Model-based Development and Assurance of Learning-enabled Cyber-Physical Systems

Compute-in-Memory: From Device Innovation to 3D System Integration

Digital PLLs: the Modern Timing Reference for Radar and Communication Systems

Transistors for 100-300GHz Wireless

Secretary of the Navy – Honorable Carlos Del Toro

NDIA Legislative Updates

Department of the Treasury OSDBU Director

Reliable Characterizations of NLP Systems as a Social Responsibility

Output-Lifted Learning Model Predictive Control

Robust Stability of Suboptimal Moving Horizon Estimation Using an Observer-Based Candidate Solution

Constraint-Adaptive MPC for Large-Scale Systems: Satisfying State Constraints without Imposing Them

Uncertainty Propagation by Linear Regression Kalman Filters for Stochastic NMPC

Offset-free Nonlinear Model Predictive Control by the Example of Maglev Vehicles

Thin Film Devices

Wide Bandgap Devices II

Cooperative Intelligent Transport Systems: Towards High-Level Automated Driving

Keynote

keynote

**Keynote Presentation 1:** Compute-in-Memory: From Device Innovation to 3D System Integration

**Keynote Speaker:** Shimeng Yu, Georgia Institute of Technology

**Session Chairs:** Louis Hutin, CEA-Leti;  Andreas Burg, École Polytechnique Fédérale de Lausanne

C1L-1: ESSDERC Keynote 1

**Keynote Presentation 1:** Digital PLLs: the Modern Timing Reference for Radar and Communication Systems

**Keynote Speaker:** Carlo Samori, Politecnico di Milano

**Session Chairs:**  Piero Andreani, Lund University; Piero Malcovati, University of Pavia

C2L-1: ESSCIRC Keynote 1

**Keynote Presentation 2:** Transistors for 100-300GHz Wireless

**Keynote Speaker:** Mark Rodwell, UC Santa Barbara

**Session Chairs:** Maud Vinet, Nadine Collaert

C1L-4: ESSDERC Keynote 2

The live session will happen on the Main Stage. Please click on the Main Stage button to watch the session. 

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**Date: **Wednesday, September 1st 
**Time: ** 11:15 AM - 11:45 AM PDT 

**Presenter: ** 
**Carlos Del Toro**, Secretary of the Navy 
![](https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/50ec15208b4aa9137d62e07d7d14a8bf.jpg) 
**Bio:** The Honorable Carlos Del Toro was sworn in as the 78th Secretary of the Navy August 9, 2021. As Secretary, he is responsible for over 900,000 Sailors, Marines, reservists, and civilian personnel and an annual budget exceeding $210 Billion. His priorities include securing the training and equipment successful naval operations demand and addressing the most pressing challenges confronting the US Navy and Marine Corps – China’s naval ambitions, climate instability, Covid’s ongoing impact, and strengthening a naval culture of inclusiveness and respect.

Born in Havana, Cuba, Del Toro immigrated to the U.S. with his family as refugees in 1962. Raised in the Hell’s Kitchen neighborhood of New York City, he attended public schools and received an appointment to the United States Naval Academy, where he earned a Bachelor of Science Degree in Electrical Engineering. Secretary Del Toro was commissioned as a Surface Warfare Officer upon his graduation in 1983.

His 22-year naval career included a series of critical appointments and numerous tours of duty at sea – including First Commanding Officer of the guided missile destroyer USS Bulkeley (DDG 84); Senior Executive Assistant to the Director for Program Analysis and Evaluation in the Office of the Secretary of Defense; and Special Assistant to the Director and Deputy Director of the Office of Management and Budget – where he helped manage the budgets of DOD, the U.S. Department of State, the Central Intelligence Agency, the Defense Intelligence Agency, the National Reconnaissance Office, and the Peace Corps.

After retiring at the rank of Commander, Secretary Del Toro founded SBG Technology Solutions, Inc. in 2004. As its CEO and President, he supported defense programs across a host of immediate and long-term Department of Navy issue areas, including shipbuilding, AI, cybersecurity, acquisition programs, space systems, health, and training.

He holds a Masters in National Security Studies from the Naval War College, a Masters in Space Systems Engineering from the Naval Postgraduate School, and a Masters in Legislative Affairs from George Washington University.

Secretary Del Toro and his wife have four children and a granddaughter.

The live session will happen on the Main Stage. Please click on the Main Stage button to watch the session. 

