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Prof. Iris Bahar at the Wilson Lecture Series

Scalable ML Architectures for Real-time Energy-efficient Computing

Despite the strengths of convolutional neural networks (CNNs) for object recognition, these discriminative techniques have several shortcomings that leave them vulnerable to exploitation from adversaries. Discriminative-generative approaches offers a promising avenue for robust perception by combining inference by deep learning with sampling and probabilistic inference models to achieve robust and adaptive understanding. Our focus is on implementing a scalable, computationally efficient generative inference stage that can achieve real-time results in an energy efficient manner. In this talk, I will present our work on a discriminative-generative approach for pose estimation that offers high accuracy especially in unstructured and adversarial environments. I will then describe our hardware implementation of this algorithm to obtain real-time performance with high energy-efficiency and its implications for future directions in designing scalable and efficient ML algorithms.

About the speaker

R. Iris Bahar received the B.S. and M.S. degrees in computer engineering from the University of Illinois, Urbana, and the Ph.D. degree in electrical and computer engineering from the University of Colorado, Boulder. She recently joined the faculty at the Colorado School of Mines in January 2022 and serves at Department Head of Computer Science. Before joining Mines, she was on the faculty at Brown University since 1996 and held dual appointments as Professor of Engineering and Professor of Computer Science. Her research interests focus on energy-efficient and reliable computing, from the system level to device level. Most recently, this includes the design of robotic systems. She is the 2019 recipient of the Marie R. Pistilli Women in Engineering Achievement Award and the Brown University School of Engineering Award for Excellence in Teaching in Engineering. She is a fellow of the IEEE and a ACM Distinguished Scientist.

Prof. Jiarong Hong at the Wilson Lecture Series

Innovative Digital Inline Holography: from Flow Measurements to Cancer Diagnostics

Particles (e.g., dust, cells, droplets) with size ranging from nm to mm are ubiquitous in our daily life. To determine their properties in situ is vital for many applications. Here I will share with you our recent advancement in both the instrumentation and computational algorithms of digital inline holography (DIH) as a low cost and compact tool for 3D imaging of particles suspended in the flow. Enabled by such advancement, we have implemented DIH not only to study fundamental problems in the field of fluid dynamics, but also characterize particle properties and behaviors in agriculture, meteorology, medical sciences, microbiology, material sciences, etc. A number of such examples including measurements of wall-bounded turbulent flows, characterization of risks of airborne disease transmission, and detection of cancer cells in a blood stream will be provided.

Prof. Jiarong Hong is with the Department of Mechanical Engineering at the University of Minnesota Twin Cities

Professional & Academic Email Writing Workshop for UMN International Students

Student English Language Support (SELS) and Career Services are collaborating to help international students successfully navigate professional & academic email writing. In this interactive workshop, you will learn about professional email etiquette, appropriate language to use in professional/academic emails, and how to concisely write all parts of a professional or academic email. This is a hybrid workshop - with an in-person and online option. Please register to confirm your option, after registering you will receive the link.

Prof. Derya Aksaray at the Wilson Lecture Series

Reinforcement Learning for Dynamical Systems with Temporal Logic Specifications

Dynamical systems such as drones, mobile robots, or autonomous cars are envisioned to achieve complex specifications which may include spatial (e.g., regions of interest), temporal (e.g., time bounds), and logical (e.g., priority, dependency, concurrency among tasks) requirements. As specifications get more complex, encoding them via algebraic equations gets harder. Alternatively, such specifications can be compactly expressed using temporal logics (TL). In this talk, I will address the problem of learning optimal control policies for satisfying TL specifications in the face of uncertainty. Standard reinforcement learning (RL) algorithms are not directly applicable when the objective is to satisfy a TL specification. To overcome this limitation, I will formulate an approximate problem that can be solved via RL and present the suboptimality bound of the proposed solution. Then, I will discuss the scalability of learning with TL objectives and present a more tractable RL formulation.

