Events

Research & Guest Speaker Events

Graduate Student Research Talk
We will invite several Ph.D. students from Pace University and M.S. students from BU MET to introduce their research work. The topics will include Artificial Intelligent, Machine Learning, Data Analytics, Image Processing, and Computer Vision. This will be a good learning opportunity if you are interested in research but need help figuring out how to start.

Thursday, February 9
12:30 p.m. EST
Register Online

Career Events & Workshops

Career Development Tips

Looking for your first professional job? Making a career change? Join us to learn about job searching tips and resources for those interested in pursuing roles related to Computer Science. We’ll also discuss ways to tailor your cover letter and resume for Computer Science related positions. This session will be facilitated by Meridith Apfelbaum, Director of Student Career Development, Metropolitan College.

Wednesday, February 8
12:00 PM EST
Register Online

Social & Informational Events

Event Archive

TECH Byte Archive

The TECH Byte series features a 20-30 minute virtual talk by a MET CS faculty member on a technical topic followed by Q&A.

Enterprise IoT Devices

Faculty Speaker: Adam Arakelian, Lecturer
October 14, 2021

Abstract: We know IoT devices like Amazon Alexa, Google Home and other primarily consumer focused IoT. However, IoT is more and more pervasive across not just simple consumer products such as home assistants, electronics and televisions, but are now beginning to show up in other areas of industry, automotive, health care and data centers.

How will we manage IoT devices at an enterprise level? How do we begin to shift from IoT being a home assistant to the medical industry or into the data center?

In this discussion, we will talk about what industries IoT is beginning to show up in and how these organizations need to be able to ensure quality and compliance.

Software Verification Architecture

Faculty Speaker: Alex Elentukh, Lecturer
Moderated by: Andrey Blidman, Computer Science Program Coordinator
December 3, 2020

Abstract: In this TECH Byte, Professor Elentukh will discuss the software verification architecture. With an ever growing number of various test types, it is crucial to strategically position tests into a coherent architecture, for both, test design and execution. In financial and medical devices industries, IT departments commonly employ more testers than coders. This is due to a huge risk involved with even a minuscule defect. Some companies use a unified title of a “software team member” responsible for all relevant activities. Still, the verification task, including writing and executing test cases, is always well-pronounced. During the presentation, Professor Elentukh will explore several industry-standard verification architectures and gladly respond to comments.

Why Software Development Methodologies Don’t Matter

Faculty Speaker: Adam Arakelian, Lecturer
Moderated by: Andrey Blidman, Computer Science Program Coordinator
November 13, 2020

Abstract: Software Development Methodologies don’t matter! That’s right, they don’t matter. In this TECH Byte, Professor Arakelian will talk about development philosophy vs. methodologies and explore methodologies such as scrum development, which are in direct conflict with the philosophical nature of Agile development. Professor Arakelian will also explore what organizations can do in order to embrace certain philosophies and adopt methodologies that work for their delivery of business value.

Using Unknowns to Reliably Estimate Software Project Duration

Faculty Speaker: John Keklak, Lecturer
Moderated by: Andrey Blidman, Computer Science Program Coordinator
October 20, 2020

Abstract: In this TECH Byte, Professor Keklak will discuss how to use the “unknowns” concept (presented earlier this summer in the TECH Byte entitled “The Power of Unknowns”) to reliably estimate how much time is required to complete a software project. In addition to presenting a method for computing reliable time estimates, Professor Keklak will point out common missteps that lead to chronic underestimation of time required to complete a project.

The Power of Unknowns

Faculty Speaker: John Keklak, Lecturer
Moderated by: Andrey Blidman, Computer Science Program Coordinator
September 15, 2020

Abstract: Identifying and focusing on unknowns is the key to software project success. In this TECH Byte, Professor Keklak will define what he means by “unknowns” and how to use them when communicating with software team members to keep projects moving to successful completion.

