Center for Smart Streetscapes

CS3 Monthly Research Exchange
2024-03-22 12:00 - 13:00 (America/New_York) | Hybrid
At each CS3 Monthly Research Exchange, faculty and student researchers in the field of smart urban planning will take the stage to share their latest findings, breakthroughs, and urban projects.
Gaurav Jain, Ph.D. Student at Columbia University

Gaurav Jain is a Ph.D. candidate in the computer science department at Columbia University, advised by Prof. Brian A. Smith in the Computer-Enabled Abilities Lab (CEAL). His research lies at the intersection of Human-Computer Interaction, Computer Vision, and Accessibility. Gaurav’s work focuses on developing AI-driven interactive systems that augment blind and low-vision people’s access to visual experiences. He has developed systems that embed AI within street intersections for independent and safe outdoor navigation for blind pedestrians. Gaurav’s work also introduces new approaches for navigation assistance, studying how technology can enable blind people to explore unfamiliar environments. Additionally, he has contributed to digital media accessibility, developing systems that generate audio representations for sports broadcasts, enabling blind viewers to visualize the action by themselves.
Presentation Abstract: Leveraging street cameras to support precise outdoor navigation for blind pedestrians.

Alon S. Levin, Ph.D. Student at Columbia University

Alon S. Levin received a B.Eng. in Electrical Engineering (magna cum laude) in 2020 and a M.Eng. in Electrical Engineering in 2021, both from The Cooper Union. His research interests are in full-duplex wireless, compressed sensing, PHY layer algorithms, and cognitive radio.
Presentation Abstract: We present a set of experiments utilizing wideband real-time adaptive full-duplex (FD) radios, demonstrating simultaneous transmission and reception on the same frequency channel. Each FD radio consists of a paired antenna interface, a switched-capacitor delay-line-based configurable Radio-Frequency Integrated Circuit (RFIC) that implements Self-Interference Cancellation (SIC), an FPGA that optimizes the RFIC configuration in under 1.1 seconds and can adapt to environmental changes in under 0.3 seconds, and a Software-Defined Radio (SDR) transmitting OFDM-like packets. We demonstrate a real-time adaptive FD radio that achieves the SIC necessary to reach the noise floor across a wide bandwidth of 100 MHz, enabling a FD wireless communication link.

The CS3 Monthly Research Exchanges are internal and open only to CS3 affiliated students, faculty, and staff. If you are interested in learning more about the research happening at CS3, please contact our team at streetscapes@columbia.edu.

CS3 Monthly Research Exchange
2024-02-16 12:00 - 13:00 (America/New_York) | Hybrid
At each CS3 Monthly Research Exchange, three faculty and student researchers in the field of smart urban planning will take the stage to share their latest findings, breakthroughs, and urban projects.
Sevin Mohammadi, Ph.D. Student at Columbia University

Presentation Abstract: Sevin will present her ongoing and completed research, which converges to enhance urban mobility and operation by leveraging data and advanced machine learning techniques. The main focus of her presentation will be enhancing Emergency Medical Services response in urban environments through data-informed decision-making and policy optimization.

Additional presenters to be announced.
The CS3 Monthly Research Exchanges are internal and open only to CS3 affiliated students, faculty, and staff. If you are interested in learning more about the research happening at CS3, please contact our team at streetscapes@columbia.edu.

CS3 Spring Welcome Session
2024-01-29 12:00 - 13:00 (America/New_York) | Hybrid
The Center for Smart Streetscapes (CS3) presents the Spring Welcome Session! We will be introducing the engineering research center’s goals and discussing the unique opportunity to engage with the Center for Smart Streetscapes, its Student Leadership Council, and upcoming events for the year. Lunch will be provided.

Students of all majors are welcome
Faculty & Staff are encouraged to join

In-Person Locations:

Columbia University
Lehman College
Florida Atlantic University
University of Central Florida

CS3 Monthly Research Exchange
2023-11-17 12:00 - 13:00 (America/New_York) | Hybrid
At each CS3 Monthly Research Exchange, three faculty and student researchers in the field of smart urban planning will take the stage to share their latest findings, breakthroughs, and urban projects.
Ariana Galindo, Undergraduate Student at Florida Atlantic University

Presentation Abstract: This project investigates the development of scalable data processing tools for large-scale spatiotemporal data.

