College of Engineering - University of Wisconsin-Madison

BME Seminar Series: Chima V. Maduka, DVM, PhD
2025-01-16 12:00 - 13:00 (America/Chicago) | 2188 Mechanical Engineering Building, 1513 University Avenue, Madison, WI, 53706, United States
Harnessing the Power of Immunometabolism to Engineer the Future of Medicine

Chima V. Maduka, DVM, PhDAHA Postdoctoral FellowBurdick Biomaterials and Biofabrication LaboratoryUniversity of Colorado

Abstract:The metabolic underpinnings of immune cells in various inflamed tissues, such as the implant microenvironment or the diseased heart, are poorly understood. For instance, polylactide (PLA) is the most widely used biopolymer in medicine. Yet, for decades, PLA had been thought to activate immune cells by reducing surrounding pH because PLA biodegrades into monomers and oligomers of lactic acid. During my talk, I will discuss an alternative paradigm underscoring immune cell metabolism (immunometabolism) as the pivotal determinant of the proinflammatory versus pro-regenerative tissue microenvironment with biodegradable and non-biodegradable biomaterial examples. Further related to tissue engineering, I will present on reversing established cardiac dysfunction and fibrosis in heart failure (following myocardial infarction) via targeted and enzyme-responsive nanomaterials. Finally, I will unveil my vision to revolutionize therapeutic strategies for the various phenotypes of heart failure by leveraging the metabolic underpinnings of immune and stromal cell populations, thereby engineering next-generation clinical interventions that shape the future of medicine.

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BME Seminar Series: Jingwen Yan, PhD
2025-01-21 12:00 - 13:00 | 2180 Mechanical Engineering, 1513 University Ave, Madison, WI, 53706, United States
Integrative -omics for improved understanding and detection of Alzheimer’s disease

Jingwen Yan, PhDAssociate Professor and Director of BioinformaticsLuddy School of Informatics, Computing and EngineeringIndiana University Indianapolis

Abstract:Integrative -omics is an emerging research field that aims to extract the knowledge from the broad multi-omic data landscape. While multiple domains included, such as brain imaging, genetics, transcriptomics and proteomics, it offers great promise to illuminate the causal pathway from genotype to phenotype and to provide optimal molecular phenotypes for early therapeutic intervention. Building on the extensive mult-omics and brain imaging datasets, we focus on the development and application of AI models and bioinformatics approaches aimed at 1) exploring the functional mechanisms linked to Alzheimer risk variants (i.e., functional genomics) and 2) modeling disease progression to improve early detection and risk assessment. In this talk, I will introduce some of our recent work on exploration of AD molecular mechanisms and early detection with integrative -omics approaches.

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BME Seminar Series: Chu Ma, PhD
2025-01-27 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
Blind-Label Subwavelength Ultrasound Imaging

Chu Ma, PhDDugald C. Jackson Assistant ProfessorAcoustic Sensing and Functional Materials (ASFM) LabDepartment of Electrical and Computer EngineeringUniversity of Wisconsin-Madison

Abstract:Ultrasound allows non-invasive, non-radiative imaging with sub-millimeter resolution, with broad applications in sensing, communication, biomedical diagnosis and non-destructive testing. In this talk, I will present our work on combining acoustic random scattering and computational imaging for improving the resolution of ultrasound imaging. Similar to all the other wave-based imaging modalities, ultrasound imaging suffers from diffraction limit, which is a trade-off between imaging resolution and wave penetration depth. Most existing acoustic subwavelength imaging technologies addressing this limit require controlled “labels,” i.e., metamaterials or contrast agents, to be deposited close to the objects and to either remain static or be tracked precisely during imaging, restricting their practical applications. We propose a “blind-label” approach. The blind labels are randomly distributed subwavelength microstructures or microparticles. The originally evanescent components in the scattered waves from the object are first converted to propagating components and then extracted by computational algorithms. Compared to conventional ultrasound imaging systems, our approach achieves an order of magnitude improvement in the imaging resolution without sacrificing the wave penetration depth. Our “blind-label” approach relaxes the restrictions of existing acoustic subwavelength imaging technologies that rely on controlled labels, thereby substantially enhancing the practicality of acoustic subwavelength imaging in real-world applications.

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BME Seminar Series: Monica Ohnsorg, PhD
2025-01-30 12:00 - 13:00 | 2180 Mechanical Engineering, 1513 University Ave, Madison, WI, 53706, United States
Using Bottlebrush Polymers to Tackle Challenges in Drug Delivery and Tissue Engineering

Monica Ohnsorg, PhDPostdoctoral FellowDepartment of Chemical and Biological EngineeringBioFrontiers InstituteUniversity of Colorado Boulder

Abstract:Macromolecular design can be a powerful tool to improve the efficacy of clinical therapeutics and develop biomaterials to support in vitro human cell-based models. In this talk, I will discuss two vignettes describing how bottlebrush polymers, macromolecular architectures which are composed of polymer chains covalently bound at one end to a linear polymer backbone, can be used to both improve oral drug delivery and study how cells respond to strain-stiffening microenvironments. First, I will introduce how bottlebrush copolymers can be used to non-covalently sequester and solubilize small molecule therapeutics. Specifically, by modulating bottlebrush polymer hydrophilicity using post-polymerization end-group modification techniques, the small molecule anti-seizure medication, phenytoin, was effectively solubilized at higher drug loadings with the bottlebrush polymer carrier compared to current industry standard excipients. Second, I will address how nonlinear elasticity, an understudied property of natural extracellular matrix, can be recapitulated using synthetic materials that support 3D cell culture. Bottlebrush polymer-based hydrogels can be used to decouple strain-stiffening biomechanical cues from stress-relaxation and observe how engineered strain-stiffening microenvironments regulate the initiation of cellular protrusion formation. Building upon these findings, I will discuss how bottlebrush polymer-based hydrogels can be used to mimic the biomechanical properties of non-mineralized, collagen type-1 rich bone osteoid to develop models of human osteocyte dendritic network formation and function. Together, these applications demonstrate how bottlebrush polymer-based materials hold great potential to recapitulate biologically relevant biomechanical and biochemical signals for in vitro cell culture, for tissue and disease modeling, and as therapeutic delivery vehicles in the future.

