MEAM Seminar: "Programmable Strain-responsive Biopolymer Networks Adapt to High Magnitudes of Mechanical Loading"
2024-08-21 10:15 - 11:15 (America/New_York) | Towne 337
Biopolymer hydrogel materials typically exhibit relatively low range of programmable modulus less than 100 kPa, which limits their biomedical applications, such as in articular cartilage and synthetic joints, where tissues are cyclically loaded with high magnitudes of peak stress on the order of 10MPa, and applications in soft robotics require moduli across orders of magnitude from 1 kPa to 100 MPa. Here, we achieved a wide range of mechanical properties with double network biopolymer hydrogels that can sustain over 10-100 MPa peak stress under repeated axial unconfined compression. Previous systems use double-network to enhance hydrogel’s toughness and strength. Here, cryogelation generates a foam network that undergoes a rarefied to densified phase transition, which is reinforced with a second dissipative network to yield highly tunable properties across orders of magnitude of applied stress. The foam network is formed by cryogelation of a covalently crosslinked collagen-glutaraldehyde (GA) biopolymer network that can sustain repeated loading through phase transition of its porous foam structure. Interpenetrating ionically-crosslinked alginate biopolymers tune the final modulus to make the hydrogel programmable in a high range of mechanical performance. This dual-network composite hydrogel system also exhibits reversible properties, achieved by chelating ions to reduce ionic crosslinks or restoring crosslinks by supplying additional ions. Together, these data demonstrate a robust hydrogel composite system adaptable to wide ranges of mechanical loading.

BE Doctoral Dissertation Defense: "Engineering Magnetic Devices and Nanoparticle Platforms to Improve Drug Accumulation and Penetration in Tumors for Enhanced Cancer Treatment" (Bian Jang)
2024-08-21 13:00 - 15:00 | Towne 337
The Department of Bioengineering at the University of Pennsylvania and Dr. Andrew Tsourkas proudly announce the Doctoral Dissertation Defense of Bian Jang.

Title: Engineering Magnetic Devices and Nanoparticle Platforms to Improve Drug Accumulation and Penetration in Tumors for Enhanced Cancer Treatment
Advisor: Andrew Tsourkas
Date: Wednesday, August 21, 2024
Time: 1:00PM EST
Location: 337 Towne Building

Zoom: https://upenn.zoom.us/j/8156254789?pwd=[REDACTED]

The public is welcome to attend.

MEAM Ph.D. Thesis Defense: "Enhancing Photophoretic Levitation using Three-dimensional Structures for Flight in the Mesosphere and on Mars"
2024-08-22 09:00 - 10:00 | Towne 319, 220 S. 33rd Street, Philadelphia, 19104, United States
Current propulsion and flight mechanisms limit atmospheric observations. The mesosphere is too dense for satellites and too thin for typical planes and balloons, with similar conditions found in the Martian atmosphere, especially at Olympus Mons. Photophoresis, the movement of gas molecules due to light, has been studied for microscale objects like aerosols and operates optimally within the pressure ranges of these regions. When applied to ultrathin, ultralight macroscale objects, levitation occurs. These objects, such as plates and disks with microstructures, absorb visible light and heat up. The resulting temperature changes pump gas molecules through microchannels and cause a recoil force from molecules striking the hotter surface. These combined effects produce enough force to levitate centimeter-scale objects with no moving parts and only light. We designed photophoretic aircraft with 3D hollow geometries to pump ambient air through sidewalls, creating a high-speed jet. Simulations and parametric studies optimized these geometries, showing potential for kilogram-scale payloads for meter-scale aircraft 50 to 80 km above Earth’s surface. This included a novel theoretical framework based on previous 2D plates but expanded to 3D structures. We also fabricated millimeter-scale versions using microfabrication methods to experimentally investigate levitation in vacuum chamber experiments. Furthermore, we developed a scalable manufacturing method for a different photophoretic aircraft with enhanced temperature gradient-induced levitation of 3D geometries made of a Mylar sandwich composite alongside a new experimental method to measure and compare photophoretic forces of solid versus porous objects. Finally, we explored solar buoyancy, through theory and experimental developments, to transport the structures to the mesosphere and discussed their potential applications for carrying sensors to measure GPS and state properties in situ. Applications of this work include atmospheric science missions in the mesosphere and on Mars in collaboration with NASA.

