Lectures

The course schedule will be updated frequently, please keep visiting this webpage for updates.

Schedule and Reading List - Tentative

Date Slides Contents Presenter Homework Materials
22-Aug Slides Course Intro and Logistics Ravi Iyer Presentation signup (via Campuswire)
Reliability, Fairness and Ethics
24-Aug Slides Generative Pretrained Transformers (Large Language Models) Dependability Issues
 Ravi Iyer Readings:
Improving Language Understanding by Generative Pre-Training
Challenges and Applications of Large Language Models
GPT-4 Technical Report
Sparks of Artificial General Intelligence: Early experiments with GPT-4
29-Aug Slides Validation (Reliability Assessment) of Generative Language Models Ravi Iyer Background Readings: DECODINGTRUST: A Comprehensive Assessment of Trustworthiness in GPT Models
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation
31-Aug Slides Trustworthy AI and Fairness Ravi Iyer, Student Presenters + Respondents Papers: Improving the Fairness of Chest X-ray Classifiers
Background Readings:
Fair ML Classification
On the Applicability of ML Fairness Notions
05-Sep Slides Assessing bias as a measure of trustworthiness Ravi Iyer Papers: Towards Understanding and Mitigating Social Biases in Language Models
Readings:
Improving fairness in machine learning systems: What do industry practitioners need?
The Landscape and Gaps in Open Source Fairness Toolkits Finspector: A Human-Centered Visual Inspection Tool for Exploring and Comparing Biases among Foundation Models
07-Sep Slides Reliability/Security: Game-theoretic models Ravi Iyer, Student presenter + respondent Project signup (via Campuswire) Paper: Game-Theoretic Methods for Robustness, Security, and Resilience of CPS Control Systems
Robustness
12-Sep Slides Modelling uncertainty in AI/ML systems Ravi Iyer Paper: Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
Background Readings:
"Uncertainty in deep learning" Introduction: The Importance of Knowing What We Don’t Know
Bayesian Deep Learning
A Deeper Look into Aleatoric and Epistemic Uncertainty
Learning Dynamic Bayesian Networks
14-Sep Impact of distribution-shifts on learning in AI/ML systems Ravi Iyer, Student Presenter + Respondent Paper:
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?
Optional Readings:
Long tail challenge (Waymo)
On Pitfalls in OoD Detection: Predictive Entropy Considered Harmful
GEN: Pushing the Limits of Softmax-Based Out-of-Distribution Detection
Addressing AI tail cases
19-Sep Recording Guest Lecture: Causal and Counterfactual Analysis for improving Robustness of DAG-based AI applications
 Dr. Saurabh Jha (IBM Research) Lecture Critique
21-Sep Slides Generative Adversarial Networks, Adversarial Robustness Ravi Iyer (Intro), Student Presenter + Respondent Paper:
Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior
Optional Readings:
Generative adversarial nets (NIPS 2014)
PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving
DeepRoad: GAN-based Metamorphic Autonomous Driving System Testing
Generative Adversarial Networks for Black-Box API Attacks with Limited Training Data
Generative Adversarial Network for Wireless Signal Spoofing
Testing DNN-based Autonomous Driving Systems under Critical Environmental Conditions
26-Sep Slides Group Activity Ravi Iyer + Student presenter
28-Sep Group Activity - Solution Presentation Student Presenter
Verification and Certification
03-Oct Slides Fault-Injection Ravi Iyer (Intro), Student Presenter + Respondent Paper
ML-based Fault Injection for Autonomous Vehicles
05-Oct Project proposal presentation Student presenter
10-Oct Slides Formal Verification Methods Ravi Iyer Paper: Formal Scenario-Based Testing of Autonomous Vehicles: From Simulation to the Real World
12-Oct Fuzz Testing Ravi Iyer Paper Reading:
AV-FUZZER: Finding Safety Violations in Autonomous Driving Systems
Background Readings:
Conformance Testing as Falsification for Cyber-Physical Systems
Security/Privacy
17-Oct AI-driven Malware Attacks Ravi Iyer(Intro), Student Presenter + Respondent Paper
Ml-driven malware that targets av safety
19-Oct Trojan Attacks and Stealing Models Student Presenter + Respondent Paper
PolicyCleanse: Backdoor Detection and Mitigation in Reinforcement Learning
24-Oct Energy-based Models Ravi Iyer + Students Paper
A Tutorial on Energy-Based Learning (Slides)
A Tutorial on Energy-Based Learning (Report)
Explanability/ Interpretability
26-Oct Counterfactual Reasoning: Introduction
Problem Definition and Application in Fault Sensitivity Assessment
Student Assessment of Assigned Papers 		Ravi Iyer (Intro), Student Presenter + Respondent Paper
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis
Optional Readings:
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples
Improving the accuracy of medical diagnosis with causal machine learning
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques
31-Oct Guest Lecture: Adversarial Robustness and Certification Guest Lecture Critique Background Reading
02-Nov Interpretability Student Presenter + Respondent Paper:
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Applications:
Concept-based model explanations for Electronic Health Records
Human-Centered Tools for Coping with Imperfect Algorithms During Medical Decision-Making
Optional Reading:
On the Interpretability of Artificial Intelligence in Radiology: Challenges and Opportunities
07-Nov Model Debugging Student Presenter + Respondent Paper
Debugging Tests for Model Explanations
Optional Readings
On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection
09-Nov Midterm Project Presentation Student presenter Project Reports Details here
New Problems
14-Nov Causal Systems Ravi Iyer, Student Presenter + Respondent Paper:
Sage: Practical & Scalable ML-Driven Performance Debugging in Microservices
16-Nov Topic Review Ravi Iyer, Student Presenter + Respondent
21-Nov FALL BREAK
23-Nov FALL BREAK
28-Nov Mechanistic Models Ravi Iyer Paper:
REMEDI: REinforcement learning-driven adaptive MEtabolism modeling of primary sclerosing cholangitis DIsease progression
Optional Reading
Reinforcement Learning based Disease Progression Model for Alzheimer's Disease
30-Nov Group Activity: Mechanistic Models + Bayesian Machine Learning
05-Dec Evolving Themes: Impact of Generative Models in Healthcare Systems, Resilience and Trust Ravi Iyer + Student presenter
07-Dec Final Project Presentation Student Presenters