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**Date: **Wednesday, September 1st 
**Time: ** 8:10 AM - 8:45 AM PDT 

**Presenter: ** 
**Colonel Wesley Hallman, USAF (Ret)** 
Senior Vice President, Strategy & Policy 
National Defense Industrial Association 
![](https://s3.amazonaws.com/pf-upload-01/u-59356/0/2021-08-18/kf03qmf/wes_hallman_300.jpg) 
**Bio:** Wes Hallman became Senior Vice President of Strategy & Policy for the National Defense Industrial Association (NDIA) on October 10, 2017.

Wes came to NDIA after a 27-year career in the Air Force, last serving as the Chief Air Force Liaison to the House of Representatives responsible for advising the Secretary and Chief of Staff of the Air Force on engagement with Congress while working directly with members of the House of Representatives and their offices on Air Force and national security matters. Prior to his work with Congress, he was the senior executive assistant to the Joint Staff Director of Strategic Plans and Policy.

Wes served in several operational and staff positions, including commanding a squadron and a fighter group. He also led a staff of over 2,000 as Chief of Staff for the Air Force’s forward headquarters in the Middle East, simultaneously managing and supporting Air Force units conducting air operations over Iraq and Afghanistan. In 2004, he was selected as a White House Fellow, serving as the Secretary of Agriculture’s Special Assistant.

Wes is a Command Pilot with 1985 hours in the T-37, T-38, AT-38, F-15A/B/C/D, and F-22A, and has over 150 hours of combat time in support of Operations Southern Watch, Provide Comfort, and Northern Watch.

Wes is an Outstanding Graduate of the U.S. Air Force Academy. He also earned a Master’s Degree in International Relations from the Ohio State University and is a graduate of Air Command and Staff College, the School of Advanced Air and Space Studies, and the Industrial College of the Armed Forces (Eisenhower School). Wes also completed the State Department’s National Security Executive Leadership Seminar and the Air Force Enterprise Leadership Seminar at the Kenan-Flagler Business School.

The live session will happen on the Main Stage. Please click on the Main Stage button to watch the session. 

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**Date: **Wednesday, September 1st 
**Time: ** 10:05 AM - 10:55 AM PDT 

**Presenter: ** 
**Ms. Donna Ragucci**, Director for the U.S. Department of Treasury, Office of Small and Disadvantaged Business Utilization (OSDBU) 
![](https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/359b59abd8c8966a37c7d498426be1f4.jpg) 
**Bio:** Ms. Donna Ragucci serves as Director for the U.S. Department of Treasury, Office of Small and Disadvantaged Business Utilization (OSDBU) and assumed her duties in March 2018. She is responsible for Small Business Programs that include mission, compliance, outreach, and training for a 5,000 member organization obligating over $6.7 billion annually. Her office ensures compliance with the federally directed Category Management Initiative and meeting the Small Business Administration statutory socio-economic small business prime and subcontracting goals. Ms. Ragucci aligns best business practices with other OSDBUs throughout the federal government. In her tenure, her office received national recognition from the Service Disabled Veteran Owned Small Business Association and the National HUBZone Association. Her office is a Core Cluster member of the White House Initiatives Group on HBCUs, championing the awareness of and increasing federal contracting opportunities for HBCUs and the underserved communities and the White House Initiatives Group on Advancing Racial Equity in Federal Procurement. Ms. Ragucci also chairs the 93-member Federal OSDBU Council that assists SBA by influencing small business policy and legislation.

Ms. Ragucci’s held numerous leadership and public trust positions during her 35 years with the federal government. She was appointed to the Senior Executive Service in March 2018. She graduated from the Senior Service College in May 2015. Ms. Ragucci has a Bachelor of Science Degree in Business from Athens State University, and she earned a Master’s Degree in Human Resource Management from Florida Institute of Technology. 

Her awards include the Secretary of the Army Excellence in Contracting Award, Department of the Army Superior Civilian Service Award, Department of the Army Commander’s Award for Excellence, and three Department of the Army Achievement Medals for Civilian Service. Ms. Ragucci is a member to the Acquisition Corps. She holds federal certification Level III in Contracting, Level II in Purchasing, and Level II in Program Management.

