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SUNMONTUEWEDTHUFRISAT
Events for February 23, 2024
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EiS Communications Hub Drop-In HoursFri, Feb 23, 2024 @ 10:00 AM - 01:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Viterbi Ph.D. students are invited to stop by the EiS Communications Hub for one-on-one instruction for their academic and professional communications tasks. All instruction is provided by Viterbi faculty at the Engineering in Society Program.
Location: Ronald Tutor Hall of Engineering (RTH) - 222A
Audiences: Viterbi Ph.D. Students
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home?authuser=0
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EiS Communications Hub Drop-In Hours
Fri, Feb 23, 2024 @ 10:00 AM - 01:00 PM
Engineering in Society Program
Student Activity
Drop-in hours for writing and speaking support for Viterbi Ph.D. students
Location: Ronald Tutor Hall of Engineering (RTH) - 222
Audiences: Everyone Is Invited
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home
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Alfred E. Mann Department of Biomedical Engineering
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Peter Chung, Ph.D., Robert D. Beyer Early Career Chair in the Natural Sciences and an assistant professor in the Department of Physics and Astronomy University of Southern California
Talk Title: Polymers and Parkinsons: Elucidating Protein Function through Soft Matter Paradigms and Techniques
Abstract: Despite being unequivocally linked to Parkinson’s disease, the function of alpha-synuclein remains unclear beyond transiently binding to the lipid membrane of synaptic vesicles (organelles filled with neurotransmitters). This is due, in part, to its intrinsically disordered nature; alpha-synuclein does not fold into a globular structure and instead behaves much like a biopolymer. While precluding traditional characterization methods, this makes alpha-synuclein incredibly amenable to investigation via a polymer physics framework. First, through purpose-designed membrane nanoparticles and advanced synchrotron X-ray methods I will demonstrate that alpha-synuclein binds to and collectively works to sterically-stabilize membrane surfaces, a biological manifestation of polyelectrolyte-stabilized colloids. I will then reconcile observed transient binding to synaptic vesicles by establishing that alpha-synuclein preferentially binds to osmotically-stressed membranes (a proxy for neurotransmitter-filled synaptic vesicles), a newly discovered biophysical function by which alpha-synuclein interrogates organelle contents. Utilizing these insights, I will contextualize alpha-synuclein as a guidepost that spatiotemporally directs non-equilibrium
Biography: Peter Chung is the Robert D. Beyer Early Career Chair in the Natural Sciences and an assistant professor in the Department of Physics and Astronomy at the University of Southern California. His research focuses on the intersection of intrinsically disordered proteins (especially those unequivocally linked to neurodegenerative disease) and soft matter physics, with the hope of understanding emergent phenomena associated with these proteins and repurposing them for basic science research and novel therapeutic approaches. Previously he was a Kadanoff-Rice Postdoctoral Fellow at the University of Chicago and earned his PhD from the University of California, Santa Barbara
Host: Eunji Chung
Location: Olin Hall of Engineering (OHE) - 100 B
Audiences: Everyone Is Invited
Contact: Carla Stanard
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CSC/CommNetS-MHI Seminar: Milad Siami
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milad Siami, Assistant Professor of Electrical and Computer Engineering | Northeastern University
Talk Title: Optimizing sparse interactions for control and sensing in complex networks
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
This presentation introduces innovative strategies for enhancing control and sensing in large- scale complex networks, with a focus on minimizing resource usage to improve system performance. We address the challenge of non-submodular sensor scheduling in large-scale linear time-varying dynamics, tackling combinatorial, non-convex, NP-hard tasks. Beginning with a simple greedy algorithm, we present an approximation bound based on submodularity and curvature concepts, showing its superiority over existing methods. Shifting to discrete-time autonomous vehicle platoons, we employ graph- theoretic principles for state feedback laws, analyzing stability conditions based on underlying graph properties and update cycles. We explore H2-based robustness, demonstrating the impact of network density and update cycles on system performance. Specifically, we show that denser networks (i.e., networks with more communication links) might require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communication links). Practical examples and results from simulations and experiments, including work with Quanser's Qlabs and Qcars, validate the effectiveness of our approaches, emphasizing strategic sensor scheduling and robust design in autonomous vehicle platoons.
Biography:
Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long- term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC. Dr. Siami's research primarily focuses on the structural/graphical underpinnings of large-scale
dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).
