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Computer Engineering and Systems Group

Texas A&M University College of Engineering

Uncategorized

CESG Seminar – Sabit Ekin

Posted on January 24, 2023 by Vickie Winston

Friday, February 3, 2023
4:10 – 5:10 p.m. (CST)
ETB 1020  (Zoom option; Links and PW in syllabus or email)

Dr. Sabit Ekin
Associate Professor
Affiliate of Electrical and Computer Engineering
Department of Engineering Technology & Industrial Distribution
Texas A&M University

Title: “An Overview of Wireless Communication, Sensing and IoT Research Projects at Texas Wireless Lab (TWL)”

Talking Points

  • mmWave/Terahertz wireless communication systems for 5G, 6G and Beyond technologies
  • Hybrid RF/Optical communication system design
  • UAV-assisted wireless communications
  • Satellite and space communications

Abstract
Wireless communication and sensing constitute two of the most critical technological advances that broadly impact myriad aspects of the evolving digital society and support the burgeoning era of smart & connected communities and the Internet of Things (IoT). In this talk, I will provide an overview of our state-of-the-art research projects that tackles new fundamental scientific questions and addresses the challenges in three main synergistic research thrusts: (i) Wireless Communication, (ii) Wireless Sensing, and (iii) Wireless IoT. Example wireless communication technologies and applications include mmWave/Terahertz wireless communication systems for 5G, 6G and Beyond technologies to support the ever-increasing demand for higher data rates, UAV-assisted wireless communications, satellite and space communications. Wireless sensing projects include gesture recognition for human-computer interaction (HCI) applications and vital signs monitoring such as respiration, heart rate, and glucose level for healthcare applications. Finally, the projects on wireless IoT applications include remote control and monitoring applications such as livestock monitoring, soil monitoring, and localization.

Biography
Dr. Sabit Ekin is a wireless system design researcher and engineer. He received his Ph.D. in Electrical and Computer Engineering from Texas A&M University (TAMU) in 2012. In January 2023, he joined TAMU as an Associate Professor of Engineering Technology & Industrial Distribution, and Electrical & Computer Engineering (affiliated faculty).  He has 11+ years (post Ph.D.) of successful track records, including 4 years of industry experience as a Wireless System Engineer at Qualcomm Inc—a world leader in wireless technologies—where he has received numerous awards for his achievements on cellular modem designs for Apple, Samsung, Google, Nokia, etc. Prior to joining TAMU, he was an Assosciate Professor of ECE at Oklahoma State University, where he worked for 6 years. He was the Director/Co-founder of Oklahoma CubeSat Initiative (OKSat)—the first CubeSat program in the state of Oklahoma. He received the Department of Energy (DOE) 2022 Early Career Award—one of the 83 scientists selected from across the nation. He is awarded with OSU PSO/Albrecht Naeter Endowed Professor of ECE (2022), and Jack H. Graham Endowed Fellow of Engineering (2021). His research focuses on design and analysis of mmWave/Terahertz wireless communication systems for 5G-6G and Beyond technologies and wireless sensing systems.  His research is sponsored by major agencies, including NSF(5), NASA(2), DOE-CAREER(1), DOD(4), DOT(2), Qatar Foundation(1), and U.S. corporations(2).

More at www.sabitekin.com

More on CESG Seminars: HERE

Please join on Friday, 2/3/22 at 4:10 p.m. in ETB 1020.
Zoom option: Links and PW in syllabus or email announcement.

Filed Under: Uncategorized

Congratulations Dr. Hu!

Posted on January 13, 2023 by Vickie Winston

CESG’s Jiang Hu has a new publication: Machine Learning Applications in Electronic Design Automation by himself and Dr. Haoxing Ren.

This book covers a wide range of the latest research on ML applications in electronic design automation (EDA), including analysis and optimization of digital design, analysis and optimization of analog design, as well as functional verification, FPGA and system level designs, design for manufacturing, and design space exploration. The ML techniques covered in this book include classical ML, deep learning models such as convolutional neural networks, graph neural networks, generative adversarial networks and optimization methods such as reinforcement learning and Bayesian optimization.