About the speaker

Derya Aksaray is currently an Assistant Professor in the Department of Aerospace Engineering and Mechanics at the University of Minnesota (UMN). Before joining UMN, she held postdoctoral research positions at the Massachusetts Institute of Technology from 2016-2017 and at Boston University from 2014-2016. She received her Ph.D. degree in Aerospace Engineering from the Georgia Institute of Technology in 2014. Her research interests lie primarily in the areas of control theory, formal methods, and machine learning with applications to autonomous systems and aerial robotics.

Prof. Jin Zhou at the Wilson Lecture Series

Radio-Frequency Commutated Circuits for Future Wireless Systems

Wireless communications and sensing have become ubiquitous. With the proliferation of wireless technologies, however, the electromagnetic spectrum has become increasingly congested. The development of interference-resilient and broadband wireless systems has become one of the biggest hurdles moving forward. 

In this talk, I will demonstrate how to use radio-frequency (RF) commutated circuits to enable unique analog signal processing capabilities for future wireless transceivers. First, I will introduce a new class of reconfigurable RF filtering front-end that fuses acoustic filters into a commutated network. In a second example, I will show how a commutated circuit helps to achieve RF self-interference cancellation and analog-domain autonomous adaptation at the same time for full-duplex wireless. Finally, I will briefly touch upon commutated-inductor-capacitor broadband delay circuits for interference cancellation and beamforming. 

About the speaker

Jin Zhou received his Ph.D. in electrical engineering from Columbia University in 2017. Since 2017, he has been with the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign as an Assistant Professor. He was a recipient of the NSF CAREER award in 2021 and is a co-founder of the IEEE Solid-State Circuits Society central Illinois chapter. His research focuses on radio-frequency and mm-wave integrated circuits and systems for wireless applications.

Prof. Dionisios Margetis at the Wilson Lecture Series

Modeling homoepitaxial crystal growth: a tale of three scales

Epitaxial growth is a process in which a crystalline material is deposited on top of another one and takes on the crystalline orientation of the substrate. This talk addresses recent advances and challenges in answering the following question: How can one connect models of homoepitaxial growth or relaxation across distinct length scales? The models include: (i) atomistic master equations; (ii) nanoscale motion laws for line or point defects; and (iii) continuum laws for the surface height profile. Surface phenomena may exhibit an effective behavior dominated by microscale events. This talk will focus on these issues via selected examples.

About the speaker

Dio Margetis is a professor of Mathematics and the Institute for Physical Science and Technology at the University of Maryland, College Park. After receiving the Electrical Engineering Diploma from the National Technical University of Athens, he went on to Harvard for a PhD in applied physics. He carried out postdoctoral work at Harvard and MIT, and joined the faculty at the University of Maryland in 2006. He has been a full professor since 2012. He was a recipient of an NSF Career Award, two Research and Scholarship Awards, and Dean's Award for Excellence in Teaching at Maryland, and Dean's Prize for Excellence in Graduate Education by MIT. He was elected as an Ordway Distinguished Lecturer and Visitor at the University of Minnesota. His research focuses on epitaxial growth, plasmonics, and quantum dynamics with the emphasis on describing the connections between models across length and time scales, from the atomistic to the continuum.


Brains Live!

The Bell Museum presents Brains Live! You will hear from neuroscientist Dr. Manny Esguerra for this special Brain Awareness Week presentation. During the live event (from a lab at the University of Minnesota), Dr. Esguerra will show us a real human brain and discuss what the brain does, how it can trick you, and what parts of a brain do important jobs.

