accountabilities Play a major role in defining, designing, and enhancing our experimental designs and analysis capabilities for our field trial experiments that support our global seeds business Assist in modernizing our field trialing system by utilizing phenomics, sensor data, and spatial analyses to gain insights and enhance decision making Model complex problems, discover insights, and identify opportunities with the use of statistics, applied mathematics, and visualization techniques Provide fit-for-purpose statistics and data analytics support Identify data needs and provide recommendations; efficiently process, clean, and verify the integrity of data used for analyses Locations available: Downers Grove or Malta, Illinois; Slater, Iowa; Raleigh-Durham, North Carolina Requirements Ph.D. or Master’s degree with equivalent experience in applied mathematics, statistics, data science or related quantitative field 2+ years of experience in statistical methods applied to experimental design and analysis, including programming, multivariate statistics, probability, and spatial statistics Experience using a programming language (Python, C/C++, Matlab) or a statistical computer language (R, Python, SQL) to manipulate data and draw insights from large data sets Experience with visualization and rapid prototyping tools (R Shiny, Spotfire, Power BI) Technical understanding of plant breeding and environmental trialing Preferred Requirements Formal training and experience in mixed-linear models, generalized linear models, machine learning models, stochastic or mathematical simulation models Experience with Agile methodology Demonstrated accountability, continuous development, collaboration, and strong communication, and storytelling skills Ability to network and collaborate with colleagues from diverse technical backgrounds to build and enable end to end solutions What We Offer: Full Benefit Package (Medical, Dental & Vision) that starts the same day you do 401k plan with company match, Profit Sharing & Retirement Savings Contribution Paid Vacation, 12 Paid Holidays, Maternity and Paternity Leave, Education Assistance, Wellness Programs, Corporate Discounts among others A culture that promotes work/life balance, celebrates diversity and offers numerous family-oriented events throughout the year   Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.   Family and Medical Leave Act (FMLA) ( http://www.dol.gov/whd/regs/compliance/posters/fmla.htm )   Equal Employment Opportunity Commission's (EEOC) ( http://webapps.dol.gov/elaws/firststep/poster_direct.htm )   Employee Polygraph Protection Act (EPPA) ( http://www.dol.gov/whd/regs/compliance/posters/eppa.htm )
  • Fort Collins, Colorado, Platte River Power Authority is a public power provider that has emerged as a leader in Colorado’s utility sector. Our staff works collaboratively and efficiently to safely deliver reliable, environmentally responsible and financially sustainable energy and services to our owner communities of Estes Park, Fort Collins, Longmont and Loveland. We share a sense of purpose and great pride in what we do and the value we provide to our communities, our region and the energy industry. If you’re searching for a collaborative working environment within a mid-sized organization that values innovative ideas, diverse perspectives and provides opportunities to make a difference, consider joining the Platte River team. Senior Resource Planner The Senior Resource Planner is responsible for developing integrated resource plans, conducting production cost studies, annual budget preparation, supply side and DER (Distributed Energy Resources) evaluation for deep decarbonization planning, transaction evaluation and providing other technoeconomic analytical support to Platte River’s strategic planning and resource planning efforts. This position will work in a cross-functional team environment with staff and management from multiple departments. Essential duties and responsibilities Must possess required knowledge, skills, abilities and experience and be able to perform, with or without reasonable accommodations, the essential functions of the job. Utilizes advanced simulation platforms such as Plexos, Aurora, EnCompass, and PROMOD, etc. to develop optimal resource portfolios for Platte River Provides production simulation results for budgeting, rate making and other requirements Utilizes advanced statistical simulation, Monte Carlo simulation, simple ant stochastic optimization to enrich the quality of analytical work Supports renewables and storage integration to meet reliability needs in a deeply decarbonized portfolio Analyzes DERs and supply-side resource alternatives Supports competitive bid evaluation for power procurement and other purchase/sale transactions Incorporates a broad range of future uncertainties in fuel prices, electric market prices, CO2 requirements, costs of renewable and storage technologies, system reliability requirements, State and Federal policies Provides analytical support for better integration into an energy market Collects and verifies data from internal and external sources. Organize data for ease of use in the modeling and future updates Keeps modeling tools and assumptions accurate and current including fuel costs, production capability (heat rates, capacity, starting and variable operating cost, scheduling flexibility, renewable profiles, etc.), contract terms and other factors Develops presentation materials from modeling and other analyses to support communications with senior management, the Board of Directors and other stakeholders This role is classified