BE Doctoral Dissertation Defense: "Right ventricular remodeling in tetralogy of Fallot" (Beth Thompson)
2024-08-22 10:00 - 12:00 | Class of 62 Auditorium, John Morgan Building, 3620 Hamilton Walk, Philadelphia, PA, 19104
The Department of Bioengineering at the University of Pennsylvania and Dr. Walter Witschey proudly announce the Doctoral Dissertation Defense of Beth Thompson.

Title: Right ventricular remodeling in tetralogy of Fallot
Advisor: Walter Witschey
Date: Thursday, August 22, 2024
Time: 10:00AM EST
Location: Class of ’62 Auditorium, John Morgan Building

Zoom:

https://upenn.zoom.us/j/99590672633?pwd=[REDACTED]
Meeting ID: 995 9067 2633
Passcode: [REDACTED]

The public is welcome to attend.

CBE Doctoral Dissertation Defense: "High-Pressure Reactions on Metals and Metal Oxides in Mesoporous Silica” (Ching-Yu Wang)
2024-08-28 09:00 - 11:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:
SBA-15, a type of mesoporous silica, is an attractive support for heterogeneous catalysts due to its high surface area, one-dimensional uniform pore structure, and high thermal stability. However, modifying SBA-15 with metal and metal oxide using conventional wetness incipient impregnation is challenging. In this thesis, Atomic Layer Deposition (ALD) was used to prepare catalysts on SBA-15. Through multiple cycles of ALD, various metal oxides can be uniformly deposited in the pores of SBA-15 as thin films, while maintaining the high surface area and well-defined mesoporous structure. Using vapor-phase infiltration, i.e., one ALD cycle, a wide range of metals can be efficiently incorporated into the SBA-15 pores, exhibiting high metal loadings and metal nanoparticle sizes of 3 to 4 nm.
The catalytic properties of the SBA-15-supported catalysts were investigated for dehydrogenation of cycloalkanes and hydrodeoxygenation of m-cresol. While Pt/SBA-15 deactivated rapidly at low pressures due to coking, it remained stable for long periods when the pressure was above certain critical values. These critical values depended on the pore size and structure of the support and the reaction temperature. It was demonstrated that hydrodeoxygenation of m-cresol, a model compound for phenolics, can be carried out over WOx-Pt/SBA-15 in a stable manner using alkanes as H2 carriers. Additionally, cycloalkane dehydrogenation over Pt/SBA-15 was found to be stable at high pressure, thereby providing high endothermicity.
Finally, the growth of metal oxides and their interactions with SBA-15 were studied. It was found that the surface silanol groups of SBA-15 were critical for stabilizing WO3 in the mesopores. CeO2 films supported by SBA-15 were more reducible than their bulk counterparts or ceria supported by Al2O3 due to a reaction between ceria and silica.

CBE Seminar: "Self-assembly Models for Crystal Growth and Phase Transitions" (Julia Dshemuchadse, Cornell University)
2024-08-28 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
How can we make new materials and better understand how their underlying structures form? The direct observation of crystal growth and transitions remains supremely challenging, but gaining insight into these fundamental processes is central to our quest of creating materials in a rational and targeted way, connecting structure to functionality. We build self-assembly models, study how they react to perturbations on the particle and system levels, and investigate their impact on crystal growth and transformation pathways. We use simple coarse-grained models to gain systematic insights into the phenomena that lead to the crystallization of complex crystal structures, partial disorder, or magic-size assemblies, allowing us to derive the essential principles that govern the formation of materials’ structures. Our goal is to use these insights to find ways to tailor crystallization pathways and to create new functional materials. Our work promises to establish new pathways to materials design through simulations, which explicitly incorporate and explore phase transformation kinetics.