More information at https://www.barnesandnoble.com/w/machine-learning-applications-in-electronic-design-automation-haoxing-ren/1141727406?ean=9783031130748

Filed Under: Front Page, News, People, Uncategorized

Dr. P.R. Kumar – IEEE Alexander Graham Bell Medal

Posted on February 17, 2022 by Vickie Winston

Dr. Kumar is the 2022 recipient of one of the Institute of Electrical and Electronics Engineers’ (IEEE) most prestigious honors — the IEEE Alexander Graham Bell Medal. It is the highest award by IEEE in communications and networking. Kumar was recognized for his seminal contributions to the modeling, analysis and design of wireless networks.

For more, go to https://engineering.tamu.edu/news/2021/12/kumar-awarded-institute-of-electrical-and-electronics-engineers-medal.html.

Congratulations Dr. Kumar!

Filed Under: Faculty, News

Dr. JV Rajendran – 2022 Young Investigator Award Recipients

Posted on February 17, 2022 by Vickie Winston

Dr. JV Rajendran has won the 2022 Young Investigator Award from the Office of Naval Research Science & Technology!

His research work is titled Steel Wool: Next-Generation Hardware Fuzzers and addresses the area of Cyber Security and Complex Software Systems.

Congratulations JV!

Filed Under: Faculty, News, Uncategorized

Best Paper Award – IEEE: Drs. Yasin and Rajendran

Posted on February 17, 2022 by Vickie Winston

Congratulations to former CESG Post-Doc Dr. Muhammad Yasin and Dr. JV Rajendran!  Their 2020 paper “Removal Attacks on Logic Locking and Camouflaging Techniques” won a Best Paper Award from the Computer Society Publications Board and IEEE Transactions on Emerging Topics in Computing.

 

Filed Under: Faculty, News, Uncategorized

Congratulations Dr. Karan Watson!

Posted on September 7, 2021 by Vickie Winston

Dr. Karan Watson, Regents Professor, was awarded the 2021 American Society for Engineering Education (ASEE) Lifetime Achievement Award in Engineering Education. Dr. Watson was recognized for her pioneering leadership and sustained contributions to education in the fields of engineering and engineering technology.

For the full article or a more in-depth look at her work, please visit: Texas A&M Engineering News and Dr. Watson’s Google Scholar Profile

Past Recipients
2012 Richard M. Felder
2014 James E. Stice
2015 Karl A. Smith
2016 Russ Pimmel
2018 James L. Melsa
2019 K.L. DeVries
2020 Don P. Giddens
2021  Karan L. Watson

Filed Under: Uncategorized

CESG Former Student Shiyan Hu Elected to European Academy of Sciences and Arts

Posted on June 7, 2021 by Paul Gratz

CESG former student, Shiyan Hu, who received his Ph.D. in Computer Engineering in 2008, has been elected as a Member for European Academy of Sciences and Arts for his significant contributions to Design, Optimization, and Security of Cyber-Physical Systems.

European Academy of Sciences and Arts currently has about 2,000 members, including 34 Nobel Prize Laureates, who are world leading scientists, artists, and practitioners of governance, with expertise ranging from Natural Sciences, Medicine, Technical & Environmental Sciences, Humanities, to Social Sciences. Academy members, who are dedicated to innovative research, international collaboration as well as the exchange and dissemination of knowledge, are elected based on their outstanding achievements.

Shiyan Hu is a professor and the Chair in Cyber-Physical System Security and Director of Cyber Security Academy at University of Southampton. He has published more than 150 refereed papers in the area of Cyber-Physical Systems, Cyber-Physical System Security, and VLSI Computer Aided Design, where most of his journal articles appeared in IEEE/ACM Transactions. He is an ACM Distinguished Speaker, an IEEE Systems Council Distinguished Lecturer, a recipient of the 2017 IEEE Computer Society TCSC Middle Career Researcher Award, and a recipient of the 2014 U.S. National Science Foundation CAREER Award. His publications have received distinctions such as the 2018 IEEE Systems Journal Best Paper Award, the 2017 Keynote Paper in IEEE Transactions on Computer-Aided Design, the Front Cover Paper in IEEE Transactions on Nanobioscience in March 2014, multiple Thomson Reuters ESI Highly Cited Papers/Hot Papers, etc. His ultra-fast slew buffering technique has been widely deployed in the industry for designing over 50 microprocessor and ASIC chips such as IBM flagship chips POWER 7 and 8.

