NYC Fall


  • SONYC participated in the ARISE program again this year, which resulted in several successful projects. Director of CUSP Juan Bello and Research Scientist Mark Cartwright mentored Marin Hyatt from Hunter College High School. Marin worked on “Trucking in Relation to Noise Pollution” in which she used machine listening with SONYC sensor data to investigate the impact of trucking activity on noise in Red Hook. Juan Bello and Postdoctoral Researcher Vincent Lostanlen also mentored Phincho Sherpa.
  • Adjunct Professor Benedetta Piantella will speak on a panel titled “Disrupting Engineering Education: Lessons from the Classroom” during the Impact.Engineered forum on October 8th, held at NYU Tandon. Impact.Engineered is a forum recognizing and celebrating the engineering profession’s commitment and contributions to social and environmental innovation.
  • Assistant Professor Giuseppe Loianno is the program chair of the upcoming IEEE International Conference on Safety, Security, and Rescue Robotics (SSRR), an international forum for furthering the study of safety, security and rescue robotics as well as solutions for fielding robots and sensor systems across a variety of application areas. The forum will be held September 2-4 in Würzburg, Germany.
  • Assistant Professor Giuseppe Loianno is also the main organizer of a major workshop at the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), one of the largest and most impacting robotics research conferences worldwide. Prof. Loianno will discuss “Challenges in Vision-based Drones Navigation,” which also has a best paper award prize.
  • Assistant Professor Giuseppe Loianno is also a member of the advisory board and jury committee in the DroneXChallenge, a $1.5M global challenge aiming at accelerating the practical deployment of drones/UAVs in key applications focusing on transportation and delivery. He is also the Senior Juror in the Unusual Solutions Competition, which tackles 3 major challenges related to drones: drone data and AI tools, last data mile, and drone and data ethics.
  • Congratulations to Siyuan Chen, a PhD student working with Professor Debra Laefer, who successfully passed his viva!
  • Congratulations to Assistant Professor Yury Dvorkin, who was recently awarded the Goddard Junior Faculty Fellowship from New York University! The Goddard Junior Faculty Fellowship program provides funds to tenure track faculty who have successfully passed their Third-Year Review to advance their research and scholarship interests.
  • Assistant Professor Chen Feng, Professor Maurizio Porfiri, and Associate Professor Ludovic Righetti (NYU Tandon) recently received a $1.2M NSF CPS award to study a new concept they proposed as collective additive manufacturing, which uses a team of mobile robots for 3D printing of large-scale 3D structures. Learn more about their research on “CPS: Medium: Accurate and Efficient Collective Additive Manufacturing by Mobile Robots” here.


Cartwright, M., Mendez, A.M.M., Cramer, A., Lostanlen, V., Dove, G., Wu, H., Salamon, J., Nov, O., Bello, J.P. SONYC Urban Sound Tagging (SONYC-UST): A Multilabel Dataset from an Urban Acoustic Sensor Network. In Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), 2019.

  • This paper presents a new dataset for urban sound tagging in which the audio was recorded from the SONYC acoustic sensor network. The paper describes the class taxonomy, the data collection and annotation process, new metric calculations to deal with class uncertainty, and a baseline tagging model trained with the dataset. The SONYC-UST dataset addresses some of the limitations of previous dataset by providing recordings from urban noise sensors across a variety of times and locations, and by more closely matching the label set to the needs of noise enforcement agencies. We hope this dataset will encourage researchers to focus on this problem and advance the state of the art in urban sound event detection, helping build tools to make cities quieter.

Cohen-Hadria, A., Cartwright, M., McFee, B., Bello, J.P. Voice Anonymization in Urban Sound Recordings. In Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2019.

  • Monitoring health and noise pollution in urban environments often entails deploying acoustic sensor networks to passively collect data in public spaces. Although spaces are technically public, people in the environment may not fully realize the degree to which they may be recorded by the sensor network, which may be perceived as a violation of expected privacy. This paper proposes a method to anonymize and blur the voices of people recorded in public spaces. The proposed blurring method aims to anonymize voices by removing both the linguistic content and personal identity from voices, while preserving the rest of the acoustic scene.

Fabian Okeke, Emily Tseng, Benedetta Piantella, Mikaela Brown, Harveen Kaur, Madeline R. Sterling, and Nicola Dell. 2019. Technology, home health care, and heart failure: a qualitative analysis with multiple stakeholders. In Proceedings of the 2nd ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS ’19). ACM, New York, NY, USA, 122-133.

