Home
About
People
Publications
Seminars
- Seminar Calendar
- Seminar Videos
Workshops
HLT Masters
Resources

Graduate Students

A-J
K-Q
R-Z

Carlos Aguirre | Website | Publications
Niyati Bafna | Website | Publications
Elina Baral
Andrew Blair-Stanek | Website | Publications
Isabel Cachola | Website | Publications
Tianyu Cao | Website | Publications
Cameron Carpenter
Jonathan Chang
Alexandra DeLucia | Website
Leo Du | Publications
Seth Ebner | Website
Anna Favaro
William Fleshman
Matthew Francis-Landau | Website | Publications
Dongji Gao | Publications
Sophia Hager
Keith Harrigian| Website | Publications
Amir Hussein
Ruizhe Huang
Zili Huang
Maliha Jahan | Publications
Zhengping Jiang | Website | Publications
Sonal Sunil Joshi

Aleem Khan | Website | Publications
Brian Lu
Xinyuan (Henry) Li
Yen-Ju Lu
Marc Marone | Website | Publications
Arya McCarthy | Website | Publications
Sabrina Mielke | Website | Publications
David Mueller | Website | Publications
Bismarck Odoom
Jiefu Ou
Candice Laine Penelton
Gwenyth Portillo Wightman | Website | Publications
Guanghui Qin | Website | Publications

Qinwan Rabbani
Desh Raj | Website | Publications
Krithika Ramesh
Samik Sadhu
Elizabeth Salesky | Website | Publications
Kate Sanders | Website | Publications
Yiwen Shao
Suzanna Sia | Website
Rafael Rivera Soto
Nate Robinson
Jamie Rosas-Smith
Kaiser Sun | Website | Publications
Steven Tan
Neha Verma
Tim Vieira | Website | Publications
Andrew Wang
Helin Wang
Miriam Wanner
Nathaniel Weir
Orion Weller | Website | Publications
Rachel Wicks
Cihan Xiao
Haoran Xu | Website | Publications
Jack Zhang
Xuan Zhang | Website | Publications

People

Faculty
- Affiliated Faculty
- Former Faculty
Postdocs
- Current Postdocs
- Former Postdocs
Graduate Students
Staff
Alumni

Subscribe to the CLSP Seminars Mailing List

Upcoming Seminars

12:00 pm Emma Strubell (Carnegie Mellon U... @ Hackerman Hall B17

Emma Strubell (Carnegie Mellon U... @ Hackerman Hall B17

Sep 25 @ 12:00 pm – 1:15 pm

12:00 pm CLSP Student Seminar – Zhengping... @ Hackerman Hall B17

CLSP Student Seminar – Zhengping... @ Hackerman Hall B17

Sep 29 @ 12:00 pm – 1:15 pm

12:00 pm CLSP Student Seminar – Anna Favaro @ Hackerman Hall B17

CLSP Student Seminar – Anna Favaro @ Hackerman Hall B17

Oct 2 @ 12:00 pm – 1:15 pm

Add

Add to Timely Calendar
Add to Google
Add to Outlook
Add to Apple Calendar
Add to other calendar
Export to XML

Seminar Videos

Abstract
Cardiac electrophysiology is a field with a rich history of integrative modeling. A particularly important milestone was the development of the first biophysically-based cell model describing interactions between voltage-gated membrane currents, pumps and exchangers, and intracellular calcium Ca2+ cycling processes in the cardiac Purkinje fiber (DiFrancesco & Noble, Phil. Trans. Roy. Soc. Lond. B 307: 353) and the subsequent elaboration of this model to describe the cardiac ventricular myocyte action potential (Noble et al. Ann. N. Y. Acad. Sci. 639: 334; Luo, C-H and Rudy, Y. Circ. Res. 74: 1071). This talk will review the “state-of-the-art”‚ in integrative modeling of the cardiac myocyte, focusing on modeling of the ventricular myocyte because of its significance to arrhythmia and heart disease. Special emphasis will be placed on the importance of modeling mechanisms of Ca2+-Induced Ca2+-Release (CICR). CICR is the process by which influx of trigger calcium (Ca2+) through L-Type Ca2+ channels (LCCs) leads to opening of ryanodine sensitive Ca2+ release channels (RyRs) in the junctional sarcoplasmic reticulum (JSR) membrane and release of Ca2+ from the JSR. It is of fundamental importance in cardiac muscle function, as it not only underlies the process of muscle contraction, but is also involved in regulation of the cardiac action potential. We will demonstrate that every model of CICR in use today has serious shortcomings, and we will offer insights as to how these shortcomings must be addressed in order to develop reconstructive and predictive models that can be used to investigate myocyte function in both health and disease. (Supported by NIH HL60133, the NIH Specialized Center of Research on Sudden Cardiac Death P50 HL52307, the Whitaker Foundation, the Falk Medical Trust, and IBM Corp)

Integrative Models of the Cardiac Ventricular Myocyte – Raimond Winslow (JHU) - 2005

Abstract

English-language news articles are no longer necessarily the best source of information. The Web allows information to spread more quickly and travel farther: first-person accounts of breaking news events pop up on social media, and foreign-language news articles are accessible to, if not immediately understandable by, English-speaking users. In this talk, I will give an overview of my dissertation work on adapting automatic summarization techniques to handle these new sources of information, focusing on summarizing online narratives of personal experience and cross-lingual summarization for low-resource languages, and suggest some further summarization and text generation tasks to explore.