He is a well-recognized international leader in his field. He is chairing the IEEE Technical Committee on Cyber-Physical Systems, leading IET Cyber-Physical Systems: Theory & Applications, and chaired the 2020 Editor-in-Chief Search Committee Chair for ACM TODAES. He has served as an Associate Edito

r for 5 IEEE/ACM Transactions such as IEEE TCAD, IEEE TII and ACM TCPS and as a Guest Editor for various IEEE/ACM journals such as Proceedings of the IEEE and IEEE Transactions on Computers. He is an Elected Member of the European Academy of Sciences and Arts, a Fellow of IET, and a Fellow of British Computer Society.

Shiyan Hu says: “I am delighted to be elected as a Member of European Academy of Sciences and Arts. It is a unique honor in recognition of my research accomplishments and international leadership in my research fields. After many years following my graduation, I still feel very grateful to the education I received from Texas A&M’s Computer Engineering Group and research experience with my Ph.D. advisor Professor Jiang Hu. These were pivotally helpful for me to contribute significantly to my fields.”

l

Filed Under: Uncategorized

Agricultural Blue Legacy Award

Posted on March 26, 2021 by Paul Gratz

Congratulations to Dr. Jiang Hu and team for receiving the Agricultural Blue Legacy Award this March.

They developed a center pivot automation and control system known as CPACS. This contributes to water conservation in the field of agriculture. To learn more, go to http://www.hpwd.org/newswire/2021/3/18/amarillo-water-management-team-honored.

The team is referred to as the “Amarillo Water Management Team” and includes:
Dr. Hongxin Kong, CEEN, PhD Graduate
Jianfeng Song, CEEN, PhD Candidate
Dr. Justin Sun, CEEN, PhD Graduate
Dr. Yanxiang Yang, CEEN, PhD Graduate
Dr. Jiang Hu, co-director of graduate programs in the Texas A&M Department of Electrical and omputer Engineering at College Station;
Dr. Gary Marek, U.S. Department of Agriculture-Agricultural Research Service agricultural engineer at Bushland;
Thomas Marek, AgriLife Research senior research engineer at Amarillo;
Dr. Dana Porter, Texas A&M AgriLife Extension Service program leader in the Department of Biological and Agricultural Engineering at Lubbock; and
Dr. Qingwu Xue, AgriLife Research crop stress physiologist at Amarillo.

Thank you Amarillo Water Management Team for improving our world with your projects!

 

Pic 1: Dr. Hongxin Kong
Pic 2: Dr. Jiang Hu & Dr. Yanxiang Yang
Pic 3: Dr. Hongxin Kong
Feature Pic: Yanxiang Yang, Thomas Marek & Justin Sun

Filed Under: Uncategorized

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CESG Seminar – Sabit Ekin

Posted on January 24, 2023 by Vickie Winston

Friday, February 3, 2023
4:10 – 5:10 p.m. (CST)
ETB 1020  (Zoom option; Links and PW in syllabus or email)

Dr. Sabit Ekin
Associate Professor
Affiliate of Electrical and Computer Engineering
Department of Engineering Technology & Industrial Distribution
Texas A&M University

Title: “An Overview of Wireless Communication, Sensing and IoT Research Projects at Texas Wireless Lab (TWL)”

Talking Points

  • mmWave/Terahertz wireless communication systems for 5G, 6G and Beyond technologies
  • Hybrid RF/Optical communication system design
  • UAV-assisted wireless communications
  • Satellite and space communications

Abstract
Wireless communication and sensing constitute two of the most critical technological advances that broadly impact myriad aspects of the evolving digital society and support the burgeoning era of smart & connected communities and the Internet of Things (IoT). In this talk, I will provide an overview of our state-of-the-art research projects that tackles new fundamental scientific questions and addresses the challenges in three main synergistic research thrusts: (i) Wireless Communication, (ii) Wireless Sensing, and (iii) Wireless IoT. Example wireless communication technologies and applications include mmWave/Terahertz wireless communication systems for 5G, 6G and Beyond technologies to support the ever-increasing demand for higher data rates, UAV-assisted wireless communications, satellite and space communications. Wireless sensing projects include gesture recognition for human-computer interaction (HCI) applications and vital signs monitoring such as respiration, heart rate, and glucose level for healthcare applications. Finally, the projects on wireless IoT applications include remote control and monitoring applications such as livestock monitoring, soil monitoring, and localization.

