Jenny Marcinkowski | Department of Computer Science

Colloquium Talk with Dr. Michael E. Locasto, November 15: An Operational Definition of Parsing (and its Consequences)

Posted on November 15, 2022 by Jenny Marcinkowski • 0 Comments

Dr. Michael Locasto, CTO at Narf Industries, will give a colloquium talk, titled “An Operational Definition of Parsing (and its Consequences)” on Tuesday, November 15 from 12:30 – 1:30 PM in the Library Auditorium.

See below for more information about Dr. Locasto.

Abstract: Narf Industries conducts advanced R&D in the space of vulnerability analysis, reverse engineering, and exploit development. This talk presents some our work conducted under the SafeDocs research program, which is concerned with how to make complex document formats safe to parse and consume. We will share our recent research on the unaddressed data management problem inherent in parsing (i.e., input language recognition) and how the problem might be addressed by the novel concept of dynamic progressive types. Far from being of interest to Computer Science theorists, the question of safe recognition is of utmost practical importance to software developers. Many kinds of vulnerabilities occur within input-handling code. The Language-theoretic Security paradigm (LangSec) posits that this association is not merely coincidental, nor is it due to simple ad doc mistakes. Rather, vulnerabilities and exploitation continue to occur because practical software engineering finds it difficult to take advantage of core Computer Science concepts of grammar definition, parsing, and language recognition. In this way, LangSec offers a “science of insecurity” by indemnifying consistent anti-patterns across many different vulnerabilities over time. Our work under SafeDocs shows how to use the latest tools in parser combinator libraries and format-aware tracers to define, guard, and monitor safe parsing.

Speaker Bio: Dr. Michael E. Locasto serves as the CTO at Narf Industries, a cadre of cybersecurity experts tackling some of the most important cybersecurity problems facing society, industry, and government. From 2016 to 2021, Dr. Locasto was a Principal Computer Scientist at SRI International in the Infrastructure Security Group of their Computer Science Laboratory. He served as a PI for four DARPA programs, and also co-led SRI’s Internet of Things Security and Privacy Center. Prior to joining SRI, he was a tenured Associate Professor at the University of Calgary, where he directed the Trustworthy Systems Group and conducted research in trustworthy systems, cooperative security mechanisms, and software security. Dr. Locasto has co-authored over 80 publications in the first of computer security, and he holds 14 U.S. patents related to software security and intrusion detection. He received his Ph.D., MPhil, and MSc degrees in Computer Science from Columbia University and graduated magna cum laude from The College of New Jersey (TCNJ) with BSc in Computer Science.

Fall 2022 Internship Information Sessions

Posted on November 15, 2022 by Jenny Marcinkowski • 0 Comments

REMINDER: All CS Majors are required to attend one internship information session before they can apply for internship (CSC 399) for credit.

Be sure to check Dr. Papamichail’s website and come prepared with any additional questions you might have.

Wednesday, November 16: (7:00 – 7:45 PM)

Zoom session link: zoom

Colloquium Talk with Dr. Matthew Fronheiser, November 4: AI/ML in Medical Imaging: Improving Care with Technology

Posted on November 2, 2022 by Jenny Marcinkowski • 0 Comments

Dr. Matt Fronheiser, a scientific director at Bristol-Myers Squibb will give a colloquium talk, titled “AI/ML in Medical Imaging: Improving Care with Technology” on Friday, November 4 from 12:30 – 1:30 PM in Science Complex P-101.

See below for more information about Dr. Fronheiser .

Abstract: This talk will provide an overview of AI/ML applications in medical imaging, looking across the image pipeline from image acquisitions through patient diagnosis and risk stratification. Examples of clinically available technology will be discussed, with a focus on how these tools are changing the imaging workflow. This will be followed by a brief review of current research utilizing medical images to create prognostic and predictive models from large sets of clinical data.

Speaker Bio: Matt Fronheiser has over 15 years of experience in the medical imaging industry. He received his PhD from Duke University with a research focus on real-time 3D ultrasound. After receiving his degree, he spent several years performing optoacoustic imaging research for breast cancer. He currently works at a pharmaceutical company, Bristol-Myers Squibb, as a scientific director implementing imaging in clinical trials.