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BME Seminar Series: Yichun He
2025-02-03 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
Bridging Molecular and Functional Understandings of Cells with Artificial Intelligence

Yichun HePhD Candidate, Harvard UniversitySchool of Engineering and Applied SciencesThe Broad Institute of MIT and Harvard

Abstract:The mammalian brain exhibits complex functions and behaviors, driven by diverse cell types distributed throughout its tissue. However, understanding the heterogeneity of cell types and neuronal functions across the entire brain remains a significant challenge. In this talk, I will present the development of one of the first spatial cell atlases of the entire mouse brain, providing a comprehensive map of molecularly defined cell types and tissue regions. Specifically, I will discuss the challenges of large-scale cell segmentation in situ and introduce my approach for scalable and accurate cell segmentation. Next, I will explore single-neuron dynamics using in vivo electrophysiology by developing a deep learning model for spike sorting over time, highlighting how this approach enables the decoding of neural population dynamics during motor task learning. Finally, I will outline my roadmap for bridging molecular and functional understandings of cells across modalities and conditions, with the ultimate goal of uncovering fundamental brain mechanisms and informing targeted therapeutics for neurological diseases.

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BME Seminar Series: Jonathan Soucy, PhD
2025-02-06 12:00 - 13:00 | 3210 Mechanical Engineering, 1513 University Ave., Madison, WI, 53706, United States
Engineering the retinal microenvironment to improve donor neuron integration post-transplantation

Jonathan Soucy, PhDPostdoctoral Research FellowOphthalmology Department at Harvard Medical SchoolSchepens Eye Research Institute of Mass. Eye and Ear

Abstract:Neuron transplantation is an exciting solution for replacing retinal ganglion cells (RGCs) lost in glaucoma and other optic neuropathies. However, one significant barrier to successful donor RGC integration is their migration into the ganglion cell layer (GCL). To address this, we developed an approach to control donor neurons in vivo by engineering their microenvironment post-transplantation.Using an in silico analysis of the developing human retina and a functional in vitro assay, we evaluated receptor-ligand candidates for their potential to control RGC migration. Among these, SDF1 emerged as our lead molecule. By establishing an SDF1 gradient in vivo, we increased donor RGC integration into the GCL nearly threefold. While this strategy has not yet restored vision, only donor RGCs that migrated into the GCL extended neurites toward the optic nerve head and expressed mature RGC markers.This work establishes a framework for controlling donor cell function through tissue microenvironment engineering, laying the foundation for future advancements in stem cell-based therapies for vision restoration.

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BME Seminar Series: Shailaja Seetharaman, PhD
2025-02-13 12:00 - 13:00 | 3210 Mechanical Engineering, 1513 University Ave., Madison, WI, 53706, United States
Vascular Dysfunction in Disease: Engineering Mechanobiology Holds the Solution

Shailaja Seetharaman, PhDPostdoctoral ResearcherJames Franck Institute and Department of PhysicsUniversity of Chicago

Abstract:Abnormalities in blood vessel and blood flow properties are key drivers of severe cardiovascular and cerebrovascular pathologies. The remarkable ability of the vasculature to sense and respond to mechanical and biochemical signals across multiple scales presents both a challenge for understanding disease progression and an opportunity for therapeutic intervention. In this talk, I will first present our recent findings on uncovering novel mechano-biochemical feedback loops that drive endothelial dysfunction in atherosclerosis. I will highlight how blood flow profiles trigger transcriptional control of force-sensitive proteins, which mediate cytoskeletal crosstalk and cellular adaptation during endothelial dysfunction. Second, building on these mechanistic insights into molecular feedback and cellular structural rearrangements, I will describe our development of one of the first ‘biologically-informed’ ML models for predicting tissue-scale function in health and disease. This work opens new avenues for decoding mechano-biochemical feedback across scales in cardio- and cerebrovascular diseases. Finally, I will outline how this integrated approach enables engineering of physiological vascular tissue function and AI-mediated discovery of disease drivers, with the ultimate goal of targeting vascular functions to reverse disease progression.

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BME Seminar Series: Dhananjay Bhaskar, PhD
2025-02-17 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
Harnessing Geometry and Topology in Machine Learning for Biomedical Discovery

Dhananjay Bhaskar, PhDPostdoctoral Researcher, Yale UniversityYale – Boehringer Ingelheim FellowKavli Institute for Neuroscience FellowVisiting Scholar in Engineering, Brown University

Abstract:Understanding the shape of data through geometry and topology offers a powerful perspective with the potential to drive breakthroughs in biomedical science and engineering. This talk explores how these mathematical frameworks, integrated with machine learning, can drive innovation in drug discovery, understanding cellular communication, and unraveling the dynamics of brain activity.

I will introduce learnable geometric scattering, a novel machine learning framework that overcomes the key limitations of conventional graph neural networks. By capturing nuanced structural features, this approach opens new frontiers in drug discovery and protein conformational analysis. Building on this, I will demonstrate how combining geometric scattering with topological data analysis uncovers hidden patterns in cell signaling and neural activity, shedding light on wound healing mechanisms and schizophrenia diagnosis. Finally, I will highlight how these tools can deepen our understanding of learning in artificial neural networks, paving the way for the development of biologically inspired, more expressive, and robust machine learning models.

This talk will emphasize the practical applications of these approaches and their transformative potential for addressing real-world challenges in health and medicine.

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ECE RISE-AI and RISE-EARTH Seminar Series - Seah Kim
2025-02-20 12:00 - 13:00 | 4610 Engineering Hall, 1415 Engineering Drive, Madison, 53711
4610 Engineering Hall

Scalable SoC Architectures for Domain-Specific Computing: From Algorithms to Silicon

Abstract:Modern software stacks contain concurrent and heterogeneous workloads with bespoke constraints. This is especially crucial for emerging edge applications, such as AR/VR, robotics, and autonomous vehicles. In response to these demands, hardware has shifted towards pervasive specialization, making development and cross-stack integration increasingly challenging. This shift raises the pressing question at the core of modern computing: How do we enable scalable specialization in modern SoCs? How do we design and integrate heterogeneous accelerators while ensuring performance scalability through efficient resource management and adaptability across system layers?In this talk, I will present my research addressing these interconnected challenges of scalable specialization through full-stack, system approaches. (1) First, I will introduce Gemmini, an award-winning, widely used DNN accelerator generator that enables agile, full-stack accelerator evaluation. Gemmini allows researchers to explore the specialized accelerator design space under a full SoC. (2) Next, I will present AuRORA, the award-winning, novel virtualized accelerator integration approach with dynamic resource allocation, paving the foundation for accelerator-rich SoCs. AuRORA redesigns a novel CPU-accelerator interface that enables fast and flexible resource repartitioning, along with a runtime system that abstracts physical accelerators into a unified virtualized resource pool. (3) ​​Then, I will introduce SuperNoVA, an algorithm-hardware co-design for real-time, dynamic workloads on resource-constrained platforms, using SLAM as a target workload. SuperNoVA tackles the challenge of balancing accuracy and real-time execution with an adaptive algorithm for large-scale SLAM. (4) Finally, I will showcase a silicon test chip I taped out that embodies my research by integrating these innovations. Silicon validation with real workloads successfully proves the feasibility of scalable specialization.By bridging hardware design, system software, application algorithms, and silicon validation, my research enables adaptive, accelerator-rich computing platforms for modern edge applications. I will revolutionize edge SoC design by combining design-time hardware-software co-optimization with runtime adaptive resource management, achieving the best of both static specialization and dynamic flexibility to address the evolving demands of future edge platforms.