Biography
Dr. Sabit Ekin is a wireless system design researcher and engineer. He received his Ph.D. in Electrical and Computer Engineering from Texas A&M University (TAMU) in 2012. In January 2023, he joined TAMU as an Associate Professor of Engineering Technology & Industrial Distribution, and Electrical & Computer Engineering (affiliated faculty).  He has 11+ years (post Ph.D.) of successful track records, including 4 years of industry experience as a Wireless System Engineer at Qualcomm Inc—a world leader in wireless technologies—where he has received numerous awards for his achievements on cellular modem designs for Apple, Samsung, Google, Nokia, etc. Prior to joining TAMU, he was an Assosciate Professor of ECE at Oklahoma State University, where he worked for 6 years. He was the Director/Co-founder of Oklahoma CubeSat Initiative (OKSat)—the first CubeSat program in the state of Oklahoma. He received the Department of Energy (DOE) 2022 Early Career Award—one of the 83 scientists selected from across the nation. He is awarded with OSU PSO/Albrecht Naeter Endowed Professor of ECE (2022), and Jack H. Graham Endowed Fellow of Engineering (2021). His research focuses on design and analysis of mmWave/Terahertz wireless communication systems for 5G-6G and Beyond technologies and wireless sensing systems.  His research is sponsored by major agencies, including NSF(5), NASA(2), DOE-CAREER(1), DOD(4), DOT(2), Qatar Foundation(1), and U.S. corporations(2).

More at www.sabitekin.com

More on CESG Seminars: HERE

Please join on Friday, 2/3/22 at 4:10 p.m. in ETB 1020.
Zoom option: Links and PW in syllabus or email announcement.

Filed Under: Uncategorized

Congratulations Dr. Hu!

Posted on January 13, 2023 by Vickie Winston

CESG’s Jiang Hu has a new publication: Machine Learning Applications in Electronic Design Automation by himself and Dr. Haoxing Ren.

This book covers a wide range of the latest research on ML applications in electronic design automation (EDA), including analysis and optimization of digital design, analysis and optimization of analog design, as well as functional verification, FPGA and system level designs, design for manufacturing, and design space exploration. The ML techniques covered in this book include classical ML, deep learning models such as convolutional neural networks, graph neural networks, generative adversarial networks and optimization methods such as reinforcement learning and Bayesian optimization.

More information at https://www.barnesandnoble.com/w/machine-learning-applications-in-electronic-design-automation-haoxing-ren/1141727406?ean=9783031130748

Filed Under: Front Page, News, People, Uncategorized

Congratulations Fall 2022 Graduates!

Posted on December 12, 2022 by Vickie Winston

CESG is proud to announce our Fall 2022 graduates who are entering the world of industry and academia after unique times of online learning, masked classes, and other firsts that Texas A&M implemented until we reached the other side of such pandemic safety concerns.  We hope they will take with them the knowledge that:

  • they can reach their goals despite a changing environment,
  • the content studied gives them a strong foothold in their careers,
  • personal connections from classes, clubs, and faculty can be a long-term resource to them,
  • we are thankful to have had them in the Computer Engineering Systems Group of ECE at TAMU, and
  • the 6 Aggie Core Values are traditions of A&M that, when practiced, will serve them throughout their lives.

Congratulations Graduates!

Doctor of Philosophy
Dr. Caio Davi (Advisor: Braga-Neto)
Dr. Luke McHale (Advisors: Gratz & Sprintson)
Dr. Jingqing Wang (Advisor: Zhang)

Master of Engineering
Florence Johnson
Rishya Sankar Kumaran
Nhat Do Minh Nguyen
Jaspal Singh Nijjar
Nonetta Marie Pierre
Lingaraju Elavarthi Vasuraju
Wei Wei
Sai Suma Yallapragda

Master of Science
Kunal Bharathi
Sourav Dokania
Haroon Faisal
Sayan Ganguly
Chien-Peng Huang
Karanam Hemachandran
Ravi Pranjal
Ruiyu Qu
Niranjan Raghuraman
Rohith Ramanujam Kumar
Santwana
Alexander J. Staggs
Ting Wei Su
Sowmya Sree Thota

