Penn Engineering Events

CIS Seminar: "Privacy-Preserving Accountability Online"
2023-02-28 15:30 - 16:30 (America/New_York) | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Technologies that enable confidential communication and anonymous authentication are important for improving privacy for users of internet services. Unfortunately, encryption and anonymity, while good for privacy, make it hard to hold bad actors accountable for misbehavior. Internet services rely on seeing message content to detect spam and other harmful content; services must also be able to identify users to attribute and respond to abuse complaints. This tension between privacy and accountability leads to one of two suboptimal outcomes: Services require excessive trust in centralized entities to hold users accountable for misbehavior, or services leave themselves and/or their users open to abuse.
In this talk, I will highlight two example applications, end-to-end encrypted messaging and anonymous web browsing, where this tension arises and how gaps in accountability can lead to real-world attacks. I will discuss how I have addressed this tension through the design of new cryptographic protocols that preserve user privacy while also providing mechanisms for holding bad actors accountable. In particular, I will cover new protocols for anonymous blocklisting, one-time-use credentials, and transparent key infrastructure.

ASSET Seminar: Statistical and Machine Learning for Electronic Health Records: Challenges and Opportunities, Qi Long (University of Pennsylvania)
2023-03-01 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
Electronic health records (EHRs) offer great promises in advancing clinical research and transforming learning health systems. However, complex, temporal EHRs are fraught with biases and present daunting analytical challenges that, if not addressed, can exacerbate health inequities. EHRs data, recorded at irregular time intervals with varying frequencies, are multi-modal and multi-scale including structured data such as labs and vitals, codified data such as diagnosis and procedure codes, and unstructured data such as doctor notes and pathology reports. They are typically incomplete and contain various data errors. What’s more, data gaps and errors in EHRs are often unequally distributed across patient groups: People with less access to care, often people of color or with lower socioeconomic status, tend to have more incomplete EHRs. In this talk, I will discuss these challenges and share my research group’s recent work on developing robust statistical and machine learning methods for addressing some of these challenges. Our experience has demonstrated that a trans-disciplinary health data science approach that involves collaboration between statisticians, informaticians, computer scientists, and physician scientists can accelerate innovation in harnessing the full power of EHRs to tackle complex real-world problems and exert meaningful impact in medicine. To this end, I will also discuss some open questions that present opportunities for future research and collaboration.

Spring 2023 GRASP SFI: Edward Hu, University of Pennsylvania, “Focusing on Task-Relevant Information in RL for Robots”
2023-03-01 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Levine 307 and virtual attendance via Zoom. This week’s presenter will be in-person as well.
ABSTRACT
While it is tempting to view robotics as a nail that can be solved with the deep learning hammer, we have seen that deep-learning based perception and action pipelines for robots are notoriously brittle and data hungry. In this talk, I advocate for a more measured approach for designing data-driven controllers by focusing learning on task-relevant portions of the MDP. Through this philosophy, I show that we can acquire capable learning systems that can transfer between morphologically distinct robots, intelligently probe the environment for imperceptible reward signals, and perform deep exploration with no priors.

CBE Seminar Series: "Decisions through Oscillation: Learning from Endothelial Cells" (Andre Levchenko, Yale University)
2023-03-01 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
Blood vessels constitute one of the most complex and most essential biological systems, sometimes referred to as a separate organ. Endothelial cells, lining blood vessels are also one of the most ‘plastic’ cell types, capable of a wide range of responses to external stimuli, conditioned on their internal states and micro-environment. Strikingly, many of these responses are triggered by the same signal, the growth factor VEGF. Understanding how the same input can trigger a variety of cellular responses in a consistent and meaningful manner has been one of the key challenges of systems biology. In this talk, based on a series of recent studies at our lab, I will share the lessons we learned about encoding and decoding of the information in cellular signaling networks more generally and in endothelial cells more specifically. In particular, I will discuss the ubiquitous presence and importance of dynamically fluctuating biochemical signaling in these and other cellular networks controlling different response time scales and outcomes.
Bio:
Andre Levchenko is a John C. Malone Professor of Biomedical Engineering at Yale University and the Director of Yale Systems Biology Institute. He graduated from Moscow Institute for Physics and Technology with MS and from Columbia University with the doctoral degrees. He completed his postdoctoral studies at Caltech, working in genetics and computer science. Thereafter, he spent 12 years on faculty of Johns Hopkins University BME department, rising through the ranks to Full Professor. In 2013, he was recruited to Yale as a founding director of the new systems biology institute. Prof. Levchenko has made foundational contributions to systems biology of cellular signaling, analysis of cell migration and development of novel micro- and nano-fabricated platforms for assaying cellular functions. He is a Fellow of the Biomedical Engineering Society, American Physical Society, American Institute for Medical and Biological Engineering and an elected member of Connecticut Academy of Science and Engineering.

