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DeFi and How Blockchain will Transform Financial Services: Tuesday, Nov 16
by Emily C. Lawrence 12 Nov '21

12 Nov '21

Speaker: ASIFF HIRJI, President of Figure and Former President and COO of Coinbase Title: DeFi and How Blockchain will Transform Financial Services Day: Tuesday, November 16, 2021 Time: 4:30 pm to 5:30 pm Location: Bowl A17 Julis Romo Rabinowitz Host: Princeton’s Bendheim Center for Finance, the Julis Rabinowitz Center for Public Policy & Finance, and the Center for Information Technology Policy Open to: Princeton University students, faculty and staff. Refreshments will be served. Event page: [ https://bcf.princeton.edu/events/defi-and-how-blockchain-will-transform-fin… | https://bcf.princeton.edu/events/defi-and-how-blockchain-will-transform-fin… ] Register here: [ https://econforms.princeton.edu/hirjirsvp/ | https://econforms.princeton.edu/hirjirsvp/ ] Abstract: Asiff Hirji, President of Figure Technologies and former President & COO of Coinbase and TD Ameritrade discusses how blockchain, and the DeFi movement, will transform financial services. Through the provision of an immutable ledger, public registry and real-time bilateral transaction settlement capability, the application of blockchain technology will meaningfully reduce the risk, cost and capital requirements associated with current financial systems and infrastructure as well as eliminate the need for most financial intermediaries. The implications for the financial industry will be profound, please join us to learn more. Bio: Asiff Hirji is President of Figure Technologies, Inc. (Figure™), a leader in transforming financial services through the power of blockchain technology. He recently served as President and COO of Coinbase where he grew the company to over $1 billion in revenue; launched new businesses; built out the management team and achieved an $8 billion valuation. Prior to Coinbase, Hirji was an Operating Partner with Andreesen Horowitz focused on helping their best companies scale faster. He previously served as President and COO of TD Ameritrade, growing that business 6x into the nation’s largest online broker. Hirji has also held senior leadership roles with TPG Capital, Saxo Bank, HP, and Bain Capital and has served on a number of public and private boards including Citrix and Advent Software.

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Nicholas Turner will present his FPO "Connectivity inference for petascale neural circuit reconstruction" on Wednesday, November17, 2021 at 4PM via zoom.
by jfarquer＠cs.princeton.edu 11 Nov '21

11 Nov '21

Nicholas Turner will present his FPO "Connectivity inference for petascale neural circuit reconstruction" on Wednesday, November 17, 2021 at 4PM via zoom. Zoom link: https://princeton.zoom.us/my/nlturner The members of his committee are as follows: Examiners: H. Sebastian Seung (Adviser), Jia Deng, Andreas Tolias (Baylor College of Medicine & Rice University) Readers: Barbara Engelhardt, R. Clay Reid (Allen Institute for Brain Science) A copy of his thesis is available upon request. Please email gradinfo(a)cs.princeton.edu <mailto:gradinfo@cs.princeton.edu> if you would like a copy of the thesis. Everyone is invited to attend the talk. Abstract follows below: The reconstruction of neural circuits from electron microscopy (EM) has great promise to improve our understanding of biological and artificial intelligence. Automated reconstruction systems designed to study EM image volumes have been used to process larger datasets in recent years. Most of this work has focused on the reconstruction of neuron morphology, while recent efforts have also produced systems that infer the synaptic connectivity between reconstructed cells. Here, we demonstrate developments of this approach through a series of analyses and technological improvements. First, we perform an analysis that is based solely on neuronal morphology in the mammalian retina. We develop statistical tests to validate potential cell types, helping shape our understanding of the information the retina sends to the brain. Next, we develop a machine learning approach for connectivity inference in large EM image volumes, and we apply this approach to help produce the largest connectivity map to date. We then analyze similar semi-automated reconstructions of mouse visual cortex to explore their value with current technology. The first finds that synapse density, mitochondrial density, and dendritic diameter correlate with one another within layer 2/3 cells of the mouse primary visual cortex. A separate analysis finds some evidence that synapse size follows a bimodal distribution, with potential implications for memory stability and neural network organization. Lastly, we build a basic prototype of a sparse inference engine to improve current morphology reconstructions by detecting errors in large EM volumes.