MEAM Seminar: "CRISPR-Programmed Microfluidic Devices for DNA Detection, Computing and Digital Display"
2024-09-03 10:15 - 11:15 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
CRISPR is a gene editing technique that allows researchers to quickly and precisely edit genome sequences. Beyond gene editing, CRISPR-Cas systems can be repurposed as a programmable platform for other various applications. In this talk, I will introduce how we use CRISPR technology to program microfluidic devices for DNA detection, DNA computing and digital display. First, I will present our advancements in investigating simple, sensitive and specific CRISPR assay technologies for DNA detection. Second, I will discuss how to integrate CRISPR assay with microfluidics technology to develop affordable and programmable microfluidic diagnostic systems for infectious disease detection and cancer diagnostics. Third, I will describe how we program CRISPR and DNA to develop paper-based microfluidic devices for DNA computing and digital display. Overall, by combining the programmability of CRISPR with the integration capability of microfluidics, we can develop next-generation tools not only for biomedical diagnostics, but also for information technology.

ASSET Seminar: "Bridging the Gap Between Learning and Programming"
2024-09-04 12:00 - 13:15 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Abstract:
For decades, we have built software by writing code, but in recent years machine learning has emerged as a new approach to create software with features that would be impossible to code by hand. However, the use of learning to build software risks ignoring some of the lessons we have learned for how to build computer systems that are robust and maintainable. In this talk, I will describe a new class of techniques we have developed under the term “neurosymbolic programming” which aim to support learning while maintaining some of the benefits of traditional programming, such as modularity, interpretability, reusability and incremental development, and will show some of the benefits these techniques can offer in domains ranging from robotics to computational biology.
Zoom Link (if unable to attend in-person): https://upenn.zoom.us/j/93017587225

CBE Seminar: "Pressure-induced Nanoparticle Assembly" (Hongyou Fan, Sandia National Laboratories)
2024-09-04 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
Precise control of structural parameters through nanoscale engineering to improve optical and electronic properties of functional nanomaterials continuously remains an outstanding challenge. Previous work on nanoparticle synthesis and assembly has been conducted largely through solution chemistry at ambient pressure and relies on specific chemical or physical interactions such as van der Waals interactions, dipole-dipole interactions, chemical reactions, ligand-receptor interactions, etc. In this presentation, I will introduce a new pressure-induced assembly and fabrication method that uses mechanical compressive force applied to nanoparticles to induce structural phase transition and to consolidate new nanomaterials with precisely controlled structures and tunable properties. By manipulating nanoparticle coupling through external pressure, instead of through solution chemistry, a reversible change in their assemblies and properties can be achieved and demonstrated. In addition, over a certain threshold, the external pressure will force these nanoparticles into contact, thereby allowing the formation and consolidation of one- to three-dimensional nanostructures. Through pressure induced nanoparticle assembly, materials engineering and synthesis become remarkably flexible without relying on traditional crystallization process where atoms/ions are locked in a specific crystal structure. Therefore, morphology or architecture can be readily tuned to produce desirable properties for practical applications. (SAND2024-00611O) Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

MEAM Ph.D. Thesis Defense: "Controlling Contact Transitions for Dynamic Robots"
2024-09-05 10:15 - 11:15 | Towne 311, 220 S. 33rd Street, Philadelphia, 19104, United States
Legged robots, robotic manipulators, and their combined embodiment as humanoid robots have received considerable attention across both academia and industry. However, with few notable exceptions, state-of-the-art demonstrations are significantly less dynamic than their biological counterparts. A considerable challenge towards achieving more dynamic robots lies within controlling contact interactions with their environment. Legged robots undergoing impacts experience near-instantaneous changes in their velocities, making accurate state estimation difficult and resulting in controller sensitivity to even small deviations in impact timing. Contact transitions are also challenging for robot manipulation due to the combinatorial complexity of planning across multiple contact modes. Frictional contact that often arises from dynamic manipulation further increases this planning complexity due to the introduction of additional contact modes and increased degree of underactuation.
To address these limitations, this thesis proposes algorithmic and systems contributions to gracefully handle contact transitions for dynamic robots. First, we identify that uncertainties from impact events enter the system dynamics in a structured manner. We leverage this structure to propose a general modification to model-based feedback controllers, enabling selective robustness to impact uncertainty while maximally retaining control authority. We validate our approach on custom dynamic jumping and running controllers on the 3D bipedal robot, Cassie.
Then, we examine dexterous dynamic manipulation through complex non-prehensile tasks that require considering the full spectrum of hybrid contact modes. We leverage recent advancements in contact-implicit MPC to generate contact-rich motion plans in real-time. We demonstrate, through careful integration of the MPC and low-level tracking controller, how contact-implicit MPC can be adapted to dynamic tasks. We perform two distinct tasks using the same model, notably without common aids such as reference trajectories or motion primitives, highlighting the generality of our approach.

