We at UMBC ACM x Vinjamuri Lab invite you all to join us at “Synergy-based Brain-Machine Interfaces” a research talk by our new CSEE professor Dr. Ramana Kumar Vinjamuri. The talk focus on Dr. Ramana’s ongoing research at the Lab and how he plans to expand it further. As attendees, you get a chance to hear Dr. Ramana speak in detail about his work and get a chance to talk with him regarding contributing further to the field.
When: Friday; Oct 23th, 2020 Time:12:00 P.M. to 1:00 P.M Meeting Link: umbc.webex.com/meet/rvinjam1 (ID: 1607007544) Join by phone: (US Toll) +1 202-860-2110 (access code: 1607007544) Contact: umbcacmofficers@gmail.com | samit1@umbc.edu
It is that time in the semester when UMBC’s student branches of The Association for Computing Machinery (ACM) and Institute of Electronics and Electrical Engineers (IEEE) host the annual CSEE Welcome Event. The event will be held on Friday, October 2, 2020, from 12-2 pm and YOU are invited! Unfortunately, we cannot hold this event in the traditional way, but do not fear you will still be able to gather with your fellow peers and faculty members. We will be hosting the event virtually on a Discord server that was created specifically for this event, the link to the server is https://discord.gg/YXuMZzm. There will be multiple chat rooms covering a variety of computer science, computer engineering, and many other technical topics. Some faculty members will even be giving presentations on their research and areas of study. You can interact with them, talk about your interests, your experience with the field, and who knows what opportunity you can grab?
So, come join a chat room relating to your favorite topics and start communicating with your fellow students and faculty who share the same interests. This event is a great way for you to network, meet new people with shared interests, get to know your professors and instructors better, and possibly even land a research position! We hope to see you there!
On behalf of the UMBC Association for Computing Machinery (ACM) Chapter you are invited to Hi-Tea for this Spring 2020 semester. Date: Friday, February 21st, 2020 Time : 12:00 p.m. to 12:30 p.m. Venue: ITE Building, 3rd Floor hallway outside of Suite 325 Refreshments, Meet with students, faculty and staff.
This is an opportunity to find out about interesting cutting/bleeding-edge research,mingle, network, explore ideas, collaborate and treat yourself to a wonderful lunch while you’re at it! Faculty, staff and especially students of the CSEE department are encouraged to participate.
Location : outside ITE 325 (Hi-Lunch) Date: December 6th 2019, Friday Time: 1pm to 1:30 pm (Hi-Lunch)
On behalf of the UMBC Association for Computing Machinery (ACM) Chapter you are invited to Hi-Tea for this Fall 2019 semester. Date: Friday, November 1st, 2019 Time : 12:30 p.m. to 1:00 p.m. Venue: ITE Building, 3rd Floor hallway outside of Suite 325 Refreshments, Meet with students, faculty and staff.
The ACM and IEEE student chapters of UMBC are back together for an event to mark and celebrate the mid-point of this fall semester.
Take this opportunity to mingle, network, explore ideas, collaborate and treat yourself to a wonderful feast while you’re at it! Faculty, staff and especially students of the CSEE and IS departments are encouraged to participate.
Dr. David Chapman Assistant Professor, Computer Science 11:30 PM – 12:30PM , Friday October 11th 2019 , ITE 346, UMBC
Abstract: We propose to develop a novel quantitative algorithm to estimate the probability of malignancy of pulmonary nodules from a time series of successive LDCT screenings in patients with a high risk of developing lung cancer. Lung cancer kills approximately 200,000 Americans annually and is responsible for 25% of all cancer-related deaths. Imaging with Low Dose Computed Tomography (LDCT) has been proven to reduce Non-Small Cell Lung Cancer (NSCLC) mortality by 20% and has become standard guidelines (NLST 2011a,b). These new clinical guidelines have led to hospitals, including Mercy Medical Center in Baltimore, to collect an abundance of LDCT images of high risk individuals since 2014. These LDCT images along with additional CT/biopsy and PET/CT images collected by Mercy hospital in Baltimore have now been organized into an IRB exempt clinical research dataset to use anonymous radiology imagery for the purpose of training and evaluation of improved Computer Aided Diagnosis (CAD) algorithms. Imaging biomarkers including cross-sectional diameter, calcification patterns, irregular margins, wall thickness all of which are known to have discriminating power to differentiate benign and malignant pulmonary nodules. Furthermore, temporal changes in the size and biomarker characteristics of pulmonary nodules over multiple images are also highly informative and yield greater ability to differentiate malignancy. The proposed CAD algorithm will be capable of detecting and quantifying temporal changes of imaging biomakers in order to estimate malignancy probability. The algorithm will make use of convolutional neural networks for feature extraction as well as recurrent neural networks to analyze the temporal changes in extracted features. The Mercy hospital dataset contains approximately 30,000 chest CT images. Training of the algorithm will incorporate semi-supervised learning using chest CT images from Mercy as well as the public portion of the NLST dataset. A fraction of the Mercy images will be designated for evaluation of the sensitivity and specificity of the proposed algorithm for determining nodule malignancy. Pulmonary nodules remain a challenging area for clinical management decision-making, and improved analysis of malignancy including temporal changes of imaging biomarkers have the potential to reduce patient morbidity and mortality through earlier and more accurate diagnosis.
On behalf of the UMBC Association for Computing Machinery (ACM) Chapter you are invited to Second Hi-Tea for this Fall 2019 semester. Date: Friday, October 11th, 2019 Time : 12:30 p.m. to 1:00 p.m. Venue: ITE Building, 3rd Floor hallway outside of Suite 325 Refreshments, Meet with students, faculty and staff.
