About

Sara Owsley Sood is a Professor of Instruction and the Chookaszian Family Teaching Professor at Northwestern University, affiliated with the Department of Computer Science. She serves as the Associate Chair for Undergraduate Education within the McCormick School of Engineering. Her work focuses on understanding the expression and impact of emotion in online communication. Specifically, her recent research involves developing systems to detect and analyze insults, profanity, and personal attacks in online forums, with a particular emphasis on the effects of anonymity on online communities. Her exploration of sentiment analysis extends to addressing challenges related to domain specificity and analyzing a range of emotions beyond simple positive, negative, or neutral classifications. Sood has been recognized for her excellence in teaching, receiving the 2019 Cole-Higgins Award for Excellence in Teaching, the 2019 University Teaching Award, and the 2010 Pomona College Wig Distinguished Professor Award for Excellence in Teaching.

Research topics

• Computer Science
• Artificial Intelligence
• Machine Learning
• Engineering
• Engineering management
• Mathematics education
• Mechanical engineering
• Composite material
• Manufacturing engineering
• Knowledge management
• Construction engineering
• Aerospace engineering
• Medical education
• Mathematics
• Database
• Materials science
• Nanotechnology

Selected publications

• Exploring high strain rate deformation of materials

  AIP conference proceedings · 2025-01-01

  article
  PublisherDOI

• Advanced machining of biomedical materials for orthopedic implant applications

  AIP conference proceedings · 2025-01-01

  article
  PublisherDOI

• Frugality is the new sexy

  Consumer Psychology Review · 2024-12-25 · 4 citations

  article

  Abstract The overarching goal of this article is to spur fresh interest in the topic of frugality and new empirical research on it. To do so, this article presents a series of research propositions that are based on the discussions provided in each section. In particular, the second section of this article reviews philosophical and religious accounts of the concept of frugality. The third and fourth sections focus on consumer psychological research on dispositional frugality. The sixth section reflects on two popular consumer lifestyles, miserliness and simple living, that require certain frugal behaviors but are inspired by non‐frugal values. The seventh section links both frugal and non‐frugal values to two sociological variables: generational cohort and social class. Last, the eighth and ninth sections review new obstacles that consumers face in today's marketplace and how consumers can practice frugality in spite of them.

  PublisherDOI

• Exploring factors affecting student placements: acomprehensive analysis of demographics, academic performance, and preparation activities

  2024-04-23

  book-chapter

  When it comes to educational institutes, the performance of their students is largely represented in terms of their placements. Placements are very important for an educational institute for its brand building and for students it is quite necessary to launch their careers. These reasons have been a major reason to take up this analysis. This work is an attempt to identify the variables and their impact towards the employability of higher education students. The factors explored included demographic details, the prior academic performance, participation in placement preparation activities and performance in benchmarking tests. The methodology used was to frame research questions corresponding to factors of interest, collect data on students on these factors and analyze the relative performance of students in terms of placement percentage to derive insights. The outcomes of this analysis indicated that prior academic performance and participation in placement preparation classeshave a significant impact on the final placement status of a student. Also, it was found that the genderor demography of students does not impact the placement status. The performance in benchmarking test was also found to have non-significant association with placement. This research is helpful for all the stakeholders in this domain including students, faculty, placement wing, management of the institute and recruiters as they get some key points out of this analysis.

  PublisherDOI

• Advance biomedical engineering – A fundamental review of composite materials and its applications

  Materials Today Proceedings · 2023 · 9 citations

  • Computer Science
  • Mechanical engineering
  • Materials science
  PublisherDOI

• Transported through Time: The Narrative Processing of Experiential Purchases

  Journal of the Association for Consumer Research · 2023-09-19 · 5 citations

  articleSenior author

  Consumer research has demonstrated that narrative and analytical processing are different styles of information processing. However, an enduring question is when do consumers engage in narrative processing? We propose that consumers are more likely to engage in narrative processing when they face an experiential purchase decision rather than a material purchase decision. Narrative transportation, a consequence of narrative processing, thus becomes a critical element for persuasion in the context of experiences, more than in the context of material products. Additionally, factors that inhibit narrative thought, such as marketing communications that include an inconsistency or reduce character identification, lower narrative transportation and harm the evaluations of experiential purchase decisions but not material purchase decisions. Two preliminary studies plus three experiments offer support for our theorizing.

  PublisherDOI

• Development of a sleep monitoring system using cloud computing and big data techniques

  2023-05-12 · 1 citations

  article

  Among the most significant sleep concerns is obstructive apnea syndrome in sleep (OASS) which harms the quality of life. A few effects of OASS include cognitive decline, impaired psychiatric function, behavior problems, and personality ailments. Real-time monitoring of this condition is thus essential for clinical services. There seem to be numerous OASS-detecting techniques. Hence, the present experiment provides a new system both for detecting and assisting therapies of OASS in elderly individuals. This design was developed for tracking a variety of variables including the surroundings where a person goes to sleep, their sleeping quality, physical activity levels, and physiological variables by utilizing open data from smarter city systems. 2 sorts of processing are performed by the suggested method. In the instance of a crisis, real-time notices can be sent to those in charge of caring for the old aged owing to the rule-relied pre-processing technique. This method fundamentally relies on a fog computing strategy applied in a smarter device functioning at networking edges which also provides enhanced interoperable ability services, including technological, semantic, and syntactic capabilities. Big data devices on cloud computing are utilized in this process. The effectiveness of the system has also been assessed given latencies. The outcomes obtained indisputably show that pre-processing of data at networking edges increases system effectiveness.

  PublisherDOI

• Anticipating Placement Status of Engineering Students using Machine Learning based Prediction Models - A Case Study of Computer Science Stream

  2023 · 8 citations

  Senior authorCorresponding
  • Computer Science
  • Machine Learning
  • Artificial Intelligence

  Quality of placements is an important parameter considered by accreditation bodies while ranking Universities or Institutes of Higher Education. Thanks to the increasing automation of placement grooming related activities, universities have started exploring using intelligent computing techniques to anticipate placement status of upcoming batches and identifying factors that play an important role in improving placement quality. In this work, machine learning techniques have been used to predict placement students of engineering students of computer science discipline. Logistic Regression and Decision Tree algorithms gave best prediction performance. Marks in ‘Xth’, ‘XIIth’, ‘Current CGPA’ and ‘Present Attendance’ were among the important factors affecting placement status of students.

  PublisherDOI

• Cold spray coating: A review of material systems and future perspectives

  Materials Today Proceedings · 2023-11-01 · 7 citations

  review
  PublisherDOI

• Empirical Analysis on Parameters for Adoption of Cloud-Based e-learning in Indian Higher Education System: A User’s Perspective

  Lecture notes in networks and systems · 2021 · 8 citations

  Senior authorCorresponding
  • Computer Science
  • Computer Science
  • Knowledge management
  PublisherDOI

Frequent coauthors

• Liat Hadar

  Tel Aviv University

  12 shared

• Yuval Rottenstreich

  9 shared

• Claudia Townsend

  8 shared

• Kristian J. Hammond

  8 shared

• Craig R. Fox

  Anderson University - South Carolina

  7 shared

• Lyle Brenner

  6 shared

• Kevin Lane Keller

  5 shared

• Aimée Drolet

  Anderson University - South Carolina

  4 shared

Education

• PhD, Graduate School of Business

  Stanford University

Awards & honors

• 2019 Cole-Higgins Awards for Excellence in Teaching
• 2019 University Teaching Awards - Charles Deering McCormick…
• 2010 Pomona College Wig Distinguished Professor Award for Ex…