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Events for February 25, 2022
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Grammar TutorialsFri, Feb 25, 2022 @ 10:00 AM - 12:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
INDIVIDUAL GRAMMAR TUTORING FOR VITERBI UNDERGRADUATE AND GRADUATE STUDENTS
Meet one-on-one with Viterbi faculty, build your grammar skills, and take your writing to the next level!
Viterbi faculty from the Engineering in Society Program (formerly the Engineering Writing Program) will help you identify and correct recurring grammatical errors in your academic writing, cover letters, resumes, articles, presentations, and dissertations.
Bring your work, and let's work together to clarify your great ideas!
Contact helenhch@usc.edu with questions.
Location: Zoom
Audiences: Graduate and Undergraduate Students
Contact: Helen Choi
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Career Development Workshop
Fri, Feb 25, 2022 @ 11:00 AM - 12:00 PM
Technology & Applied Computing Program (TAC)
Workshops & Infosessions
Career development workshop taking place on Feb 25th 2-4pm in GFS 106 (USC Campus) Lunch provided!
Watch these testimonials from last semesters students!
https://youtu.be/z6oCQhw44Vc
Confused about where you want your career to be? Is your mind overwhelmed with too many to-do's, Interested in learning tips and methodologies that you can apply to both your professional and personal life to find success? Join Professor Gregg Ibbotson's Career and Development workshop to cultivate these skills and gain clarity in your life! Open to any student at USC!
Sign up today at the webcast link below!Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 106
WebCast Link: https://forms.gle/FZMLkM2ZH8T3fF8j8
Audiences: Everyone Is Invited
Contact: Gregg Ibbotson
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Love, Viterbi
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Fri, Feb 25, 2022 @ 11:00 AM - 04:00 PM
Viterbi School of Engineering Student Organizations
Student Activity
As our final event for Engineers Week 2022, on February 24th from 11 am to 4 pm, we'll be out in the E-Quad giving out flowers and very limited USC beanies to students who write a thank you note to individuals in Viterbi, organizations in Viterbi, or anyone you appreciate! Stop by also for a chance to meet the Tommy Trojan mascot and take pictures with friends
Location: Epstein Family Engineering Plaza
Audiences: Everyone Is Invited
Contact: Viterbi Undergraduate Programs
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CILQ Internal Seminar
Fri, Feb 25, 2022 @ 12:00 PM - 01:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Alan Willner, Professor, USC
Talk Title: Optical Communications: Innovations and Applications Abound
Abstract: Optical communications has enjoyed tremendous impact over the past 50 years. Relatively soon after the concrete proposal of optical fiber communications was reported and the low-loss fiber was demonstrated, fiber-based communications dramatically impacted the way society transfers information. However, there are other key areas beyond fiber-based communications that were also envisioned ~50 years ago but are only recently emerging. Such emergence is due to enhanced capacity needs and critical innovations, including advances in photonic integrated circuits (PICs). This talk will highlight various examples of the innovations and emerging applications of optical communications, including:
1. Free-space optical communications: As opposed to RF, optical links have high directionality and large bandwidth. There is great excitement in the recent emergence of deployed free-space optical links, be they through air or outer-space. Moreover, due to the extremely high losses of RF, even underwater links in the blue-green are gaining significant interest. Also to be discussed is capacity enhancement using multiplexing of multiple orbital-angular-momentum beams.
2. Non-conventional wavelengths: Fiber systems are overwhelmingly in the near-IR, whereas free-space links can take advantage of a much wider frequency range, from THz to visible. Such systems may utilize: (a) native high-speed components, and/or (b) wavelength-band conversion of near-IR channels to other frequencies.
3. Optical signal processing (OSP): OSP has long held the promise of high-speed operation and the avoidance of inefficient optical-electrical-optical conversion. Although OSP deployment has been limited, advances in PICs, power efficiency and multi-wavelength operation may soon enable the emergence of OSP for high-performance functions.
Host: CILQ
Webcast: https://usc.zoom.us/j/92417517950?pwd=WUkycy90cndVQko5R3RhQ1U3STBDdz09Location: via zoom
WebCast Link: https://usc.zoom.us/j/92417517950?pwd=WUkycy90cndVQko5R3RhQ1U3STBDdz09
Audiences: Everyone Is Invited
Contact: Corine Wong
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PhD Thesis Proposal - Liyu Chen
Fri, Feb 25, 2022 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
University Calendar
Time: 2:00-3:00pm Feb 25, Friday
Committee: Haipeng Luo (chair), Rahul Jain, David Kempe, Ashutosh Nayyar, Vatsal Sharan.
Title: Online Goal-Oriented Reinforcement Learning
Abstract: Reinforcement Learning (RL) studies how an agent learns to behave optimally in an unknown environment. It has been a popular topic in both industries and academia since AlphaGo demonstrated its great potential. However, there is still a large gap between theory and practice of RL due to the strong assumptions made in theoretical RL. My research focuses on online learning in a goal-oriented Markov Decision Process model named Stochastic Shortest Path (SSP), where the learner's objective is to reach a goal state with the smallest possible cost. Many real applications can be modeled by SSP such as games, car navigation, and robotic manipulations. To understand the SSP model better, we first focus on establishing minimax regret bounds in various settings. Specifically, for SSP with stochastic costs, we develop a simple minimax optimal algorithm concurrent to other works; for SSP with adversarial costs, we develop efficient minimax optimal algorithms with known transition, and near-optimal algorithms with unknown transition. Next, we focus on developing practical learning algorithms for SSP from different perspectives. Specifically, we develop the first model-free algorithm, the first set of policy optimization algorithms, and improved algorithms with linear function approximation.
For future work, I plan to study SSP for more general settings and develop more practical algorithms. For example, I plan to study the non-stationary SSP where both the transition and cost functions are changing, and SSP under general function approximation. I also plan to develop parameter-free SSP algorithms under different settings.WebCast Link: https://usc.zoom.us/j/97003272644
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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