Commencement: Saturday, 12/17/22 @ 9 a.m. in Reed Arena

Filed Under: Uncategorized

CESG Seminar – Sanjay Shakkottai

Posted on November 2, 2022 by Vickie Winston

Friday, November 18, 2022
10:20 – 11:10 a.m. (CST)
Zoom (Links and PW in syllabus or email)

Dr. Sanjay Shakkottai
Professor, Department of Electrical and Computer Engineering
University of Texas at Austin

Title: “The Power of Adaptivity in Representation Learning: from Meta-Learning to Federated Learning”

Talking Points

  • Algorithms for multi-task learning that learn representation
  • Understanding the training dynamics of meta-learning and federated averaging with fine tuning

Abstract
A central problem in machine learning is as follows: How should we train models using data generated from a collection of clients/environments, if we know that these models will be deployed in a new and unseen environment? In the setting of few-shot learning, two prominent approaches are: (a) develop a modeling framework that is “primed” to adapt, such as Model Adaptive Meta Learning (MAML), or (b) develop a common model using federated learning (such as FedAvg), and then fine tune the model for the deployment environment. We study both these approaches in the multi-task linear representation setting. We show that the reason behind generalizability of the models in new environments trained through either of these approaches is that the dynamics of training induces the models to evolve toward the common data representation among the clients’ tasks. In both cases, the structure of the bi-level update at each iteration (an inner and outer update with MAML, and a local and global update with FedAvg) holds the key — the diversity among client data distributions are exploited via inner/local updates, and induces the outer/global updates to bring the representation closer to the ground-truth. In both these settings, these are the first results that formally show representation learning, and derive exponentially fast convergence to the ground-truth representation. Based on joint work with Liam Collins, Hamed Hassani, Aryan Mokhtari, and Sewoong Oh. Papers: https://arxiv.org/abs/2202.03483 , https://arxiv.org/abs/2205.13692

Biography
Dr. Sanjay Shakkottaireceived his Ph.D. from the ECE Department at the University of Illinois at Urbana-Champaign in 2002. He is with The University of Texas at Austin, where he is a Professor in the Department of Electrical and Computer Engineering, and holds the Cockrell Family Chair in Engineering #15. He received the NSF CAREER award in 2004 and was elected as an IEEE Fellow in 2014. He was a co-recipient of the IEEE Communications Society William R. Bennett Prize in 2021. He is currently the Editor in Chief of IEEE/ACM Transactions on Networking. His research interests lie at the intersection of algorithms for resource allocation, statistical learning and networks, with applications to wireless communication networks and online platforms.

Webpage to learn more about Dr. Shakkottai: HERE

More on CESG Seminars: HERE

Please join on Friday, 11/18/22 at 10:20 a.m. in ETB 1020.

Filed Under: Uncategorized

CESG Seminar – Mohammad Ghavamzadeh

Posted on October 28, 2022 by Vickie Winston

Friday, November 11, 2022
10:20 – 11:10 a.m. (CST)
Virtual via Zoom: https://tamu.zoom.us/j/93347193479 (password in emails or syllabus)

Dr.  Mohammad Ghavamzadeh
Senior Staff Research Scientist
Google

Title: “Mitigating the Risk Associated with Epistemic and Aleatory Uncertainties in MDPs”

Abstract
Prior work on safe reinforcement learning (RL) has studied risk-aversion to randomness in dynamics (aleatory) and to model uncertainty (epistemic) in isolation. We propose and analyze a new framework to jointly model the risk associated with epistemic and aleatory uncertainties in finite-horizon and discounted infinite-horizon MDPs. We call this framework that combines risk-averse and soft-robust methods RASR. We show that when the risk-aversion is defined using either the entropic value-at-risk (EVaR) or the entropic risk measure (ERM), the optimal policy in RASR can be computed efficiently using a new dynamic program formulation with a time-dependent risk level. As a result, the optimal risk-averse policies are deterministic but time-dependent, even in the infinite-horizon discounted setting. We also show that particular RASR objectives reduce to risk-averse RL with mean posterior transition probabilities. Our empirical results show that our new algorithms consistently mitigate uncertainty as measured by EVaR and other standard risk measures.