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Corey Sinnamon will present his Pre-FPO "Improved analysis of self-adjusting heaps" on Wednesday, November 17, 2021 at 11AM via Zoom
by jfarquer＠cs.princeton.edu 09 Nov '21

09 Nov '21

Corey Sinnamon will present his Pre-FPO "Improved analysis of self-adjusting heaps" on Wednesday, November 17, 2021 at 11AM via Zoom. Zoom link: https://princeton.zoom.us/my/sinnamon Committee: Examiners: Robert Tarjan (Advisor), Bernard Chazelle, and Maria Chudnovsky. Readers: Huacheng Yu and László Kozma (Freie Universität Berlin). All are welcome to attend the talk. Abstract: Improved analysis of self-adjusting heaps Heaps (priority queues) are a classic and well-studied class of data structures. Among these are self-adjusting heaps, those that take an implicit approach to managing the heap state and require little or no auxiliary data to operate. The pairing heap is the classic example of this, and yet its exact complexity remains unknown, despite decades of study and improved upper and lower bounds. Indeed, we know of no self-adjusting heap that matches the bounds commonly conjectured for pairing heaps. The recently-invented smooth heap is an excellent candidate for an optimal self-adjusting heap. We present analyses of pairing and smooth heaps and their variants, and the challenges that remain for determining their exact complexity.

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Princeton Wireless Distinguished Seminar Series: Shyam Gollakota, University of Washington - Wednesday, Oct 27
by Emily C. Lawrence 03 Nov '21

03 Nov '21

Princeton Wireless Distinguished Seminar Series Speaker : Shyam Gollakota, University of Washington Title : Creating the Internet of Biological and Bio-Inspired Things Day : Wednesday, October 27, 2021 Time : 12:20 pm Location : Online - Please register here: [ https://princeton.zoom.us/j/97984650886 | https://princeton.zoom.us/j/97984650886 ] Hosts : Yasaman Ghasempour and Kyle Jamieson Abstract : Living organisms can perform incredible feats. Plants like dandelions can disperse their seeds over a kilometer in the wind, and small insects like bumblebees can see, smell, communicate, and fly around the world, despite their tiny size. Enabling some of these capabilities for the Internet of things (IoT) and cyber-physical systems would be transformative for applications ranging from large-scale sensor deployments to micro-drones, biological tracking, and robotic implants. In this talk, I will explain how by taking an interdisciplinary approach spanning wireless communication, sensing, and biology, we can create programmable devices for the internet of biological and bio-inspired things. I will present the first battery-free wireless sensors, inspired by dandelion seeds, that can be dispersed by the wind to automate deployment of large-scale sensor networks. I will then discuss how integrating programmable wireless sensors with live animals like bumblebees can enable mobility for IoT devices, and how this technique has been used for real-world applications like tracking invasive "murder" hornets. Finally, I will present an energy-efficient insect-scale steerable vision system inspired by animal head motion that can ride on the back of a live beetle and enable tiny terrestrial robots to see. Bio : Shyam Gollakota is a Torode Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington. He works across multiple disciplines at the University including Computer Science, Electrical Engineering, Mechanical Engineering, biology and the School of Medicine. His work has led to three startups, Jeeva Wireless, Sound Life Sciences and Wavely Diagnostics, has been licensed by ResMed Inc and is in use by millions of users. His lab also worked closely with the Washington Department of Agriculture to wireless track the invasive "murder" hornets, which resulted in the destruction of the first nest in the United States. He is the recipient of a National Science Foundation Career Award, an Alfred P. Sloan Fellowship, the SIGMOBILE Rockstar award, ACM Grace Murray Hopper Award in 2020 and recently named as a Moore Inventor Fellow in 2021. He was also named in MIT Technology Review’s 35 Innovators Under 35, Popular Science ‘brilliant 10’ and twice to the Forbes’ 30 Under 30 list. His group’s research has earned Best Paper awards at MOBICOM, SIGCOMM, UbiComp, SenSys, NSDI and CHI, appeared in interdisciplinary journals like Science Translational Medicine, Science Robotics and Nature Digital Medicine as well as named as a MIT Technology Review Breakthrough technology of 2016 as well as Popular Science top innovations in 2015. He is an alumni of MIT (Ph.D., 2013, winner of ACM doctoral dissertation award) and IIT Madras.