MEAM Seminar: "Control of Jump Stochastic Systems by Learning Recurrent Spatiotemporal Patterns"
2023-03-02 10:00 - 11:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Efficient learning for stochastic control and estimation remains a topic of high interest in a variety of disciplines and there are well-known advantages and disadvantages to both model-free and model-based learning. On one hand, it is becoming increasingly more feasible to rely entirely on model-free/data-driven methods for controlling complex stochastic systems, but a well-known issue with these methods is the inefficiency of their data consumption and computation time. On the other hand, most model-based control methods are designed for a very simple class of stochastic systems, e.g., Gaussian white noise systems. In this talk, our aim is to leverage the abundance of tools and theory from mathematics on various stochastic processes to expand the capabilities of model-based methods so that model-free methods don’t need to be implemented end-to-end. We demonstrate this with the broad class of jump stochastic systems (JSSs), i.e., systems with random and repetitive jump phenomena, which are an excellent case study due to the plentiful theory that exists on various jump processes and because JSSs are highly prevalent in diverse real-world applications. The core part of this talk will focus on the development of a controller architecture called “pattern-learning for prediction” (PLP) for discrete-time/discrete-event systems (e.g., Markovian jump systems), in which we take advantage of the fact that the driving stochastic process is a sequence of random variables that occurs as repeated “patterns of interest”. We then present explicit implementations of the PLP controller architecture to two real-world applications: 1) the control of networks with dynamic topology (e.g., fault-tolerant control of a power grid susceptible to line failures), for which PLP is integrated with variations of the novel system level synthesis framework for disturbance-rejection; 2) the congestion control of vehicle traffic flow over metropolitan networks of signalized intersections, for which PLP is extended to a version called “pattern learning with memory and prediction” via the integration of episodic control to reduce memory consumption.

MSE Seminar: "Fundamental Understanding of Mechanical Properties and Deformation Mechanisms of Emerging Complex Alloys Serving under Extreme Conditions" (Lawrence Berkeley National Laboratory)
2023-03-02 10:30 - 23:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The development of stronger and tougher materials serving under extreme conditions is a long-term goal of materials research that has been made even more urgent recently by our quests for space exploration and energy sustainability. Recently, the advent of alloys with increased complexity, e.g., multi-principal element alloys (MPEAs), additively manufactured (AM) alloys, and alloys with hierarchical microstructures, has brought forth vast opportunities for the discovery and design of new materials with unprecedented mechanical properties that can meet the engineering requirements for these applications. This seminar navigates the scientific frontiers of emerging complex alloys through a wide range of temperatures: 1. The excellent combination of strength and toughness for CrCoNi-based FCC MPEAs at cryogenic or room emperatures; 2. The loss of strength for CrCoNi-based FCC MPEAs at intermediate temperatures and its remedies using additive manufacturing and oxide dispersion strengthening; and 3. The prospects and limitations of high-temperature, high-strength BCC refractory MPEAs and BCC/B2 refractory high-entropy superalloys. These fundamental investigations demonstrate how the combination of dedicated mechanical testing, state-of-the-art characterization, and multiscale computer simulations can advance the understanding and development of these highly complex alloys.

ESE Spring Seminar - "Scalable Data-Driven Decision-Making for Smart Autonomous Power and Energy Systems"
2023-03-02 12:30 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Rapidly growing renewable generations and peak loads pose a serious threat to the security and reliability of modern power and energy systems. A critical question is “how to accommodate a high penetration of renewable generation and deep electrification?”. This talk focuses on two key challenges, i.e., unknown information and the scalability issue of coordinating large-scale distributed energy resources. I will present two examples of developing distributed algorithms and learning-assisted control methods to address these challenges. One example is distributed model-free optimal voltage control to handle unknown physical system models, and the other is online learning and human-in-the-loop decision-making for residential demand response to deal with unknown human user behaviors.