CS Senior Presents Research at AAAI FSS ToM for Teams

Posted on November 11, 2021 by Jenny Marcinkowski • 0 Comments

Alexander (AJ) Viola, a computer science senior, presented his recent research work titled “Constructivist Approaches for Computational Emotions: A Systematic Survey” at the Association for the Advancement of Artificial Intelligence (AAAI) Fall Symposium Series (FSS) Computational Theory of Mind for Human-Machine Teams (ToM) on November 4, 2021.

Under the supervision of his mentor, Dr. Sejong Yoon, AJ conducted a systematic survey on an emerging topic in affective computing that aims to design and reason human emotions and computationally reproduce or predict them. This work is the outcome of his years of mentored research under Dr. Yoon’s supervision and will be submitted for publication as a post-proceeding journal article in December.

For more information on the AAAI FSS ToM for Teams, see: https://sites.google.com/view/tomforteams/

Colloquium Talk with Dr. Paul Youping Xiao, November 5: Deep Learning and Biomedical Imaging

Posted on November 2, 2021 by Jenny Marcinkowski • 0 Comments

Dr. Paul Youping Xiao of Bristol Meyers Squibb will give a virtual colloquium talk on Friday, November 5, from 12:30 – 1:30 PM. Dr. Xiao has done extensive research in brain imaging and has pioneered the application of machine learning to the analysis of intrinsic optical imaging.

See below for more information about Dr. Xiao and the links for the event.

Abstract: Target segmentation is a crucial step in the analysis of biomedical images. Recent advances in deep learning have enabled automation of semantic and instance segmentations. At BMS we have applied the U-Net neural network and its variant to the segmentation of various targets in microscopic images with a sub-cellular resolution. The automated and consistent segmentations enable quantitative analyses of drug occupancy, T-cell infiltration and other metrics important for the development of novel drugs. The application of U-Net to analyzing biomedical images of various modalities will also be discussed.

Speaker Bio: Paul Youping Xiao has a bachelor’s degree in electronics, a master’s degree in physiology, and PhD in neuroscience. He has extensive experience in brain imaging including the discovery of color maps in the primate visual cortex. He pioneered the application of machine learning to the analysis of intrinsic optical imaging. At BMS he is leading the effort of automating high-content imaging with artificial intelligence.

Zoom Meeting (ID: 941 0711 6653/ Password: d7dnMrs5)

https://tcnj.zoom.us/j/96195035078?pwd=OTZ4V3VkZHFPZ1p6aGphTnAwUXZ0QT09

Colloquium Talk with Dr. Faisal Khan, October 19: AI and Data Science in Healthcare and the Lifesciences

Posted on October 13, 2021 by Jenny Marcinkowski • 0 Comments

Dr. Faisal M. Khan, the Executive Director of Advanced Analytics and Artificial Intelligence at AstraZeneca, will give a virtual colloquium talk on Tuesday, October 19, from 12:30 PM – 1:30 PM. Dr. Khan is known for his work on the applications of machine learning and AI for healthcare and the life sciences.

See below for more information about Dr. Khan and the links for the event.

Abstract: Dr. Khan will discuss the broad range of applications that data science and AI are driving to impact live and improve health in healthcare and the life sciences. The talk will focus on various application areas, algorithmic and real-world challenges and issues which emerge, as well as things to keep in mind when deploying within regulated and industrial environments.

Speaker Bio: Faisal M. Khan, Ph.D. is the Executive Director of Advanced Analytics and Artificial Intelligence at AstraZeneca. His team focuses on the applications of AI and data science throughout the drug discovery lifecycle, from target identification through Phase 3 trials and beyond. His interests focus on the intersections of data science, digital health, biostatistics, bioimaging, personalized medicine, and healthcare delivery. His career has encompassed all aspects of healthcare and biomedical analytics, including diagnostics, devices, clinical trials/therapeutics, and payers/insurance. Dr. Khan has worked or consulted across academia and industry with both startups and Fortune-50 companies. He has over 100 published papers, abstracts, and patents on the applications of machine learning and artificial intelligence for healthcare and the life sciences.

Zoom Meeting (ID: 961 9503 5078 / Password: N842wT31)