Please join us as we bring you a series of talks highlighting department research and topical issues in our field. If you like these talks, be sure to check out the ISRC research series.
Title: Research Challenges and Opportunities in the Center for Real-Time Distributed Sensing and Autonomy
Speaker: Dr. Aryya Gangopadhyay
Date and Time: Thursday, March 10th, 2022 – 12:00-1pm
Description: In this talk we will present the research challenges and opportunities in CARDS, a center created by the inaugural grant from the Army Research Laboratory to conduct research on AI and autonomy for multi-agent systems. The talk will cover the following areas: (1) Developing novel AI/ML algorithms in real-time contested environments on resource-constrained devices. This is emblematic of many real-world situations where various environmental factors can nullify the efficacy of systems developed in lab-based controlled environments; (2) Securing cyberspace against ever increasing attack surfaces due to the proliferation of distributed, autonomous systems in both civilian and military applications; and (3) Connecting systems over short and long hauls such that the data gathered at the edge can be translated into collaborative, actionable intelligence.
Title: Aesthetic Rationality in Design Research
Speaker: Dr. Jeff Bardzell
Date and Time: Friday, March 4th at 12pm
Location(s): Online: https://umbc.webex.com/meet/fhamidi or In-person: ITE459
Designs—whether they are products, buildings, or computational devices—physically embody the knowledge that went into their making. We understand this intuitively when we talk about “reverse-engineering” a design, which is the act of extracting technical knowledge from a finished product. Leveraging the knowledge-embedding abilities of design, the HCI and design communities are integrating acts designing and researching: examples include research through design, critical and speculative design, conceptual design, constructive design, etc. Yet these efforts have faced challenges: how to articulate such knowledge as research, how to demonstrate the intellectual rigor and reliability of such knowledge, and how to build on it to move the field forward. Driving these challenges are as yet unresolved conflicts between words and things, and their underlying epistemologies, in HCI. Such conflicts, I believe, are the result of insufficient understandings of the contributions of aesthetic rationality to HCI knowledge. In this talk, I offer a theoretical account of the knowledge contributions of aesthetics to interaction design, and I demonstrate it through analyses of several design research products. I conclude by looking ahead at the implications for aesthetic rationality on emerging research agendas, such as explainable AI (XAI), that also seek to render knowledge embedded in the system available.
Jeffrey Bardzell is Associate Dean of Graduate and Undergraduate Studies and Professor in the College of Information Sciences and Technology at Penn State University. His research contributes to human-computer interaction and design, with emphases on research through design, creativity support, social innovation, and user experience design. He is co-editor of Critical Theory and Interaction Design (MIT Press, 2018) and co-author of Humanistic HCI (Morgan & Claypool, 2015). Bardzell’s work is funded by the National Science Foundation and the Intel Science and Technology Center for Social Computing.
Description: In this talk, our speakers provide an introduction and overview of two of the research centers in the Information Systems department at UMBC.
The Interactive Systems Research Center (ISRC), founded in 2002, acts as a bridge for faculty and their graduate students across the UMBC campus with expertise in designing, building, or studying uses of interactive computing systems. It facilitates the sharing of resources and experience in solving computing problems from a user-centered perspective grounded in user needs and not in simply applying previously designed solutions to new domains. The ISRC, equipped via NSF and UMBC awards, offers faculty and students access to software and technologies for measuring and monitoring human behavior to support their research activities, foster collaboration, and facilitate the integration of research and teaching.
Real-time analytics is the leading edge of a smart data revolution, pushed by advances in internet-connected sensor hardware on the one side, and accelerated Artificial Intelligence (AI)/Machine Learning (ML) analysis on the other. The Center of Accelerated Real Time Analytics (CARTA) explores the ways in which new approaches to these technologies and their integration can be developed that have relevance to our industrial and agency partners. Dr. Karuna Joshi is the Director of CARTA at UMBC. The center is focused on horizontal foundational technologies that create an infrastructure powering applications of national significance. This center, an NSF-sponsored Industry University Cooperative Research Center (IUCRC), includes sites at UMBC, NCSU, Rutgers University and University of Miami. CARTA offers a unique opportunity for Faculty and graduate students to collaborate with industrial partners on applications of relevance to these partners, who represent a suite of potential future employers for the graduate students.
With the rising of the Internet of Things (IoT), many traditional spaces (e.g., our homes) have been turned into multi-stakeholder environments. In these environments, not only the end users but also other entities (e.g., visitors, passersby) can potentially face severe privacy risks caused by the ubiquitous data collection by IoT devices. One way to help people stay informed and make rational privacy decisions is to increase their awareness of the surroundings data practices. However, the various, sometimes conflicting needs among different stakeholders and the associated social relationships and power dynamics make adequate privacy notice difficult to achieve. In this talk, I will walk through our latest effort in exploring designing effective privacy notices in one typical multi-stakeholder environment, i.e., smart homes, and discuss how we can effectively build unobtrusive privacy notification mechanisms.