CNT/PHT Seminar: "The Future of Brain Interfacing" (Philip Sabes, Neuralink, UCSF)
2023-03-02 13:00 - 14:00 | Rubenstein Audtorium, Smilow Center for Translational Research
“The Future of Brain Interfacing”
Brain interfacing holds immense promise, both for restoring lost sensory, motor or cognitive function and for the treatment of neurological and neuropsychiatric disorders. The promise is driving a great deal of interest in brain interfacing technologies — from researchers, industry, investors, and the public — yet the clinical impact of these technologies is still limited. I’ll present my view of present state of brain interfacing and the key challenges and opportunities, as seen through the lens of my earlier research at UCSF and my more recent work in the startup world.

Co-hosted by the Center for Neuroengineering and Therapeutics (CNT) and Penn Health-Tech (PHT): contact littlab@seas.upenn.edu with any questions.

RSVP here

BE Seminar: "Building Tissues: Engineering Complexity Through Biomaterial Design" (Brendan Harley, University of Illinois)
2023-03-02 15:30 - 16:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Advances in the fields of tissue engineering and regenerative medicine require biomaterials that instruct, rather than simply permit, a desired cellular response. A major challenge to progress in our field is the complex organization of the tissues in our bodies, which are hierarchical, vary in space and time, and can differ person-to person. Prof. Harley’s research program is developing approaches to structurally and biomolecularly pattern biomaterials to enable tissue regeneration after injury as well as to study processes linked to homeostasis and disease progression outside of the body. A major area of our work targets development of a degradable biomaterial to regenerate craniomaxillofacial bones and musculoskeletal insertions. We are using bioinspired design motifs to create composite materials that instruct desired cell activities while retaining mechanical competence required for clinical translation. I will describe (granular) hydrogel models to study niche regulation of hematopoietic stem cells and patient-derived glioblastoma specimens. These tools enable study of dynamic processes such as niche remodeling and reciprocal signaling linked to stem cell quiescence as well as the role of angiocrine signals and immune interactions on invasive spreading and drug resistance in primary brain cancer. We are adapting these approaches to develop hierarchical models of the endometrial tissue microenvironment to investigate trophoblast invasion and endometrial pathologies.

CIS Seminar: " Foundations of Responsible Machine Learning"
2023-03-02 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Algorithms make predictions about people constantly. The spread of such prediction systems has raised concerns that machine learning algorithms may exhibit problematic behavior, especially against individuals from marginalized groups. This talk will provide an overview of my research building a theory of “responsible” machine learning. I will highlight a notion of fairness in prediction, called Multicalibration (ICML’18), which requires predictions to be well-calibrated, not simply overall, but on every group that can be meaningfully identified from data. This “multi-group” approach strengthens the guarantees of group fairness definitions, without incurring the costs (statistical and computational) associated with individual-level protections. Additionally, I will present a new paradigm for learning, Outcome Indistinguishability (STOC’21), which provides a broad framework for learning predictors satisfying formal guarantees of responsibility. Finally, I will discuss the threat of Undetectable Backdoors (FOCS’22), which represent a serious challenge for building trust in machine learning models.

Spring 2023 GRASP on Robotics: Jeannette Bohg, Stanford University, "Scaling Robot Learning for Long-Horizon Manipulation Tasks with Language, Logic and Youtube"
2023-03-03 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom. This week’s presenter will be in-person as well.

ABSTRACT
My long-term research goal is enable real robots to manipulate any kind of object such that they can perform many different tasks in a wide variety of application scenarios such as in our homes, in hospitals, warehouses, or factories. Many of these tasks will require long-horizon reasoning and sequencing of skills to achieve a goal state. While learning approaches promise generalization beyond what the robot has seen during training, they require large data collection – a challenge when operating on real robots and specifically for long-horizon tasks. In this talk, I will present our work on enabling long-horizon reasoning on real robots for a variety of different long-horizon tasks that can be solved by sequencing a large variety of composable skill primitives. We approach this problem from many different angles such as (i) using large-scale, language-annotated video datasets as a cheap data source for skill learning; (ii) sequencing these learned skill primitives to resolve geometric dependencies prevalent in long-horizon tasks; (iii) learning grounded predicates thereby enabling closed-loop, symbolic task planning.