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Lauren Pick will present her FPO "Scaling Automatic Modular Verification" on Tuesday, November 2, 2021 at 3PM at Friend 101 and via Zoom (revised)
by jfarquer＠cs.princeton.edu 29 Oct '21

29 Oct '21

Please note revised changes to include Zoom Link and Event Attendance Requirement: ---------------------------------------------------------------------------- -------------------------------------------- Lauren Pick will present her FPO "Scaling Automatic Modular Verification" on Tuesday, November 2, 2021 at 3PM at Friend 101 and via Zoom. Location: Friend 101 Zoom Link: https://princeton.zoom.us/j/98885075628 The members of Lauren's committee are as follows: Examiners: Aarti Gupta (Adviser), E. Lennart Beringer and Zachary Kincaid Readers: Andrew Appel and Grigory Fedyukovich (Florida State University) A copy of her thesis is available upon request. Please email gradinfo(a)cs.princeton.edu <mailto:gradinfo@cs.princeton.edu> if you would like a copy of the thesis. Everyone is invited to attend her talk. Please note: For in-person meetings on campus such as the FPO, it is required that all attendees complete an event attendance sheet attesting that they are fully vaccinated for COVID-19. A sample of the form is attached for your information. A copy of the form will be circulated and will need to be filled out by all in-person attendees prior to the start of the FPO. Abstract follows below: Automated software verification techniques, while widely successful, often suffer from scalability issues due to state-space explosion. In both automated and manual verification, modular approaches help scale verification by breaking verification problems into several easier-to-solve subproblems. These subproblems often involve discovering suitable invariants that can be used to help derive a proof that the entire system meets the desired specification. In this dissertation, I describe work toward developing modular automatic techniques for software verification in which such invariants are discovered automatically. These techniques notably involve exploiting the structure and syntax of both system components and/or their specifications in order to find useful invariants for scaling verification. I have developed techniques for several related kinds of verification problems: the verification of k-safety properties, the verification of safety properties for general single-threaded interprocedural programs, and the verification of information-flow security-a specific kind of 2-safety property. For each of these verification problems, I have implemented the developed techniques in a verification tool and compared the tool to existing state-of-the-art tools for solving the verification problem. Experimental results demonstrate that the developed techniques help scale verification over existing state-of-the-art and allow more verification problems to be solved automatically.

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Lauren Pick will present her FPO "Scaling Automatic Modular Verification" on Tuesday, November 2, 2021 at 3PM at Friend 101.
by jfarquer＠cs.princeton.edu 27 Oct '21

27 Oct '21

Lauren Pick will present her FPO "Scaling Automatic Modular Verification" on Tuesday, November 2, 2021 at 3PM at Friend 101. Location: Friend 101 The members of Lauren’s committee are as follows: Examiners: Aarti Gupta (Adviser), E. Lennart Beringer and Zachary Kincaid Readers: Andrew Appel and Grigory Fedyukovich (Florida State University) A copy of her thesis is available upon request. Please email gradinfo(a)cs.princeton.edu <mailto:gradinfo@cs.princeton.edu> if you would like a copy of the thesis. Everyone is invited to attend her talk. Abstract follows below: Automated software verification techniques, while widely successful, often suffer from scalability issues due to state-space explosion. In both automated and manual verification, modular approaches help scale verification by breaking verification problems into several easier-to-solve subproblems. These subproblems often involve discovering suitable invariants that can be used to help derive a proof that the entire system meets the desired specification. In this dissertation, I describe work toward developing modular automatic techniques for software verification in which such invariants are discovered automatically. These techniques notably involve exploiting the structure and syntax of both system components and/or their specifications in order to find useful invariants for scaling verification. I have developed techniques for several related kinds of verification problems: the verification of k-safety properties, the verification of safety properties for general single-threaded interprocedural programs, and the verification of information-flow security—a specific kind of 2-safety property. For each of these verification problems, I have implemented the developed techniques in a verification tool and compared the tool to existing state-of-the-art tools for solving the verification problem. Experimental results demonstrate that the developed techniques help scale verification over existing state-of-the-art and allow more verification problems to be solved automatically.

