The goal of this project is to collect anonymized traces from the Columbia network in order to analyze video traffic characteristics during the work/study-from home period. This information will be used for developing various ML-based tools for Quality of Experience (QoE) measurement. We will perform the feature extraction at the collection time itself and use anonymization techniques (e.g., IP address anonymization), to preserve user privacy. Students will analyze/measure encrypted network traffic to provide ground truth for potential RL/ML algorithms for estimating video QoE and identifying device/application (e.g., the start of a video streaming session). These algorithms can serve as a basis for new video adaptation techniques (see for example - https://wimnet.ee.columbia.edu/wimnet-team-wins-3rd-place-in-the-acm-mmsys20-twitch-grand-challenge/)

Continue reading

We have a position open for a student(s) who is/are interested in working on systems biology projects in bladder and prostate cancer. Specifically, we are looking for students who are well versed in statistical analysis, basic understanding of standard statistical techniques (appied to biology is a plus) and knowledge of R is required. The position will entail supporting post-doctoral members of the lab with computational analyses of different types of biological data in a wide range of projects.

Continue reading

The goal of this project is to study the molecular background of various congenital disorders affecting the cranial nerves, which are important in senses (hearing, vision, smell), facial muscle movements and more. Abnormal cranial nerve development can cause hearing loss, eye-movement disorders, facial weakness, loss of smell, and difficulties with respiration and swallowing. Some individuals may also have other motor, sensory, intellectual, behavioral and social disabilities. These disorders cause significant disability and are caused by genetic variants, often novel variation or de novo. Unfortunately, disorders affecting the 8th cranial nerve or vestibulocochlear nerve (CN VIII), important in hearing and balance, have been largely understudied. As various cranial nerves can be affected together, such as in Moebius syndrome, and as the vestibulocochlear nerve (CN VIII) and facial nerve (CN VII) also share a path in the internal auditory canal, it is likely that these disorders share underlying genes or closely interacting genes. To investigate the genetic architecture of cranial nerve abnormalities we suggest to molecularly investigate an in-house CN VIII cohort and other cranial dysinnervation cohorts. We will study rare genomic variants (both small variant as structural variants) to identify shared molecular pathways and genes amongst individuals with cranial dysinnervation disorders.

Continue reading

This project investigates the long-term effects of perinatal serotonin modulation on unlearned fear and anxiety like behaviors. The project will use DeepLabCut (a method for 3D pose estimation based on transfer learning with deep neural networks) to quantify fear and anxiety-related behaviors in animals, in which serotonin has been chemogenetically manipulated early in life.

Continue reading

Health care professionals cannot examine every person calling the office with a question nor can they return every call. Therefore, medical offices seeking to improve the speed and efficiency of evaluating and triaging patients must utilize telephone personnel who are often non-clinical staff. These telephone triage personnel may be limited in their knowledge and ability to obtain the necessary details of the patient’s medical symptoms and direct medical care accordingly. Their role is not to make diagnoses by phone, but rather to collect sufficient data related to the patient’s complaints and assign them appropriately in order to get the patient to the right level of care with the right provider in the right place at the right time.

Continue reading

Using NLP techniques to discover 1) new e-cig products online and 2) proposed health claims that users advocate for.

Continue reading

This study is the first step in exploring an emerging and previously understudied data stream - verbal communication between healthcare providers and patients. In partnership between Columbia Engineering, School of Nursing, Amazon, and the largest home healthcare agency in the US, the study will investigate how to use audio-recorded routine communications between patients and nurses to help identify patients at risk of hospitalization or emergency department visits. The study will combine speech recognition, machine learning and natural language processing to achieve its goals.

Continue reading