Research Software Engineer (AI/ML) at MIT
Multidisciplinary Computer Scientist
I am currently a computational research developer at the Massachusetts Institute of Technology (MIT). I am the lead developer of Brain-Score, a tool to measure how brain-like neural networks are.
What makes us human? What is a mind? Can we create an artificial general intelligence (AGI)? What is the nature of consciousness? Can we create safe, robust, and dependable AGI systems? These are among the most important questions humanity will ever ask, and my life is dedicated to researching their answers.
“The important thing is not to stop questioning. Curiosity has its own reason for existence. One cannot help but be in awe when he contemplates the mysteries of eternity, of life, of the marvelous structure of reality. It is enough if one tries merely to comprehend a little of this mystery each day.
My foray into the arcane world of AI
PROSPECTION VERSION 1.1
I am the creator and maintainer of PROSPECTION, a novel RNN LSTM machine learning model to scan the S&P 500 and determine which stock will go up at open 24 hours later.
NEURAL NETWORK CONFERENCE PAPER
"Complexity Analysis and u-net Based Segmentation of Meningeal Lymphatic Vessels"
Published in the 54th Asilomar Conference on Signals, Systems and Computers, November 1-4th 2020. Coauthored with graduate student Nazia Tabassum.
Machine Learning Statistics Paper
“Are Many Top Kaggle Datasets Fraudulent?”
In Peer Review, Big Data, Special Issue: Evaluations and Experimental Design in Machine Learning
THE SIGMA COGNITIVE ARCHITECTURE
I was a remote research intern at the University of Southern California, part of the Sigma Cognitive Architecture Group. I worked on reinforcement learning and graphical models.
August 2018 - Currently
BOOK-A-WEEK CHALLENGE PARTICIPANT
Over two years ago, I set out to read 1 book a week. I am currently on book 131 (The Aleph and Other Stories, by Borges). I have read mainly computer science, cognitive science, literature, and general nonfiction.
May 2020 - August 2020
SUMMER RESEARCH INTERN
I was a research intern for University of Southern Claifornia (USC ICT), working on the Sigma Cognitive Architecture, applying Sigma to virtual agents and reinforcement learning in complex environments using the architecture.
Spring 2020, Fall 2020, Spring 2021
STUDENT - PROFESSOR OF CS: 1501 ARTIFICIAL GENERAL INTELLIGENCE
As part of UVA’s student-taught classes program, I was selected by the Engineering School to teach a course on AGI to UVA undergraduates. It looks at relevant research, problems, and questions of the AGI field, with an emphasis on interdisciplinary material with philosophy and cognitive neuroscience. Designed entire curriculum, syllabus, lecture material, and assignments on my own, totaling 16 hour-long lectures with material pulled from research papers, books read, and online courses. The total enrollment was over 60 students for Spring 2020, and 30 for Fall 2020/Spring 2021.
May 2019 - August 2019
ASSISTANT RESEARCH COORDINATOR/RESEARCH ASSISTANT
I managed and coordinated data and data collection efforts of around 6,000 participants spanning almost 20 years in the University of Virginia Cognitive Aging Lab. I have almost 200 hours (100 participants, 2 hours/sessions) of 1-on-1 session time with participants, running through numerous cognitive assessments. Worked directly under Dr. Timothy Salthouse (Professor of Psychology at UVA). I was promoted after 1 month of being an RA to managerial role.
I am a TA for second-year course, CS 2102: Discrete Mathematics. I help students learn fundamental concepts of recursion, induction, proofs, symbolic logic, and functional programing, as well as DM topics like Relations, Sets, and Complexity. I headed many review sessions for all the students in lecture-style.
Fluent in Python, Java, C,C++, and HTML/CSS. 5+ years Python.
MACHINE LEARNING PACKAGES
Extensive ML Experience (3+ years) with Keras, Tensofrlow, Pandas, and Numpy.
CEFR Level B1/B2 in Swedish.
Familiar and experienced with most regression and classification algorithms, with specialties in deep learning architectures computational neuroscience.
Select accomplishments thus far
LOUIS T. RADER 2020 UNDERGRADUTE TEACHING AWARD
UVA Department of Computer Science end of the year award given to students
who make remarkable contributions to UVA courses. I was recognized for outstanding performance teaching CS 1501: Artificial General Intelligence, (see below) and extremely high reviews on student feedback. Also recognized for incredible work done in creating the course material. .
FIRST RECIPIENT OF THE SHERRY K. AND JAMES H. AYLOR SCHOLARSHIP
Scholarship awarded by the University of Virginia School of Engineering, for full tuition and fees for 4 years of undergraduate studies ($90,000). This was the first and only merit-based scholarship that UVA Engineering has ever awarded. I was chosen out of the entire incoming Engineering Class of 2021 (around 5,000
RECIPIENT OF THE DOUBLE-HOO RESEARCH GRANT
$6000 research grant given by the University of Virginia to undergraduate/graduate pairs. Project entitled: “Data Augmentation of Meningeal Lymphatic Vessels for Segmentation and Analysis Using Deep Learning Networks”. I am applying neural networks to mice brain microscopy images of lymphatic vessels. I designed a custom segmentation network architecture to work with our proprietary images. I also authored a custom data processing pipeline for Linux/OSX to streamline the data pre-processing phase, integrating data augmentation techniques within it.