More details at the Bell Museum 

Professor Joseph S. Friedman at the Wilson Lecture Series

Spintronic Phenomena for Unconventional Computing Applications

The rich physics present in a wide range of spintronic materials and devices provide opportunities for a variety of computing applications. This presentation will describe four distinct proposals to leverage spintronic phenomena for reversible computing, neuromorphic computing, reservoir computing, and hardware security. The presentation will begin with an introduction to reversible computing, and the primary focus of this presentation will be on a solution for reversible computing in which magnetic skyrmions propagate and interact in a scalable system with the potential for energy dissipation below the Landauer limit. An approach for neuromorphic computing based on the stochastic switching of spin-transfer torque magnetic tunnel junctions (MTJs) will then be discussed, including results from the first experimental demonstration of a neuromorphic network with MTJ synapses. Next, a reservoir computing system will be described that efficiently leverages the dynamics of frustrated nanomagnets. This presentation will conclude with a logic locking paradigm based on nanomagnet logic, the first logic locking system that is secure against both physical and algorithmic attacks.

About the speaker

Joseph S. Friedman is an assistant professor of electrical and computer engineering at the University of Texas at Dallas and director of the NeuroSpinCompute Laboratory. He holds a Ph.D. and M.S. in electrical and computer engineering from Northwestern University and undergraduate degrees from Dartmouth College. He was previously a CNRS Research Associate with Université Paris-Saclay, a summer faculty fellow at the U.S. Air Force Research Laboratory, a visiting professor at Politecnico di Torino, a guest scientist at RWTH Aachen University, and worked on logic design automation at Intel Corporation. Friedman is a member of the editorial boards of IEEE Transactions on Nanotechnology and Microelectronics Journal, has been on the technical program committees of DAC, DATE, SPIE Spintronics, NANOARCH, GLSVLSI, VLSI-SoC, ICRC, NICE, ICECS, NMDC, and LASCAS, and the ISCAS and AICAS review committees. He has been a member of the organizing committee of NANOARCH, VLSI-SoC, and DCAS, is the vice-chair of the Dallas Chapter of the IEEE Electron Devices Society, and is the founder and chairperson of the Texas Symposium on Computing with Emerging Technologies (ComET). He has also been awarded the NSF CAREER award.

Prof. Matthew Lakin at the Wilson Lecture Series

Engineering molecules and cells for programmable biology

Programming the biological world is an important grand challenge for science and engineering. The fields of molecular computing and synthetic biology address this challenge by implementing computational functions using engineered biomolecules and engineered cells, respectively. The long-term goal of my research is to enable programmable control of biomolecular computing systems for use in practical applications for which micro-processors cannot be used, in particular, for biomedical diagnostics within living cells. This talk will outline three strands of research ongoing in my group: on computational tools and languages for biodesign, on DNA nanotechnology and molecular programming, and on synthetic biology and synthetic cells. The common thread tying these research directions together is the application of concepts and tools from computer science to experimental bioengineering.

About the speaker

Matthew Lakin is an Assistant Professor in the Computer Science Department at the University of New Mexico. He is also affiliated with the UNM Center for Biomedical Engineering and the Department of Chemical & Biological Engineering. Lakin obtained his Ph.D. in Computer Science from the University of Cambridge and was subsequently a postdoc at Microsoft Research. His work integrates computational and experimental work in DNA nanotechnology and synthetic biology to program biomolecular assemblies, cells, and synthetic cell-like systems. His long-term research goal is to apply biomolecular computing systems to address important societal challenges, with a particular focus on applications where regular computing devices cannot be deployed, such as the autonomous diagnosis and treatment of disease in living cells. Lakin received the NSF CAREER award in 2021.

International Student Virtual Career Fair Preparation Workshop 

Many UMN colleges will be hosting virtual internship and career fairs in February! These fairs are opportunities to connect with potential employers and learn more about their internship and career opportunities. Career Services and ISSS staff are arranging International Student Virtual Career Fair Preparation Workshops. You will learn what to expect at the fair, how to interact with employers, and what work authorization options are available to you. We hope to address any questions you might have. 

These virtual workshops will be held on Zoom, and a recording will be available later. All UMN International Students are welcome to join. We recommend attending one of the two available workshops. Use the Handshake link to learn more, and register via the Zoom link to join.

If you have questions, please email Jane, UMN International Career Consultant, at