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Antonio Molina Lovett will present his General Exam "Modern Social Choice: Seeking Efficient and Strategy-Proof Voting Rules" on Thursday, October 28, 2021 at 3PM via Zoom.
by jfarquer＠cs.princeton.edu 26 Oct '21

26 Oct '21

Antonio Molina Lovett will present his General Exam "Modern Social Choice: Seeking Efficient and Strategy-Proof Voting Rules" on Thursday, October 28, 2021 at 3PM via Zoom. Zoom Link: https://princeton.zoom.us/j/93726975342?pwd=aHNhL2JjcFFFQitIZXJKVDlwTm1udz09 The members of his committee are as follows: Mark Braverman (adviser), Elad Hazan, Matt Weinberg Abstract and Reading List: https://www.dropbox.com/sh/1dqhj4zwgfzqlja/AABAJWhfUraWxV6cM6ZqOicHa?dl=0 Everyone is invited to attend the talk, and those faculty wishing to remain for the oral exam following are welcome to do so.

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12:20pm Wed Oct 27: Shyam Gollakota (UW) on "Creating the Internet of Biological and Bio-Inspired Things"
by Jennifer Rexford 18 Oct '21

18 Oct '21

> > > > > Princeton Wireless Distinguished Seminar Series > > Speaker: > Shyam Gollakota, University of Washington > Title: > Creating the Internet of Biological and Bio-Inspired Things > Day: > Wednesday, October 27, 2021 > Time: > 12:20 pm > Room: > Please register here <https://princeton.zoom.us/j/97984650886> > Host: > Yasaman Ghasempour and Kyle Jamieson > > Abstract: Living organisms can perform incredible feats. Plants like dandelions can disperse their seeds over a kilometer in the wind, and small insects like bumblebees can see, smell, communicate, and fly around the world, despite their tiny size. Enabling some of these capabilities for the Internet of things (IoT) and cyber-physical systems would be transformative for applications ranging from large-scale sensor deployments to micro-drones, biological tracking, and robotic implants. In this talk, I will explain how by taking an interdisciplinary approach spanning wireless communication, sensing, and biology, we can create programmable devices for the internet of biological and bio-inspired things. I will present the first battery-free wireless sensors, inspired by dandelion seeds, that can be dispersed by the wind to automate deployment of large-scale sensor networks. I will then discuss how integrating programmable wireless sensors with live animals like bumblebees can enable mobility for IoT devices, and how this technique has been used for real-world applications like tracking invasive "murder" hornets. Finally, I will present an energy-efficient insect-scale steerable vision system inspired by animal head motion that can ride on the back of a live beetle and enable tiny terrestrial robots to see. > > > Bio: Shyam Gollakota is a Torode Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington. He works across multiple disciplines at the University including Computer Science, Electrical Engineering, Mechanical Engineering, biology and the School of Medicine. His work has led to three startups, Jeeva Wireless, Sound Life Sciences and Wavely Diagnostics, has been licensed by ResMed Inc and is in use by millions of users. His lab also worked closely with the Washington Department of Agriculture to wireless track the invasive "murder" hornets, which resulted in the destruction of the first nest in the United States. He is the recipient of a National Science Foundation Career Award, an Alfred P. Sloan Fellowship, the SIGMOBILE Rockstar award, ACM Grace Murray Hopper Award in 2020 and recently named as a Moore Inventor Fellow in 2021. He was also named in MIT Technology Review’s 35 Innovators Under 35, Popular Science ‘brilliant 10’ and twice to the Forbes’ 30 Under 30 list. His group’s research has earned Best Paper awards at MOBICOM, SIGCOMM, UbiComp, SenSys, NSDI and CHI, appeared in interdisciplinary journals like Science Translational Medicine, Science Robotics and Nature Digital Medicine as well as named as a MIT Technology Review Breakthrough technology of 2016 as well as Popular Science top innovations in 2015. He is an alumni of MIT (Ph.D., 2013, winner of ACM doctoral dissertation award) and IIT Madras.

