I never felt I belonged anywhere or to anyone until the moment I found myself. Only then did I realize what home meant, only then did I belong. This is me, my freedom, my peace, my joy, forever and ever. ~Niloufar Sarraf
I’m a researchoholic and a passionate writer! A researcher natively interested in biofeedback, mind control, wearable computing, and affective search. Natively interested in how humans interact with everything! Student of emotional motivation, information retrieval, and sensory cognition.
Author of “The Advances of Wearable EEG Neuroheadsets in the Tech and Business Industries” (available on Amazon Kindle).
Connecting and integrating the disciplines of neuroscience, technology, and cognitive psychology, Dr. Niloufar Sarraf positioned her doctoral dissertation within the emerging field of Nuero Information Science. In this body of work, she mapped the neurological dimensions of information search within the human brain. After completing her PhD, she published her first book as an attempt to ‘humanize’ neuroscience for the non-traditional neuroscience industries. While working on her next book, Niloufar is pursuing her long time dream of building virtual research practices/labs to help merge neuroscience within the non-traditional neuroscience industries, such as entertainment, media, marketing, mindfulness, etc.
Moreover, Niloufar loves spreading her passion for neuroscience to the masses, as she is quite active creating YouTube videos, building Udemy courses, giving talks at conferences, writing books, etc.
Years of research experience at Stanford University, Unity Technologies, Google, Yahoo, IBM, VMWare, SAP, etc.
In-progress PhD, positioning in Neuro Information Science.
My humble ‘out of the box’ passion: Neuro Smart (Affective) Search (I’ll probably end up changing the name):
“I envision/hope to have my dissertation add to the body of knowledge, helping develop search engines that, through wearable computing devices, are able to read human brain waves, and dimensions of emotions thereof, in order to improve search results based on the neurological feedback that the search engines receive from user’s brain waves. In other words, search engines become an extension of the human brain by receiving brain waves that constantly provide neurological feedback in terms of the search results that they provide.”
affective information retrieval, affective search, neuro-information science, brain computer interaction, information systems design
November 11th, 2012 at 2:21 pm
Hello Nilo Sarraf,
Your blog greatly appeals to me for your interest in the way affect influences information users. I am currently a SLIS student, and one of my main goals is to integrate my strong interest in contemporary psychoanalytic theory (or psychodynamics) with information science. Do you know of any researchers who are doing work in this area?
Thank you,
Todd Pierce
November 11th, 2012 at 2:40 pm
Todd,
Great to hear. Please see the work of some of the PhD students at Rutger university. I just came from the ASIST 2012 conference and they presented some pretty impressive papers and posters.
See here for their info:
http://comminfo.rutgers.edu/
https://sites.google.com/site/rumbalab/
http://comminfo.rutgers.edu/~jacekg/index.html
November 11th, 2012 at 2:46 pm
Thank you for your quick response.
Todd
July 9th, 2015 at 6:20 pm
Hi Nilo,
In my research your name has been coming up quite a bit and I am hoping you could provide some guidance to me. Based on your linkedin article, it seems like you are quite familiar with raw EEG analysis, especially with the Emotiv EPOC and EEGLAB. I am trying to meet a deadline with a research project but I am running into a lot of issues in the analysis phase because I am a complete novice and can’t find a contact who is familiar enough with EEGLAB to assist me. I am looking to analyze frontal alpha asymmetry in EEGLAB from data I recorded using the Emotiv EPOC. Can you just tell me your best estimate of the steps I need to take to fully analyze the data?
Can I just filter the data to 8 – 12 Hz? Is that sufficient or is there more I need to do? As I said, I am a novice so rejecting artifacts by eye or component maps isn’t really something I’m confident with. My plan was to apply those filters, then clip the continuous data for the epochs I want to examine, and then just do spectral analysis to see if there is a significant difference between the epochs. The problem is: this seems way too simple to be everything that I need to do. Am I missing anything (if so, what more should I do), or would this be valid enough data to get reliable results and use in my paper?
I would be so grateful for your input.
Best,
Evan
July 11th, 2015 at 1:09 pm
Evan, Great valid questions! I feel your pain, as I have gone through the same. Since I get asked these questions quite often, I am going to write a blog post about the methods that I ended up choosing/using. Please stay tuned. Meanwhile, please keep in mind that running these analysis are totally individual to each study, as research questions/needs vary. So, there is no ‘one’ answer. I spent months studying and reading through forums, discussions, and papers until I established what I needed to do for my particular research (using EEGLab on MatLab) with the Emotiv research edition. Hope my upcoming post helps. Thanks!