MEAM Seminar: "Strategies for Approaching One Hundred Percent Dense Lithium-Ion Battery Cathodes"
2023-03-03 15:30 | Towne 309, 220 S. 33rd Street, Philadelphia, PA, 19104, United States
Creating thick electrodes with low porosity can dramatically increase the available energy in a single cell and decrease the number of electrode stacks needed in a full battery, which results in higher energy, lower cost, and easier to manufacture batteries. However, existing electrode architectures cannot simultaneously achieve thick electrodes with high active material volume fractions and good power. These particle-based architectures rely on electrolyte transport within the pores of the cathode to fully lithiate active material particles during discharge. As cathode solid volume fractions approach 100%, batteries experience electrolyte depletion which leads to inaccessible cathode reaction sites. The additional theoretical capacity that comes from increased cathode density, therefore, is impractical if that energy cannot be fully extracted.
We combine experiments and simulations of high density and high thickness cathodes to understand the transport and performance trade-offs of LIBs as the cathode solid volume fraction approaches 100%, which we use to reveal the cathode properties needed to achieve high performance at high relative density and thickness. We use one- and two-dimensional simulations to compare the discharge performance of two cathode architectures, a traditional particle-based architecture and a continuous cathode architecture created via electrodeposition. We show that there is a large opportunity space for improved energy density at high relative densities by using new electrode manufacturing techniques to create continuous diffusion pathways and high diffusivities.
This work uses a comparative analysis of cathode architectures to explore the interdependent impact of solid volume fraction, solid-diffusivity, cathode thickness, and discharge rate on lithium-ion battery areal capacity. We should how a combination of high diffusivity and continuous solid-state diffusion pathways provides an exciting path for realizing ultra-dense and thick cathodes with high energy density.

ESE Spring Seminar - "Architecting High Performance Silicon Systems for Accurate and Efficient On-Chip Deep Learning"
2023-03-13 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The unabated pursuit for omniscient and omnipotent AI is levying hefty latency, memory, and energy taxes at all computing scales. At the same time, the end of Dennard scaling is sunsetting traditional performance gains commonly attained with reduction in transistor feature size. Faced with these challenges, my research is building a heterogeneity of solutions co-optimized across the algorithm, memory subsystem, hardware architecture, and silicon stack to generate breakthrough advances in arithmetic performance, compute density and flexibility, and energy efficiency for on-chip machine learning, and natural language processing (NLP) in particular. I will start, in the algorithm front, by discussing award-winning work on developing a novel floating-point based data type, AdaptivFloat, which enables resilient quantized AI computations; and is particularly suitable for NLP networks with very large parameter distribution. Then, I will describe a 16nm chip prototype that adopts AdaptivFloat in the acceleration of noise-robust AI speech and machine translation tasks – and whose fidelity to the front-end application is verified via a formal hardware/software compiler interface. Towards the goal of lowering the prohibitive energy cost of inferencing large language models on TinyML devices, I will describe a principled algorithm-hardware co-design solution, validated in a 12nm chip tapeout, that accelerates Transformer workloads by tailoring the accelerator’s latency and energy expenditures according to the complexity of the input query it processes. Finally, I will conclude with some of my current and future research efforts on further pushing the on-chip energy-efficiency frontiers by leveraging specialized non-conventional dynamic memory structures for on-device training — and recently prototyped in a 16nm tapeout.

PSOC Seminar: “The Nuclear Lamina and Cell Fate in the Preimplantation Embryo” (Robin Skory, Penn)
2023-03-13 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Spring 2023 Hybrid-Seminar Series
Mondays 1.00-2.00 pm (EST)
Towne 225 / Raisler Lounge
“For Zoom link, please contact <manu@seas.upenn.edu>”

MEAM Seminar: "Bioinspired Microrobotic Systems for Interfacing with Cells and Tissues"
2023-03-14 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Control over the microscopic world, at the scale of the smallest organisms, depends on the development of robots and machines that can operate at micro-nanoscales. However, fundamental limitations in the efficient miniaturization of macro-scale robotic technologies require bioinspired/hybrid approaches for actuation, sensing, and control of microrobots. Recent advances in materials, fabrication and actuation technologies have enabled the realization of wireless microrobots powered by external fields, biological organisms, and catalytic reactions. In the first part of this talk, I will introduce cell-sized (<10 µm) surface-rolling multifunctional microrobots, inspired by leukocytes in the circulatory system, actuated by external magnetic fields. Microrollers generate unprecedented strong propulsion (up to 100 body lengths per second) enabling their upstream navigation in physiological blood flow and their functionalization with targeting agents and drug molecules allows targeted, on-demand drug delivery to desired cells. In the second part, I will present reprogrammable shape morphing of small-scale magnetic soft machines enabled by heat-assisted high-resolution (<40 µm), discrete, and 3D magnetic encoding. Heat-assisted magnetic programming allows experimental optimization of the functional behavior of small-scale soft systems, including reconfigurable mechanical behavior of an auxetic metamaterial structure, tunable locomotion of a surface-walking soft robot, and adaptive grasping of a soft gripper. I will conclude the talk with a stimulating discussion on a path forward toward bio-integrated robotics at cellular and tissue scales for healthcare applications beyond targeted therapeutic delivery.