MSE Seminar: "Working Safely in the Lab: Navigating Common Laboratory Hazards in MSE Research"
2024-09-05 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
EHRS staff will discuss how to work safely in the lab while navigating the changing landscape of materials science and engineering research.
The talk will also cover;
– Standard orientation topics (physical/bio/chem safety, waste disposal, Workday training, etc.)
– The new methylene chloride regulations and how they will affect EHRS and Penn operations.
– Safe use of tube furnaces, especially in combination with flammable gases.
– Hazards associated with old chemical inventory.
– EHRS’s new incident reporting form.
– Sustainability initiatives at Penn

BE Doctoral Dissertation Defense: "Developing Translational Multimodal Neurotechnology Across Multiple Scales Using Novel Materials And Approaches" (Sneha Shankar)
2024-09-05 12:00 - 14:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
The Department of BIoengineering and Dr. Flavia Vitale proudly announce the Doctoral Dissertation Defense of Sneha Shankar. Details are as follows:

Title: “Developing Translational Multimodal Neurotechnology Across Multiple Scales Using Novel Materials And Approaches”
Date: September 5th, 2024
Time: 12pm
Location: Glandt Forum, Singh Center for Nanotechnology
Advisor: Flavia Vitale
Zoom option: https://upenn.zoom.us/j/97587304173?pwd=[REDACTED]

The public is welcome to attend.

BE Seminar: "Designing Programmable Protein Therapeutics with Generative Language Models" (Pranam Chatterjee, Duke University)
2024-09-05 15:30 - 16:30 | 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 to undruggable proteins, such as those driving pediatric cancers (alveolar rhabdomyosarcoma and Ewing’s sarcoma) and neurodegenerative diseases (Huntington’s and Alexander Disease). Our generative language models, including SaLT&PepPr, PepPrCLIP, and PepMLM, design short binding peptides from target sequence alone, with no dependence on stable 3D structures, and by fusing these “guide” peptides to E3 ubiquitin ligases, deubiquitinases, and other modifying enzymes, we have created a CRISPR-analogous system to edit these proteins. To be even more specific, we train isoform-specific targeting models such as PTM-Mamba for PTM-specific binding, FusOn-pLM for fusion oncoprotein-specific degradation, and moPPIt for motif-specific targeting of protein-protein interactions. Inspired by the power of language models, we further show how we can extend this programmability to DNA with our PAM-free CRISPR enzymes and our recent DPAC model, which allows us to design proteins that can bind and modulate any DNA sequence. Moreover, we are creating binders for heavy metals through our MetaLATTE algorithm, aiming to sequester and detoxify metals from contaminated environments, and addressing chemical pollutants, such as PFAS, by leveraging our generative models to develop proteins that can bind and degrade these persistent environmental toxins. Finally, we will explore our long-term goal of generating new cell states with model-designed proteins, highlighting our recent work on transcription factor-directed stem cell differentiation to ovarian cell types, such as granulosa cells and oogonia. By combining generative design with experimental engineering, our hybrid lab aims to translate these advances into practical applications for treating intractable diseases and addressing environmental challenges.

MEAM Seminar: "Elasticity of Fluids in Nanopores: Molecular Modeling and Ultrasonic Experiments"
2024-09-10 10:15 - 11:15 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Fluids confined in nanopores are ubiquitous in nature and technology. In recent years, the interest in confined fluids has grown, driven by research on unconventional hydrocarbon resources — shale gas and shale oil, much of which are confined in nanopores. When fluids are confined in nanopores, many of their properties differ from those of the same fluid in the bulk. These properties include density, freezing point, transport coefficients, thermal expansion coefficient, and, as it was shown recently, elastic properties.
The elastic modulus of a fluid confined in the pores contribute to the overall elasticity of the fluid-saturated porous medium and determine the speed at which elastic waves traverse through the medium. In this talk I will show how elastic modulus of a confined fluid in a nanopore can be calculated based on Monte Carlo and molecular dynamics simulations and illustrate it with calculations for various fluids. Additionally, I will present our recent experimental measurements of elastic properties of water confined in nanoporous glass samples. Our results suggest that some of the models widely used for describing elasticity of fluid-saturated porous solids need to be revised.