  • Home health aides (HHAs) increasingly being used by adults with heart failure for long-term assistance and post-hospitalization care. Despite being heavily involved in numerous aspects of heart failure management, most HHAs have not received heart failure training. They also struggle to get in touch with supervising nurses or other members of the care team when they have clinical questions, which may result in unnecessary visits to the emergency room. In addition, despite serving as a backbone in the health system for patients, HHAs, who are mostly women and minorities, are a marginalized and vulnerable group of frontline caregivers, enduring erratic employment, low wages, discrimination, and high levels of burnout. Although digital technologies could help to address many of the challenges HHAs face, little is known about the current impact of technology on HHAs work practices. To this end, we conducted a multi-stakeholder qualitative study with 38 participants in New York City using semi-structured interviews and focus groups. We uncover the ways in which technology is used, the complex socio-technical factors that underpin heart failure care, and stakeholder suggestions for how technology could improve HHAs work. Building on these insights, we synthesize design opportunities for researchers and designers interested in developing tools that support the delivery of home health care for patients suffering from life-threatening diseases like heart failure.

J O’Donnell, L Truong-Hong, N Boyle, E Corry, J Cao, DF Laefer. LiDAR point-cloud mapping of building façades for building energy performance simulation. Automation in Construction 107, 102905.

  • Current processes that create Building Energy Performance Simulation (BEPS) models are time consuming and costly, primarily due to the extensive manual inputs required for model population. In particular, generation of geometric inputs for existing building models requires significant manual intervention due to the absence, or outdated nature of available data or digital measurements. Additionally, solutions based on Building Information Modelling (BIM) also require high quality and precise geometrically-based models, which are not typically available for existing buildings. As such, this work introduces a semi-automated BEPS input solution for existing building exteriors that can be integrated with other related technologies (such as BIM or CityGML) and deployed across an entire building stock. Within the overarching approach, a novel sub-process automatically transforms a point cloud obtained from a terrestrial laser scanner into a representation of a building’s exterior façade geometry as input data for a BEPS engine. Semantic enrichment is performed manually. This novel solution extends two existing approaches: (1) an angle criterion in boundary detection and (2) a voxelisation representation to improve performance. The use of laser scanning data reduces temporal costs and improves input accuracy for BEPS model generation of existing buildings. The approach is tested herein on two example cases. Vertical and horizontal accuracies of 1% and 7% were generated, respectively, when compared against independently produced, measured drawings. The approach showed variation in accuracy of model generation, particularly for upper floors of the test case buildings. However, the energy impacts resulting from these variations represented less than 1% of the energy consumption for both cases.

Lostanlen, Vincent; Hecker, Florian. “The Shape of RemiXXXes to Come: Audio Texture Synthesis with Time-frequency Scattering.” Digital Audio Effects (DAFX) Conference. eprint arXiv:1906.09334. June 2019.

  • This article explains how to apply time–frequency scattering, a convolutional operator extracting modulations in the time–frequency domain at different rates and scales, to the re-synthesis and manipulation of audio textures. After implementing phase retrieval in the scattering network by gradient backpropagation, we introduce scale–rate DAFx, a class of audio transformations expressed in the domain of time–frequency scattering coefficients. One example of scale–rate DAFx is chirp rate inversion, which causes each sonic event to be locally reversed in time while leaving the arrow of time globally unchanged. Over the past two years, our work has led to the creation of four electroacoustic pieces: “FAVN”; “Modulator (Scattering Transform)”; “Experimental Palimpsest”; “Inspection”; and a remix of Lorenzo Senni’s “XAllegroX”, released by Warp Records on a vinyl entitled “The Shape of RemiXXXes to Come”. The source code to reproduce experiments and figures is made freely available here. A companion website containing demos is available here.

Alexandria B. Boehm, Andrea I. Silverman, Alexander Schriewer, and Kelly Goodwin. 2019. Systematic review and meta-analysis of decay rates of waterborne mammalian viruses and coliphages in surface waters. Water Research, 164.

  • Surface waters are essential natural resources. They are also receiving waters for a variety of anthropogenic waste streams that carry a myriad of pollutants including pathogens. Watershed and fate and transport models can help inform the spatial and temporal extent of microbial pollution from point and non-point sources and thus provide useful information for managing surface waters. Viruses are particularly important water-related pathogens because they often have a low infectious dose, which means that ingestion of even a small volume of water containing a low concentration of virions has the potential to cause disease. We conducted a systematic review of the literature, following best practices, to gather decay rate constants (k) of mammalian waterborne viruses (enteroviruses, adenoviruses, noroviruses, astroviruses, rotaviruses, and hepatitis A viruses) and coliphages in raw surface waters to aid in the parameterization of virus fate and transport models.


  • A huge welcome to NYU CUSP’s newest graduate students! Our Fall 2019 cohort began their journey last week during new student orientation, where they worked on city challenges and prepared for their intensive year-long degree.