Open educational resources (OER) are teaching, learning, and research resources that are in the public domain or are licensed for reuse. OER can be entire courses, textbooks, modules, software and more.
Affordable Learning Solutions @ SJSU encourages faculty to reduce the cost of a college education for their students by adopting and using OER in the classroom. It is coordinated at San Jose State University by the University Library in cooperation with our campus partners: the Center for Faculty Development, the Accessible Education Center, the Office of the Provost, and the Spartan Bookstore.
Are you a faculty member at SJSU who is interested in adding an open educational resource to SJSU ScholarWorks? Please contact us: scholarworks@sjsu.edu.
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The Strategic Impact of Emerging Artificial Intelligence in the Ethical Realm of the Enterprise Landscape
Vishnu S. Pendyala
Presentation made at the IEEE Computer Society Enterprise GenAI Summit, Hotel Signia by Hilton San Jose, 170 South Market Street, San Jose, CA, on August 20, 2025.
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The Sketches of Infinite Data and Algorithms for Real-Time Data Insights
Vishnu S. Pendyala
How are machine learning algorithms able to answer questions from any nook and corner of the World Wide Web? How are trending hashtags from the near infinite microblog posts, unique visitors and other distinct counts in the near infinite website traffic determined? How do blogging websites avoid recommending articles a user has previously read? In general, how can we answer complex queries about enormous data streams without storing them entirely, in real-time? The answer often lies in clever approximation algorithms and data "sketches" that capture essential properties using vastly reduced space. The relentless flow of data in modern systems indeed presents significant challenges. These data streams are often too large to store and too fast to process exhaustively with traditional methods. This talk introduces key sketching and approximation techniques that help generate real-time data insights by processing data streams.
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Crafting Research That Resonates
Vishnu S. Pendyala
A short presentation made to the students of SJSU’s Gateway PhD Program with Manchester Metropolitan University on August 5, 2025, at their annual research workshop. It serves as some general advice and inspiration to aspiring doctoral students.
More about the program here: https://ischool.sjsu.edu/gateway-phd-library-and-information-management
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Unveiling the Transformative Power of Unsupervised machine learning through Clustering
Vishnu S. Pendyala
Clustering methods demonstrated their transformative potential across various industries through image segmentation, anomaly detection, bioinformatics, and customer segmentation. The presentation explores these techniques in unsupervised machine learning, focusing on foundational clustering algorithms such as K-means, Hierarchical Clustering, and DBSCAN. Through an in-depth analysis of their underlying principles and computational intricacies, the presentation highlights how these methods have evolved to address complex, high-dimensional data problems. The presentation provides insights into how K-means remains a versatile tool for partitioning data in linear spaces. It delves into Hierarchical Clustering's unique approach to building dendrograms and capturing multi-scale data relationships, and how DBSCAN's density-based framework reveals clusters amidst noise, making it ideal for discovering patterns in irregular, real-world datasets. The presentation offers a comprehensive understanding of these algorithms and equips aspiring data scientists and industry professionals with the tools to harness the power of clustering for impactful, data-driven decisions.
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Carbohydrate Counting: Traditional Filipino Food Lists for Management and Prevention of Diabetes Mellitus
Ashwini Wagle
The Carbohydrate Counting tool was created to address the specific dietary needs of the Filipino population. It is an original intellectual work by Ashwini Wagle, Ed.D., MS, RD, Chair of the Department of Nutrition, Food Science, and Packaging at San Jose State University (SJSU).
The development of this tool was made possible through the collaboration and support of several contributors. Serena Starr, MS; Justine Martinez Cuaresma, MS, RD; Nazli Goudarzi, MS; Leah Olaivar; and Joe Johnston—a graduate student in the Department—played integral roles in the project. Their contributions included verifying the authenticity of traditional foods, designing culturally appropriate meal plans, and categorizing foods within the appropriate food groups.
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Quantitative analysis of Machine Learning model performance and the need to consider explainability
Vishnu S. Pendyala
This presentation, titled "Quantitative analysis of Machine Learning model performance and the need to consider explainability," delves into various metrics used for evaluating machine learning models. It thoroughly examines fundamental classification metrics like accuracy, precision, recall, and F-score, while also discussing more advanced measures such as the Kappa Statistic and Matthews Correlation Coefficient (MCC), particularly highlighting their relevance in scenarios with imbalanced datasets. The presentation underscores the importance of model accuracy in real-world applications and briefly introduces regression metrics like R-squared and F-statistic. Additionally, it addresses challenges related to data imbalance and fairness in ML models, stressing the critical need for explainability alongside performance.
More details: https://events.vtools.ieee.org/m/442073
Video Recording: https://ieeetv.ieee.org/channels/computer-society/quantitative-analysis-of-machine-learning-model-performance-and-the-need-to-consider-explainability
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Machine Learning Applications and Sustainable Development
Vishnu Pendyala
This presentation, "Machine Learning Applications and Sustainable Development," explores the intersection of machine learning and its impact on privacy, equity, and societal well-being. It delves into the potential for re-identification of "anonymized" data through various techniques like k-anonymity, L-diversity, and the vulnerabilities of large language models, illustrating these concepts with real-world examples such as the AOL search data, Netflix Prize dataset, and Strava's fitness tracking. The presentation also discusses solutions to enhance data privacy, including differential privacy and the emerging field of machine unlearning, highlighting their applications and limitations. Finally, it addresses the broader implications for civil rights and ethical considerations in AI development, referencing recent initiatives and executive orders aimed at ensuring the safe, secure, and trustworthy deployment of artificial intelligence.