Biomedical Data Science Seminar Series - "Unlocking Brain Insights: Machine Learning for Neuroimaging Studies"
2024-09-10 10:30 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, 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 AI have emerged as promising tools for these analyses, capable of producing personalized, quantitative imaging-based indices with diagnostic and prognostic value, potentially revolutionizing healthcare delivery. However, technical challenges persist due to the high dimensionality of imaging data, disease heterogeneity, and the integration of these technologies into clinical workflows. In this talk, I will discuss novel computational approaches that harness advanced machine learning techniques to tackle these challenges. First, I will present progress toward a scalable unsupervised non-negative matrix factorization framework for interpretable and reproducible dimensionality reduction of neuroimaging data. Second, I will delve into a deep learning framework designed to parse disease heterogeneity and generate subject-specific abnormality maps. Finally, I will explore deep learning models aimed at overcoming obstacles in implementing AI-enabled clinical workflows. I will illustrate the broad impact of these approaches through their applications in diverse settings, with a focus on Alzheimer’s disease.

BE Doctoral Dissertation Defense: "Guided organogenesis using mosaic patterns of progenitors" (Catherine Porter)
2024-09-11 10:00 - 12:00 | BRB Auditorium
The Department of Bioengineering at the University of Pennsylvania and Dr. Alex Hughes are pleased to announce the Doctoral Dissertation Defense of Catherine Porter.

Title: Guided organogenesis using mosaic patterns of progenitors

Date: September 11, 2024
Time: 10:00 AM
Location: BRB Auditorium

Zoom info:
Topic: Catherine Porter’s Dissertation Defense
Time: Sep 11, 2024 10:00 AM Eastern Time (US and Canada)
Join Zoom Meeting
https://upenn.zoom.us/j/99041449653?pwd=[REDACTED]
Meeting ID: 990 4144 9653
Passcode: [REDACTED]

The public is welcome to attend.

ASSET Seminar: "Machine Learning and Brain Imaging: Contributions to Diagnostics, Prognostication, and Treatment Guidance"
2024-09-11 12:00 - 13:15 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, 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 shown promise in prognostication, as well as in guiding personalized treatments. This talk will present work on deriving imaging signatures of diagnostic and predictive value. It will then focus on weakly-supervised machine learning methods for analysis of the heterogeneity of brain imaging phenotypes, arriving at a dimensional representation reflecting the heterogeneity of brain aging and of various brain diseases. Finally, international consortia pooling and harmonizing large numbers of brain MRIs from many studies are presented as means for creating sufficiently large datasets for robust machine learning training and heterogeneity analysis, but also pose new challenges, including that or harmonization and domain adaptation across studies.
Zoom Link (if unable to attend in-person): https://upenn.zoom.us/j/92905415705

BE Doctoral Dissertation Defense: "Quantitative Intracranial EEG Methods for Targeted Therapy in Drug-resistant Epilepsy" (Akash Pattnaik)
2024-09-11 13:30 - 15:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Brian Litt proudly announce the Doctoral Dissertation Defense of Akash Pattnaik.

Title: Quantitative Intracranial EEG Methods for Targeted Therapy in Drug-resistant Epilepsy

Date: Wednesday September 11
Time: 1:30pm
Location: Glandt Forum, Singh Center for Nanotechnology
Advisor: Dr. Brian Litt
Zoom option: https://upenn.zoom.us/j/93665199428?pwd=[REDACTED]

The public is welcome to attend.