MSE Seminar: "Textile Materials for Soft Wearable Robotics" (Stanford University)
2023-03-14 10:30 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Wearable robots and devices—garments with embedded elements that actuate to change shape or apply forces to the wearer, typically based on signals from integrated sensors—offer promise for assistive and augmentative applications including rehabilitative gloves, haptic devices, and dynamically thermoregulating clothing. Early iterations of wearables from the 50s and 60s primarily took the form of rigid exoskeletons; however, in the past twenty years, a growing subset of this field has transitioned to the use of soft components and materials to improve portability, accessibility, fit, and comfort, guided in part by advances in the related field of soft robotics. Based on the unique requirements for wearables, including personalization for varied bodies and low cost for accessibility, automated and highly customizable textile-compatible materials and manufacturing strategies must be developed to support the fabrication and integration of all the necessary components (sensors, actuators, interconnections). This seminar will explore the intersection of knowledge from the field of textile materials and manufacturing with the needs of soft robots and devices, specifically focusing on wearable applications, including performance metrics, material and component choices, and fabrication strategies. Several integrated design and fabrication platforms will be presented in the context of their ability to create constituent components for wearable robots and devices.

CIS Seminar: "The Design of a General-Purpose Distributed Execution System"
2023-03-14 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Scaling applications with distributed execution has become the norm. With the rise of big data and machine learning, more and more developers must build applications that involve complex and data-intensive distributed processing.
In this talk, I will discuss the design of a general-purpose distributed execution system that can serve as a common platform for such applications. Such a system offers two key benefits: (1) common system functionality such as distributed resource management can be shared across different application domains, and (2) by building on the same platform, applications across domains can easily interoperate.
First, I will introduce the distributed futures interface, a powerful yet expressive distributed programming abstraction for remote execution and memory. Second, I will introduce ownership, an architecture for distributed futures systems that simultaneously provides horizontal scalability, low latency, and fault tolerance. Finally, I will present Exoshuffle, a large-scale shuffle system that builds on distributed futures and ownership to match the speed and reliability of specialized data processing frameworks while using an order of magnitude less code. These works have reached a broad audience through Ray, an open-source distributed futures system for

ASSET Seminar: Computational Social Listening for Public Health (Sharath Guntuku, University of Pennsylvania)
2023-03-15 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
How can A.I.-based methods inform social listening applications during public health crises? The COVID-19 pandemic has uprooted the mode and method of human communication and interaction. The magnitude of the pandemic has led to an ‘infodemic’ along with considerable increase in stress and anxiety across communities. At the same time, the use of social media has increased dramatically as individuals sheltered in place. In this talk, I will introduce how our group is using big data from social media sources for contributing to social good. I will discuss the application of machine learning and natural language processing techniques to obtain insights on the heterogeneity in vaccine acceptance and mental health measurement across communities in the United States and outside.

