Masters of Science in IT Privacy Carnegie Mellon is offerning a new one-year M.S. in IT Privacy for privacy engineers and technical privacy managers. The program covers practical techniques for engineering privacy into systems, as well as, the broader implications in social, legal and economic perspectives of privacy.

I have taught or co-taught the following courses...

Prompt Engineering
17-630 for graduate students
This course covers in-context learning with large language models (LLMs), including strategies and tactics to prompt LLMs while achieving high accuracy and reliability. In addition to chain-of-thought, the course covers topics in multi-stage prompting, including augmentation with vector databases and function calls, self-consistency and self-evaluation, and task decompostion strategies. The course reviews techniques for constructing and fine-tuning LLMs, including a range of alignment-related topics, such as hallucinations, sychophancy, misdirection, bias, ethics and morality and deception. Taught in Spring 2024

Artificial Intelligence for Software Engineering
17-649 for graduate students
This graduate course covers topics in clustering and topic modeling, symbolic reasoning using Description Logic, sentiment analysis using supervised machine learning (naive bayes, logistic regression, decision trees and random forests), and deep learning, including CNN, RNN, LSTM and Encoder-Decoder models. These techniques are applied to software artifacts to solve software engineering problems, such as finding duplicate bug reports, inferring trace links between requirements, predicting app review ratings, and generating code fixes. Taught in Fall, Spring 2019

Foundations of Software Engineering
15-313 for undergraduate students
This undergraduate course covers the software engineering lifecycle, beginning with testing, code maintenance, before transitioning into design, requirements and software ecosystems. Students participate in an active real-world, open-source project of their choosing and multi-group project to develop framework plug-ins. Taught in Fall 2010

Methods: Deciding What to Design
17-652 for SE Masters students
17-752 for PhD students
This graduate course covers requirements engineering methods, including goal-oriented requirements, use cases and contextual design. Students apply the methods to their MSE Studio Projects during the first semester of their MSE program. Taught in Fall 2011, 2012

Engineering Privacy
08-605 for graduate students
This graduate-level course introduces students to modern system requirements, design and testing methods to build and evaluate systems based on established privacy principles, regulations and standards. Students learn to identify and reason about privacy harms and about strategies to balance trade-offs between privacy, security and transparency through contemporary problems in the private and public sector. See the Spring 2014 course syllabus.

Privacy Policy, Law and Technology
Cross-listed 15-508 (CSD),08-533 and 08-733 (ISR), 19-608 (EPP), and 95-818 (MSISPM)
This undergraduate and graduate-level course reviews the role of law and technology on personal privacy from three viewpoints: individual, corporate and government perspectives. Students in the course participate in in-class debates both in support of, and against privacy laws and policy by appealing to technology constraints, economics, personal and social harms, and ethics. See the Spring 2012 course syllabus.