Live Session will take place on the main stage. Please click on the main stage button below to join the session. 
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**Date: **Tuesday, 3 August 2021 
**Time: **15:30 UTC - 16:30 UTC 
**Session Chair: ** Fei Xia 
**Speaker: **Christopher Potts, Stanford University 

**[Christopher Potts recorded talk](https://drive.google.com/file/d/1CAzYdiPKLjb1nfEmkagwcn3tNk4DPZ6A/view?usp=sharing)
 [Christopher Potts speaker slides ](http://web.stanford.edu/~cgpotts/talks/potts-acl2021-slides-handout.pdf)**

**Title: **Reliable Characterizations of NLP Systems as a Social Responsibility 

**Abstract: **This is an incredible moment for NLP. We all routinely work with models whose capabilities
would have seemed like science fiction just two decades ago, powerful organizations eagerly await our
latest results, and NLP technologies are playing an increasingly large role in shaping our society. As
a result, all of us in the NLP community are likely to participate in research that will contribute (to
varying degrees and perhaps only indirectly) to technologies that will impact many people’s lives, with
both positive and negative consequences for example, technologies that broaden accessibility, enhance
creative self-expression, heighten surveillance, and create propaganda. What can we do to fulfill the
social responsibility that this brings? As a (very) partial answer to this question, I will review a number
of important recent developments, spanning many research groups, concerning dataset creation, model
introspection, and system assessment. Taken together, these ideas can help us more reliably characterize
how NLP systems will behave, and more reliably communicate this information to a wider range of
potential users. In this way, they can help us meet our obligations to the people whose lives are impacted
by the results of our research. 

**Bio: **Christopher Potts is Professor and Chair of Linguistics and Professor (by courtesy) of Computer
Science at Stanford, and a faculty member in the Stanford NLP Group and the Stanford AI Lab. His
group uses computational methods to explore how emotion is expressed in language and how linguistic
production and interpretation are influenced by the context of utterance. This research combines methods
from linguistics, cognitive psychology, and computer science, in the service of both scientific discovery
and technology development. He was previously Chief Scientist at Roam Analytics, a start-up focused
on applying NLP in healthcare and the life sciences (now Parexel AI Labs). He is a long-time Action
Editor at TACL, a frequent Area Chair at ACL conferences, and currently an Ethics Committee co-chair
for EMNLP 2021.

Keynote 3 # Speaker: Chris Potts

**Session Chair:** Gabriele Pannocchia
 **Authors:** Nair Siddharth 
**Paper link:** Please find my paper [**here**](https://drive.google.com/file/d/16gRM4npywgeqWKsgYYHwSXWljLErXpcA/view)
 
![](https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/5c6aa6320fe07a7045ba87a42947a740.png)

**Biography**:
 Siddharth Nair is a PhD candidate advised by Prof. Francesco Borrelli, in the Department of Mechanical Engineering at UC Berkeley. He graduated from IIT Bombay in 2018 with a Bachelor's and Master's degree in Aerospace Engineering. His research interests are Nonlinear Model Predictive Control, Convex Optimization and Hybrid Systems.

**Abstract**:
 We present a Learning MPC framework for a class of nonlinear systems that employs data-driven construction of continuous, convex terminal sets and terminal costs in the space of specific output sequences.

Keynote Session 3:  Output-Lifted Learning Model Predictive Control

**Session Chair:** Michal Kvasnica
 **Author:** Schiller Julian D. 
**Paper link:** Please find my paper [**here**](https://drive.google.com/file/d/1RleQCoKFG1kqUa61Cc113VcN_q29t4K3/view?usp=sharing) 

![](https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/71060124b16c399dd373994cb5920622.png)

**Biography:**
 Julian D. Schiller received his Master degree in Mechatronics from the Leibniz University Hannover, Germany, in 2019. Since then, he is a doctoral student at the Institute of Automatic Control at the Leibniz University Hannover under the supervision of Prof. Matthias A. Müller. His research interests are in the area of optimization-based state estimation and the control of nonlinear systems.

**Abstract:**
 In this talk, we propose a suboptimal moving horizon estimator for nonlinear systems. For the stability analysis we transfer the “feasibility-implies-stability/robustness” paradigm from model predictive control to the context of moving horizon estimation in the following sense: Using a suitably defined, feasible candidate solution based on the trajectory of an auxiliary observer, robust stability of the proposed suboptimal estimator is inherited independently of the horizon length and even if no optimization is performed.

Keynote Session 2: Robust Stability of Suboptimal Moving Horizon Estimation Using an Observer-Based Candidate Solution

**Session Chair:** Michal Kvasnica
 **Author:** Nouwens Sven 
**Paper link:** Please find my paper [**here**](https://drive.google.com/file/d/1l7fVrIJI5NnAjlPdst5A4B4Msw8-TIKw/view)


![](https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/d794bab3aa85a24e50d34305dc9cbf20.png)


 **Biography**:
 Sven Nouwens started his PhD reseach in March of 2020 in the Control Systems Technology group at the Technical University Eindhoven under the supervision of Maurice Heemels, Bram de Jager, and Maarten Paulides. His work focusses on enabeling MPC-based feedback control for hyperthermia cancer treatments. This subject motivated the research presented here.