CBE Seminar Series: "Electrification and Decarbonization of Chemical Synthesis" (Karthish Manthiram, California Institute of Technology)
2023-03-15 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
Chemical synthesis is responsible for significant emissions of carbon dioxide worldwide. These emissions arise not only due to the energy requirements of chemical synthesis, but since hydrocarbon feedstocks can be overoxidized or used as hydrogen sources. Using renewable electricity to drive chemical synthesis may provide a route to overcoming these challenges, enabling synthetic routes which operate at benign conditions and utilize sustainable inputs. We are developing an electrosynthetic toolkit in which distributed feedstocks, including carbon dioxide, dinitrogen, water, and renewable electricity, can be converted into diverse fuels, chemicals, and materials.
In this presentation, we will first share recent advances made in our laboratory on nitrogen fixation to synthesize ammonia at ambient conditions. Specifically, our lab has investigated a continuous lithium-mediated approach to ammonia synthesis and understood the reaction network that controls selectivity. We have developed non-aqueous gas-diffusion electrodes which lead to high rates of ammonia synthesis at ambient conditions. Then, we will discuss how water can be used as a sustainable oxygen-atom source and how carbon dioxide can be used to achieve carbon chain extension. These findings will be discussed in the context of a broader range of electrosynthetic transformations which could lead to local and on-demand production of critical chemicals and materials.
Bio:
Karthish Manthiram is a Professor of Chemistry and Chemical Engineering at Caltech. The Manthiram Lab is focused on the molecular engineering of electrocatalysts for the synthesis of organic molecules, including pharmaceuticals, fuels, and commodity chemicals, using renewable feedstocks. Karthish received his bachelor’s degree in Chemical Engineering from Stanford University in 2010 and his PhD in Chemical Engineering from UC Berkeley in 2015. After a one-year postdoc at the California Institute of Technology, he joined MIT as an Assistant Professor in 2017. In 2021, he moved to Caltech as a Full Professor of Chemistry and Chemical Engineering. Karthish’s research has been recognized with several awards, including the DOE Early Career Award, NSF CAREER Award, Sloan Research Fellowship, 3M Nontenured Faculty Award, American Institute of Chemical Engineers 35 Under 35, American Chemical Society PRF New Investigator Award, Dan Cubicciotti Award of the Electrochemical Society, and Forbes 30 Under 30 in Science. Karthish’s teaching has been recognized with the Camille Dreyfus Teacher-Scholar Award, C. Michael Mohr Outstanding Undergraduate Teaching Award, the MIT Chemical Engineering Outstanding Graduate Teaching Award, and the MIT Teaching with Digital Technology Award. He serves on the Early Career Advisory Board for ACS Catalysis and on the Advisory Board for Trends in Chemistry.

MSE Seminar: "Interacting Opto-Moiré Quantum Matter" (University of Washington)
2023-03-16 10:30 - 12:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Moiré superlattices of two-dimensional (2D) materials are an emerging platform for studying new physical phenomena with high tunability. Strong excitonic responses in transition metal dichalcogenides (TMDs) allow optical access to the wealth of physics. In this talk, I will present our recent results about interactions between excitons and charge carriers trapped in moiré potentials. We have discovered novel exciton many-body ground states composed of moiré excitons and correlated electron lattices, resulting from new interaction between exciton and charges enabled by unusual quantum confinement in 2D moiré superlattices. The interaction further enriches the magnetic phases in such moiré superlattices. We have observed that the spin-spin interactions between moiré trapped holes can be drastically tuned by optical excitation power. The mechanism points to the unique excitons-mediated long-range exchange interaction between moiré trapped carriers. This discovery adds a new and dynamic tuning knob to the rich many-body Hamiltonian of moiré quantum matter. Our work provides the framework for understanding and engineering electronic and excitonic states in moiré quantum matters.

ESE Spring Seminar - "Supercharging Programming Through Compiler Technology"
2023-03-16 12:30 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The decline of Moore’s law and an increasing reliance on computation has led to an explosion of specialized software packages and hardware architectures. While this diversity enables unprecedented flexibility, it also requires domain-experts to learn how to customize programs to efficiently leverage the latest platform-specific API’s and data structures, instead of working on their intended problem. Rather than forcing each user to bear this burden, I propose building high-level abstractions within general-purpose compilers that enable fast, portable, and composable programs to be automatically generated.
This talk will demonstrate this approach through compilers that I built for two domains: automatic differentiation and parallelism. These domains are critical to both scientific computing and machine learning, forming the basis of neural network training, uncertainty quantification, and high-performance computing. For example, a researcher hoping to incorporate their climate simulation into a machine learning model must also provide a corresponding derivative simulation. My compiler, Enzyme, automatically generates these derivatives from existing computer programs, without modifying the original application. Moreover, operating within the compiler enables Enzyme to combine differentiation with program optimization, resulting in asymptotically and empirically faster code. Looking forward, this talk will also touch on how this domain-agnostic compiler approach can be applied to new directions, including probabilistic programming.

