Resume-aware faculty matching

Find professors who actually fit you

Upload your resume. Four AI agents analyze your background, rank the faculty who fit, inspect their recent research, and help you draft outreach — grounded in their actual work, not templates.

Free to startNo credit cardCancel anytime
Top matches Balanced preset
Dr. Sarah Chen
Stanford · Interpretability · NLP
91
Dr. Marcus Holloway
MIT · Robotics · RL
84
Dr. Aisha Okonkwo
CMU · Fairness · HCI
82
Nova · Professor Researcher · re-ranking top 20…

Víctor H Cervantes

· Assistant Professor

University of Illinois Urbana-Champaign · Psychology

Active 2005–2024

h-index11
Citations625
Papers4014 last 5y
Funding
See your match with Víctor H Cervantes — sign in to PhdFit.Sign in

About

Víctor H Cervantes is an Assistant Professor in the Department of Psychology at Illinois College of Liberal Arts & Sciences. His research areas include Cognitive Psychology and Quantitative Psychology, with a focus on mathematical psychology, foundations of probability, and probabilistic contextuality across sciences. His work involves the theory of measurement and psychometrics, as well as knowledge and learning spaces. Cervantes holds a Ph.D. in Mathematical and Computational Cognitive Science from Purdue University and has received the J. William Fulbright Fellowship for doctoral studies from Fulbright Colombia in 2014. His contributions include research on the relation between the Contextual Fraction and CNT 2, contextuality in random variables, and probabilistic contextuality in human choices, among other topics.

Research topics

  • Artificial Intelligence
  • Quantum mechanics
  • Physics
  • Mathematics
  • Computer Science
  • Philosophy
  • Statistics
  • Pure mathematics
  • Epistemology
  • Theoretical physics
  • Discrete mathematics

Selected publications

  • On the Quantum-like Contextuality of Ambiguous Phrases

    arXiv (Cornell University) · 2021 · 8 citations

    Senior authorCorresponding
    • Computer Science
    • Artificial Intelligence
    • Computer Science

    Language is contextual as meanings of words are dependent on their contexts. Contextuality is, concomitantly, a well-defined concept in quantum mechanics where it is considered a major resource for quantum computations. We investigate whether natural language exhibits any of the quantum mechanics' contextual features. We show that meaning combinations in ambiguous phrases can be modelled in the sheaf-theoretic framework for quantum contextuality, where they can become possibilistically contextual. Using the framework of Contextuality-by-Default (CbD), we explore the probabilistic variants of these and show that CbD-contextuality is also possible.

  • Contextuality and noncontextuality measures and generalized Bell inequalities for cyclic systems

    Physical review. A/Physical review, A · 2020 · 29 citations

    Senior authorCorresponding
    • Mathematics
    • Discrete mathematics
    • Statistics

    Cyclic systems of dichotomous random variables have played a prominent role in contextuality research, describing such experimental paradigms as the Klyachko-Can-Binicio\ifmmode \breve{g}\else \u{g}\fi{}lu-Shumovsky, Einstein-Podolsky-Rosen-Bell, and Leggett-Garg ones in physics, as well as conjoint binary choices in human decision making. Here, we understand contextuality within the framework of the Contextuality-by-Default (CbD) theory, based on the notion of probabilistic couplings satisfying certain constraints. CbD allows us to drop the commonly made assumption that systems of random variables are consistently connected (i.e., it allows for all possible forms of ``disturbance'' or ``signaling'' in them). Consistently connected systems constitute a special case in which CbD essentially reduces to the conventional understanding of contextuality. We present a theoretical analysis of the degree of contextuality in cyclic systems (if they are contextual) and the degree of noncontextuality in them (if they are not). By contrast, all previously proposed measures of contextuality are confined to consistently connected systems, and most of them cannot be extended to measures of noncontextuality. Our measures of (non)contextuality are defined by the ${L}_{1}$-distance between a point representing a cyclic system and the surface of the polytope representing all possible noncontextual cyclic systems with the same single-variable marginals. We completely characterize this polytope, as well as the polytope of all possible probabilistic couplings for cyclic systems with given single-variable marginals. We establish that, in relation to the maximally tight Bell-type CbD inequality for (generally, inconsistently connected) cyclic systems, the measure of contextuality is proportional to the absolute value of the difference between its two sides. For noncontextual cyclic systems, the measure of noncontextuality is shown to be proportional to the smaller of the same difference and the ${L}_{1}$-distance to the surface of the box circumscribing the noncontextuality polytope. These simple relations, however, do not generally hold beyond the class of cyclic systems, and noncontextuality of a system does not follow from noncontextuality of its cyclic subsystems.

Frequent coauthors

  • Ehtibar N. Dzhafarov

    Purdue University West Lafayette

    23 shared
  • Martha Eugenia Alfaro Cuevas

    9 shared
  • Janne V. Kujala

    University of Turku

    6 shared
  • Edilberto Cepeda‐Cuervo

    Universidad Nacional de Colombia

    3 shared
  • Giulio Camillo

    Universidade de São Paulo

    3 shared
  • Iván Díaz

    2 shared
  • Wilson Aguilar

    2 shared
  • Diana Rodríguez

    Columbia University

    2 shared

Awards & honors

  • J. William Fulbright Fellowship for doctoral studies, Fulbri…

Similar researchers at University of Illinois Urbana-Champaign

  • Resume-aware match score
  • Save to shortlist
  • AI-drafted outreach

See your match with Víctor H Cervantes

PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.

  • Free to start
  • No credit card
  • 30-second signup