Prof. Marie desJardins, new AAAI fellow, advocates for CS education in K–12 schools

Prof. Marie desJardins, new AAAI fellow, advocates for CS education in K–12 schools

Marie desJardins, associate dean of the College of Engineering and Information Technology and professor of computer science, recently wrote a piece for The Baltimore Sun about the importance of computer science education in K12 schools. She is a leader in the artificial intelligence field and has been nationally recognized for her commitment to mentoring, work increasing diversity in computing, and success expanding computer science education in K12 schools.

In the op-ed, desJardins writes about why it is important to expose K12 students to computer science, for both their benefit (in terms of expanded career options) and the benefit of fields that rely on STEM talent. “The need for computer science and computational thinking skills is becoming pervasive not just in the world of software engineers, but in fields as varied as science, design, marketing, and public policy,” she writes.

desJardins describes in the Sun her work with “CS Matters in Maryland,” an initiative that seeks to ensure all students across the state have access to computer science education as part of their regular curriculum. “Our ‘CS Matters in Maryland’ project has trained high school teachers in all of the state’s school systems, emphasizing equity and inclusion for all student demographics and all school systems,” she says.

While this particular project focuses on the state of Maryland, desJardins has been honored across the U.S. for her work in the field. In the past month alone, she has received the Distinguished Alumni Award in Computer Science from UC Berkeley, her alma mater and was formally recognized as a fellow of the Association for the Advancement of Artificial Intelligence.

“I was absolutely overwhelmed when I learned that I had been named one of UC Berkeley’s two Outstanding Alumni in Computer Science for 2018, joining a group of computer scientists for which I have immense respect and admiration,” desJardins said. “It is hard to put into words how much it meant to me to have received this award in the same week that I was inducted as a Fellow of the Association for the Advancement of Artificial Intelligence, a recognition that only a handful of AI scientists receive each year. It is especially meaningful to me that the citations on both awards refer equally to my research and to my mentoring, teaching, and diversity efforts.”

A recent interview with Iridescent brings together desJardin’s research on “intelligent learning” — how robots can learn to solve complicated tasks in complex settings — with her work with students from diverse backgrounds, across all majors. In describing UMBC’s Grand Challenge Scholars Program, she highlights how technology matters, but can’t stand alone — how combining the perspectives of people from all backgrounds and all fields is essential to solving the world’s problems.

“Getting these students together from really different perspectives and having them talk about some of these hard problems is initially really exciting and also very hard,” she explains. “Then, it gets easier. The initial barrier is often just one of language and perspective.”

desJardins continues to work to bridge those divides through her teaching, advocacy, and research, and is now recognized by both Forbes and TechRepublic as a top artificial intelligence expert to follow online.

Read the entire piece in The Baltimore Sun, “All Kids Should Have a Computer Science Education.

Adapted from an article in UMBC News by Megan Hanks.

talk: Semi-supervised Learning for Visual Recognition, 1pm Fri 2/23, ITE325, UMBC

ACM Faculty Talk Series

Semi-supervised Learning for Visual Recognition

Dr. Hamed Pirsiavash, Assistant Professor, CSEE

1:00-2:00pm Friday, February 23, 2018, ITE 325, UMBC

We are interested in learning representations (features) that are discriminative for semantic image understanding tasks such as object classification, detection, and segmentation in images. A common approach to obtain such features is to use supervised learning. However, this requires manual annotation of images, which is costly, time-consuming, and prone to errors. In contrast, unsupervised or self-supervised feature learning methods exploiting unlabeled data can be much more scalable and flexible. I will present some of our efforts in this direction.

Hamed Pirsiavash is an assistant professor at the University of Maryland, Baltimore County (UMBC). Prior to joining UMBC in 2015 he was a postdoctoral research associate at MIT and he obtained his PhD at the University of California Irvine. He does research in the intersection of computer vision and machine learning.

This talk is sponsored by the UMBC Student Chapter of the ACM. Contact with any questions regarding this event.

UMBC’s Haibin Zhang shares tips to secure data in the cloud

UMBC’s Haibin Zhang shares tips to secure data in the cloud

As more consumers rely on cloud-based data storage for everything from family photos to financial information, both experts and general users have voiced concerns about cloud security. In a new Conversation article recently published by Scientific American, Haibin Zhang, assistant professor of computer science and electrical engineering, explains precautions consumers can take to protect their files in the cloud.

Zhang explains that data stored and secured using commercial cloud storage systems is encrypted, which means that without the key, the information looks like a series of meaningless characters. Encryption keys have the potential to be misused, if they end up in the wrong hands, which can compromise the security of files stored in a cloud.