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Linda Cai will present her General Exam "99% Revenue with Constant Enhanced Competition " on Monday, October 25, 2021 at 11AM via Zoom.
by jfarquer＠cs.princeton.edu 18 Oct '21

18 Oct '21

Linda Cai will present her General Exam "99% Revenue with Constant Enhanced Competition" on Monday, October 25, 2021 at 11AM via Zoom. Zoom Link: https://princeton.zoom.us/j/5668379247 The members of her committee are as follows: Matt Weinberg (Adviser), Mark Braverman and Ran Raz. Abstract: https://docs.google.com/document/d/1U4p8tEL9ynuXDLrXiQx54ySO9Xb6uUh5VKWhuipM 5O0/edit?usp=sharing Reading List: https://docs.google.com/document/d/18FDkPcfi55p_ZI64aI1nxHIA2mazJMa0jKUNlX4D B1M/edit?usp=sharing Everyone is invited to attend the talk, and those faculty wishing to remain for the oral exam following are welcome to do so.

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CDH Machine Predictions Roundtable - October 26th @ 4:30PM via ZOOM
by jfarquer＠cs.princeton.edu 13 Oct '21

13 Oct '21

Machine Predictions and Synthetic Text: A Roundtable on Large Language Models in the Humanities Join us on October 26 at 4:30 pm Eastern on Zoom. All are welcome! Register <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=5ea4dcdfdb&e=477ba78033> here. Since it was published in March 2021, " <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=62f0a0984a&e=477ba78033> On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?" has sparked impassioned conversations on the unintended consequences and potential harms of prominent natural language processing (NLP) projects. While this groundbreaking paper has been influential in computer and data science-prompting reflection on the dangers of relying on poorly conceptualized and curated data-it is only beginning to be discussed by humanities scholars who use NLP methods in their research. For this roundtable, two co-authors of "Stochastic Parrots" will speak with three leading digital humanities scholars about the implications of the article for humanities research employing NLP methods. Together, they will discuss how the authors' attention to process (data gathering, documentation, standards) and ethics in AI can be turned to humanists creating data and models for the study of literature, history, and culture. Panelists * <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=eeed6fcdd7&e=477ba78033> Angelina McMillan-Major (University of Washington, Computational Linguistics) * <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=06f51e5a08&e=477ba78033> Gimena del Rio Riande (University of Buenos Aires, Romance Philology) * <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=561f9992ac&e=477ba78033> Lauren Klein (Emory University, English and Quantitative Theory & Methods) * <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=fe44cf7160&e=477ba78033> Margaret Mitchell (CEO & Research Scientist, Ethical AI LLC) * <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=c8a7a5c88d&e=477ba78033> Ted Underwood (University of Illinois, Information Sciences) Moderator * <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=1503ecd64f&e=477ba78033> Toma Tasovac (DARIAH-EU) This event is part of the <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=a7fa8b45cc&e=477ba78033> New Languages for NLP project, supported by the National Endowment for the Humanities, and is co-sponsored by the <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=2c6e71db2c&e=477ba78033> Center for Statistics and Machine Learning at Princeton and <https://princeton.us16.list-manage.com/track/click?u=a77a39541c9fc9c8b625cb 379&id=990b0d6c85&e=477ba78033> DARIAH-EU. Copyright C 2021 Center for Digital Humanities, All rights reserved. You are receiving this email because you opted in via our website. Our mailing address is: Center for Digital Humanities Firestone Library, Floor B Princeton University Princeton, Nj 08540 <https://princeton.us16.list-manage.com/vcard?u=a77a39541c9fc9c8b625cb379&id =3f268a40cb> Add us to your address book Want to change how you receive these emails? You can <https://princeton.us16.list-manage.com/profile?u=a77a39541c9fc9c8b625cb379& id=3f268a40cb&e=477ba78033&c=947498457e> update your preferences or <https://princeton.us16.list-manage.com/unsubscribe?u=a77a39541c9fc9c8b625cb 379&id=3f268a40cb&e=477ba78033&c=947498457e> unsubscribe from this list. <http://www.mailchimp.com/email-referral/?utm_source=freemium_newsletter&utm _medium=email&utm_campaign=referral_marketing&aid=a77a39541c9fc9c8b625cb379& afl=1> -- Grant Wythoff, PhD (he/him) Center for Digital Humanities Princeton University https://wythoff.net

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