Seah Kim

Bio:Seah Kim is a Ph.D. Candidate at UC Berkeley, specializing in Computer Architecture and VLSI. Her research spans the full computing stack, from chip design and hardware development to system software and application algorithms, with a focus on scalable domain-specific SoC design. She has been awarded the IEEE Micro Top Pick in Computer Architecture (MICRO 2023), the Best Paper Award (DAC 2021), and the Distinguished Artifact Award (ISCA 2023). Prior to UC Berkeley, she earned a B.S. in Electrical and Computer Engineering from Seoul National University. Seah was selected as a 2024 Rising Star in EECS and a 2023 ML and Systems Rising Star.

BME Seminar Series: Mehmet Orman, PhD
2025-02-24 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
Metabolic Adaptations of Drug-Tolerant Persister Cells

Mehmet A Orman, PhDAssociate ProfessorChemical and Biomolecular Engineering DepartmentUniversity of Houston

Abstract:My research focuses on understanding drug-tolerant phenotypes, particularly persister cells, in both prokaryotic and eukaryotic systems. Persister cells are temporarily tolerant to drugs and contribute significantly to disease recurrence. We investigate their molecular makeup, including metabolite profiles, RNA expression, protein composition, and regulatory networks, to identify key survival mechanisms and potential therapeutic targets. Our ongoing projects include investigating self-digestion-mediated tolerance in bacterial persisters, host-pathogen interactions in drug tolerance, metabolic and repair pathways in bacterial and cancer persisters, and the immunomodulatory potential of microbial cells to harness host-pathogen interactions for cancer therapy.

In this talk, I will highlight our strategies to study and target persister cell metabolism in bacteria and cancer. Contrary to the belief that persister cells in bacteria have suppressed metabolism, we show that their survival depends on energy metabolism, particularly oxidative phosphorylation. In bacteria, the cyclic-adenosine monophosphate and its receptor protein redirects metabolism from anabolism to oxidative phosphorylation, highlighting the importance of the tricarboxylic acid cycle, electron transport chain, and ATP synthase. Similarly, in melanoma persisters, chemotherapy-induced stress increases mitochondrial activity, revealing a dual role of treatment—inducing apoptosis in most cells while promoting a dormant, drug-tolerant subpopulation. Understanding these metabolic adaptations opens new avenues for therapeutic interventions, aiming to eradicate persister cells and prevent disease recurrence.

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ECE RISE SEMINAR SERIES: AI for Next-Generation Electronics and Chip Design - Olivia Hsu
2025-02-25 12:00 - 13:00 | 1240 Computer Sciences, 1210 W. Dayton St., Madison, 53711
1240 Computer SciencesLIVE STREAM: https://uwmadison.zoom.us/j/93718552231?pwd=[REDACTED]

From Language to Silicon: Programming Systems for Sparse Accelerators

Abstract:In this era of specialization, modern hardware development focuses on domain-specific accelerator design due to the plateau in technology scaling combined with a continual need for performance. However, domain-specific programming systems for these accelerators require extreme engineering effort, and their complexity has largely caused them to lag behind. Fundamentally, the widespread usability, proliferation, and democratization of domain-specific accelerators hinge on their programming systems, especially when targeting new domains.This talk presents research on accelerator programming systems for the emerging domain of sparsity targeting emerging sparse accelerators. The first system, the Sparse Abstract Machine (SAM), introduces a unified abstract machine model and compiler abstraction for sparse dataflow accelerators. SAM defines a novel streaming representation and abstract dataflow interfaces that serve as an abstraction to decouple sparse accelerator implementations from their programs, similar to a stable ISA for dataflow. The second system, Mosaic, introduces modular and portable compilation solutions across different sparse accelerators and high-performance systems. These systems are a first step towards usable and programmable heterogeneous hardware acceleration for all. I will conclude by discussing the next steps to reach this goal, which include programming systems for accelerators in other domains and interoperation between accelerators across domains.

Olivia Hsu

Bio:Olivia Hsu is a final-year Computer Science PhD student at Stanford University, advised by Professors Kunle Olukotun and Fredrik Kjolstad. She received her BS in Electrical Engineering and Computer Science (EECS) at UC Berkeley. Her broad research interests include computer architecture, computer and programming systems, compilers, programming languages, and digital circuits/VLSI. Olivia is a 2024 Rising Star in EECS and an NSF Graduate Research Fellow, and her research won a distinguished paper award at PLDI 2023. To learn more about her work, please visit her website at https://cs.stanford.edu/~owhsu.

ECE RISE SEMINAR SERIES: Clean Energy Technologies - Dr. Nishil Talati
2025-02-25 16:00 - 17:00 | 2255 Engineering Hall, 1415 Engineering Drive, Madison, 53711
2255 Engineering Hall

Systems-Architecture Co-Design for AI and Large-Scale Data Analytics

AbstractModern computing systems are increasingly bottlenecked by the demands of data-intensive applications such as AI, data analytics, and scientific computing. These challenges stem from both the massive scale of data and inefficiencies caused by irregular access patterns. In this talk, I will present my research on innovative co-design approaches to systems and architectures that tackle these pressing issues. First, I will introduce Vortex, a system that accelerates large-scale data analytics on GPUs by orchestrating efficient data transfers across multi-GPU systems, proposing a concept called GPU resource disaggregation. Then, I will discuss Prodigy, a hardware-software co-design framework that minimizes memory stalls in irregular workloads on CPUs through advanced workload analysis and prefetching techniques. Together, these advances highlight how domain-specific co-design can drive transformative improvements, addressing fundamental bottlenecks in modern computing. Finally, I will share my vision for tackling future challenges in scaling AI capabilities and the research directions I am eager to pursue to address them.

