- talks - lists.cs.princeton.edu

NextG Webinar: Minjie Chen, Nov 5 at 12pm
by Emily C. Lawrence 29 Oct '24

29 Oct '24

Princeton Faculty Spotlight Series Featured Faculty: Professor Minjie Chen Date: November 5, 2024 Time: 12:00 pm Speaker: Minjie Chen, Princeton University Registration: Participate remotely by visiting [ https://princeton.zoom.us/meeting/register/tJIsfuCqqTotGdKxqOkFvfDbjh6uEDNp… | this link ] WEBINAR Followed by Live Q&A/Discussion. Register [ https://princeton.zoom.us/meeting/register/tJIsfuCqqTotGdKxqOkFvfDbjh6uEDNp… | here ] . Minjie Chen is an Associate Professor of Electrical … [View More]

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ACEE Annual Meeting: Tuesday, Oct 29
by Emily C. Lawrence 25 Oct '24

25 Oct '24

Dear colleagues and friends: You are cordially invited to join us on October 29, Tuesday at Andlinger Center for Energy and the Environment 2024 Annual Meeting. This year we will focus on the synergy between Energy and AI. Registration Link: [ https://acee.princeton.edu/2024-annual-meeting/ | https://acee.princeton.edu/2024-annual-meeting/ ] The event is in-person only. Speaker Institutions - Academia: Princeton, Harvard, Clemson, NYU - Industry: Microsoft, Nvidia, … [View More]

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ECE Seminar: Nov. 1: Sudipto Chakraborty, IBM Research
by Emily C. Lawrence 25 Oct '24

25 Oct '24

Speaker: Sudipto Chakraborty, IBM Research Date: November 1, 2024 Time: 4:30 p.m. Location: B205 Engineering Quadrangle Hosts: Kaushik Sengupta Event Page: [ https://ece.princeton.edu/events/challenges-and-opportunities-ultra-low-pow… | https://ece.princeton.edu/events/challenges-and-opportunities-ultra-low-pow… ] Title: Challenges and Opportunities for Ultra-low Power Design for Quantum Computing Applications Abstract: This talk will cover practical challenges for cryogenic CMOS … [View More]

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NextG Distinguished Seminar Series: Arjuna Madanayake, NEW DATE Oct 31
by Emily C. Lawrence 24 Oct '24

24 Oct '24

NextG Distinguished Seminar Series Speaker: Arjuna Madanayake, Florida International University Day: October 31, 2024 Time: 10 :30 a m Location: B205 Engineering Quadrangle Hosts: Yasaman Ghasempour and Kaushik Sengupta Event Page: [ https://ece.princeton.edu/events/spectre-signal-processing-efficient-comput… | https://ece.princeton.edu/events/spectre-signal-processing-efficient-comput… ] Title: SPECTRE: Signal Processing with Efficient Compute for Transmit and Receive Environments … [View More]Abstract: Wideband radio frequency (RF) array processors form an integral building block of modern wireless communications, location, sensing, and electronic warfare systems. There is interest in multifunctional and frequency agile antenna arrays with fully digital beam processing and machine learning (ML) algorithms at the backend that operate across a wide span of frequencies starting from VHF/UHF up to mm-waves and even sub-THz ranges. Digital signal processing (DSP) across massive bandwidths – today up to about 30 GHz for some sub-THz applications – requires careful consideration of multiple design constraints. Most array DSP operations consist of typical functions, such as discrete Fourier transforms (DFTs), finite impulse response (FIR) filters, cross-correlators, multiply-accumulators, and linear algebra (LA) functions like matrix inversion. Arithmetic complexity of basic DSP algorithms must be carefully factored into their design. A classic example is the use of sparse matrix factorizations on the DFT matrix leading to the suite of fast algorithms known as Fast Fourier Transforms (FFTs) of which the most famous is the Cooley-Tukey FFT invented at Princeton and IBM. The claim to fame for the FFT is its enormously useful factorizations having low arithmetic complexity at O(N log2 N), which is tiny compared to the case of the DFT. The DFT is computed brute-force at arithmetic complexity O(N2) where N is the number of points used. The theoretical lower bounds of DFT complexity have been rigorously proven decades in the past by Heideman and Burrus. Luckily, we can get around these bounds via a sequence of approximations. We achieve O(N) complexity for FFT-like operations by recognizing how real-world RF systems have multiple sources of error. The theoretical complexity bounds of the DFT could be circumvented by computing judiciously tailored low-complexity DFT matrix approximations capable of closely preserving mathematical properties of the exact DFT. In this talk, we discuss the use of approximate DFTs (ADFT) with corresponding sparse factorizations that are free of multiplications. The author and his collaborator RJ Cintra have developed an approach for superfast wideband RF signal processing for FFT applications, including multi-beam spacetime orthogonal beamforming, orthogonal frequency division multiplexing (OFDM) and maximally-decimated uniform-DFT polyphase FIR filterbanks, that replace O(N log2 N) FFTs of Cooley-Tukey fame with factorized ADFTs that are within 2 dB of performance of exact DFT but show much lower arithmetic complexity at just O(N). This extra log2 N reduction beyond what is possible from FFTs – which of course comes at a small price – has massive benefits in both chip area and power consumption for many wideband RF systems. In this talk, the author discusses our recent DARPA, ONR, and NSF funded research activities surrounding low-complexity low-power DSP for real-world RF multi-beam beamforming, low-SWaP spatio-temporal multidimensional spectrum sensing, and low-complexity adaptive digital null-forming using Howells-Applebaum adaptive arrays that make use of the O(N) ADFTs. The talk covers the basic mathematical theory, algorithms, RF/microwave systems, digital compute and FPGA/RF-SoC and chiplet based CMOS realizations underway at Florida International University. Bio: Arjuna Madanayake is an Associate Professor of Electrical and Computer Engineering at Florida International University (FIU), Miami, Florida. He runs the RAND Lab which has 15 PhD students at present. His area of specialization is multidimensional systems and signal processing. Dr. Madanayake’s wider research interests span one- and multi-dimensional signal processing and filter design (both analog and digital), RF/microwave systems, analog-CMOS and analog computer architecture, digital systems and FPGA/RF-SoC systems, fast algorithms and digital ASIC, digital hardware based ``software defined’’ radios, electromagnetics and sub-THz nearfield processing, wireless communications, 5G/6G and mm-wave systems, spectrum, RF artificial intelligence and machine learning (AI/ML) and semiconductor technologies. [View Less]

