Past Member

Neo (Mostafa) Mohsenvand

Fluid Interfaces
Groups
  • Postdoctoral Associate

My name is Mostafa 'Neo' Mohsenvand and I was a PhD candidate and a Postdoc at the Fluid Interfaces group at MIT Media Lab. My background is in Applied Mathematics (MSc, University of Oxford), Electrical Engineering (BSc, Tehran Polytechnic)  and Biomedical Engineering (BSc, Tehran Polytechnic). My research interests are:

1. Artificial Intelligence and Machine Learning

2. Electroencephalography and Brain-Computer Interfaces

3. Visual Design, Information Design, and Product Design.

4. Virtual/Augmented/Mixed Reality

My email address: mmv@mit.edu

I have moved to BrainCo as a head of research. For work-related inquiries, contact neo.mohsenvand@brainco.tech

My name is Mostafa 'Neo' Mohsenvand and I was a PhD candidate and a Postdoc at the Fluid Interfaces group at MIT Media Lab. My background is in Applied Mathematics (MSc, University of Oxford), Electrical Engineering (BSc, Tehran Polytechnic)  and Biomedical Engineering (BSc, Tehran Polytechnic). My research interests are:

1. Artificial Intelligence and Machine Learning

2. Electroencephalography and Brain-Computer Interfaces

3. Visual Design, Information Design, and Product Design.

4. Virtual/Augmented/Mixed Reality

My email address: mmv@mit.edu

I have moved to BrainCo as a head of research. For work-related inquiries, contact neo.mohsenvand@brainco.tech

Project Research

Large-scale EEG-Based User-Identification Using Self-supervised Learning

EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy…
Project Research

Physiophone: Electrophysiology Sonification

The human body produces a variety of different electrophysiological signals from brain-waves (EEG) to the electrical activity of the heart …
Archived
Project Research

SeqCLR: Self-supervised learning of features for time-series data

Interpreting human electroencephalogram (EEG) is a challenging task and requires years of medical training. We present a framework for lear…
Archived
Publication Research

Contrastive Representation Learning for Electroencephalogram Classification

Mohsenvand, M.N., Izadi, M.R. & Maes, P.. (2020). Contrastive Representation Learning for Electroencephalogram Classification. Proceedings of the Machine Learning for Health NeurIPS Workshop, in Proceedings of Machine Learning Research 136:238-253 Available from http://proceedings.mlr.press/v136/mohsenvand20a.html.
Project Research

Affective Memory Summarization

Using affective signals to summarize 16 hours of body-cam video into 15 minutes of daily recap. See the video below.
Project Research

Flower: EEG visualization with the aid of machine learning

Flower is a new visualization tool for in-depth study of multi-sensor recordings in the time domain. It has been released for public downlo…
Project Research

SkipNorm

Skip Norm is a new and flexible building block for Deep Learning that serves as a skip connection and normalization block simultaneously. I…
Project Research

inSight: Deep Neurofeedback

inSight is a brain decoding system. It uses  generative models (BigGAN and MusicVAE) to stimulate the brain with synthetic, but natura…
Archived
Project Research

The Foodome: Building a Comprehensive Knowledge Graph of Food

The Foodome addresses how to create deeper understanding and predictive intelligence about the relationships between how we talk and learn …
Archived
Publication Research

Rumor Gauge: Predicting the Veracity of Rumors on Twitter

Soroush Vosoughi, Mostafa ‘Neo’ Mohsenvand, and Deb Roy. (2017). Rumor Gauge: Predicting the Veracity of Rumors on Twitter. ACM Trans. Knowl. Discov. Data 11, 4, Article 50 (July 2017), 36 pages.
Academic Paper, July 2017
Project Research

Rhizome

The World Health Organization estimates that more than 55 million people worldwide suffer from dementia. As the proportion of older people …
Project Research

DataVRse

Visualizing the social network of twitter conversations, Presidential Elections 2016. Try it!
Project Research

The Electome: Measuring responsiveness in the 2016 election

The Electome: Where AI meets political journalismThe Electome project is a machine-driven mapping and analysis of public sphere content and…
Event Events

reThink Food

LocationNapa Valley, CA DescriptionThe reThink Food Annual Leadership Conference brings together a diverse group of thought leaders and inn…
Friday — Sunday
November 6, 2015 —
November 8, 2015
Project Research

VR Maze in Zero Gravity

The brain uses space to index, organize, and retrieve memories. However, our sense of space depends on our perception of gravity. We p…
Video Videos

#85: The Electome

The Electome: Where political journalism meets AIBuilt at the Laboratory for Social Machines (LSM) with support from Twitter and Knight Fou…
Article Research

This man’s quest to understand memory starts with obsessive bodycam recording and brain-wave tracking

By-products include striking short films that speed up and slow down along in response to body signals.
Article Research

The Process of Making Lasting Memories: Mostafa (Neo) Mohsenvand and Hannah Campbell at TEDxYouth@CEHS

Neo Mohsenvand and filmmaker/singer/songwriter Hannah Campbell contemplate memory, data, and the future at TEDxYouth@CEHS.
Project Research

AINA: Aerial Imaging and Network Analysis

This project is aimed at building a machine learning pipeline that will discover and predict links between the visible structure of village…
Archived
Project Research

Journalism Mapping and Analytics Project (JMAP)

Over the last two decades, digital technologies have flattened old hierarchies in the news business and opened the conversation to a multit…
Archived