Host: Dr. Mihailo Jovanovic
More Info: https://csc.usc.edu/seminars/2024Spring/siami.html
More Information: 2024.02.23 Seminar - Milad Siami.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://csc.usc.edu/seminars/2024Spring/siami.html
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CSC/CommNetS-MHI Seminar: Milad Siami
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milad Siami, Assistant Professor of Electrical and Computer Engineering | Northeastern University
Talk Title: Optimizing sparse interactions for control and sensing in complex networks
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
This presentation introduces innovative strategies for enhancing control and sensing in large- scale complex networks, with a focus on minimizing resource usage to improve system performance. We address the challenge of non-submodular sensor scheduling in large-scale linear time-varying dynamics, tackling combinatorial, non-convex, NP-hard tasks. Beginning with a simple greedy algorithm, we present an approximation bound based on submodularity and curvature concepts, showing its superiority over existing methods. Shifting to discrete-time autonomous vehicle platoons, we employ graph- theoretic principles for state feedback laws, analyzing stability conditions based on underlying graph properties and update cycles. We explore H2-based robustness, demonstrating the impact of network density and update cycles on system performance. Specifically, we show that denser networks (i.e., networks with more communication links) might require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communication links). Practical examples and results from simulations and experiments, including work with Quanser's Qlabs and Qcars, validate the effectiveness of our approaches, emphasizing strategic sensor scheduling and robust design in autonomous vehicle platoons.
Biography:
Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long- term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC. Dr. Siami's research primarily focuses on the structural/graphical underpinnings of large-scale dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).
Host: Dr. Mihailo Jovanovic
More Info: https://csc.usc.edu/seminars/2024Spring/siami.html
More Information: 2024.02.23 Seminar - Milad Siami.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://csc.usc.edu/seminars/2024Spring/siami.html
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CSC/CommNetS-MHI Seminar: Milad Siami
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milad Siami, Assistant Professor of Electrical and Computer Engineering | Northeastern University
Talk Title: Optimizing sparse interactions for control and sensing in complex networks
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
This presentation introduces innovative strategies for enhancing control and sensing in large- scale complex networks, with a focus on minimizing resource usage to improve system performance. We address the challenge of non-submodular sensor scheduling in large-scale linear time-varying dynamics, tackling combinatorial, non-convex, NP-hard tasks. Beginning with a simple greedy algorithm, we present an approximation bound based on submodularity and curvature concepts, showing its superiority over existing methods. Shifting to discrete-time autonomous vehicle platoons, we employ graph- theoretic principles for state feedback laws, analyzing stability conditions based on underlying graph properties and update cycles. We explore H2-based robustness, demonstrating the impact of network density and update cycles on system performance. Specifically, we show that denser networks (i.e., networks with more communication links) might require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communication links). Practical examples and results from simulations and experiments, including work with Quanser's Qlabs and Qcars, validate the effectiveness of our approaches, emphasizing strategic sensor scheduling and robust design in autonomous vehicle platoons.
Biography:
Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long- term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC. Dr. Siami's research primarily focuses on the structural/graphical underpinnings of large-scale dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).
Host: Dr. Mihailo Jovanovic
More Information: 2024.02.23 Seminar - Milad Siami.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
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CSC/CommNetS-MHI Seminar: Milad Siami
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milad Siami, Assistant Professor of Electrical and Computer Engineering | Northeastern University
Talk Title: Optimizing sparse interactions for control and sensing in complex networks
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
This presentation introduces innovative strategies for enhancing control and sensing in large- scale complex networks, with a focus on minimizing resource usage to improve system performance. We address the challenge of non-submodular sensor scheduling in large-scale linear time-varying dynamics, tackling combinatorial, non-convex, NP-hard tasks. Beginning with a simple greedy algorithm, we present an approximation bound based on submodularity and curvature concepts, showing its superiority over existing methods. Shifting to discrete-time autonomous vehicle platoons, we employ graph- theoretic principles for state feedback laws, analyzing stability conditions based on underlying graph properties and update cycles. We explore H2-based robustness, demonstrating the impact of network density and update cycles on system performance. Specifically, we show that denser networks (i.e., networks with more communication links) might require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communication links). Practical examples and results from simulations and experiments, including work with Quanser's Qlabs and Qcars, validate the effectiveness of our approaches, emphasizing strategic sensor scheduling and robust design in autonomous vehicle platoons.