Healthcare Data Analytics: Medical Expenditures of Diabetes-Related Hospitalizations in the United States

Faculty Speaker: Dr. Guanglan Zhang, Associate Professor of Computer Science
Moderated by: Andrey Blidman, Computer Science Program Coordinator
August 4, 2020

Abstract: According to the 2017 National Diabetes Statistics Report, over 30 million (9.4%) of Americans have diabetes as of 2015. At the same time, hospital stays involving patients with diabetes contributed almost $83 billion or 23% of the total hospitalization costs in the United States. Understanding diabetes-related medical expenditures is essential in predicting the financial impact caused by the disease and planning for its better management. Using data from the Truven Health Analytics MarketScan Databases, we studied the characteristics of medical expenditures associated with diabetes-related hospitalizations (inpatient data). We tried to identify the specific macro-level (socio-economic) and micro-level (individual-patient-related) factors that affect the cost of inpatient care among diabetes patient and to study if there is a significant difference between inpatient care expenditures of women and men.

Machine Learning for Lung Cancer Screening

Faculty Speaker: Dr. Vineet Raghu, Lecturer
Moderated by: Andrey Blidman, Computer Science Program Coordinator
July 7, 2020

Abstract: Lung cancer is the leading cause of cancer death in the United States, as it accounts for more cancers than the next three cancer types combined. The primary known cause of lung cancer is cigarette smoking; however, it is unclear how to decide which smokers are at the highest risk for developing lung cancer. The National Lung Screening Trial showed that mortality due to lung cancer can be reduced through the use of screening. Screening consists of scanning the chest using low-dose Computed Tomography to search for the presence of abnormal growths in the lung (lung nodules). However, the majority of lung nodules (96%) turn out to be benign and do not become cancerous. This raises two pressing questions: 1) How do we determine who should be screened for lung cancer? and 2) How do we know which nodules will eventually become cancerous? In this talk, I explore whether machine learning techniques can be used to address this question. I discuss deep learning from chest x-rays to select high-risk individuals for screening, and I discuss graphical models from CT scan data to identify lung nodules likely to become cancerous.

The Unseen Effects of Technology

Faculty Speaker: Dawson Williams, Lecturer
Moderated by: Andrey Blidman, Computer Science Program Coordinator
June 17, 2020

Abstract:We will go into the history of technology, the current views on technology and finally the impact we can have (and the care we should take) in employing technology.

Antidote Application: An Educational System for Treatment of Common Toxin Overdose

Speaker: Dr. Guanglan Zhang, Associate Professor of Computer Science
Moderated by: Andrey Blidman, Computer Science Program Coordinator
June 3, 2020

Abstract:Poisonings account for almost 1% of emergency room visits each year. Time is a critical factor in dealing with a toxicologic emergency. Delay in dispensing the first antidote dose can lead to life-threatening sequelae. Current toxicological resources that support treatment decisions are broad in scope, time-consuming to read, or at times unavailable. Our review of current toxicological resources revealed a gap in their ability to provide expedient calculations and recommendations about appropriate course of treatment. To bridge the gap, we developed the Antidote Application (AA), a computational system that automatically provides patient-specific antidote treatment recommendations and individualized dose calculations. We implemented 27 algorithms that describe FDA (the US Food and Drug Administration) approved use and evidence-based practices found in primary literature for the treatment of common toxin exposure. The AA covers 29 antidotes recommended by Poison Control and toxicology experts, 19 poison classes and 31 poisons, which represent over 200 toxic entities. To the best of our knowledge, the AA is the first educational decision support system in toxicology that provides patient-specific treatment recommendations and drug dose calculations. The AA is publicly available at http://projects.met-hilab.org/antidote/.

The Visualization of Evolving Software Design

Speakers: Dr. Eric Braude, Associate Professor of Computer Science; Dr. Michael Huang, Lecturer; Aviral Srivastava, MS in Computer Science graduate student
Moderated by: Andrey Blidman, Computer Science Program Coordinator
May 21, 2020

Abstract: The visualization of evolving software design is as important as ever, and UML should be an effective means for this; however, the overwhelming tangle of traditional whole-UML has turned out to be impractical for the development of realistically-sized applications. We have developed a UML form called RUML (Rectangular UML) that addresses this. RUML formats class models, use cases, and sequence diagrams for evolving applications at scale on a single spreadsheet. Its compactness and standardized format promote unified overviews, selective focus, and continuous use-case-to-code round-trip engineering.

