2019-Present
Post-Bac Research: Orthogonal Research & Education Lab | Dr Bradly Alicea
Representational Brains & Phenotypes (Research Group)
DevoWorm / DevoWorm Machine Learning ( OpenWorm Subgroup)
GitHub | Research Gate | Google Scholar
(Preprint) Stefan Dvoretskii, Ziyi Gong, Ankit Gupta, Jesse Parent and Bradly Alicea, . "Braitenberg Vehicles as Developmental Neurosimulation".
Jesse Parent and Yelin Kim. “Towards Emotion Recognition with Automatic Social and Relational Context Discovery in HRI Systems.” The AAAI Fall Symposium Series: Artificial Intelligence for Human-Robot Interaction (AI-HRI). November, 2017.
David Turetsky, Brian Nussbaum, Jesse Parent, Manpreet Duggal, Meghan Anderson. "Success Stories in Cyber Security Information Sharing". University at Albany Publications, October 2019
Bradly Alicea, Richard Gordon, Abraham Kohrmann, Jesse Parent, Vinay Varma. "Pre-trained Machine Learning Models for Developmental Biology", The Node. October 29, 2019
State University of New York at Albany
2018-2019
Berg Research Lab | Dr George Berg, Informatics & Computer Science
Scimemi Lab | Dr Annalisa Scimemi, (Neuroscience) Biology
SSCIS Research Team | J.D. David Turetsky, Cybersecurity. Funded By Hewlett Foundation Research Grant, Employed by SUNY Research Foundation
2016-2017
INSPIRE Lab (Human-Robot Interaction) | Dr Yelin Kim, Electrical & Computer Engineering
Earlier Research: State University of New York at Geneseo
Sustainable International Development: Microfinance (Senegal)
Civic Engagement: The Ghana Project; Gold Leader Mentor Program
I am drawn to a place between the study of natural and artificial intelligence. I'm fond of the word "comprehension", which to me has to do with how understanding is created. There is a lot to explore along the lines of how actors operate: from the actual reception of information at a cellular mechanistic and hardware level; its processing in a more cognitive level; and decision-making and behavior at broader level. I'm interested in these systems in general, and in specific their qualities and relations between actors, the environment within which they operate and how it influences learning, interpretation or communication of information, behavior, and related matters. Here are a few topical questions below that I'd like to explore:
An unordered and sporadically updated list of questions I'm interested in pursuing in the future
Embodied Cognition & environmental interaction: how do agents develop modeling or cognitive abilities, and how does this vary with what environmental factors (or social conditions) are available?
Generative models and their augmentation - how are 'worldviews' or system-wide conceptions interpreted?
Meta-learning: how do we learn to learn (in both natural and artificial intelligence settings)?
Complex systems and information prioritization: how is salience or pertinence identified?
Environmental impacts on comprehension: how do external factors influence information processing or behavior?
Information and moral decision making: how does comprehension and discernment of knowledge from incoming data incline sentiment about the data, or about actions taken processing such data?
The engineering of morality: what are the infrastructures that enable moral evaluation? What is their biological evolution, and how can these be developed or modeled in artificial settings? What are the infrastructure variations in different life forms and how does that impact their ability to evaluate behavior?
What would an advanced artificial intelligence (towards 'human-level AI' or an AGI) need to know, what kind of guidance would it benefit from? (Under the broader umbrella of terms like "value alignment" and "control problem")
Cognition security: how do we enable verification that our thoughts and sentiments are sovereign in a world where there is ever-more attempts at influencing comprehension itself? This has societal implications as well as actual hardware and technological substance.
General brain-computer interface: what are the physical limits of communication? Of consciousness?
Human-Robot interaction: how do we move towards quantifying or making intelligible to machines the complexities of human social interaction?
Keywords: embodiment, emergence, computational cognitive neuroscience, informatics, human-robot interaction, cybernetics, intelligent systems, meta-learning, cognition, cognitive liberty, memory, decision-making, affective computing. embodied cognition, evolutionary learning.