GRASP Seminar: Shlomi Laufer, Technion – Israel Institute of Technology, "Enhancing Surgical Skill Assessment Through Computer Vision"
2024-09-11 14:00 - 15:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This seminar will be held in-person in Levine 307 as well as virtually via Zoom.
ABSTRACT
Medical education traditionally employs the apprenticeship model, where trainees learn directly under the supervision of experienced practitioners. This model necessitates close follow-up and typically provides extremely subjective and non- standardized feedback. Over the years, efforts to introduce more objective assessment tools have gained momentum, although these tools often remain time-consuming and can still be influenced by subjective evaluations. Recently, the integration of motion sensors with medical simulators has provided a more objective form of feedback. However, they are typically limited to different aspects of motion economy. In this presentation, I will explore how advancements in computer vision can be utilized to create more informative assessments and feedback on surgical skills. I will also briefly discuss automatic assessment of anesthesiologists. Additionally, I will demonstrate how introducing cameras into the operating room provides a new avenue
for analyzing surgical workflows.

MSE Seminar: "Sustainability Efforts at Dow: Vision, Strategy, Case Studies, and Challenges,” Kumar Sanketh, Dow
2024-09-12 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Materials and chemicals impact daily life, as they enable modern healthcare, preservation of food, and delivering performance and efficiency of transportation and infrastructure. The talk will focus on Dow’s vision and path for carbon neutrality. An overview of Dow Chemical’s portfolio and the breadth of chemistries being practiced will be discussed. Dow has a vision of being carbon neutral by 2050 and recycling 3MM MT of plastics by 2030. To meet this ambitious goal, innovation is being focused on four different fronts related to sustainable chemistry and Engineering. They include Reducing Hazards, Atom economy, Energy footprint, & Holistic design. Case studies will be presented on how innovation in these spaces is being developed and commercialized. To address the complex challenges in sustainable materials and circularity there is a need for collaborative efforts across Industry, academia, and government policy. In this regard, some of the challenges which can be considered for collaboration will be presented.

BE Doctoral Dissertation Defense: "Mechanistic Elucidation and Amelioration of RNA Lipid Nanoparticle Side Effects for Therapeutic Applications" (Serena Omo-Lamai)
2024-09-12 14:00 - 16:00 | BRB 1412
The Department of Bioengineering at the University of Pennsylvania and Dr. Jacob Brenner proudly announce the Doctoral Dissertation Defense of Serena Omo-Lamai.

Title: Mechanistic Elucidation and Amelioration of RNA Lipid Nanoparticle Side Effects for Therapeutic Applications
Advisor: Jacob Brenner, MD, PhD

Date: Thursday September 12th
Time: 2:00pm
Location: BRB 1412

Zoom Option Info: Serena Omo-Lamai is inviting you to a scheduled Zoom meeting.
Topic: Serena Omo-Lamai’s Thesis Defense Time: Sep 12, 2024 02:00 PM Eastern Time (US and Canada)
Join Zoom Meeting https://upenn.zoom.us/j/99710440253 Meeting ID: 997 1044 0253

The public is welcome to attend.

CIS Seminar: "Trustworthy Forecasting Algorithms"
2024-09-12 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Algorithms are increasingly tasked with forecasting the probabilities of uncertain events: a creditor repaying a loan, a user clicking an advertisement, or a word appearing next in a stream of text, for example. Such forecasts are trustworthy if their users can be sure they won’t regret treating the predicted probabilities as if they were actual distributions from which outcomes would be sampled. The term “calibration” refers to various measures of forecast accuracy that formalize this property of trustworthiness. Defining calibration, and designing algorithms to achieve it, turns out to be a tightrope walk between strong definitions, which ensure reliable results for users but are computationally and statistically harder to achieve, and weak definitions, which have the opposite benefits and drawbacks. I will report on some recent research aimed at locating a sweet spot between these two extremes: calibration properties that are achievable using no more samples or computation than the easiest statistical learning tasks, while providing guarantees for downstream users that are, in many cases, as powerful as the strongest notions of calibration.
This talk is based on joint work with Michael Kim, Princewill Okoroafor, Renato Paes Leme, Jon Schneider, and Yifeng Teng.