Except for small portions, the software industry rarely uses classical UML for large-scale applications due to its complexity. Utilizing a large existing open source application, we demonstrate the advantages of RUML for large-scale applications. We have also developed a tool to create RUML from source code.

Practical Adversarial Attacks Against Speech Recognition Platforms

Faculty Speaker: Dr. Shengzhi Zhang, Assistant Professor
Moderated by: Andrey Blidman, Computer Science Program Coordinator
May 14, 2020

Abstract: The popularity of ASR (automatic speech recognition) systems, like Google Voice, Cortana, Amazon Echo, brings in security concerns, as demonstrated by recent attacks. The impacts of such threats, however, are less clear, since they are either less stealthy (producing noise-like voice commands), requiring the physical presence of an attack device (using ultrasound), or not practical (unable to attack the physical speech recognition devices). In this talk, I will show that not only are more practical and surreptitious attacks feasible but they can even be automatically constructed. Specifically, the voice commands can be stealthily embedded into songs, which, when played, can effectively control the target system through ASR without being noticed. I will present the novel techniques that address a key technical challenge: integrating the commands into a song in a way that can be effectively recognized by ASR through the air, in the presence of background noise, while not being detected by a human listener. Our research shows that this can be done automatically against real world ASR systems, and even devices like Google Home, Amazon Echo, Apple Siri, etc.

Building Bots and Apps in Slack

Faculty Speaker: Adam Arakelian, Lecturer
Moderated by Andrey Blidman, Computer Science Program Coordinator
May 7, 2020

Abstract: Heard of slack and used it? Ever built a bot or app in slack? Do you often hear Slack and DevOps together? In this talk we can unleash the power of Slack as Adam Arakelian will walk you through how to connect your various DevOps tools to Slack and how to create a bot or an application changing how you use slack to a PaaS in order to be more productive.

Career Guest Speaker Event Archive

Building Your Career in Tech? Ask the Experts. Our panelists will discuss their career paths and answer questions about a variety of topics including tips to find jobs, interview techniques and industry insights.

Resume & Cover Letter Workshop
October 17, 2022

Expert Panelist: Narali Taglialavore, Associate Director of Career Education at Boston University’s CCD

Promotion & Salary Negotiation 101
November 9, 2021

Expert Panelists:
Adam Arakelian, Lecturer, Director of Engineering, DELL EMC
Dawson Williams, Lecturer, Head of Research & Product Development at Plum Laboratories, LLC
Moderated by Dr. Anatoly Temkin, Chair, Department of Computer Science

Building Your Career in Tech? Ask the Experts
April 14, 2021

Panelists:
Jack Polnar, Data Management Specialist, Newton Public Schools
Digisha Singhal, Data Analyst, BlueCross BlueShield
Melissa Mednikoff, Business Intelligence Engineer, Amazon
Moderated by Dr. Anatoly Temkin, Chair, Department of Computer Science

Healthcare Industry Career Panel
March 23, 2021

Healthcare Industry Experts
Mike Levinger, Chief Operating Officer, Primaris Healthcare
John D’Amore, Founder, Diameter Health
Jon Long, Clinical Informatics, Providence Saint Joseph Health
Moderated by Dr. Anatoly Temkin, Chair, Department of Computer Science

Student & Alumni Panel: Interning in Tech
February 24, 2021

Student & Alum Panelists:
Vamsi Krishna Reddy Padala, MS in Computer Science, Intern at Labby Inc.
Asad Malik, MS in Computer Information Systems (MET ’21), Interned at Philips Research
Shreyas Prakash, MS in Computer Science, Intern at Tesla and Nokia

Moderated by Ronette Lyle, Academic Program Administrator , Department of Computer Science

Industry Panel: Building Your Career in Tech
January 26, 2021

Expert Panelists
Adam Arakelian, Director of Engineering, Dell EMC
Jennifer Pixley, Sr. Consultant Program Manager, Dell Technologies
Dawson Williams, Head of Research & Product Development at Plum Laboratories, LLC
Moderated by Dr. Anatoly Temkin, Chair, Department of Computer Science