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PPH Seminar: “AI in Medical Care: Deus or Machina?” TODAY at 12pm
by Emily C. Lawrence 18 Oct '24

18 Oct '24

Please join the Princeton Precision Health (PPH) Initiative for the next talk of our fall semester series on Friday, October 18, at 12:00 pm, at 252 Nassau Street. William Hanson, MD, Chief Medical Information Officer and Vice President, Hospital of the University of Pennsylvania, will present a talk, “AI in Medical Care: Deus or Machina?” Abstract: In the last 20 years, spurred by governmental incentives (American Recovery and Reinvestment) the digitization of devices and widespread … [View More]

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Matthew Weaver will present his FPO "Bicubical Directed Type Theory" on October 31, 2024 at 11am in CS 301.
by Gradinfo 17 Oct '24

17 Oct '24

Matthew Weaver will present his FPO "Bicubical Directed Type Theory" on October 31, 2024 at 11am in CS 301. The members of his committee are as follows: Andrew Appel (Advisor) Daniel Licata (Advisor/Wesleyan University) Zachary Kincaid (Reader) David Walker (Examiner) Aarti Gupta (Examiner) Title: Bicubical Directed Type Theory Directed type theory is an analogue of homotopy type theory where types represent categories, generalizing groupoids. A classical, bisimplicial approach to … [View More]directed type theory, developed by Riehl and Shulman, is based on equipping each type with both a notion of path and a separate notion of directed morphism. In this setting, a directed analogue of the univalence axiom asserts that there is a universe of covariant discrete fibrations whose directed morphisms correspond to functions—a higher-categorical analogue of the category of sets and functions. While this approach suffices for formalizing mathematics, for applications to computer science we would like a computational interpretation of directed type theory. In this thesis we give a constructive model of a directed type theory with directed univalence in bicubical sets. We formalize much of this in Agda following the approach of Orton and Pitts. First, building on the cubical techniques used to give computational models of homotopy type theory, we show that there is a universe of covariant discrete fibrations with a partial directed univalence principle asserting that functions are a retract of morphisms in this universe. To complete this retraction into an equivalence, we refine the model using Coquand, Ruch, and Sattler’s work on constructive sheaf models. We introduce the cobar modality and by restricting to fibrant types that are also cobar modal, we are able to complete our construction of directed univalence. We then describe a generalization of the fibrant Riehl-Shulman extension types. We prove this in the setting of an arbitrary presheaf category with respect to a new notion of fibrancy that is given by a generic filling problem. This abstraction is general enough to capture all of the current presheaf models of type theories and their classifications of types specified by filling problems. In addition, this result extends the potential syntax of these type theories to be able to internally express any of these filling problems as fibrant types. We use this to then define a type theory in which the user can internally define classifying universes for any such filling problem. Lastly, we overview our implementation of bicubical directed type theory. [View Less]

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NextG Webinar: Maria Apostolaki, Oct 22 at 12pm
by Emily C. Lawrence 15 Oct '24