Nishil Talati

BioNishil Talati is an Assistant Research Scientist in the Computer Science and Engineering department at the University of Michigan, where he also earned his PhD. His research focuses on computer architecture and systems software design to enhance the efficiency of modern data-driven applications. Nishil’s work has been featured in top-tier venues such as ISCA, MICRO, HPCA, ASPLOS, and VLDB, and has made a significant impact through industry tech-transfers, inspiring follow-up research, and earning several accolades. These include the 2021 HPCA Best Paper Award, honorable mentions at DATE 2023 and IISWC 2023, recognition as a 2023 ProQuest Distinguished Dissertation Award finalist, the Best Faculty Research Pitch Award at MIDAS event in 2023, and finalist status in the 2022 CSE Honors Competition.

ECE RISE SEMINAR SERIES: Clean Energy Technologies - Dr. Noman Bashir
2025-02-27 12:00 - 13:00 | 4610 Engineering Hall, 1415 Engineering Drive, Madison, 53711
4610 Engineering Hall

Designing the Next Generation of Computer Systems for Sustainable AI

Abstract:Abstract: The key technology trend for the next decade is the transformative potential of artificial intelligence (AI), alongside its rapidly growing energy consumption and associated environmental impacts. However, our longstanding focus on energy efficiency alone will not solve the problem, and current computer systems powering AI applications are not designed to optimize carbon efficiency — that is, the amount of work performed per unit of carbon emitted. In this talk, I will present my work on rethinking how we design and operate computer systems for AI to enable carbon-aware optimizations. I will present my work on virtualizing the energy system to provide both visibility into, and software-defined control over, energy systems for computer applications. I will also describe how the proposed abstractions allow a wide range of AI applications to manage the variability of clean energy in software — accommodating diverse user and application requirements, goals, strategies, and tolerances for reducing carbon and energy. I will share my work on uncertainty- aware modeling of lifecycle carbon footprint, which helps stakeholders in computing and AI assess the discernibility of their decisions. Finally, I will outline my vision for enabling sustainable AI capabilities in a rapidly evolving landscape of AI hardware and software, and I will illustrate how these advances can drive broader societal decarbonization.

Noman Bashir

Bio:Noman Bashir is a Computing & Climate Postdoctoral Impact Fellow at the MIT Computer Science & Artificial Intelligence Laboratory (CSAIL) and the MIT Climate & Sustainability Consortium (MCSC). His research rethinks the design and operation of large-scale computer systems to address emerging challenges, including rapidly rising computing demand, increasing energy constraints, and unintended socio- environmental implications. His work on improving resource utilization — deployed across all Google datacenters — demonstrates significant real-world impact. He earned his Ph.D. from the University of Massachusetts Amherst in 2022.

BME Seminar Series: Jacob Witten, PhD
2025-03-03 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
Artificial intelligence for state-of-the-art gene therapy

Jacob Witten, PhDPostdoctoral FellowAnderson LabMassachusetts Institute of Technology

Abstract:Lipid nanoparticles (LNPs) for RNA delivery have exploded onto the biomedical research scene with the success of mRNA vaccines for COVID-19. In addition to their promise as mRNA vaccines for infectious disease and cancer, LNPs have the potential to treat or cure patients with deadly lung diseases such as cystic fibrosis. However, gene therapy in the lung is a notoriously difficult challenge that has frustrated decades of researchers. Here, I take two approaches to identifying LNPs capable of addressing this challenge. First, I developed an in vitro primary cell platform to screen LNPs for lung mRNA delivery and identify two state-of-the-art LNPs for respiratory tract delivery to mice. Second, I developed Lipid Optimization using Neural networks (LiON), a deep learning strategy for LNP design. Using LiON I evaluated 1.6 million possible LNPs and identified two, FO-32 and FO-35, with mRNA delivery matching that of LNPs in ongoing clinical trials. Overall, this work shows the potential of deep learning to bring gene therapy to patients suffering from genetic disease.

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ECE RISE SEMINAR SERIES: Trustworthy AI – Dr. Lydia Zakynthinou
2025-03-03 12:00 - 13:00 | 2534 Engineering Hall, 1415 Engineering Drive, Madison, Wisconsin, 53706, United States
2534 Engineering Hall

Algorithmic Stability for Trustworthy Machine Learning and Statistics

Abstract:Data-driven systems hold immense potential to positively impact society, but their reliability remains a challenge. Their outputs are often too brittle to changes in their training data, leaving them vulnerable to data poisoning attacks, prone to leaking sensitive information, or susceptible to overfitting. Establishing fundamental principles for designing algorithms that are both stable—to mitigate these risks—and efficient in their use of resources is essential for enabling trustworthy data-driven systems.In this talk, I will focus on statistical estimation under differential privacy—a rigorous framework that ensures data-driven system outputs do not reveal sensitive information about individuals in their input. I will present algorithmic techniques that take advantage of beneficial structure in the data to achieve optimal error for several multivariate tasks without requiring any prior information about the data, by building on robustness against data poisoning attacks. Lastly, I will highlight the deeper connection between differential privacy and robustness that underpins these results.

Bio:Lydia Zakynthinou is a FODSI postdoctoral research fellow in the Simons Institute for the Theory of Computing at UC Berkeley, hosted by Michael I. Jordan. She earned her Ph.D. in Computer Science from Northeastern University under the supervision of Jonathan Ullman and Huy Nguyen. Her research lies in trustworthy machine learning and statistics, with a focus on data privacy and generalization, and has been recognized with a Meta PhD fellowship and a Khoury PhD Research Award. She holds a diploma in Electrical and Computer Engineering from NTUA and a MSc in Logic, Algorithms, and Theory of Computation from NKUA in Greece.

ECE RISE SEMINAR SERIES: Trustworthy AI - Dr. Mahdi Haghifam
2025-03-05 12:00 - 13:00 | 4610 Engineering Hall, 1415 Engineering Drive, Madison, 53711
4610 Engineering Hall

The Interplay of Generalization, Memorization, and Privacy in Trustworthy Machine Learning

Abstract:Machine learning is transforming numerous aspects of modern society, and its increasing use in high-stakes applications necessitates responsible development. In this talk, I will present my research on the foundations and methodologies for building trustworthy ML, focusing on three interconnected challenges: generalization, memorization, and privacy. First, I will explore generalization: how can we ensure that ML models reliably predict on unseen data? I will discuss my work on developing novel information-theoretic measures to characterize and reason about generalization. Next, I will examine data memorization, showing how it can coexist with generalization and may even be necessary for accurate learning. Finally, I will focus on differential privacy, a rigorous framework for mitigating data memorization, and present my work on designing differentially private optimization algorithms. I will conclude by discussing key open questions in the area of trustworthy ML.