CIS Seminar: "Designing Provably Performant Networked Systems"
2023-03-16 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
As networked systems become critical infrastructure, their design must reflect their new societal role. Today, we build systems with hundreds of heuristics but often do not understand their inherent and emergent behaviors. I will present a set of tools and techniques to prove performance properties of heuristics running in real-world conditions. Rigorous proofs can not only inspire confidence in our designs, but also give counter-intuitive insights about their performance.
A key theme in our approach is to model uncertainty in systems using non-random, non-deterministic objects that cover a wide range of possible behaviors under a single abstraction. Such models allow us to analyze complex system behaviors using automated reasoning techniques. I will present automated tools to analyze congestion control and process scheduling algorithms. These tools prove performance properties and find counter-examples where widely deployed heuristics fail. I will also show that current end-to-end congestion control algorithms that bound delay cannot avoid starvation and present a method to beamform wireless signals using thousands of antennas.

Spring 2023 GRASP on Robotics: Emilio Frazzoli, ETH Zürich, "A self-contained karma economy for socially efficient and equitable autonomy"
2023-03-17 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom. This week’s presenter will be in-person as well.

ABSTRACT
Autonomous systems of the near future have the potential to impact and improve our lives in unprecedented ways. As an example, an autonomous taxi service can be instructed to take the socially responsible route minimizing congestion (and associated carbon emissions) instead of the purely selfish shortest route. In order for such a system to be robust and gain public acceptance, it is critical that it respects the users’ personal incentives, as well as ensures that different users enjoy equitable service. Until now, the vast majority of incentive schemes used in engineering systems have been monetary. Examples include road-tolling to reduce traffic congestion, surge-pricing to manage excessive demand in ride-hailing, and time-varying energy tariffs to encourage consumption off peak hours. In this talk, we argue that the use of money in engineering systems is fundamentally flawed. The sensitivity of users to money can vary widely for factors outside the system (e.g., income and inter-generational wealth accumulation), and therefore monetary schemes implicitly favor the wealthy. We introduce the concept of a self-contained karma economy as an alternative incentive scheme. In a karma economy, each user is endowed with tokens (called karma) that are non-tradable for money, and the users repeatedly obtain or yield a preferential service in exchange of karma. We demonstrate this concept on the stylized yet insightful example of autonomous intersection management, where an agent passing first in an intersection transfers karma to that yielding. We lay the mathematical foundations that ensure that such an economy is well-defined and the strategic behavior of its users (i.e., how much karma they spend) can be predicted. We then analyze the performance of the karma economy in numerical case studies, showcasing that it achieves socially efficient outcomes in a self-contained, and thereby equitable, manner.

Celebration of Diversity
2023-03-17 15:00 - 18:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Presented by Penn Engineering’s Office of Diversity, Equity & Inclusion (ODEI) , the Underrepresented Student Advisory Board in Engineering (USABE), the Penn chapter of the National Society of Black Engineers (NSBE), the Penn chapter of the Society of Hispanic Professional Engineers (SHPE), and the Penn Society of Women Engineers (SWE), the gathering will include remarks from student and alumni speakers, creative performances, and – of course – delicious food. This event is an opportunity to celebrate students, staff, and faculty from all backgrounds and to reinforce a sense of solidarity.

We hope to see you there!

BE Seminar: "Vein-to-Vein Microfluidic Engineering for Cell Therapies" (Abe Lee, UC Irvine)
2023-03-20 10:00 - 11:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Adoptive cell therapy (ACT) is a type of immunotherapy that involves the processing of blood from a donor to isolate immune cells (e.g. T cells) for genetic manipulation followed by reinfusion of the cells into patients. Specifically for CAR T cell therapy, genetic coding material (e.g. DNA, mRNA) is inserted into the T cells to express chimeric antigen receptors to target biomarkers of cancer cells and trigger an activated immune response towards the tumor of interest. This process that starts from blood drawn from one person and ends with specialized engineered cells delivered to the same patient includes multiple tedious and costly steps, and can require a long time that the patient may not have. Microfluidics techniques are being developed that can address all steps of this cell manufacturing process, including cell harvesting, cell isolation, cell activation and expansion, and cell transfection. In this talk I will introduce two microfluidic platforms in my lab, one is the lateral cavity acoustic transducer (LCAT) and the other is droplet microfluidics. LCAT was used for processing blood samples, isolating T cells, transfecting T cells, and finally expanding T cells to scale up for treatment. Based on LCAT, we developed the acoustic electric shear orbiting poration (AESOP) device to uniformly deliver genetic cargo dosage into a large population of cells simultaneously. Based on droplet microfluidics we constructed a single cell artificial antigen presenting cells (aAPCs) for T cell activation. By trapping single cells in microfluidic compartments, we are able to study the cell morphology and cell-cell communications to further understand immune cell activation and immune cell synapses.