Biography 
Dr. Mohammad Ghavamzadeh received a Ph.D. degree from UMass Amherst in 2005. He was a postdoctoral fellow at UAlberta from 2005 to 2008. He was a permanent researcher at INRIA from 2008 to 2013. He was the recipient of the “INRIA award for scientific excellence” in 2011, and obtained his Habilitation in 2014. Since 2013, he has been a senior researcher at Adobe and FAIR, and now a senior staff research scientist at Google. He has published over 100 refereed papers in major machine learning, AI, and control journals and conferences. He has co-chaired more than 10 workshops and tutorials at NeurIPS, ICML, and AAAI. His research has been mainly focused on the areas of reinforcement learning, bandit algorithms, and recommendation systems.

More information on Dr. Ghavamzadeh can be found at
https://mohammadghavamzadeh.github.io/
https://scholar.google.ca/citations?user=Bo-wyrkAAAAJ&hl=en

More info. on past and future CESG Seminars at CESG Seminars (tamu.edu)

* Friday, 11/11/22 at 10:20 a.m. via Zoom *

Filed Under: Uncategorized

CESG Seminar – Alan Kuhnle

Posted on October 28, 2022 by Vickie Winston

Friday, November 4, 2022
10:20 – 11:10 a.m. (CST)
ETB 1020 – **In-person** (Zoom option; Links and PW in syllabus or email)

Dr. Alan Kuhnle
Assistant Professor, Computer Science and Engineering
Texas A&M University

Title: “Scalable and Learned Algorithms for Discrete Optimization”

Talking Points

  • Linear-time algorithms for subset selection problems
  • RL for learning local search algorithm

Abstract
In this talk, I present the work of the Optimization and Learning Systems Lab on the design of scalable algorithms for optimization problems on big data. In particular, I describe our work on linear-time, parallelizable algorithms for combinatorial optimization problems arising from online social networks. Finally, I give an overview of future directions of the lab, which include augmenting algorithms with learned components to improve practical performance; optimization with incomplete information; and submodular planning.

Biography
Dr. Alan Kuhnle is an Assistant Professor of Computer Science & Engineering at Texas A&M University, where he directs the Optimization and Learning Systems Lab. His work focuses on the design and analysis of scalable algorithms for ubiquitous combinatorial optimization problems arising in data science applications, such as vehicle routing and marketing on social networks. He is the recipient of the First Year Assistant Professor Award at Florida State University in 2020 and his work has led to 34 publications in leading academic journals and conferences. He has served on the program committee of machine learning conferences and is Associate Editor of Journal of Combinatorial Optimization.

Recent TAMU article on Dr. Kuhnle: HERE

More on CESG Seminars: HERE

Please join on Friday, 11/4/22 at 10:20 a.m. in ETB 1020.

Filed Under: Uncategorized

CESG Seminar: Dileep Kalathil

Posted on October 27, 2022 by Vickie Winston

Friday, October 28, 2022
10:20 – 11:10 a.m. (CST)
Virtual via Zoom: https://tamu.zoom.us/j/93347193479 (password in emails or syllabus)

Dr.  Dileep Kalathil
Assistant Professor in the Dept. of Electrical and Computer Engineering
Texas A&M University

Title: “Reinforcement Learning with Robustness and Safety Guarantees”

Talking Points
*How do we develop reinforcement learning algorithms that can overcome the simulation-to-reality gap?
*How do we develop reinforcement learning algorithms that maintain safety constraints during learning?

Abstract
Reinforcement Learning (RL) is the class of machine learning that addresses the problem of learning to control unknown dynamical systems. RL has achieved remarkable success recently in applications like playing games and robotics. However, most of these successes are limited to very structured or simulated environments. When applied to real-world systems, RL algorithms face two fundamental sources of fragility. First, the real-world system parameters can be very different from that of the nominal values used for training RL algorithms. Second, the control policy for any real-world system is required to maintain some necessary safety criteria to avoid undesirable outcomes. Most deep RL algorithms overlook these fundamental challenges which often results in learned policies that perform poorly in the real-world settings. In this talk, I will present two approaches to overcome these challenges. First, I will present an RL algorithm that is robust against the parameter mismatches between the simulation system and the real-world system. Second, I will discuss a safe RL algorithm to learn policies such that the frequency of visiting undesirable states and expensive actions satisfies the safety constraints. I will also briefly discuss some practical challenges due to the sparse reward feedback and the need for rapid real-time adaptation in real-world systems, and the approaches to overcome these challenges.
Robust RL papers: R-P1, R-P2, R-P3
Safe RL papers: S-P1, S-P2, S-P3, S-P4