“Just like regular keys, if someone else has them, they might be stolen or misused without the data owner knowing,” says Zhang. “And some services might have flaws in their security practices that leave users’ data vulnerable.”

Zhang notes that some cloud services allow customers to maintain their encryption key themselves, which give the consumer the control in ensuring that their data remains safe. Other services keep the encryption keys internally and manage the security for their customers. He says that while each option has benefits, it is important to recognize that “some services might have flaws in their security practices that leave users’ data vulnerable.”

To keep data secure in the cloud, Zhang suggests using enhanced security features offered by cloud storage companies and taking additional precautions that are available to individual customers. He recommends that people use a cloud storage service that allows customers to encrypt their data before uploading it for storage, and to rely on services that have been “validated by independent security researchers.”

Read “How secure is your data when it’s stored in the cloud?” in The Conversation for Zhang’s additional recommendations on securing data on the cloud. The piece also appeared in Scientific American, and has so far been read nearly 20,000 times.

Adapted from a UMBC News article by Megan Hanks. Photo by Yuri Samoilov, CC by 2.0.

Jennifer Sleeman receives AI for Earth grant from Microsoft

Jennifer Sleeman receives AI for Earth grant from Microsoft

Visiting Assistant Professor Jennifer Sleeman (Ph.D. ’17)  has been awarded a grant from Microsoft as part of its ‘AI for Earth’ program. Dr. Sleeman will use the grant to continue her research on developing algorithms to model how scientific disciplines such as climate change evolve and predict future trends by analyzing the text of articles and reports and the papers they cite.

AI for Earth is a Microsoft program aimed at empowering people and organizations to solve global environmental challenges by increasing access to AI tools and educational opportunities, while accelerating innovation. Via the Azure for Research AI for Earth award program, Microsoft provides selected researchers and organizations access to its cloud and AI computing resources to accelerate, improve and expand work on climate change, agriculture, biodiversity and/or water challenges.

UMBC is among the first grant recipients of AI for Earth, first launched in July 2017. The grant process was a competitive and selective process and was awarded in recognition of the potential of the work and power of AI to accelerate progress.

As part of her dissertation research, Dr. Sleeman developed algorithms using dynamic topic modeling to understand influence and predict future trends in a scientific discipline. She applied this to the field of climate change and used assessment reports of the Intergovernmental Panel on Climate Change (IPCC) and the papers they cite. Since 1990, an IPCC report has been published every five years that includes four separate volumes, each of which has many chapters. Each report cites tens of thousands of research papers, which comprise a correlated dataset of temporally grounded documents. Her custom dynamic topic modeling algorithm identified topics for both datasets and apply cross-domain analytics to identify the correlations between the IPCC chapters and their cited documents. The approach reveals both the influence of the cited research on the reports and how previous research citations have evolved over time.

Dr. Sleeman’s award is part of an inaugural set of 35 grants in more than ten countries for access to Microsoft Azure and AI technology platforms, services and training.  In an post on Monday, AI for Earth can be a game-changer for our planet, Microsoft announced its intent to put $50 million over five years into the program, enabling grant-making and educational trainings possible at a much larger scale.

More information about AI for Earth can be found on the Microsoft AI for Earth website.

CSEE Professor Marie desJardins interviewed for Voices in AI podcast

Voices in AI – Episode 20: A Conversation with Marie desJardins

Byron Reese interviewed UMBC CSEE Professor Marie desJardins as part of his Voices in AI podcast series on Gigaom. In the episode, they talk about the Turing test, Watson, autonomous vehicles, and language processing.  Visit the Voices in AI site to listen to the podcast and read the interview transcript.

Here’s the start of the wide-ranging, hour long interview.

Byron Reese: This is Voices in AI, brought to you by Gigaom. I’m Byron Reese. Today I’m excited that our guest is Marie des Jardins. She is an Associate Dean for Engineering and Information Technology as well as a professor of Computer Science at the University of Maryland, Baltimore County. She got her undergrad degree from Harvard, and a Ph.D. in computer science from Berkeley, and she’s been involved in the National Conference of the Association for the Advancement of Artificial Intelligence for over 12 years. Welcome to the show, Marie.

Marie des Jardins: Hi, it’s nice to be here.

I often open the show with “What is artificial intelligence?” because, interestingly, there’s no consensus definition of it, and I get a different kind of view of it from everybody. So I’ll start with that. What is artificial intelligence?

Sure. I’ve always thought about artificial intelligence as just a very broad term referring to trying to get computers to do things that we would consider intelligent if people did them. What’s interesting about that definition is it’s a moving target, because we change our opinions over time about what’s intelligent. As computers get better at doing things, they no longer seem that intelligent to us.