MEAM Seminar: "Natural Structural Materials: Lessons on Toughening Mechanisms, Weight Reduction, and Multifunctionality"
2024-09-17 10:15 - 11:15 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Structural materials that are damage-tolerant, lightweight, multifunctional, and sustainable are highly desirable for many engineering applications. Such combinations of properties are often found in the biological world. Organisms from nature construct various biological structural materials for protection, predation, body support, camouflage, etc. Despite the fact that these materials are made from limited constituent materials with usually poor intrinsic mechanical properties, such as brittle minerals and soft biopolymers, biological materials are often able to achieve remarkable mechanical properties while offering additional functionalities simultaneously, such as low density, coloration, transparency, flexibility, visual sensitivity, etc. In this talk, I will present our recent work in elucidating the structure-property relationships in some natural structural materials by focusing on their strategies for achieving damage tolerance, weight reduction, and multifunctionality. For example, I will present a unique damage-tolerant, dual-scale, single-crystalline, low-density microlattice we recently discovered in an echinoderm skeletal system. Our research combines quantitative multiscale 3D structural analysis, in-situ mechanical analysis, theoretical and computational modeling, and design and manufacturing of bio-inspired materials. I hope this talk will stimulate more discussions in research areas such as materials, mechanics, biomimetics, biology, and manufacturing.

ESE Fall Seminar - "Big AI for Small Devices"
2024-09-17 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
As artificial intelligence (AI) transforms industries, state-of-the-art models have exploded in size and capability. However, deploying these models on resource-constrained edge devices remains a significant challenge. Smartphones, wearables, and IoT sensors face stringent limitations on compute, memory, power, and communication, creating a gap between demanding AI models and edge hardware capabilities that hinders the deployment of intelligence. In this talk, we will re-examine techniques to bridge this gap and embed big AI on small devices. We will begin by discussing how the properties of various hardware platforms impact the design strategies of efficient deep neural network (DNN) models, such as quantization and pruning. Next, we will discuss techniques aimed at reducing the inference and training costs of distributed collaborative edge AI systems. Finally, we will delve into the underlying design philosophies and their evolution toward efficient, scalable, robust, and secure edge computing systems.

CIS Seminar: "Recent Advances in Spatial Generative AI"
2024-09-17 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Generative spatial AI offers unprecedented capabilities for photorealistic scene representation, generation, and novel-view synthesis, among other tasks. In this talk, we discuss recent advances in large-scale 3D scene representations, efficient neural rendering approaches, and generative AI strategies that allow us to generate photorealistic multi-view-consistent digital humans and general 3D scenes.

ASSET Seminar: "Representation-based Learning and Control for Dynamical Systems"
2024-09-18 12:00 - 13:15 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, 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 with many other requirement such as verifiability, robustness, and safety. In this talk, we bridge this gap by introducing innovative representations to develop nonlinear stochastic control and reinforcement learning methods. Key in the representation is to represent the stochastic, nonlinear dynamics linearly onto a nonlinear feature space. We present a comprehensive framework to develop control and learning strategies which achieve efficiency, safety, robustness, and scalability with provable performance. We also show how the representation could be used to close the sim-to-real gap. Lastly, we will briefly present some concrete real-world applications, discussing how domain knowledge is applied in practice to further close the loop from data to actions.
Zoom Link (if unable to attend in-person): https://upenn.zoom.us/j/99029916016

BE Doctoral Dissertation Defense: "Quantitative Informatics Approaches to Characterize and Predict Childhood Genetic Epilepsies" (Peter Galer)
2024-09-18 13:00 - 15:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania along with Drs. Brian Litt and Ingo Helbig proudly announce the Doctoral Dissertation Defense of Peter Galer.

Title: Quantitative Informatics Approaches to Characterize and Predict Childhood Genetic Epilepsies
Date: Wednesday September 18
Time: 1:00pm
Location: Glandt Forum, Singh Center for Nanotechnology
Advisors: Dr. Brian Litt & Dr. Ingo Helbig
Zoom link: https://upenn.zoom.us/j/97035487377

The public is welcome to attend.

Fall 2024 GRASP SFI: Dian Wang, Northeastern University, “Equivariant Learning for Robotic Manipulation”
2024-09-18 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom.
ABSTRACT
Despite recent advances in machine learning for robotics, current approaches often lack sample efficiency, posing a significant challenge due to the enormous time consumption to collect real-robot data. In this talk, I will present our innovative methods that tackle this challenge by leveraging the inherent symmetries in the physical environment. Specifically, I will outline a comprehensive framework of equivariant policy learning and its application across various problem settings, including reinforcement learning, behavior cloning, and grasping. Our methods not only significantly outperform state-of-the-art baselines but also achieve these results with far less data, both in simulation and in real-world scenarios. Furthermore, our approach demonstrates robustness in the presence of symmetry distortions, such as variations in camera angles.