In my work, I investigate how to ubiquitize healthcare by moving the process of diagnosis closer to the patient. Today, diagnosis requires patients to see a doctor to provide samples, which are then sent to a wetlab. The lab conducts tests on the samples and reports back to the doctor, who ultimately reports back to the patient. This process tends to take days or even weeks – valuable time during which patients live in uncertainty and disease is allowed to spread. What if instead doctors could perform the tests while the patient waits? Or, what if we could empower patients to perform selected tests at home, as part of their decision whether to see a doctor in the first place?
I pursue this vision by creating cyber-physical systems based on small electronic devices called biochips. Biochips manipulate droplets of fluids by executing “bio-protocols” – simple programs that move, split, and mix droplets with chemical compounds (“reagents”). Biochips thereby automate processes traditionally performed manually in wet labs. The key advantage of biochips is that they are adaptable, thus capable of running different bio-protocols. Instead of going to a specialist, a patient can download a bio protocol. This transforms diagnosis into a software problem that has the potential to scale the way software scales.
In order to enable the transition towards doctors and ultimately patients, I am working on ways to design biochips that can be operated at the level of expertise of doctors and patients. I design and fabricate novel biochip hardware (recently adopted by researchers at universities like MIT and the University of Washington), write system-level software (real-time compilation and fault-tolerant synthesis), and am currently developing a user-facing system that allows users to edit bio-protocol interactively.
Mirela (assistant professor, ATLAS Institute, Computer Science) investigates the extent to which we can change healthcare to make it a personal process. Her research focuses around microfluidic biochips, devices that enable direct interaction of humans with their microbiome for diagnosis purposes. So far Mirela has built systems based on biochips to serve as personal laboratories: small portable devices that people can own and use to develop customized bio-protocols (“bio-apps”).
Mirela is an active contributor to the DIYBio movement, having led and co-founded community wetlabs. In this context, she organizes interactive performances, art installations and open workshops, in order to engage the public in direct interaction with living materials (e.g., bacteria, viruses, fungi)
Mirela received her PhD from the Technical University of Denmark in 2014, and until 2018, she was a postdoc in Patrick Baudish’s lab at Hasso Plattner Institute in Germany. Mirela’s work is published in top-tier journals and conferences (IEEE TCAD) and has been demonstrated at venues such as IEEE ESWeek and Molecular Communications. Mirela has served as a guest editor for Current Biotechnology journal (CBNT) and as a reviewer for venues such as Applied Materials and Interfaces, DATE, TCAD, ToDAES, NanoCom and UIST.
How did China’s mass manufacturing and “copycat” production become transformed, in the global tech imagination, from something holding the nation back to one of its key assets? Prototype Nation offers a transnational analysis of how the promise of democratized innovation and entrepreneurial life has shaped China’s governance and global image. Lindtner reveals how a growing distrust in Western models of progress and development, including Silicon Valley and the tech industry after the financial crisis of 2007–8, shaped the rise of the global maker movement and the vision of China as a “new frontier” of innovation. Lindtner’s investigations draw on more than a decade of research in makerspaces, tech incubators, corporate offices, and factories. She examines how the ideals of the maker movement, to intervene in social and economic structures, served the technopolitical project of prototyping a “new” optimistic, assertive, and global China. In doing so, Lindtner demonstrates that entrepreneurial living influences governance, education, policy, investment, and urban redesign in ways that normalize the persistence of sexism, racism, colonialism, and labor exploitation. Prototype Nation shows that by attending to the bodies and sites that nurture entrepreneurial life, technology can be extricated from the seemingly endless cycle of promise and violence.
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Silvia Lindtner (she/her) is Associate Professor at the University of Michigan in the School of Information and Associate Director of the Center for Ethics, Society, and Computing (ESC). She is a founding member of Precarity Lab, a research collective working on various forms of insecurity, vulnerability, and social and cultural exclusion that digital platforms produce, and mediate. Lindtner’s research interests include cultures and politics of technology innovation and entrepreneurship, with a particular focus on the gendered and racialized forms of labor necessary to incubate entrepreneurial life and sustain technological promise. Lindtner draws from more than ten years of multi-sited ethnographic research, with a particular focus on China’s shifting position in the global political economy of technology production, economic development, and science and technology policy. Lindtner’s work contributes to the fields of STS (science and technology studies), cultural and feminist anthropology, China studies, HCI (human computer interaction), global communication studies, science and technology policy, and design. Her research has been awarded support from the US National Science Foundation, IMLS, Intel Labs, Google Anita Borg, and the Chinese National Natural Science Foundation.