**Abstract**:
 In this presentation, I cover the basic concepts used in our paper which enables real-time MPC for large scale system. To this end, the contraint selection/removal procedure is detailed and the requirements for recursive feasbility and constraint satisfaction are explained. Last, a simulation study is presented to visualize the ca-MPC scheme.

Keynote Session 2:  Constraint-Adaptive MPC for Large-Scale Systems: Satisfying State Constraints without Imposing Them

**Session Chair:** Martin Klaučo 
 **Author:** Quirynen Rien 
**Paper link:** Please find my paper [**here**](https://drive.google.com/file/d/1YVy9HmNjfGjoINqO0rHZirHut1l4XJgT/view)

![](https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/847f8bd43348aaf89e3e86b766c6ee1f.png)

**Biography**:
 Rien Quirynen received his PhD from KU Leuven and University of Freiburg in 2017, after which he joined MERL where he is currently a principal research scientist. His research focuses mainly on numerical optimization algorithms for planning and control of autonomous systems.

**Abstract**:
 Stochastic nonlinear model predictive control (SNMPC) allows to directly take model uncertainty into account, e.g., by including probabilistic chance constraints. This paper proposes linear-regression Kalman filtering to perform high-accuracy propagation of mean and covariance information for the nonlinear system dynamics in a tractable approximation of the stochastic optimal control problem. In addition, a tailored adjoint-based sequential quadratic programming (SQP) algorithm is presented to considerably reduce the computational cost and allow a real-time implementation of the resulting SNMPC. The prediction accuracy and control performance of the proposed approach are illustrated on a vehicle control application subject to external disturbances, while highlighting a worst-case computation time of 10 ms for SNMPC which is close to that of deterministic NMPC for this particular case study.

Keynote Session 1: Uncertainty Propagation by Linear Regression Kalman Filters for Stochastic NMPC

**Live Session**
 **Date and Time:** July 12, 16:00-16:30 (CEST)

**Ses Code:** MoKey1T1.2 
**Session Chair:** Martin Klaučo
 **Author:** Schmid Patrick 
**Paper link:** Please find my paper [**here**](https://drive.google.com/file/d/16cGOLnnDuuMrGUq4lYKG8UsBdAJFP3OS/view)

![](https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/250a50e8f7d4f774df72e60d311fc0a8.png)

**Biography**:
 Patrick Schmid received the B.Sc. and M.Sc. degrees in mechanical engineering from the University of Stuttgart, Stuttgart, Germany, in 2015 and 2018, respectively, where he is currently pursuing the Ph.D. degree with the Institute of Engineering and Computational Mechanics.

He is a member of the Research Staff at the Institute of Engineering
and Computational Mechanics, University of Stuttgart. His research interests include magnet modeling, control theory, and its application to high-speed Maglev vehicles, in particular model-based control methodologies such as model predictive control (MPC).


 **Abstract**:
 Offset-free action of model predictive control (MPC) for nonlinear systems with the number of measured outputs greater than controlled outputs is a nontrivial problem. Motivated by investigating the possible application of MPC for the control system of magnetic levitation (Maglev) vehicles -- tracking only the gap while measuring the gap, acceleration, and current -- for higher speeds than hitherto travelled, different possible offset-free nonlinear MPC strategies are reviewed and discussed.

Moreover, a novel approach based on a two-stage observer is introduced, requiring less effort to design an offset-free MPC. The different strategies are applied and analyzed in detail for a realistic model of the control system of the latest Transrapid vehicle, called TR09. Unlike usual offset-free MPC studies, the controller performance is also studied in a typical dynamic scenario, revealing the conflict and trade-off between the requirements for speed of command response and the robustness of closed-loop stability.

Keynote Session 1: Offset-free Nonlinear Model Predictive Control by the Example of Maglev Vehicles

(DRC) Session 8 - Thin Film Devices

(DRC) Session 9 - Wide Bandgap Devices II

Keynote Lectures

Physical Sciences, Engineering and Technology

Engineering

Aerospace Engineering

**Biomedical Engineering** is the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving, and decision making, driven by efforts to **improve human health**.