Mahdi Haghifam

Bio:Mahdi Haghifam is a Distinguished Postdoctoral Researcher at Khoury College of Computer Sciences, Northeastern University, hosted by Jonathan Ullman. He received his PhD from the University of Toronto and the Vector Institute, where he was advised by Daniel M. Roy. Mahdi’s research focuses on the foundations and algorithms of trustworthy machine learning, particularly in the areas of privacy, generalization, and memorization. During his PhD, he worked as a research intern at Google Brain and ServiceNow Research. His contributions have been recognized with a Best Paper Award at ICML 2024 and several fellowships from the University of Toronto.

BME Seminar Series: Arash Farhad, PhD
2025-03-06 12:00 - 13:00 | 2180 Mechanical Engineering, 1513 University Ave, Madison, WI, 53706, United States
Engineering multistate trackable cells for smart precision therapeutics

Arash Farhadi, PhDPostdoctoral ScholarVoigt LabMassachusetts Institute of Technology

Abstract:The engineering of immune cells and microbes into living therapeutics is emerging as a powerful approach for treating many diseases. However, two key challenges must be addressed to unlock the full potential of living therapeutics: intricately programming cells to perform diverse therapeutic tasks, and effectively monitoring them once administered to the body. My research provides the foundation to address these major challenges. In my presentation, I will outline how cells can be engineered to differentiate into multistate communities with distributed functions, using Synthetic Differentiation circuits. The biomolecular mechanism of Synthetic Differentiation circuits can be engineered to tune the community composition, expand the number of unique states, and replenish population imbalances in the community. I will highlight examples demonstrating the versatility of these circuits in applications spanning living therapeutics and agricultural biotechnology. Additionally, I will demonstrate noninvasive methods for tracking the location and function of cells deep in the body. Most methods to image cells rely on light, which has limited penetration depth. Conversely, ultrasound can image deep in tissue but lacks genetic reporters. I will introduce the first acoustic reporter genes (ARGs)—a ‘GFP’ for ultrasound—that enable imaging of cells and their gene expression inside the living, intact animal. Together, these technologies will enable next-generation living therapeutics capable of simultaneously targeting many disease hallmarks while providing real-time feedback to scientists and clinicians.

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ECE RISE SEMINAR SERIES: Trustworthy AI - Chulin Xie
2025-03-07 12:00 - 13:00
Via Zoom

Improving Trustworthiness in Foundation Models: Assessing, Mitigating, and Analyzing ML Risks

AbstractAs machine learning (ML) models continue to scale in size and capability, they expand the surface area for safety and privacy risks, raising concerns about model trustworthiness and responsible data use. My research uncovers and mitigates these risks. In this presentation, I will focus on the three cornerstones of trustworthy foundation models and agents: safety, privacy, and generalization. For safety, I will introduce our comprehensive benchmarks designed to evaluate trustworthiness risks in Large Language Models (LLMs) and LLM-based code agents. For privacy, I will present a solution for protecting data privacy with a synthetic text generation algorithm under differential privacy guarantees. The algorithm requires only LLMs inference API access without model training, enabling efficient safe text sharing. For generalization, I will introduce our study on the interplay between the memorization and generalization of LLMs in logical reasoning during the supervised fine-tuning (SFT) stage. Finally, I will conclude with my future research plan for assessing and improving trustworthiness in foundation model-powered ML systems.

Chulin Xie

BioChulin Xie is a PhD candidate in Computer Science at the University of Illinois Urbana-Champaign, advised by Professor Bo Li. Her research focuses on the principles and practices of trustworthy machine learning, addressing the safety, privacy, and generalization risks of Foundation Models, agents, and federated (distributed) learning. Her work was recognized by an Outstanding Paper Award at NeurIPS 2023, a Best Research Paper Finalist at VLDB 2024, and press coverage like The Verge and TechCrunch. She was a recipient of 2024 Rising Star in Machine Learning and IBM PhD Fellowship. During her PhD, she gained industry experience through research internships at NVIDIA, Microsoft, and Google.

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ECE RISE SEMINAR SERIES: Clean Energy Technologies - Dr. Dorsa Talebi
2025-03-12 12:00 - 13:00 | 4610 Engineering Hall, 1415 Engineering Drive, Madison, 53711
4610 Engineering Hall

Electrical Drive Systems: Lightweight and Scalable Propulsion for Aerospace and Sustainable Energy

Abstract:As AI and machine learning revolutionize software and computing, as our transportation is being electrified, global energy needs are growing dramatically. At the core of energy conversion and motion systems, electrical drive systems are the unsung heroes—powering everything from the wheels of electric cars to the propellers that lift air taxis into the sky to the emerging humanoid robots. This presentation will outline the developments to shape the next era of electric drive systems for air vehicle electrification and sustainable energy.Join this talk to explore how non-traditional axial flux machines are pushing the boundaries of electric powertrain technology, achieving an unprecedented 14.8 kW/kg power-to-mass ratio—nearly three times the state-of-the-art 5 kW/kg benchmark of commercial systems today. This breakthrough is made possible through amultidisciplinary integration of electric machine design, advanced thermal management, and next-generation manufacturing techniques, delivering over 94% efficiency at the takeoff for an aircraft flight profile and redefining what’s possible for electric transportation in the future.Beyond aviation, electrification of transportation presents new challenges, including geopolitical concerns surrounding rare-earth materials. This talk will introduce the development of rare-earth-free motors, a transformative step toward sustainable electrification—impacting not only traction motors but also renewable energy applications like wind turbine generators. This innovation builds upon conventional wound-field synchronous machines but eliminates the need for additional mechanical or electrical exciters. Instead, by leveraging existing stationary coil sets and systematic harmonic injection, the excitation magnetic field is generated on the rotor without the use of brushes or permanent magnets. This novel approach merges the fundamentals of conventional electric machines with a modern harmonic excitation approach and simple and robust rotating power electronics.The presentation will conclude with a summary of upcoming research trends and opportunities.

Bio:Dorsa Talebi earned her Ph.D. in Electrical and Computer Engineering from Texas A&M University in 2024 under the supervision of Prof. Toliyat. Her research focuses on advancing unconventional electric machine designs, with integrated cooling systems, particularly axial flux machines, to enable hyper-efficient,lightweight solutions for aircraft propulsion, drones, robotics, and more. During her graduate studies, Dorsa gained industry experience in powertrain R&D through internships at Tesla and Lucid Motors and co-invented a rare-earth-free electric machine, addressing material sustainability challenges while achieving high-performance electric drive systems for electric traction and renewable energy applications, supported by Texas A&M’s Advancing Discovery to Market (ADM) funding. Her expertise spans electric machine design and the multidisciplinary co-design of power electronic converter, thermal management systems, and structural components.Dorsa holds multiple issued U.S. patents and patent applications and has authored multiple papers published in various IEEE conferences and journals. Her achievements include several awards and scholarships, such as the Texas A&M Energy Institute Graduate Fellowship. Dorsa is currently a postdoctoral fellow at the Advanced Electrical Machines & Power Electronics (EMPE) Lab at Texas A&M University.