as a marketing function employee under FERC (Federal Energy Regulatory Commission) Standards of Conduct. The employee will need to become familiar with, and follow FERC Standards of Conduct Maintains regular and reliable attendance Other functions Interfaces and works with different organizations within Platte River Researches, tracks and evaluates new and innovative technologies to enhance electric service tot he Municipalities and their customers Performs other duties as assigned   Bi-weekly salary range for this position: $3,935 - $5,411 (placement DOQ) (if annualized: $102,312 - $140,676 DOQ) Platte River Power Authority offers employees an outstanding benefits package. Benefits offered for this position may include the following: health insurance options including PPO and high deductible with health savings account; telemedicine; benefit advocacy; dental and vision insurance; FSA; basic as well as voluntary life insurance and accidental death and disability; long-term disability insurance; paid holidays; paid time off; wellness program; in-house training opportunities; tuition reimbursement; and employee assistance program. For additional information, please see our website careers page at: https://www.prpa.org/careers/benefits/ Knowledge, skills and abilities The following are required: Extensive analytical skills including statistical and optimization modeling Excellent computer skills with the ability to learn new software applications quickly High attention to detail with the ability to produce accurate results Excellent verbal and written communication skills Strong interpersonal and collaborative skills with the ability to work independently and as part of cross functional teams Ability to think strategically for innovative ways to incorporate various possible situations Ability to manage shifting priorities Excellent facilitation skills Demonstrated knowledge of electric generating unit's operation and performance characteristics The following are preferred: Project Management Professional Certification Minimum qualifications Bachelor's degree in Engineering, Finance, Statistics, Operation Research, Economics, Mathematics, Business or related field Minimum three years of electric utility resource planning with specific experience in computer modeling and analysis Minimum one year of experience running planning tools like Plexos, Aurora, Promod, Encompass Current valid driver's license and ability to remain insurable under Platte River's vehicle liability policy
  • Daejeon, South Korea, The Department of Industrial & Systems Engineering at KAIST invites applications for tenure-track faculty positions at the levels of Associate/Assistant Professor . KAIST is a globally renowned science and technology institution, particularly well known for its excellence in engineering and technology. The institute is dedicated to promoting a vibrant academic culture and offers an internationally-minded environment through ways such as teaching all courses in English.  We seek candidates who are genuinely interested in solving complex system design and operations problems in manufacturing and service industries. In this term of invitation, we would like to invite all areas of expertise related to industrial & systems engineering discipline, including (but not limited to) the followings: Optimization : LP/IP, combinatorial, stochastic programming, convex opt., non-linear opt. as well as optimization for machine learning and machine learning for optimization. Statistical methods : Statistics, data mining/statistical ML, applied statistics such as quality engineering, experimental design, reliability. Manufacturing system engineering : smart factory, manufacturing system innovation for 2050. Knowledge-based service engineering (KSE): ML/AI for various KSE domains (financial service, health service, legal service, education service, social welfare and so on). KSE domain researchers (those who have earned doctoral degrees in medicine, healthcare, economics, finance, law, education, social welfare, etc.) with experience and strong willingness in applying ML/AI to the domain are also welcome to apply. System engineering : Modeling and simulation (incl. discrete event simulation, simulation optimization), domain specific system engineering (energy system, healthcare delivery system, traffic system, other public infra-structures). Human factors : HCI, AR/VR, Data visualization, ergonomics. Emerging fields relevant to industrial & systems engineering. Industrial or academic experience will be considered preferably, and students who are expected to complete their PhDs within 6 months from the application date will also be considered. Application documents along with an up-to-date CV should be sent to: Professor Hayong Shin    Department of Industrial & Systems Engineering, KAIST    Email: hyshin@kaist.ac.kr Applications are considered on a rolling basis (reviewed each month) until the positions are filled. We strongly recommend applying at your earliest convenience. For general information about the Department of Industrial & Systems Engineering at KAIST, please visit http://ie.kaist.ac.kr  and also http://kse.kaist.ac.kr. You can also find out more about KAIST at  http://kaist.ac.kr. If you have further inquiries regarding this faculty position announcement such as targeting areas, you may contact Prof. Hayong Shin at hyshin@kaist.ac.kr.

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.


  • photo not available
    Sandeep Juneja
    29 Points
  • photo not available
    Serhan Ziya
    22 Points
  • photo not available
    Jing Dong
    16 Points