BE Seminar: “Designing Programmable Protein Therapeutics with Generative Language Models” (Pranam Chatterjee, Duke University)

216 Moore Building

CRISPR has revolutionized biotechnology by enabling the simple design of guide RNAs to target and edit almost any DNA sequence. By developing new generative protein design algorithms, my hybrid lab focuses on extending this CRISPR-like programmability to proteins and other key molecules. In this talk, we will first delve into our algorithms that design binders […]

Biomedical Data Science Seminar Series – “Unlocking Brain Insights: Machine Learning for Neuroimaging Studies”

Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

Modern neurotechnologies generate vast and intricate imaging data across multiple modalities, capturing nuanced aspects of brain structure and function in both healthy and diseased states, thus propelling neuroimaging into the 'big data' era. The quantitative analysis of such extensive neuroimaging datasets presents unprecedented opportunities for uncovering novel insights into various neuroscience problems. Machine learning and […]

ASSET Seminar: “Machine Learning and Brain Imaging: Contributions to Diagnostics, Prognostication, and Treatment Guidance”

Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

Abstract: Neuroimaging has significantly expanded our understanding of brain changes in neuropsychiatric disorders as well as in aging and neurodegenerative diseases. However, it wasn’t until the advent of machine learning tools that imaging signatures that can be detected in individuals, rather than groups, were constructed. More importantly, imaging signatures derived via machine learning models have […]

ASSET Seminar: “Representation-based Learning and Control for Dynamical Systems”

Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

Abstract:  The explosive growth of machine learning and data-driven methodologies have revolutionized numerous fields. Yet, the translation of these successes to the domain of dynamical physical systems remains a significant challenge. Closing the loop from data to actions in these systems faces many difficulties, stemming from the need for sample efficiency and computational feasibility, along […]

ASSET & Warren Center Research Mixer

Glandt Forum, Singh Center for Nanotechnology 3205 Walnut Street, Philadelphia, PA, United States

The ASSET and Warren Center will be hosting a research mixer to welcome new PhD students and expose new and current students to the wide range of research in Penn Engineering in AI/ML. The program will consist of (short) faculty talks, poster presentations by students/postdocs, and a reception to end the night!

ASSET Seminar: “Robustness in the Era of LLMs: Jailbreaking Attacks and Defenses”

Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

Abstract: Despite efforts to align large language models (LLMs) with human intentions, popular LLMs such as chatGPT, Llama, Claude, and Gemini are susceptible to jailbreaking attacks, wherein an adversary fools a targeted LLM into generating objectionable content. For this reason, interest has grown in improving the robustness of LLMs against such attacks. In this talk, we review the current state of […]

ASSET Seminar: “Towards Pluralistic Alignment: Foundations for Learning from Diverse Human Preferences”

Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

Abstract: Large pre-trained models trained on internet-scale data are often not ready for safe deployment out-of-the-box. They are heavily fine-tuned and aligned using large quantities of human preference data, usually elicited using pairwise comparisons. While aligning an AI/ML model to human preferences or values, it is important to ask whose preference and values we are […]

ASSET Seminar: “Wood Wide Models”

Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

Abstract:  Foundation models are monolithic models that are trained on a broad set of data, and which are then in principle fine-tuned to various specific tasks. But they are ill-suited to many heterogeneous settings, for instance numeric tabular data, or numeric time-series data, where training a single monolithic model over a large collection of such […]

ASSET Seminar: “Some Displaced Vignettes on Generalized Notions of Equivariance”

Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

Abstract: The explicit incorporation of task-specific inductive biases through symmetry has emerged as a crucial design precept in the development of high-performance machine learning models. Symmetry-aware neural networks, such as group equivariant networks, have achieved notable success in areas like protein and drug design, where capturing task-specific symmetries improves generalization. Recent efforts have focused on […]

IDEAS Seminar: “Equivariant Neural Inertial Odometry”

Room 401B, 3401 Walnut 3401 Walnut Street, Philadelphia, PA, United States

Abstract:  In this talk, we introduce a new class of problems related to integrating inertial measurements obtained from an IMU that play a significant role in navigation combined with visual data. While there have been tremendous technological advances in the precision of instrumentation, integrating acceleration and angular velocity still suffers from drift in the displacement […]