BME Seminar Series: Wei Qiu
2025-03-13 12:00 - 13:00 | 2188 Mechanical Engineering Building, 1513 University Avenue, Madison, WI, 53706, United States
Understanding Aging at Multi-scale Using Explainable AI

Wei QiuPhD CandidateComputer Science and Engineering DepartmentUniversity of Washington

Abstract:As human lifespans continue to extend, it becomes increasingly critical to understand the aging process not only to increase lifespan but also to enhance healthspan. This talk explores how Artificial Intelligence (AI), coupled with Explainable AI (XAI), can illuminate the complex mechanisms of aging at multiple scales, enhancing our ability to predict and explain these processes transparently.

First, I will introduce my work in AI for personalized health insights. I will present the ENABL Age framework, which integrates AI and XAI to provide precise and interpretable assessments of biological aging. This model not only estimates biological age but also explicates the factors contributing to aging, offering insights for personalized health strategies.

Second, I will discuss my AI innovations in omics data analysis, with a focus on cancer as an age-related disease. I have designed DeepProfile, which analyzes large-scale cancer datasets to identify key biomarkers and pathways, enhancing our approach to precision oncology. Additionally, I have developed StrastiveVI, which further isolates aging-related signals from single-cell transcriptomic data, revealing universal aging patterns and facilitating targeted anti-aging interventions.

Third, the discussion will turn to our pioneering work in the automated generation of plain language, democratizing access to complex biomedical findings and enhancing public health literacy. This work advances biomedical communication by enabling more comprehensible health-related information.

In conclusion, I will outline a vision for future directions in integrating transparent AI with aging research. This effort requires extensive collaboration across biology, clinical science, AI research, public health, and data science. Emphasizing a multidisciplinary approach, we aim to address the complex challenges associated with aging, paving the way for innovative solutions that not only enhance the precision but also the accessibility of healthcare.

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ISyE - Student lunch
2025-03-14 11:30 - 12:00
3121 Mechanical Engineering

Come have FREE LUNCH prior to hearing from Binil Starly, the Director for the ASU School of Manufacturing Systems and Networks as he speaks on ISyE Cyber-Manufacturing: Delivering Manufacturing Services Over Web 3.0. More information about Binil Starly and his presentation can be found here.

BME Seminar Series: Shalin Mehta, PhD
2025-03-17 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
Mapping cellular responses to perturbations with dynamic computational imaging and AI

Shalin Mehta, PhDPlatform LeaderComputational MicroscopyChan Zuckerberg Biohub

co-sponsors: Morgridge Institute for Research and the Center for Quantitative Cellular Imaging

Abstract:Discovery of biological mechanisms, drugs, and therapeutics is being accelerated by image-based profiling of cellular responses to perturbations. In this seminar, I will discuss our recent work on computational imaging to visualize the dynamic responses to perturbations and self-supervised learning to analyze the perturbations and responses.

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ECE Seminar Series in Advanced Semiconductor Materials and Devices - Dr. Kuangye Lu
2025-03-26 12:00 - 13:00 | 4610 Engineering Hall, 1415 Engineering Drive, Madison, 53711
4610 Engineering Hall

Seamless Monolithic 3D Heterogeneous Integration Enabled by Advanced Epitaxy

Abstract:Three-dimensional heterogeneous integration (3D heterointegration) is emerging as the leading approach to enhancing performance in the field of microelectronics. However, this method often relies on complex wafer-to-wafer bonding processes, which introduce alignment challenges and interfacial defects. Alternatively, heteroepitaxy offers another route for implementing 3D heterointegration but suffers from material degradation due to defects and strain caused by lattice and thermal mismatches.In this talk, I will introduce three new epitaxy paradigms designed to address the key limitations of current 3D heterointegration processes. First, I will discuss Remote Epitaxy, which enables wafer-scale exfoliation of ultra-thin membranes across a broad range of materials. By leveraging a 2D interlayer, these membranes can be transferred and monolithically 3D (M3D) integrated onto arbitrary substrates with ultra-high throughput and low cost, effectively addressing the challenges associated with wafer-to-wafer bonding. I will then present Remote Heteroepitaxy, a technique that significantly reduces defect density in heteroepitaxy utilizing strain relaxation mechanism at the 2D/3D interface. This advancement enhances materials quality and device performance over conventional heteroepitaxy, broadening opportunities for M3D heterointegration. Lastly, I will introduce single-crystal materials growth on amorphous substrates, which is made possible with a bold substrate design and carefully engineered materials growth conditions, offering an entirely new scheme of M3D heterointegration.Building on these epitaxy paradigms, I will demonstrate various novel (opto)electronic devices as examples of their applications, including fabrication of world’s smallest micro-LED pixels and accurate placement of laser coupons on photonic circuits (based on Remote Epitaxy), defect-free direct growth of III-V on silicon for next-generation transistor applications (based on Remote Heteroepitaxy), and advanced 3D stacking of 2D transistors (based on single-crystal materials growth on amorphous substrates). I will conclude the talk with a perspective on future materials development that could enable diverse innovations across advanced 3D logic/memory, XR, quantum information, and beyond, driven by new devices leveraging advancements in M3D heterointegration.

Kuangye Lu

Bio:Dr. Kuangye Lu is currently a Postdoctoral Associate at the Research Laboratory of Electronics, Massachusetts Institute of Technology (MIT). He earned his Ph.D. in Mechanical Engineering from MIT in 2023 under the supervision of Prof. Jeehwan Kim and received his B.S. with honors in Physics from Zhejiang University (ZJU) in 2018.His research focuses on the invention and development of advanced epitaxy techniques for compound semiconductor and 2D materials, as well as their heterointegration for device fabrication and applications, including monolithic 3D integration of high-quality III-V and III-N optoelectronic devices on silicon, transistors designed for next-generation advanced nodes, and reconfigurable AI chips.Dr. Lu has authored peer-reviewed articles in high-impact journals, including Nature, Nature Nanotechnology, and Nature Electronics. He is also the recipient of the Chu Ko-Chen Scholarship, the highest honor for graduates of ZJU, and the MIT Shangzhi Wu Fellowship. Additionally, Dr. Lu has served as a conference organizer of AEFM (Advanced Epitaxy of Freestanding Membranes and 2D Materials Conference) and a Review Editor for Frontiers in Energy Research. He is also a reviewer for various journals including Nature Chemical Engineering, Science Advances, and Nano Letters.