PSOC Seminar: "Adventures in Cellular Herding: from flocks of cells to bioelectric shepherds" (Daniel J. Cohen, Princeton)
2023-03-20 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

MEAM Seminar: "Additive Manufacturing: Future of Healthcare"
2023-03-21 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Personalized medicine as an emerging solution for health problems is leveraged by advanced manufacturing technologies. Personalized medical devices, tissue grafts, biomonitoring systems, and precision medicine are customized based on each patient’s needs and health background. However, the current manufacturing techniques are challenged when it comes to fabricating architected structures with complex designs. Additive manufacturing has been a strong tool for fabricating such architectures for tissue regenerative applications. In combination with sacrificial biomanufacturing, functional living materials are developed with 3D internal permeable macrochannels that enable nutrition transfer for prolonged cell viability. Conventional approaches for implantation of fully functional 3D printed tissue constructs require invasive surgeries, raising the need for more efficient alternative biomanufacturing technologies. Sound in vivo printing is a unique solution that enables printing tissue scaffolds deep inside the body where in lieu of open surgeries, the target organs can be reached through minimally invasive devices such as catheters to deliver biomaterials. For this purpose, focused ultrasound-triggered crosslinking is used for creating complex biostructures centimeters deep into the organs. Next-generation in vivo printing technology enables a smart biomanufacturing scheme for a wide range of functional biomaterials for applications in tissue regeneration, bioelectronics, drug delivery, etc.

BE Undergraduate Student Focus Group
2023-03-21 10:30 - 11:30
Attention BE Master’s Students! We want your thoughts on the job search! Sign up for this upcoming focus group to give us your opinion on industries of interest, employers & recruiting events.
Register now: http://tinyurl.com/bdzz8cna.
Contact Lauren Kemp with any questions: laurem@seas.upenn.edu

MSE Seminar: "VdW Heterostructures: A New Route to Designing Quantum Material" (Princeton University)
2023-03-21 10:30 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
From superconductivity to fractionalized particles, fascinating phenomena arise in quantum materials due to the collective behaviors of electrons. These quantum effects challenge our understanding of nature and open up new possibilities for future technologies in quantum information. In my talk, I will discuss the use of van der Waals (vdW) heterostructures to create new quantum materials. These heterostructures, made by mechanically assembling layers of two-dimensional materials together, offer a new way to create quantum matter and break through traditional material synthesis limitations.

I will present two examples of this approach. In the first example, I will illustrate how Coulomb interactions across separate atomic layers pair fermions (electrons and holes) into bosons to achieve a superfluid condensate state. The second example will introduce the concept of moiré band engineering, where the interference between two atomic lattices reforms electronic band structures and creates new electronic orders. Finally, I will briefly discuss applications of local probe techniques to uncover hidden quantum properties in vdW platforms and share visions of leveraging rich interplays across atomic interfaces to create new quantum states of matter, new quantum devices, and new local measurements.

ESE Spring Seminar - "Aligning Robot and Human Representations"
2023-03-21 12:30 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
To perform tasks that humans want in the world, robots rely on a representation of salient task features; for example, to hand me a cup of coffee, the robot considers features like efficiency and cup orientation in its behavior. Prior methods try to learn both a representation and a downstream task jointly from data sets of human behavior, but this unfortunately picks up on spurious correlations and results in behaviors that do not generalize. In my view, what’s holding us back from successful human-robot interaction is that human and robot representations are often misaligned: for example, our lab’s assistive robot moved a cup inches away from my face — which is technically collision-free behavior — because it lacked an understanding of personal space. Instead of treating people as static data sources, my key insight is that robots must engage with humans in an interactive process for finding a shared representation for more efficient, transparent, and seamless downstream learning. In this talk, I focus on a divide and conquer approach: explicitly focus human input on teaching robots good representations before using them for learning downstream tasks. This means that instead of relying on inputs designed to teach the representation implicitly, we have the opportunity to design human input that is explicitly targeted at teaching the representation and can do so efficiently. I introduce a new type of representation-specific input that lets the human teach new features, I enable robots to reason about the uncertainty in their current representation and automatically detect misalignment, and I propose a novel human behavior model to learn robust behaviors on top of human-aligned representations. By explicitly tackling representation alignment, I believe we can ultimately achieve seamless interaction with humans where each agent truly grasps why the other behaves the way they do.