Emotions are powerful, mediate humans’ experiences with their surroundings, and impact decision-making and attention online and off. Sharing and signaling one’s emotions to other humans can be beneficial, but involves privacy calculations and complex decision-making processes. Despite the deeply personal nature of human emotion, artificial intelligence (AI) algorithms are being built to recognize and infer emotions using data sources such as social media behavior, streaming service use, voice, facial expressions, biometrics, and body language in ways often unknown to users.
A key perspective missing from debates in emotion AI/recognition is that of the humans who produce the data that make emotion recognition possible, and whose experiences are shaped by these technologies. In this talk I will share insights from my recent work around data subjects’ attitudes toward and conceptions of emotion recognition technologies, factors informing these attitudes, as well as anticipated risks and benefits. I focus on social media as a technological context and discuss data subjects’ attitudes towards emotion recognition on social media broadly, as well as emotion AI’s use in wellbeing and advertising domains. I then complicate accuracy and transparency notions in emotion recognition through an analysis of data subjects’ attitudes towards these notions and related folk theories. I conclude with a discussion of my research group’s ongoing and future research in this space.
Dr. Nazanin Andalibi is an assistant professor at the University of Michigan School of Information. She is also affiliated with the Center for Social Media Responsibility, the Center for Ethics, Society, and Computing, and the Digital Studies Institute. Her research interests are in social computing, computer-mediated communication, and human-computer interaction, including examining relationships between emotions, identity, and technologies in contexts ranging from social media to artificial intelligence. Through this research agenda, Dr. Andalibi seeks to inform theory, design, activism, and policy for socio-technical futures that foreground the values and needs of marginalized individuals to support qualities such as wellbeing, safety, privacy, ethics, and equity. Dr. Andalibi’s work is published in venues such as ACM CHI, CSCW, TOCHI, JMIR, and New Media and Society, and featured by media outlets such as CNN, Fast Company, and Huffington Post. Her publications have received several Best Paper Honorable Mention Awards at ACM CHI and CSCW and her work is sponsored by the National Science Foundation.
Time: Wednesday, February 17, 12-1pm ET.
Speaker: Dr. Edward Raff, Booz Allen Hamilton. Visiting Professor, UMBC Dept. of Computer Science
Abstract: Malware is an ever growing problem, single malware families have caused billions in damages and the first direct death attributed to malware taking down a hospital has occurred. To detect new malware, machine learning is a naturally attractive approach. However, malware poses a number of unique challenges that have slowed the progress of ML based solutions. In this talk we will look at the task of malware detection from byte based analysis, why is poses many challenging ML research problems, and progress we have made on these tasks by taking some non-standard approaches to machine learning: building shallow and wide networks instead of deep, handicapping the features of our model to make it robust, and using literal compression algorithms (LZMA) to find similar content.
Bio: Edward Raff leads Booz Allen’s machine learning research group and supports clients developing new ML solutions. His research includes cyber security, adversarial machine learning, fairness and ethics, fingerprint biometrics, and high-performance computing. In his spare time, he is the author of the JSAT machine learning library. He received his BS and MS in Computer Science from Purdue University, and his PhD in CS from UMBC. Dr. Raff is a Nvidia Deep Learning certified instructor, and Visiting Professor at UMBC.
Abstract: Since its founding in 1950, the National Science Foundation has sought “to promote the progress of science; to advance the national health, prosperity, and welfare; and to secure the national defense.” NSF-funded research has advanced foundational, exploratory research, like the detection of gravitational waves validating Einstein’s general theory of relativity, as well as use-inspired, translational research, like the page-rank algorithm that became the basis for Google.
In this two-part talk, I will first describe NSF’s leadership of computer and information science and engineering (CISE) discovery and innovation through its support of research, education, and research infrastructure. Then I will more generally explore the opportunity to enhance the synergies between exploratory and translational research to meet today’s societal grand challenges, thereby improving the critical services that communities deliver to their residents, transforming higher education to meet the needs of tomorrow’s workforce, and advancing public policies.
Bio: Dr. Erwin Gianchandani currently serves as the National Science Foundation’s (NSF) Senior Advisor for Translation, Innovation, and Partnerships, reporting to the NSF Director. For the last five and one-half years, he has been the NSF Deputy Assistant Director for Computer and Information Science and Engineering (CISE), twice serving as NSF Acting Assistant Director for CISE. In this role, he has contributed to the leadership and management of NSF’s CISE directorate, including formulation and implementation of the directorate’s $1 billion annual budget, strategic and human capital planning, and oversight of day-to-day operations. In recent years, he has led the development and launch of several new NSF investments, including Smart & Connected Communities, Platforms for Advanced Wireless Research, and the National Artificial Intelligence Research Institutes. Before joining NSF in 2012, Dr. Gianchandani was the inaugural Director of the Computing Community Consortium, providing leadership to the computing research community in identifying and pursuing audacious, high-impact research directions. He has published extensively and presented at international conferences on computational systems biology. He holds a B.S. in computer science and M.S. and Ph.D. in biomedical engineering from the University of Virginia.