We use the word “intelligent,” too, and I’m not going to dwell on definitions, but what do you think intelligence is at its core?

So, it’s definitely hard to pin down, but I think of it as activities that human beings carry out, that we don’t know of lower order animals doing, other than some of the higher primates who can do things that seem intelligent to us. So intelligence involves intentionality, which means setting goals and making active plans to carry them out, and it involves learning over time and being able to react to situations differently based on experiences and knowledge that we’ve gained over time. The third part, I would argue, is that intelligence includes communication, so the ability to communicate with other beings, other intelligent agents, about your activities and goals.

Well, that’s really useful and specific. Let’s look at some of those things in detail a little bit. You mentioned intentionality. Do you think that intentionality is driven by consciousness? I mean, can you have intentionality without consciousness? Is consciousness therefore a requisite for intelligence?

I think that’s a really interesting question. I would decline to answer it mainly because I don’t think we ever can really know what consciousness is. We all have a sense of being conscious inside our own brains—at least I believe that. But of course, I’m only able to say anything meaningful about my own sense of consciousness. We just don’t have any way to measure consciousness or even really define what it is. So, there does seem to be this idea of self-awareness that we see in various kinds of animals—including humans—and that seems to be a precursor to what we call consciousness. But I think it’s awfully hard to define that term, and so I would be hesitant to put that as a prerequisite on intentionality.

talk: Ferraro on Understanding What We Read and Share, 1pm Fri 11/10, ITE325, UMBC

 

ACM Faculty Talk Series

Understanding What We Read and Share:
Event Processing from Text and Images

Dr. Frank Ferraro, Assistant Professor, CSEE
1:00-2:00pm Friday, 10 November 2017, ITE 325, UMBC

A goal of natural language processing (NLP) is to design machines with human-like communication and language understanding skills. NLP systems able to represent knowledge and synthesize domain-appropriate responses have the potential to improve many tasks and human-facing applications, like virtual assistants such as Google Now or question answering systems like IBM’s Watson.

In this talk, I will present some of my work—past, on-going, and future—in developing knowledge-aware NLP models. I will discuss how to better (1) encode linguistic- and cognitive science-backed meanings within learned word representations, (2) learn high-level representations for document and discourse understanding, and (3) how to generate compelling, human-like stories from sequences of images.

Frank Ferraro is an assistant professor in the CSEE department at UMBC. His research focuses on natural language processing, computational event semantics, and unlabeled, structured probabilistic modeling over very large corpora. He has published basic and applied research on a number of cross-disciplinary projects, and has papers in areas such as multimodal processing and information extraction, latent-variable syntactic methods and applications, and the induction and evaluation of frames and scripts.

Gymama Slaughter: The Art of Powering Implantable Electronics

The Art of Powering Implantable Electronics

UMBC professor Gymama Slaughter give a short talk at the Grit-X event on her recent research on powering implantable devices for medical applications.

The number of smart implantable devices is on the rise, especially as we approach the ramping up of the “internet of things.” A key challenge for implantable electronic devices has been keeping these devices properly and conveniently powered. Current battery technologies are sealed within these devices, thereby forcing the surgical replacement of the device once the battery is depleted. We need an inconspicuous means of powering implantable electronics with imperceptible methods that moves us toward new innovative solutions to the power challenge in implantable devices. A lightweight bio-solution that leverages the biochemical energy from human biological fluids is a step forward for powering these smart implantable technologies.

Marie desJardins receives UC Berkeley Distinguished Alumni Award in Computer Science

Prof. Marie desJardins receives UC Berkeley Distinguished Alumni Award in Computer Science

CSEE professor Marie desJardins has been selected for the 2018 Distinguished Alumni Award in Computer Science by the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. Professor desJardins received a Ph.D. degree in Computer Science from UC Berkeley in 1992.

Each year since 1991, the award has recognizes two distinguished alumni of Berkeley who have made valuable contributions to the field of computer science. Past recipients can be seen here The award will be presented during the Berkeley EECS Annual Research Symposium (BEARS ) on in February 2018.

CSEE faculty Banerjee and Slaughter to give short talks at UMBC Grit-X, Sat. 10/14, UMBC

Two CSEE faculty give short talks at UMBC Grit-X

Back by popular demand from UMBC’s 50th Anniversary weekend, it’s Grit-X! Head to UMBC’s Black Box Theatre on Saturday, 14 October 2017 from 10:00 a.m. to noon, and be enlightened by short TED-style talks from some of the most intriguing alumni and faculty minds. See the complete program and register for the event here.