15 Oct '24

Faculty Spotlight Series Featured Faculty: Professor Maria Apostolaki Date: October 22, 2024 Time: 12:00 pm Speaker; Maria Apostolaki, Princeton University Registration: Participate remotely by visiting [ https://princeton.zoom.us/meeting/register/tJYucOGqrD4oGdU6LE3hruA8tNc_RD3J… | this link ] Maria Apostolaki is an Assistant Professor of Electrical and Computer Engineering at Princeton University. Her research draws from networking, security, and machine learning. Overall, her goal is to … [View More]

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PPH Seminar Fri Oct 18 “AI in Medical Care: Deus or Machina?” William Hanson, MD / Registration open for Nov 7 PPH-NOAA health & climate symposium
by Emily C. Lawrence 14 Oct '24

14 Oct '24

Please join the Princeton Precision Health (PPH) Initiative for the next talk of our fall semester series on Friday, October 18, at 12:00 pm, at 252 Nassau Street. William Hanson, MD, Chief Medical Information Officer and Vice President, Hospital of the University of Pennsylvania, will present a talk, “AI in Medical Care: Deus or Machina?” Abstract: In the last 20 years, spurred by governmental incentives (American Recovery and Reinvestment) the digitization of devices and widespread … [View More]adoption of electronic record keeping systems has transformed medical care for better (and some would argue for worse). Medical care and research has spawned the development of vast troves of digitized clinical and research data. Medical information flows through countless visible and invisible conduits, and has become the new oil, coveted by large companies, research initiatives and governments. This talk will describe the digitization of medicine, the players, the intended and unintended consequences and the potential benefits of AI and precision medicine. It will offer a perspective on what has gone right, what wrong and what entities like Princeton Precision Health can bring to the table. Lunch will be provided. Please note that getting to the seminar space currently requires that you climb a set of stairs. If an accommodation is needed, please contact PPH in advance at: [ mailto:princetonPPH@princeton.edu | princetonPPH(a)princeton.edu ] ********************************** [ https://pph.princeton.edu/events/data-driven-precision-health-integrating-g… | Registration ] is now open for PPH-NOAA November 7 conference: "Data-Driven Precision Health: Integrating Genomics, Climate, and the Environment.” The conference, a collaboration between Princeton Precision Health and NOAA’s Geophysical Fluid Dynamics Laboratory and co-sponsored by Princeton’s High Meadows Environmental Institute , will bring together an interdisciplinary community from academia, government, and industry to explore research questions at the intersection of human health, climate, and environment. The event aims to spark discussions and inspire new research directions on future health impacts, with a focus on predicting outcomes and developing equitable risk mitigation strategies. The conference will be held in Maeder Hall, at the Andlinger Center for the Energy and the Environment. Keynote speakers include Jane Burns , Director of the Kawasaki Disease Research Center at UC San Diego and whose work on Kawasaki Disease, environment, and climate has been featured in the [ https://www.nytimes.com/2024/02/27/health/kawasaki-disease-cause.html | NY Times ] , and Juli Trtanj , Director of the NOAA Climate and Health Program and NOAA One Health Lead and co-chair of Global Heat Health Information Network (GHHIN) Management Committee . In addition, Provost Jennifer Rexford and Dean For Research Peter Schiffer will be giving remarks at the conference. Registration is free but required. [View Less]

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PPH Seminar: TODAY, 12pm @ 252 Nassau St
by Emily C. Lawrence 11 Oct '24

11 Oct '24

Please join the Princeton Precision Health (PPH) Initiative for the next talk of our fall semester series TODAY, October 11, at 12:00 pm, at 252 Nassau Street. Zeynep Tufekci, Henry G. Bryant Professor of Sociology and Public Affairs, will present a talk, “The Pandemic: Science, Policy and Trust.” Abstract: A key tenet of dealing with a pandemic is remembering that it is as much a communication emergency as much as a medical crisis, or so warns us the C.D.C. in its pre-pandemic publications.… [View More]

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Akhil Jakatdar will present his General Exam "Inferring Phylogenetic Trees from Longitudinal Single-Cell Tumor Samples" on Friday, October 11, 2024 at 3:30 PM in CS 402.
by CS Grad Department 08 Oct '24

08 Oct '24

Akhil Jakatdar will present his General Exam "Inferring Phylogenetic Trees from Longitudinal Single-Cell Tumor Samples" on Friday, October 11, 2024 at 3:30 PM in CS 402. Committee Members: Ben Raphael (advisor), Mona Singh, Yuri Pritykin Abstract: Recent advances in high-throughput single-cell sequencing technology provide the opportunity to better understand the tumor evolutionary process through large-scale longitudinal profiling studies. These studies allow for cancer progression to be … [View More]

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