Dimitris A. Pados, Professor and I-SENSE Fellow at Florida Atlantic University

Presentation Abstract: We examine the problem of dynamically optimizing arbitrary multiple-input multiple-output (MIMO) wireless waveforms in potentially heavily utilized frequency bands with applications to near-field (or far-field) autonomous machine-to-machine communications. We look at the problem from the point of view of spectrum sharing and autonomous interference avoidance. In this context, we seek the transmitter beam weight vector and the pulse code sequence that maximize the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum SINR joint space-time receiver filter. We derive two novel model-based solutions: (a) Disjoint, space first (transmit weight vector) then time (pulse code sequence) waveform optimization and (b) jointly optimal transmit weight vector and pulse code sequence optimization (a mixed integer programming problem.) The proposed formally derived algorithmic solutions are studied in extensive simulations under varying waveform code length, near-field/far-field and spread-spectrum/non-spread-spectrum interference, in light and dense interference scenarios. The findings highlight (a) the effectiveness of the described methods compared to static conventionally designed optimal-receiver MIMO links and (b) the remarkable ability of the joint space-time optimized waveforms to avoid heavy interference.

Navid Salami Pargoo, Ph.D. Student at Rutgers University

Presentation Abstract: In this talk, join me on a journey into transformative assistive technologies for the visually impaired, crafting a synergy between interactive AI agents and the smart streetscape. Discover our innovative strides in machine learning, deep learning, computer vision, and sensing, forming the heartbeat of this human-centric AI agent. I will show how they harmoniously integrate into streetscapes, enhancing safety, inclusivity, and enriched urban interactions.

The CS3 Monthly Research Exchanges are internal and open only to CS3 affiliated students, faculty, and staff. If you are interested in learning more about the research happening at CS3, please contact our team at streetscapes@columbia.edu.

CS3 Monthly Research Exchange
2023-10-20 12:00 - 13:30 (America/New_York) | Hybrid
At each CS3 Monthly Research Exchange, three faculty and student researchers in the field of smart urban planning will take the stage to share their latest findings, breakthroughs, and urban projects.
Chinwendu Enyioha, Assistant Professor at University of Central Florida (UCF)

Presentation Abstract: In the talk, I will present some results on fully distributed cooperative state estimation in communication-constrained environments. I will show how agents can effectively manage communication bandwidth by compress state information being shared with neighbors and summarize stability guarantees.

Zhaobin Mo, Ph.D. Student at Columbia University

Presentation Abstract: For its robust predictive power (compared to pure physics-based models) and sample-efficient training (compared to pure deep learning models), physics-informed deep learning (PIDL), a paradigm hybridizing physics-based models and deep neural networks (DNN), has been booming in science and engineering fields. One key challenge of applying PIDL to various domains and problems lies in the design of a computational graph that integrates physics and DNNs. In other words, how physics is encoded into DNNs and how the physics and DL components are represented. We present a variety of architecture designs of PIDL computational graphs and how these structures are customized to different tasks in transportation, i.e., traffic state estimation and car-following behavior modeling.

Sonia Moshfeghi, Ph.D. Student at Florida Atlantic University

Presentation Abstract: As in-vehicle telematics technologies advance, they offer applicable techniques for monitoring and evaluating driving behavior. Telematics systems can combine telecommunication and information processing to capture various types of driving data, such as acceleration, GPS, and onboard diagnostics (OBD) data. Identifying significant patterns and behaviors with feature extraction techniques provides insights into driver performance for applications like autonomous vehicles, demand estimations, insurance pricing strategies, driver training programs, and accident prevention strategies.

CS3 VALIDATE Accelerator Program:
Attendees of this month’s CS3 Research Exchange are welcome to stay after the presentations for an informational session (1:00 – 1:30PM) on the CS3 VALIDATE Accelerator Program.
The NSF Engineering Research Center for Smart Streetscapes (CS3) VALIDATE Accelerator is a 9-week non-dilutive program focused on validating and scaling successful early-stage ventures through in-depth education, mentorship, and business model design. It offers early stage teams a customized program with education from industry and academic research experts, hands-on value-added workshops, active mentoring, and venture creation opportunities.
The program will run February through April of 2024.
The CS3 Monthly Research Exchanges are internal and open only to CS3 affiliated students, faculty, and staff. If you are interested in learning more about the research happening at CS3, please contact our team at streetscapes@columbia.edu.