Biography

I am a final-year PhD candidate and NSF IGERT Fellow in the Natural Language Processing Group at Columbia University, supervised by Prof. Kathy McKeown. My research is in automatic summarization of non-traditional genres, such as blog entries, recorded conversations, and non-English documents, and I am generally interested in how summarization and related natural language technologies affect the accessibility of information.

Adapting Automatic Summarization to New Sources of Information -- Jessica Ouyang (Columbia) - 2019

Abstract

Question Answering (QA) is one of the most exciting areas in artificial intelligence today, aiming at augmenting human’s cognitive capabilities with computing systems that are capable of generating meaningful and insightful answers to questions in natural language, which ultimately help human reason and make decisions more effectively.

In this talk, I will present a few recent results from my group that have advanced QA using a variety of new models based on deep learning, which includes improved representation learning for passage-based non-factoid QA, and a novel two-way attention mechanism with neural networks. Our two-way attention mechanism is a general framework independent of the underlying representation learning, and it has been applied to both convolutional neural networks (CNNs) and recurrent neural networks (RNNs) in our studies. I will also share a large-scale non-factoid QA data sets we created that researchers can use to benchmark their models and report progresses.

Time permitting, I will also overview our work around DL-based natural language generation, and the proposed structured memory architecture for general-purpose learning frameworks such as Neural Turing Machines.

Biography
Dr. Bowen Zhou leads IBM’s research efforts, across IBM Research and Watson Group, around the creation and application of new state-of-the-art statistical learning techniques, such as deep learning, tomake algorithmic advancements in the fields of question answering, natural language understanding, reading comprehension, knowledge acquisition, reasoning and decision making. Bowen also leads the development of cloud services exposing these capabilities in the IBM cloud, and enabling other researchers, developers and offerings to integrate these state-of-the-art algorithms.

Since he joined IBM Research in 2003, Bowen has held a number of positions in research and management. He has published more than 80 papers in the fields of speech recognition, machine translation, speech-to-speech translation, natural language understanding, deep learning and question answering. Bowen was the main technical contributor, and later the leader, of the IBM’s speech translation technologies. He has also served as the Principal Investigator for a number of large-scale research projects funded by DARPA and others since 2008. He has received numerous technical awards at IBM including a number of Outstanding Innovation Awards, Outstanding Technical Achievement Awards, and the “Best of IBM” award in 2015.

Bowen has been active in both IEEE and ACL communities. He was elected to serve in the IEEE Speech and Language Processing Technical Committee for 2010-2015. He has been an Associate Editor for IEEE/ACM Transactions Audio, Speech and Language Processing since 2013. He has also frequently served as the Area Chairs for ICASSP and NAACL et al., and as the invited speakers and panelists at international conferences such as Interspeech and NAACL.

Recent Advances of Deep Learning for Question Answering -- Bowen Zhou (IBM) - 2016

October 13, 2017

Abstract

We all turn towards Wikipedia with questions we want to know more about, but eventually find ourselves on the limit of its coverage. Instead of providing “ten blue links” as common in Web search, why not answer any web query with something that looks and feels like Wikipedia? This talk is about algorithms that automatically retrieve and identify relevant entities and relevant relations and can identify text to explain this relevance to the user. The trick is to model the duality between structured knowledge and unstructured text. This leads to supervised retrieval models can jointly identify relevant Web documents, Wikipedia entities, and extract support passages to populate knowledge articles.

Biography

Laura Dietz is an Assistant Professor at the University of New Hampshire, where she teaches “Information Retrieval” and “Data Science for Knowledge Graphs and Text”. She coordinates the TREC Complex Answer Retrieval Track and runs a tutorial/workshop series on Utilizing Knowledge Graphs in Text-centric Retrieval. Previously, she was a research scientist in the Data and Web Science group at Mannheim University, and a research scientist with Bruce Croft and Andrew McCallum at the Center for Intelligent Information Retrieval (CIIR) at UMass Amherst. She obtained her doctoral degree with a thesis on topic models for networked data from Max Planck Institute for Informatics, supervised by Tobias Scheffer and Gerhard Weikum.

Retrieving Complex Answers through Knowledge Graph and Text -- Laura Dietz (U of New Hampshire) 2017

Generative Agents: Interactive Simulacra of Human Behavior - Joon Sung Park (Stanford)

Load More... Subscribe

Johns Hopkins University, Whiting School of Engineering

Center for Language and Speech Processing
Hackerman 226
3400 North Charles Street, Baltimore, MD 21218-2680

(410) 516-4237
[email protected]

Whiting School of Engineering
Johns Hopkins University

Privacy Statement
Legal

© 2023 Johns Hopkins University

Center for Language and Speech Processing