Video Recording: https://www.youtube.com/watch?v=GyYWvyLjfvg&list=PLLsxQYv4DdJkI1SshLhWCdVdBZfn8SrXl&index=7
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Slowly changing dimensions and fast changing facts - the story of the traditional data warehouse
Vishnu Pendyala
This presentation, "Slowly Changing Dimensions and Fast Changing Facts - The Story of the Traditional Data Warehouse," explores how to generate actionable insights from organizational performance data. It begins by discussing the challenges of generating insights directly from existing databases and introduces the concept of data cubes for efficient aggregate storage. The core of the presentation focuses on dimensional modeling, particularly the Star Schema, as a solution for analytical processing needs that cannot be met by transactional systems. It details the characteristics of fast-changing fact tables (long, lean, numeric) and slowly changing dimension tables (descriptive, wide, containing strings and numbers). The presentation then delves into various Slowly Changing Dimension (SCD) types (Type 0, 1, 2, 3, 4, 5, and 6), explaining how each handles changes in dimensional data to preserve or overwrite historical information. Key considerations for designing star schemas, such as the number of dimensions and the granularity of facts, are also addressed.
More details: https://events.vtools.ieee.org/m/363162
Video Recording: https://ieeetv.ieee.org/video/slowly-changing-dimensions-and-fast-changing-facts-the-story-of-the-traditional-data-warehouse
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Exploring the math in Support Vector Machines
Vishnu Pendyala
“SVMs are a rare example of a methodology where geometric intuition, elegant mathematics, theoretical guarantees, and practical algorithms meet” – Bennet and Campbell
Support Vector Machines (SVMs) are used for supervised machine learning and have been successful in many applications, including those like image classification that favor deep learning. SVM owes its power to the intriguing math involved in its fabrication. This talk will introduce SVM and cover some of that math. Topics covered will include constrained and unconstrained optimization, convexity, the general notion of a function space, minmax equilibrium, duality, the Cover theorem, Kernels, and the Mercer theorem.
More Details: https://events.vtools.ieee.org/m/324950
Video Recording: https://ieeetv.ieee.org/video/exploring-the-math-in-support-vector-machines
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Machine Learning, the mortar of modernization
Vishnu Pendyala
Machine Learning is advancing civilization and is one of the key drivers of the economy today. Machine Learning literacy may one day become essential, the way computer literacy is today. This talk intends to explain Machine Learning concepts to wider audiences by using easy-to-relate real-world analogies and serves as a refresher to those already initiated. A fundamental concept in machine learning is similarity. The dot product that is ubiquitously present in machine learning is a measure of similarity. Similarity is key to human learning as well. We learn in delta increments by comparing and contrasting with what we already know. Analogies or similarities help.
Machine learning is an exciting field for many, but the rigor, math, and its rapid evolution are often found to be formidable, keeping them away from studying and pursuing a career in this area. This talk will use similarity to explain the underpinnings of machine learning to those who want to get insights into machine learning and data science. A number of concepts, techniques, and algorithms in machine learning are explained, relating them to real-world analogies in a way that audiences with little or no background in the area will also be able to appreciate. More details: https://events.vtools.ieee.org/m/315186 Video Recording: https://ieeetv.ieee.org/video/meta-algorithms-in-machine-learning
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Meta-algorithms in Machine Learning
Vishnu Pendyala
This presentation explores how to make the best of models impacted by bias and variance. Meta-learning minimizes loss. Ensemble methods, including Bagging, Adaboost, Random Forest, Gradient Boosting, and Stacking, are discussed. These methods perturb data (X or Y) using techniques like bootstrap sampling, k-fold sampling, weighted sampling, and random subspaces. Models are generated in parallel or sequentially, with aggregation strategies such as mean, mode, weighted response, and metamodel. The presentation also touches upon deep learning and one-shot learning, and explains how distances become less meaningful in high dimensions.
More details: https://events.vtools.ieee.org/m/315184
Video Recording: https://ieeetv.ieee.org/video/meta-algorithms-in-machine-learning
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Science, Physiology, and Nutrition For the Nonscientist
Judi S. Morrill
A wonderful blend of physiology, nutrition, biochemistry, genetics, biology, evolution, chemistry--what we all need to know as informed citizens. A basic knowledge of the life sciences and how our bodies work--to promote our own good health, especially as we're bombarded with misleading advertisements, soundbites, and the like. DNA fingerprinting, calorie requirements, dietary advice, genetic engineering (including gene editing with CRISPR cas9)--all in an easy-to understand book.
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Realities of Nutrition
Judi S. Morrill
What Is Nutrition Reality? Is it in the advertising claims that a food is natural or supplies instant energy? Is it in the myriad of dietary supplements? Is it in the diet plans for instant weight loss and glowing health? The only way to find out is to learn the basic principles of nutrition science, so you can be your own nutrition expert. Here is the true introduction to nutrition that you will read with pleasure and real understanding. It will free you from dependence on popular sources of information - often misinformation - so you can distinguish illusion from the realities of nutrition.
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Courts and Society in the United States
Margaret Stevenson
Courts and Society in the United States was created to support JS 103: Courts and Society. This course reviews the structure and function of the United States court system with an emphasis on the roles of attorneys and judges and the court process itself. It also examines the societal and legal effect of federal and state legislative, executive, and judicial branch actions, including Supreme Court decisions in civil and criminal cases.
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Melodia : A Comprehensive Course in Sight-Singing (Solfeggio)
Samuel W. Cole and Leo R. Lewis
Melodia is a 1904 book designed to teach sight-singing. The educational plan is by Samuel W. Cole; the exercises were written and selected by Leo R. Lewis.
Melodia is presented here as a complete edition and has also been divided into its four separate books.