Biography 
Dr. Dileep Kalathil  is an Assistant Professor in the Department of Electrical and Computer Engineering here at Texas A&M University (TAMU). His main research area is reinforcement learning theory and algorithms, and their applications in communication networks and power systems. Before joining TAMU, he was a postdoctoral researcher in the EECS department at UC Berkeley. He received his Ph.D. from University of Southern California (USC) in 2014, where he won the best Ph.D. Dissertation Prize in the Department of Electrical Engineering. He received his M. Tech. from IIT Madras, where he won the award for the best academic performance in the Electrical Engineering Department. He received the NSF CRII Award in 2019 and the NSF CAREER award in 2021. He is a senior member of IEEE.

More information on Dr. Kalathil can be found HERE.

More info. on past and future CESG Seminars at CESG Seminars (tamu.edu)

* Friday, 10/28/22 at 10:20 a.m. via Zoom *

Filed Under: Uncategorized

CESG Seminar – Dr. George Ligler

Posted on October 3, 2022 by Vickie Winston

Friday, October 7, 2022
10:20 – 11:10 a.m. (CST)
ETB 1020 – **In-person** (Zoom option; Links and PW in syllabus or email)

Dr. George T. Ligler
Professor, Multidisciplinary Engineering
Texas A&M University

Title: “Automatic Dependent Surveillance—Broadcast (ADS-B): A Major Aviation System’s Conception, Development, and Operational Implementation”

Talking Points

  • In order to be successful, computer systems engineers need to learn to work with the full set of project stakeholders.
  • The “best” technical solution to a problem is often not the one employed or that should be employed–broaden your view of he “trade space”!
  • Computer system engineers have the opportunity to constantly learn while being instrumental in “getting things done”.
  • We have a worldwide shortage of interdisciplinary computer systems engineers.

Abstract
ADS-B provides the largest improvement in air traffic surveillance since the advent of radar in the 1940’s. This presentation discusses the 27-year journey of the ADS-B System from concept development to operational implementation on over 100,000 aircraft in the U.S. National Airspace System alone. The role of interdisciplinary computer system engineering in the development and implementation of this high-impact system is highlighted.

Biography
Dr. George T. Ligler is a Professor and Dean’s Excellence Chair of Multidisciplinary Engineering at Texas A&M University. He is also the proprietor of GTL Associates, a consultancy which has provided systems integration/engineering and product management services in multiple fields to over 40 clients on three continents. An elected member of the U.S. National Academy of Engineering, Dr. Ligler is a member and past Chair of the Academy’s Section 12, Special Fields and Interdisciplinary Engineering.  With regard to aviation, he has served on one or more aviation standards development committees since 1992 and since 2005 has been the Co-Chair of RTCA Special Committee 159, Navigation Equipment Using the Global Navigation Satellite System (GNSS). He has been recognized with RTCA’s highest award, the Achievement Award, in 2006 and 2017 and was a co-recipient of the Air Traffic Control Association’s 2015 Chairman’s Citation Award of Merit to the NextGen Institute’s Equip 2020 Initiative for ADS-B.  Dr. Ligler has also participated in nine National Academies of Sciences, Engineering, and Medicine committees advising the Departments of Transportation, Treasury, and Commerce, and is a current member of the Academies’ Aeronautics and Space Engineering Board. He holds a doctorate in mathematics from the University of Oxford, with his studies supported by a Rhodes Scholarship.

Recent TAMU article on Dr. Ligler: HERE

More on CESG Seminars: HERE

Please join on Friday, 10/7/22 at 10:20 a.m. in ETB 1020.

 

Filed Under: Uncategorized

CESG Seminar – Bhuvana Krishnaswamy

Posted on September 30, 2022 by Vickie Winston

Friday, October 21, 2022
10:20 – 11:10 a.m. (CST)
Virtual via Zoom: https://tamu.zoom.us/j/93347193479 (password in emails or syllabus)

Dr.  Bhuvana Krishnaswamy
Assistant Professor in Electrical and Computer Engineering
University of Wisconsin-Madison

Title: “Scalability in Low Power Wide Area Networks”

Talking Points:
* Long range and low power requirements have contrasting demands on the network.
* Current LPWAN solutions do not satisfy the large-scale needs of practical deployments.