CBE Seminar: "Autonomous Soft and Colloidal Matter Fueled by Chemical Reactions" (Taylor Woehl, University of Maryland)
2024-09-18 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
Biological systems utilize networks of biochemical reactions to drive autonomous and dynamic processes. Examples include the dynamic polymerization of microtubules and the dynamic min protein system in E. Coli. In contrast, synthetic soft and colloidal matter generally requires active stimulation to undergo reconfiguration, such as application of external fields or manual changes in solution chemistry. These materials exhibit singular responses to stimulation, such as shape change or self-assembly, but lack temporal control. In recent years, synthetic chemical reaction cycles have been discovered that enabled active soft materials that exhibit transient responses to a single chemical stimulus. This seminar will describe recent work in Professor Woehl’s lab that utilize chemical reactions to drive transient and autonomous responses in colloids and hydrogels. In the first of three vignettes, I will discuss the colloidal interactions occurring during chemically fueled assembly of micron sized colloids. Here, aqueous colloids are exposed to a carbodiimide chemical fuel that temporarily renders their surface hydrophobic. We systematically identify ranges of fuel concentration that lead to no assembly, transient assembly, and irreversible assembly of colloids. Experimental measurements of colloid surface charge and hydrophobicity inform a colloidal interaction model that corroborates the experimental observations. This work identifies electrostatic and hydrophobic forces as critical for controlling transient assembly and establishes a colloidal interaction model for rationally choosing fuel concentrations for colloids of varying size. In the second vignette, I will discuss the use redox reaction cycles to generate transient protein hydrogels. Here, a strong oxidizer and weak reducing agent are concurrently added to denatured serum albumin, which causes formation of a transient disulfide crosslinked hydrogel. We found that increasing the denaturant concentration decreased the lifetime of the hydrogel. Biophysical measurements revealed this to be due to changes in the unfolding state of the protein, which mediated the concentration of free cysteines available to react with the oxidizer. This work uncovered a novel approach to tune the lifetime of transient protein hydrogels and established a connection between molecular protein structure and macroscopic hydrogel properties. In the final vignette, I will present recent work on chemically fueled shape changes in porous hydrogels. Prior work has demonstrated slow responses of polymer hydrogels to chemical fuels, typically on the order of ~10 hours. Here we utilize a combination of co-polymer hydrogels, porosity, and pH clock reactions to reduce the reconfiguration time to ~10 minutes. This work demonstrates the most rapid autonomous shape change in chemically fueled hydrogels to date.

MEAM Ph.D. Thesis Defense: "Contacts with Dynamically Tunable Adhesion and Friction via Active Materials with Thermally Modulated Stiffness"
2024-09-19 10:00 - 11:00 | Room 337, Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Contact interactions, including adhesion and friction, are critical to the design of many engineered systems. Currently, most systems rely on materials with static mechanical properties, requiring careful selection of materials to realize effective systems for specialized tasks. However, with advances in smart materials, system design is no longer limited to materials with static properties. There is a significant potential to exploit active materials for dynamic control of mechanical behaviors, including adhesion and friction, to enable the design of systems with improved performance and new functionalities. Example applications of such systems include the gripping and manipulation of objects in robotics and manufacturing, the temporary attachment of wearable devices, and the creation of tactile interfaces for virtual reality. In this work, active control of adhesion and friction is realized using materials with tunable stiffness. In particular, thermally responsive polymers, which exhibit substantial changes in stiffness, provide significant potential for adhesion and friction control. We demonstrate the use of a conductive thermoplastic and a shape memory polymer, both with thermally modulated stiffness, to dynamically tune adhesion and friction. Through a combination of experimentation and finite element analysis, we present a composite microstructured adhesive with high strength and adhesion switchability, while highlighting the role of scale in achieving fast response times. Through further experimentation, we investigate the ability to tune friction, using stiffness modulation to enable a transition from Coulomb friction to adhesion-dominated friction. This ability to dynamically control adhesion and friction offers new opportunities for the design of engineered systems.
