Month: November 2017

[ACM Tech Talk ]A Practitioner’s Introduction to Deep Learning

Presented by :  Ashwinkumar Ganesan, PhD student

1 pm – 2 pm Friday, November 17 2017 , ITE 325 UMBC

In recent years, Deep Neural Networks have been highly successful at performing a number of tasks in computer vision, natural language processing and artificial intelligence in general. The remarkable performance gains have led to universities and industries investing heavily in this space. This investment creates a thriving open source ecosystem of tools & libraries that aid the design of new architectures, algorithm research as well as data collection.


This talk (and hands-on session) introduce people to some of the basics of machine learning, neural networks and discusses some of the popular neural network architectures. We take a dive into one of the popular libraries, Tensorflow, and an associated abstraction library Keras.

Workshop requirements: Laptop

Following are the list of libraries to be installed:
1. numpy, scipy & scikit-learn.
2. tensorflow / tensoflow-gpu. (The first one is the GPU version).
3. matplotlib for visualizations (if necessary).
4. jupyter & ipython. (We will use python2.7 in our experiments).
Following are helpful links:
All of the above can be installed using pip. In case of windows or (any other OS) consider doing an installation of anaconda that has all the necessary libraries.

[Tech Talk] Understanding What We Read and Share: Event Processing from Text and Images

Dr. Frank Ferraro, Assistant Professor, CSEE 
1 pm – 2 pm Friday, November 10, 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.
Dr. 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.

[Tech Talk] How to make yourself comfortable with coding interviews

ACM Career Talk Series – 1

How to make yourself comfortable with coding interviews

Chetan Sai Kumar Thalisetty, 2nd year Master student in C. E.
2 pm – 3 pm Friday, November 3, 2017, ITE 217, UMBC

Getting first-hand knowledge on anything is a privilege, particularly when it helps enhancing your career. The speaker will shed light on ways to prepare for coding interviews drawing on his own experiences, both mentally and technically. He would also indulge the audience on the interview that led him to get the job.

Hi-Tea Series – III

The UMBC ACM Student Chapter welcomes you to the Hi-Tea event.

An opportunity to mingle, network, explore ideas, collaborate and treat yourself to a tea and snacks while you’re at it!

We welcome one and all!

Date: Thursday, November 2, 2017
Time: 1.30 pm-2.00 pm
Venue: CSEE hallway outside ITE 325
Hosted by: Agniva Banerjee