A conversation with Dr. Berk Birand, co-founder and CEO of Fero Labs
2023-09-22 13:00 - 14:00 (America/New_York) | Zoom
Join us for a conversation with Dr. Berk Birand, who served as the Vice President of another ERC SLC before becoming the co-founder and CEO of Fero Labs! Berk, a Columbia Electrical Engineering and WiMNet Lab PhD ’15 alumnus, will share insights from his journey. This event is open to students from NSF CS3-ERC institutions (Columbia, FAU, UCF, Rutgers, Lehman).

CS3 Monthly Research Exchange
2023-09-15 12:00 - 13:00 (America/New_York) | Hybrid
At each CS3 Monthly Research Exchange, three faculty and student researchers in the field of smart urban planning will take the stage to share their latest findings, breakthroughs, and urban projects.
Abhishek Adhikari, M.S/Ph.D Student at Columbia University

Presentation Abstract: Beyond-5G and 6G wireless networks can sense the nearby environment in addition to performing traditional communication responsibilities via Joint Communications and Sensing (JCAS). A potential application of JCAS could be to sense vehicles crossing a street intersection and communicate to pedestrians who may be visually impaired. In this talk, we share preliminary vehicle detection results at a street intersection in NYC using a Nokia Bell Labs 28 GHz channel sounder traditionally used for propagation modeling in communication.

Stepan Mazokha, Ph.D. Student at Florida Atlantic University

Presentation Abstract: In this presentation, I will discuss the details of my recent paper entitled, “MobLoc: CSI-based Location Fingerprinting with MUSIC”. The objective of the project has been to implement and evaluate a passive WiFi localization method using Channel State Information. The latter has been designed using a fingerprinting method using a 1D MUSIC algorithm and was able to achieve meter-level localization in several indoor environments.

Jorge Ortiz, Assistant Professor at Rutgers University

Presentation Abstract: This talk focuses on human-AI interaction through multimodal learning and interaction, highlighting my lab’s past and future work on intelligent agents that utilize and integrate multimodal learning techniques to infer human intent and enable innovative forms of interaction. We explore interaction within vehicles, robots that assist disabled individuals, and investigate methods to close the learning loop through interactive learning agents. Additionally, we examine various forms of intervention in a vehicular context and assess how these techniques translate to future Streetscape interactive systems.

The CS3 Monthly Research Exchanges are internal and open only to CS3 affiliated students, faculty, and staff. If you are interested in learning more about the research happening at CS3, please contact our team at streetscapes@columbia.edu.

CS3 Monthly Research Exchange
2023-08-18 12:00 - 13:00 UTC | Hybrid
At each CS3 Monthly Research Exchange, three faculty and student researchers in the field of smart urban planning will take the stage to share their latest findings, breakthroughs, and urban projects.
Sharon Di, Associate Professor at Columbia University

Presentation Abstract: Transportation digital twins have become increasingly popular tools to improve traffic efficiency and safety. However, the majority of effort nowadays is focused on the “eyes” of the digital twin, which is object detection using computer vision. I believe the key to empowering the intelligence of a transportation digital twin lies in its “brain,” namely, how to utilize the information extracted from various sensors to infer traffic dynamics evolution and devise optimal control and management strategies with real-time feedback to guide the transportation ecosystem toward a social optimum. My research aims to employ tools including machine learning and game theory to develop an urban transportation digital twin.

Abigail Joseph, Undergraduate Student at Florida Atlantic University

Presentation Abstract: Integrating Unity with real data, AI technology, and C# scripting is used to a create digital twin environment of West Palm Beach, where multiple agents’ traveling behaviors are defined at a streetscape level, including walking at a particular speed, stopping at an intersection to look for cars before crossing, and avoiding other pedestrians. It is anticipated that the methods which produced these results will be used to simulate the interactions between vehicles and pedestrians with substantial accuracy.

Carl Vondrick, Associate Professor at Columbia University

Presentation Abstract: Computer vision algorithms need to combine many skills — spatial, physical, mathematical, geometrical, and cognitive — in order to accurately analyze the visual world. In this talk, I will show how large generative models equip neural networks with these skills, thereby providing versatile representations for reconstructing 3D, answering questions, and recognizing objects. Through a series of experimental results, I will moreover show how this approach naturally provides inherent explainability of the decision making process, while also achieving state-of-the-art zero-shot performance across different tasks and benchmarks. In some cases, this framework can even perform super-human perception.

The CS3 Monthly Research Exchanges are internal and open only to CS3 affiliated students, faculty, and staff. If you are interested in learning more about the research happening at CS3, please contact our team at streetscapes@columbia.edu.