The first session (10:00—10:30am) includes a talk by CSEE professor Nilanjan Banerjee:

When What You Wear Understands You, Prof. Nilanjan Banerjee

How can cutting-edge research on textile sensors and wearable radar sensors help us recognize gestures, monitor sleep fragmentation, and diagnose sleep disorders? The Banerjee lab has developed and applied sensors to users with upper extremity mobility impairments, adults suffering from insomnia and restless leg syndrome, and kids with attention deficit/hyperactivity disorder, with the intent to begin answering that question.

and the second session (10:45—11:15am) has one by CSEE professor Gymama Slaughter:

The Art of Powering Implantable Electronics, Gymama Slaughter

The number of smart implantable devices is on the rise, especially as we approach the ramping up of the “internet of things.” A key challenge for implantable electronic devices has been keeping these devices properly and conveniently powered. Current battery technologies are sealed within these devices, thereby forcing the surgical replacement of the device once the battery is depleted. We need an inconspicuous means of powering implantable electronics with imperceptible methods that moves us toward new innovative solutions to the power challenge in implantable devices. A lightweight bio-solution that leverages the biochemical energy from human biological fluids is a step forward for powering these smart implantable technologies.

Marie desJardins receives award for inspiring women to pursue careers in computing, engineering and math

 

Professor Marie desJardins was selected for the 2017 A. Richard Newton Educator ABIE Award by the Anita Borg Institute. The annual award recognizes an educator who has developed innovative teaching practices and approaches that attract girls and women to computing, engineering, and math. As part of the award Dr. desJardins will take part in a panel on efforts to increase women’s representation and success in technology at the 2017 Grace Hopper Celebration of Women in Computing in Orlando this October.

Increasing gender diversity in computing has become both a professional focus and personal commitment for desJardins over the course of her career. “It’s part of a broader equity issue — for everyone to be able to envision themselves as creators of technology, and for the future of technology to be created by a diverse community of scientists and engineers,” she says.

This summer, desJardins shared her passion for encouraging girls and women to pursue careers in computing with nearly 150 elementary and middle school girls who attend the Mind, Body, Coding camp at UMBC. “Seeing these young girls whose lives could be transformed by greater access to computing is incredibly inspiring,” she says. “It’s a big part of what gets me energized every day to do the work that I do, from supporting diversity in K-12 computing education to mentoring junior female faculty who will train the next generation of computer scientists.”

The award announcement cited Professor desJardins for her many accomplishments in education, research and support of and commitment to improving student diversity, access, and quality of computer science courses at the high school level.

“Marie is known on campus and throughout her professional community for her dedication to mentoring, diversity, outreach, and innovative educational practices. Marie was named one of UMBC’s 10 “Professors Not to Miss” in 2011, and is regularly sought out to give invited talks to student groups. In 2010, she was invited to be a CRA-W/CDC Distinguished Lecturer. She was also one of the inaugural Hrabowski Innovation Fellows, and with that award, helped to create the ACTIVE Center, a new classroom that supports pedagogical approaches that increase student engagement and active problem solving.

Marie has become known nationally for her support of and commitment to improving student diversity, access, and quality of computer science courses at the high school level, and has received multiple NSF awards to support her efforts in this area. She is the lead PI on the NSF-sponsored “CS Matters in Maryland” project, which is creating curriculum and training high school teachers to teach the new AP CS Principles course. She has built a statewide coalition to increase access to K-12 CS education, with a focus on inclusion and diversity. She is also the Maryland team leader for the Exploring Computing Education Pathways (ECEP) Alliance, an NSF-funded initiative that is coordinating state-level CS education efforts.

Marie is UMBC’s 2014-17 Presidential Teaching Professor and was a founding member of the Maryland chapter of the Computer Science Teachers Association, for which she is currently the university liaison. Her research focuses on artificial intelligence, particularly machine learning, planning and decision making, and multi-agent systems. She has published over 100 scientific papers on these topics, and was recently named one of the “Ten AI Researchers to Follow on Twitter” by TechRepublic and one of “14 Women in AI You Should Follow on Twitter” by craigconnects.

At UMBC, Marie has been PI or co-PI on over $6,000,000 of external research funding, including a prestigious NSF CAREER Award, and has graduated 11 Ph.D. students and 25 M.S. students. She is particularly well known on campus and in her professional community for her commitment to student mentoring. She has been involved with the AAAI/SIGART Doctoral Consortium for the last 16 years and has worked with 90 undergraduate researchers and high school student interns. She was awarded the 2014 NCWIT Undergraduate Research Mentoring Award and the 2016 CRA Undergraduate Research Mentoring Award in recognition of her commitment to undergraduate research.”

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