BME Seminar Series: Lori A. Setton, PhD
2025-03-31 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
The Death and Re-Birth of the Intervertebral Disc Cell

Lori A. Setton, PhDLopata Distinguished Professor and Chair of Biomedical EngineeringMcKelvey School of Engineering, Washington University in St. Louis

Corrine Bahr Memorial Lecture

Abstract:Intervertebral disc disorders are among the greatest contributors to pain and disability annually, such that low back pain and neck pain are ranked #1 and #4 for disease impact globally. Microenvironmental conditions for resident cells of the intervertebral disc contribute to an early decrease in cellularity, and associated tissue destruction, loss of hydration and eventual disc collapse or herniation. The most vulnerable of disc cells are the nucleus pulposus cells, derived from embryonic notochord, that are distinct from the neighboring mesenchymal cells that form the anulus fibrosus. Our laboratory has studied the micromechanical environment of these nucleus pulposus cells and factors that regulate nucleus pulposus cell phenotype and biosynthesis. We have demonstrated an ability to promote biosynthesis and survival by presenting key peptides and proteins to pathological nucleus pulposus cells, that replicate some features of notochordal development. We have also advanced knowledge of environmental cues that promote a healthy, biosynthetically active nucleus pulposus cell, and identified biomaterial strategies to restore a healthy environment for the pathological disc. This talk will review an understanding of the micromechanical environment and mechanobiology of the disc cells, and our work with engineering substrates and protein-conjugated biomaterials to promote matrix regeneration, cell differentiation and consequently cell “re-birth” in the intervertebral disc.

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About the Corrine Bahr Memorial Lecture Series:Corrine L. Bahr, born in Madison on February 23, 1949, dedicated 38 years of her career to the University of Wisconsin. She served as an administrator in the Biomedical Engineering Department within the Engineering Centers Building and passed away in 2007 following a courageous battle with cancer.

Corrine was actively involved in various organizations and causes, including the Bahai Faith, AFS Intercultural Programs, Inc., Supper Club for Ethnic and Racial Harmony, Middleton Historical Society, and the Good Neighbor Festival, where she served as a board member for more than 12 years.

In her memory, the family suggests that memorials be made instead of sending flowers to support cancer research, the University of Wisconsin Children’s Hospital, or a charitable organization of the donor’s choice. The “Corrine Bahr Memorial Lecture Series” was established in honor of her legacy. This series features speakers who discuss emerging technologies in the field of biomedical research.

BME Seminar Series: Daniel Gallego-Perez, PhD
2025-04-07 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
Nanotransfection-driven gene and cell therapies

Daniel Gallego-Perez, PhDEdgar C. Hendrickson Chair in Biomedical EngineeringProfessor, Surgery GeneralThe Ohio State University

Abstract:Gene and engineered cell therapies hold transformative potential for treating a wide range of conditions. However, current approaches face significant practical and translational challenges, including a heavy reliance on viral vectors and high variability, which often result in inefficient or unpredictable outcomes. To address these limitations, we developed a novel nanotechnology-based approach that enables deterministic cell (in vitro) or tissue nano-transfection (TNT) (in vivo) without the need for viral vectors. These platform technologies offer a minimally disruptive and non-viral solution, making them particularly suited for complex disease systems such as neurodegenerative conditions and metabolic disorders. Nano-transfection chips were manufactured from silicon or polymeric track etched membranes using cleanroom-based approaches, as described previously. These chips were then used to nanotransfect skin cells, in vitro or in vivo, with pro-vasculogenic or pro-adipogenic gene cocktails, which were then evaluated (for their therapeutic potential) in different murine models of neurodegenerative conditions, including ischemic stroke, and Alzheimer’s disease (AD), as well as models of metabolic dysfunction. Different molecular, histological, and functional outcomes studies were conducted to assess the extent to which these therapies mitigated disease burden in each model. In murine models of ischemic stroke, nanotransfected fibroblasts improved brain vascularization, perfusion, as well as neuroprotection and neuroregeneration in the motor cortex, which led to improved motor function. In murine models of AD, nanotransfected fibroblasts led to improved brain vascularization, perfusion, and reduced amyloid beta load. This also correlated with improved memory and cognitive function. Finally, in murine models of metabolic dysfunction, TNT-treated skin cells were successfully coopted to partially fulfill brown adipogenic functions, which led to improved weight control and cardiometabolic function. Overall, these findings highlight the potential of cell and tissue nano-transfection to drive therapeutic processes for restoring damaged or diseased tissue structure and function, paving the way for innovative treatments across diverse pathological conditions.

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BME Seminar Series: Alan Jassanof, PhD
2025-04-21 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
Analyzing Brain-Wide Function Using New Molecular Imaging Tools

Alan Jasanoff, PhDProfessor of Biological Engineering and Brain and Cognitive SciencesMassachusetts Institute of Technology

Abstract:Behavior and cognition depend on the integrated action of neural structures and populations distributed throughout the brain. Deciphering mechanisms by which this takes this place is both a tremendous scientific problem and a major engineering challenge, because of the need to establish suitable measurement technologies. We are creating a set of molecular imaging tools that enable multiregional neural processing to be studied at a brain-wide scale in rodents and nonhuman primates. Here we will describe how a novel genetically encoded activity reporter we have engineered enables information flow in virally labeled neural circuitry to be monitored by fMRI. Using the reporter to perform functional imaging of synaptically defined cell populations in the rat somatosensory system, we show how activity is transformed within brain regions to yield characteristics specific to distinct output projections. We also show how this approach enables regional activity phenomena to be modeled in terms of inputs, in a paradigm that we are extending to address circuit-level origins of functional specialization in marmoset brains. In the second part of the talk, we will discuss how some of our MRI tools now enable the detection of optical reporters in deep neural tissue. We use novel imaging probes to detect luminescent proteins, yielding a hybrid optical/MRI noninvasive imaging modality that surpasses limitations of conventional methods. This work demonstrates the possibility of investigating diverse brain-wide processing phenomena using advanced molecular neuroimaging methods.

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BME Seminar Series: Jessica Wagenseil, PhD
2025-04-28 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
Biomechanics of Thoracic Aortic Aneurysms

Jessica Wagenseil, DScProfessor, Mechanical Engineering and Materials ScienceVice Dean for Faculty AdvancementMcKelvey School of EngineeringWashington University

Abstract:Thoracic aortic aneurysms are a dilation of the aortic wall that can be asymptomatic for many years until they dissect or rupture. Dissection or rupture is associated with a high mortality rate. Surgical replacement is the current treatment standard and is performed when the aortic aneurysm reaches a specified size or growth rate. However, many aortic aneurysms fail before reaching these thresholds and many pass the thresholds without failing. We are interested in predicting how the aneurysm will grow, remodel, and fail in response to mechanical stimuli using mouse models of human aneurysmal disease. Data will be presented from our work on biomechanical metrics associated with aneurysms, correlations between mechanical changes and biochemical signaling, growth and remodeling predictions of aneurysm progression, fluid-solid structure interaction modeling of aneurysm biomechanics and failure, and transmural fluid and solid transport, as possible contributions to aneurysmal disease.