Biography:
Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long- term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC. Dr. Siami's research primarily focuses on the structural/graphical underpinnings of large-scale dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).
Host: Dr. Mihailo Jovanovic, mihailo@usc.edu
More Info: https://csc.usc.edu/seminars/2024Spring/siami.html
More Information: 2024.02.23 Seminar - Milad Siami.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://csc.usc.edu/seminars/2024Spring/siami.html
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CSC/CommNetS-MHI Seminar: Milad Siami
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milad Siami, Assistant Professor of Electrical and Computer Engineering | Northeastern University
Talk Title: Optimizing sparse interactions for control and sensing in complex networks
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
This presentation introduces innovative strategies for enhancing control and sensing in large- scale complex networks, with a focus on minimizing resource usage to improve system performance. We address the challenge of non-submodular sensor scheduling in large-scale linear time-varying dynamics, tackling combinatorial, non-convex, NP-hard tasks. Beginning with a simple greedy algorithm, we present an approximation bound based on submodularity and curvature concepts, showing its superiority over existing methods. Shifting to discrete-time autonomous vehicle platoons, we employ graph- theoretic principles for state feedback laws, analyzing stability conditions based on underlying graph properties and update cycles. We explore H2-based robustness, demonstrating the impact of network density and update cycles on system performance. Specifically, we show that denser networks (i.e., networks with more communication links) might require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communication links). Practical examples and results from simulations and experiments, including work with Quanser's Qlabs and Qcars, validate the effectiveness of our approaches, emphasizing strategic sensor scheduling and robust design in autonomous vehicle platoons.
Biography:
Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long- term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC. Dr. Siami's research primarily focuses on the structural/graphical underpinnings of large-scale dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).
Host: Dr. Mihailo Jovanovic, mihailo@usc.edu
More Info: https://csc.usc.edu/seminars/2024Spring/siami.html
More Information: 2024.02.23 Seminar - Milad Siami.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://csc.usc.edu/seminars/2024Spring/siami.html
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ECE Seminar
Fri, Feb 23, 2024 @ 03:30 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jorge F. Silva, PhD, Universidad de Chile
Talk Title: Information Theoretic Measures for Representation Learning
Abstract: Information-theoretic measures have been widely adopted for machine learning (ML) feature design. Inspired by this, we look at the relationship between information loss in the Shannon sense and the operation loss in the minimum probability of error (MPE) sense when considering a family of lossy representations (or encoders). In this talk, we introduce a series of results that show how adequate the adoption of mutual information (MI) is for predicting the operational quality of a representation in classification. Our findings support the observation that selecting/designing representations that capture informational sufficiency (IS) is appropriate for learning. However, we also show that this selection is rather conservative if the intended goal is achieving MPE in classification. We conclude by discussing the capacity of the information bottleneck (IB) method to achieve lossless prediction and the expressive power of digital encoders in ML.
Biography: Information-theoretic measures have been widely adopted for machine learning (ML) feature design. Inspired by this, we look at the relationship between information loss in the Shannon sense and the operation loss in the minimum probability of error (MPE) sense when considering a family of lossy representations (or encoders). In this talk, we introduce a series of results that show how adequate the adoption of mutual information (MI) is for predicting the operational quality of a representation in classification. Our findings support the observation that selecting/designing representations that capture informational sufficiency (IS) is appropriate for learning. However, we also show that this selection is rather conservative if the intended goal is achieving MPE in classification. We conclude by discussing the capacity of the information bottleneck (IB) method to achieve lossless prediction and the expressive power of digital encoders in ML.
Host: Dr. Eduardo Pavez
More Information: Jorge Silva Seminar 2.23.24.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gloria Halfacre
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KIUEL: L'Oreal Brandstorm Demo Day (National Engineers Day)
Fri, Feb 23, 2024 @ 06:00 PM - 09:00 PM
USC Viterbi School of Engineering
Receptions & Special Events
The competition finale hosted by the Society of Cosmetic Chemists and KIUEL. Follow KIUELâs Instagram for updates!
Location: Sign into EngageSC to View Location
Audiences:
Contact: Kevin Giang
Event Link: https://engage.usc.edu/viterbi/rsvp?id=395824