Abstract
Wireless data delivery over long distance is power consuming and challenging for large-scale deployments. Low-power wide area networks (LPWAN) are increasingly in need to develop wireless solutions that satisfy the following requirements (1) Increased battery life, (2) Longer communication range, (3) Large-Scale, and (4) Low-cost. Existing strategies for addressing low-power and long-range do not efficiently address all of these in a large-scale network. In this talk, the fundamental challenges in meeting the above needs of LPWANs will be identified. Collision resolution approaches to meet the demands of large-scale, commercially available LPWANs – LoRa – will be the focus of this talk.

Biography 
Dr. Bhuvana Krishnaswamy is an Assistant Professor in the Department of Electrical and Computer Engineering at University of Wisconsin-Madison. She obtained her MS and Ph.D. in from Georgia Institute of Technology. She is the recipient of NSF CAREER Award, N2Women Rising Star Award, and the Grainger Faculty Scholarship Award. Her research interests are in low-power wireless communication and its challenges in practical deployments. Additional details about her research and team can be found at https://uwconnect.ece.wisc.edu/

More information on Dr. Krishnaswamy can be found HERE.

More info. on past and future CESG Seminars at CESG Seminars (tamu.edu)

* Friday, 10/21/22 at 10:20 a.m. via Zoom *

Filed Under: Uncategorized

CESG Seminar – Aditya Mahajan

Posted on September 29, 2022 by Vickie Winston

Friday, October 14, 2022
10:20 – 11:10 a.m. (CST)
Virtual via Zoom: https://tamu.zoom.us/j/93347193479 (password in emails or syllabus)

Dr.  Aditya Mahajan,
Associate Professor in Electrical and Computer Engineering
McGill University – Montreal, Canada

Title: “Approximate Planning and Learning for Partially Observed Systems ”

Talking Points:
* Propose a theoretical framework–based on the fundamental notion of information state–for approximate planning and learning in partially observed systems.
* Define an approximate information state (AIS) and a corresponding approximate dynamic program (ADP).
* Bound the error in using the policy obtained by the solution of the AIS-based ADP.
* Develop RL algorithms based on these bounds and illustrate that they perform well in high-dimensional partially observed grid-world environments.

Abstract
Reinforcement learning (RL) provides a conceptual framework for designing agents which learn to act optimally in unknown environments. RL has been successfully used in various applications ranging from robotics, industrial automation, finance, healthcare, and natural language processing. The success of RL is based on a solid foundation of combining the theory of exact and approximate Markov decision processes (MDPs) with iterative algorithms that are guaranteed to learn an exact or approximate action-value function and/or an approximately optimal policy. However, for the most part, the research on RL theory is focused on systems with full state observations.

In various applications including robotics, finance, and healthcare, the agent only gets a partial observation of the state of the environment. In this talk, I will describe a new framework for approximate planning and learning for partially observed systems based on the notion of approximate information state. The talk will highlight the strong theoretical foundations of this framework, illustrate how many of the existing approximation results can be viewed as a special case of approximate information state, and provide empirical evidence which suggests that this approach works well in practice.

Joint work with Jayakumar Subramanian, Amit Sinha, Raihan Seraj, and Erfan Seyedsalehi

Biography 
Dr. Aditya Mahajan is Associate Professor of Electrical and Computer Engineering at McGill University, Montreal, Canada. He is affiliated with the McGill Center of Intelligent Machines (CIM), Montreal Institute of Learning Algorithms (Mila), and Group for research in decision analysis (GERAD). He received the B.Tech degree in Electrical Engineering from the Indian Institute of Technology, Kanpur, India in 2003 and the MS and PhD degrees in Electrical Engineering and Computer Science from the University of Michigan, Ann Arbor, USA in 2006 and 2008.

He is the recipient of the 2015 George Axelby Outstanding Paper Award, the 2016 NSERC Discovery Accelerator Award, the 2014 CDC Best Student Paper Award (as supervisor), and the 2016 NecSys Best Student Paper Award (as supervisor). His principal research interests are learning and control of decentralized stochastic system.

More information on Dr. Mahajan HERE.

More info. on past and future CESG Seminars at CESG Seminars (tamu.edu)

* Friday, 10/14/22 at 10:20 a.m. via Zoom *

 

 

Filed Under: Uncategorized

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