Address

Bicocca
Stanza: n.a.

Contact Information

Call: 02 64483308

Email: pasquale.palumbo@iasi.cnr.it, pasquale.palumbo@unimib.it

Personal site: www.iasi.cnr.it

Pasquale Palumbo

Role: Research Associate

Research group: BIOSYS

5-year laurea degree and PhD in Electrical Engineering
Research Interests: Mathematical Modeling of Biological Systems; Mathematical Modeling and Control of Tumor Growth and Treatment; Mathematical Modeling of Epidemics; Systems Biology; Dynamical System Identification and Filtering.
Settori ERC:
PE1_10, PE1_20, PE7_1, LS2_15

Recent publications

  1. 2016
    Glucose control with incomplete information
    A Borri, Simona Panunzi, Pasquale Palumbo, C. Manes, Andrea De Gaetano
  2. 2016
    Carleman discretization of impulsive systems: application to the optimal control problem of anti-angiogenic tumor therapies
    F. Cacace, Valerio Cusimano, A. Germani, Pasquale Palumbo
  3. 2016
    Noise reduction for enzymatic reactions: a case study for stochastic product clearance
    A Borri, Pasquale Palumbo, A Singh
  4. 2016
    Cubification of Nonlinear Stochastic Differential Equations and Approximate Moments Calculation of the Langevin Equation
  5. 2016
    Whi5 phosphorylation embedded in the G1/S network dynamically controls critical cell size and cell fate
    Pasquale Palumbo, M. Vanoni, Valerio Cusimano, S Busti, M. Marano, C. Manes, L. Alberghina
  6. 2016
    The impact of negative feedback in metabolic noise propagation
    A Borri, Pasquale Palumbo, A Singh
  7. 2016
    A state predictor for continuous-time stochastic systems
    F. Cacace, Valerio Cusimano, A. Germani, Pasquale Palumbo
  8. 2016
    Block-tridiagonal state-space realization of Chemical Master Equations: a tool to compute explicit solutions
  9. 2016
    Preliminary results on glucose control with sampled information
    Alessandro Borri, Simona Panunzi, Pasquale Palumbo, Costanzo Manes, Andrea De Gaetano
  10. 2016
    A Cubification Approach for the Approximate Moments Computation in Stochastic Differential Equations: Application to the Chemical Langevin Equation