Modern distribution systems need to fulfill a wide variety of requests quickly with little warning in small units to many dispersed locations at low costs. This is fundamentally different than yesterday’s demand, which aggregated at fixed (store) locations. Thus, today’s supply chains are optimized for yesterday’s customers.
To close the gap between current supply chain operations and customer expectations, our research team rethinks supply chain design. We are exploring creative solutions around on-demand warehousing and crowdsourced deliveries, in which marketplaces provide access to resources (when and where they are needed), rather than owning them. This creates a dynamic supply network, able to respond to changing demand requirements. But, such systems are inherently more complex than traditional systems. To address these challenges, we are researching new network design models to capture on-demand business models (for a quick overview, check out Flexe’s videos ) and will use these models to quantity the benefit in terms of access to scale, reduced commitment granularity, and reduced capacity granularity. We are also conducting basic research on how best to provide a set of decentralized suppliers choice to entice them to provide access to their resources on-demand. By tapping into underutilized supply capacity, supplier choice can increase participation – and thus capacity – and provides agility through more flexible use of suppliers. This can improve e-commerce profitability and enable a new on-demand volunteer base. Our research team has partnered with community nonprofits to test how on-demand grocery delivery systems for mobility-restricted clients can help address the needs of residents living in food deserts.
Sound interesting? If so, I encourage you to apply to join my research lab. I’m looking for talented, curious new Ph.D. students. Check out my website (https://jenpazour.wordpress.com/) to learn more about our research and team. Feel free to contact me (firstname.lastname@example.org) if you have questions or to request a SKYPE appointment to learn more.
Earning a Ph.D. fundamentally changed — for the better both — my professional and personal paths in life. I encourage you to think about a Ph.D. I also entered the Ph.D. program pretty naive. So below I provide what I (now) believe is needed to be successful in a Ph.D. program, and a research career beyond, as well as reasons why I think RPI’s Industrial and Systems department is a good place to be a Ph.D. student.
First, a Ph.D. is a research degree. This is in contrast to bachelor degrees and (today) most masters degrees, which are coursework degrees. Getting good grades in school is not sufficient to succeeding in graduate school.
So what do I believe it takes to succeed in graduate school? Well, first, you have to be ready to fail. Research is about discovering something new or doing something that has never been done before. There are no answers at the back of the book. The discovery process is exciting, but also non-linear. Many of the things we try, do not work. You have to be OK with this.
But, you also need to succeed enough to outweigh all the failing. Bob Dylan, the great Nobel prize-winning poet, summed up life in academia well, “She knows there’s no success like failure. And that failure’s no success at all.” You need to be excited about what you are doing and willing to put in the time and follow through the failures to get to success. Because ultimately to graduate, you need to succeed. Your research needs to make contributions. Failure is not enough. Follow through is critical. You need to be able to make yourself do the mundane (whether that’s writing up results, responding to reviewers comments, writing up research funding reports, or responding to emails). In fact, to be successful as a faculty member, I believe you need to be efficient at the mundane. You need to be able to efficiently juggle many different projects, requests, and emails.
To succeed at a Ph.D. it is (in my opinion) necessary to be able to do both: to (1) excel at new idea generation and to bounce back after failure, and to (2) follow through (and even be efficient) with mundane tasks. While you do not need to an expert at either of these as an incoming Ph.D. student, you need to work at and keep improving on both types of tasks. Therefore, skills I am particularly looking for in Ph.D. Students:
- Kind Human Being
- Writing and Logic Skills
- Communication Skills
- Ability to think about and improve our understanding of complex problems
- Mathematical ability
- Coding background
- Ability to deal with uncertainty.
- Critical Thinking.
Reasons why I would like to be a graduate student at Rensselaer’s Industrial and Systems Engineering department:
- It’s a small co-hort. We have a small, but mighty faculty, and our Ph.D. admission process is deliberately geared towards recruiting a small, but mighty group of Ph.D. students. We limit the number of Ph.D. students admitted to ensure each Ph.D. student fits with the research interests of our department and is provided mentoring and funding.
- We are in this together. Research in my lab is a collaborative process. This means my graduate and undergraduate students and I are putting our heads collectively together to generate new knowledge and create new models and methods. We work on the research together. I meet with Ph.D. students at least once a week and spend many additional hours reading, editing, and writing journal papers with my students.
- It’s a disruptive time to be in supply chain design. As the introduction to this post illustrates, its a disruptive time to be in supply chain design. My hypothesis is that supply chains of today are optimized for yesterday’s customers. This means the world needs more creative ideas and needs to utilize the massive amounts of data being generated today to drive decision making. Thus, the research we are doing is important and has the potential to improve efficiency of commercial and nonprofit organizations. To learn more, check out my RED (Research, Education and Discovery) Talk “the Data Promise” (where I describe research on data in supply chains starting at 7:50), a webinar where I describe on-demand warehousing and logistics, and this interview about on-demand logistics .
- Low boundaries to collaboration across campus. My students and my research have benefited greatly from the insights of RPI’s helpful faculty members, both in the ISE department and beyond. Ph.D. students are encouraged to take courses across disciplines (e.g., Ph.D. students take data analytics from IDEA, optimization theory from mathematics, machine learning, data mining, and algorithms classes from computer science, transportation and econometric modeling from Civil Engineering, queuing from Electrical Engineering, data analytics from ITWS, sourcing from Lally business school, and decision making from cognitive science departments).
Applicants are encouraged to apply to Rensselaer’s Decision Sciences and Engineering Systems Ph.D. program, housed in the Industrial and Systems Engineering Department. Please indicate in your statement of purpose, your interest to work with me. If you currently reside in the US, we sponsor trips to have top accepted PhD students visit the campus, meet with faculty, and see the area. Students in my research lab are funded, either via research assistantships, teaching assistantships, or fellowships. Additional funding and scholarships are available for talented domestic applications.
If interested, please apply by January 2nd, 2018. Note, applications are reviewed beyond the deadline, so apply even if you miss the January 2nd deadline. Admission decisions are made by a committee and the final decision resides with the graduate school (outside of our department).
Please reach out to me via email (email@example.com) if you have any questions. Tell your friends, co-workers, former students, current students, etc. Thanks! Jen