Christopher Monterola
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Christopher Monterola | |
|---|---|
 | |
| Founding Head Aboitiz School of Innovation, Technology, and Entrepreneurship | |
| In office November 08, 2017 – present | |
| Founding Executive Director Analytics, Computing, and Complex Systems Laboratory | |
| In office November 08, 2017 – present | |
| Personal details | |
| Born | Christopher P. Monterola |
| Nationality | Filipino |
| Born | |
| 🎓 Alma mater | University of the Philippines (BSc, MSc, PhD) |
| 💼 Occupation | |
| 🌐 Website | www |
Christopher P. Monterola (born 1976) is a Filipino physicist[1][2] and machine learning scientist, educator, entrepreneur, and technology advisor for various enterprises and organizations in Asia. He sits on the board of Xurpas, Inc.[3], a publicly listed technology company in the Philippine Stock Exchange that has offered innovative IT products and services for the past twenty years.[4]
Dr. Monterola is also a National Academy of Science and Technology Academician[5] who holds an Aboitiz Chair in Data Science[6] and a Professorship at the Asian Institute of Management (AIM). He is also AIM's Founding Head of the Aboitiz School of Innovation, Technology, and Entrepreneurship (ASITE). ASITE is the newest of the four schools of AIM that houses five academic programs: MSc in Data Science, Masters in Innovation and Business, Masters in Entrepreneurship, Ph.D. in Data Science, and a Bachelor of Science in Data Science and Business Administration. Under ASITE is also an advanced analytics industry-facing research lab, the Analytics, Computing, and Complex Systems (ACCeSs) lab, where he is the Executive Managing Director.
Education and early career[edit]
Monterola spent his childhood in the Narra and Puerto Princesa, Palawan. The family then moved to San Pablo, Laguna, in his teenage years. In his early education, he moved from one school to another, from Narra Pilot Elementary School to Puerto Princess Elementary School to Laguna College in High School.
Chris majored in physics at the National Institute of Physics at the University of the Philippines, Diliman, in 1992. He graduated magna cum laude, at the top of the Applied Physics cohort. He was recognized to be among the top 15 graduates of the entire UP system upon graduation. Monterola also earned his master of science degree and doctorate in physics from the same university where he graduated as the Most Outstanding Ph.D. student of the College of Science and the Edgardo Gomez Awardee for Excellence in Research. His dissertation was titled Neural Networks: New Insights and Applications, which spun into two publications in top-tiered journals including Physical Review Letters, a top journal of the American Physical Society.[7][8] After getting his Ph.D., he joined the Max Planck Institute for the Physics of Complex Systems in Dresden, Germany as a post-doctoral researcher, where he studied the dynamics of the olfactory system, aside from algorithmic innovations in the collective computing of neural networks.[9]
References[edit]
- ↑ "Chris Monterola's Google Scholar page".
- ↑ "Department of Science and Technology Specialized Philippine Enterprise Reference of Experts and Scientists: Chris Monterola". Retrieved 1 March 2023.
- ↑ "PSE Disclosure on Chris Monterola's Appointment". 14 November 2022. Retrieved 24 February 2023.
- ↑ "PSE Edge Company Information: Xurpas". Retrieved 24 February 2023.
- ↑ "NAST Member Page: Christopher Monterola".
- ↑ "Acer supercomputer boosts AIM artificial intelligence education". 29 May 2022. Retrieved 24 February 2023.
- ↑ Quito, Marcelino Jr.; Monterola, Christopher; Saloma, Caesar (21 May 2001). "Solving N-Body Problems with Neural Networks". Physical Review Letters. 86. Retrieved 1 March 2023.
- ↑ Monterola, Christopher; Saloma, Caesar (1 February 1998). "Characterizing the dynamics of constrained physical systems with an unsupervised neural network". Physical Review E. 57 (R1247(R)). Retrieved 1 March 2023.
- ↑ Monterola, Christopher; Zapotocky, Martin (23 March 2005). "Noise-enhanced categorization in a recurrently reconnected neural network". Physical Review E. 71 (036134). Retrieved 1 March 2023.
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