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ECE Research Seminar Series: Dr. Oliver Burrow
2025-07-28 11:00 - 12:00 | 2321 Engineering Hall, 1415 Engineering Drive, Madison, 53711
2321 Engineering Hall

Compact Cold-Atom Platforms Enabled by Grating MOTs and Progress to Real-World Quantum Sensing

Abstract:

Laser cooling of atoms is the first step in a wide range of atomic and molecular experiments, where low temperatures enable precision measurements. Traditionally, laser-cooling apparatus were large, often approaching room-scale, but over the past decade there have been concerted global efforts, including the UK’s Quantum Hubs initiative, to reduce their size, weight, power, and cost to enable the real-world deployment of quantum technologies.

The University of Strathclyde developed the grating magneto-optical trap (gMOT), which replaces the traditional six-beam MOT optical-geometry with a single input beam and a diffractive optic. This greatly reduces system complexity, eases miniaturisation, and provides a large solid angle of optical access. Typical Rb gMOTs trap >10⁷ atoms from vapour and achieve microkelvin temperatures. Recent advances at Strathclyde include gMOT atomic fountains, optical lattices with the gMOT optic as the reflector, and integration with sub-wavelength RF cavities, paving the way for compact atomic clocks with stabilities approaching 10⁻¹³ τ -1/2.

Another challenge is achieving compact vacuum systems suitable for laser cooling. In collaboration with industrial partners, we have created centilitre-scale ultra-high vacuum chambers with integrated gMOT optics, demonstrating long operational lifetimes without active pumping. When combined with packaged electronics and beam-launch optics, these become true cold-atom platform subsystems, requiring only a power supply and a fibre-coupled laser input.

These platforms are now being translated into field-ready quantum sensors through UK academic–industrial partnerships. Applications include compact atomic clocks (gClock) and hybrid classical–quantum inertial navigation systems, with initial sea trials planned for 2025.

Bio:

Oliver Burrow

Dr. Oliver Burrow is a Research Fellow in the University of Strathclyde’s Experimental Quantum Optics and Photonics Group. He completed his MPhys in Physics with Theoretical Physics at the University of Manchester in 2011 before moving to the University of Liverpool, where his studies were developing a prototype atom interferometer to probe the dark contents of the vacuum under the supervision of Dr Jon Coleman, earning his PhD in 2016. That research group has since become a founding member of the AION and MAGIS collaborations, which are developing cutting-edge atom interferometers for gravitational-wave detection.

Since joining Strathclyde in 2015, Dr. Burrow’s research has focused on developing compact components for laser cooling, with a strong emphasis on knowledge exchange and industrial collaboration. He has played a key role in advancing gMOT optics with Kelvin Nanotechnology and in developing centilitre-scale ultra-high vacuum gMOT systems with CPI-TMD. These technologies have become integral to next-generation quantum sensors in the UK, and he is now leading efforts at Strathclyde with industry to deploy these cold-atom platforms as core subsystems in practical quantum sensors.

Dr. Burrow’s visit is hosted by ECE Associate Professor Jennifer Choy, and ECE Antoine-Bascom Professor and Jack St. Clair Kilby Professor Mikhail Kats

ECE Research Seminar Series: Professor Carsten Ronning
2025-07-31 11:00 - 12:00 | 2321 Engineering Hall, 1415 Engineering Drive, Madison, 53711
2321 Engineering Hall

Ion beams for photonics and quantum technology

Abstract:

Ion beam technologies are today routine methods in electronic device manufacturing, e.g. the production of a modern processor needs 20-30 ion implantation steps. On the other hand, the 21 st Century is considered by many to be the century of light following a century of developments in electronics. Therefore, Ronning will present several experiments for the manipulation of the optical properties of (nano)materials using ion beams, as well as corresponding strategies for the realization of photonic and quantum devices.

Bio:

Carsten Ronning

Carsten Ronning is full professor and director of the Institute of Solid State Physics at the Friedrich Schiller University Jena, Germany. He studied physics at the Universities of Bremen and Konstanz, and completed his PhD thesis entitled “Diamond-like materials prepared via mass selected ion beam deposition” in 1996. After holding a post-doc position at the North Carolina State University (USA), he performed intense research at the University of Göttingen on thin films, semiconductor physics as well as on semiconductor nanowires. He moved to the Friedrich Schiller University Jena in 2008, where his group is today studying the synthesis, modification and characterization of nano-scale solids, where the optical properties of semiconductor nanowires and metasurfaces are in focus.

CBE Seminar Series: Harry Atwater
2025-09-09 16:00 - 17:00
Harry AtwaterDepartment of Applied Physics and Materials ScienceCalifornia Institute of TechnologyPasadena, California

Design of Materials and Devices for Carbon Dioxide Capture and Conversion using Sunlight

Over the next two decades, science advances will be needed to enable scalable technologies for i) direct capture of dilute CO2 at the gigaton scale as well as ii) CO2 reduction to fuels, chemicals, and materials, powered by renewable energy or directly by sunlight. I will discuss materials and device advances needed for a promising capture approach, a scalable energy-efficient route to direct ocean capture of CO2, via an electrochemical pH swing. This scheme utilizes bipolar membrane electrodialysis to create the pH swing required to capture CO2 drawn down into the ocean in the form of dissolved inorganic carbon. I will also explore approaches for directly generating liquid solar fuels from carbon dioxide, sunlight, water. This requires new photocatalysts and thermocatalytic structures to facilitate transfer of electrons, protons, and reactants, to selectively yield multi-carbon products at semiconductor photoelectrode surfaces and catalytic sites. Two tandem reaction schemes for liquid solar fuel generation from CO2 will be discussed: i) a three-terminal tandem photoelectrode with two monolithically integrated but distinct catalytic centers operating at independent potentials to yield products via a cascaded reaction sequence, and ii) a tandem photoelectrochemical/solar thermocatalytic cascade that uses electrochemically synthesized ethylene, carbon monoxide and hydrogen as intermediates to yield multi-carbon products (butene, hexene, and heavier hydrocarbons) synthesized via solar-driven thermocatalytic reactions.
