Vikas Goud Jukanti Receives AITF Best Poster Award at the 12th International Conference on Boiling and Condensation Heat Transfer
The Department of Mechanical Engineering is proud to announce that Vikas Goud Jukanti, a graduate student advised by Professor Vinod Srinivasan, has received the AITF Best Poster Award for AI and Machine Learning Applications in Boiling and Condensation Heat Transfer at the 12th International Conference on Boiling and Condensation Heat Transfer (ICBCHT-12), held at MIT, Cambridge, USA, June 14–17, 2026.
Sponsored by Elsevier, the AITF Best Poster Award is presented at a conference held once every three years that brings together the world’s leading researchers in two-phase heat transfer. A panel of internationally recognized scientists representing the breadth of the boiling and condensation research community evaluated 115 poster submissions, selecting the winner based on scientific originality, technical rigor, and significance of contribution to the field. This recognition was given specifically for outstanding work at the intersection of AI and machine learning and boiling heat transfer.
Jukanti's award-winning work presents a supervised learning framework for predicting Critical Heat Flux (CHF) proximity from high-frequency temperature measurements, replacing expensive imaging systems with a low-cost sensor. CHF refers to an applied power level at which the near-surface liquid film responsible for bubble formation is replaced by a thin insulating vapor film, causing catastrophic temperature spikes and component failure in systems such as data centers and nuclear reactors. The model generalizes across different fluids and surface geometries without retraining, making CHF proximity estimation practical for a wide range of industrial applications.
Boiling heat transfer underpins power generation, nuclear reactors, and electronics cooling, yet its unpredictable nature near CHF forces engineers to operate these systems conservatively. This work lays the groundwork for data-driven CHF proximity monitoring, addressing one of the most critical bottlenecks in modern thermal engineering.
His advisor, Professor Vinod Srinivasan, highlighted the collaborative nature of the work and its broader scientific significance:
“This work is built on extensive contributions by Ankit Saini, now an instructor in the department, who acquired the majority of the data used for analysis. Together, Vikas and Ankit have shown that a time-series analysis of single sensor data provides insights that many in the heat transfer community have been seeking through image-based spatial analysis of temperature distributions. This is a novel approach that suggests strong future potential for analyzing systems that slowly progress towards an abrupt, unpredictable transition to a different state. Boiling and the onset of CHF appears to share similarities with other systems such as earthquakes, electrical grid outages and solar flares where the system spontaneously switches to a different regime through an extreme event.”
Reflecting on what this recognition means within a community of researchers whose work has shaped his own doctoral journey, Jukanti shares:
“Receiving the AITF Best Poster Award at ICBCHT-12 is something I am very grateful for. Boiling heat transfer is full of challenging problems, and it has been exciting to explore how AI and machine learning can help address one of them. Seeing this work recognized by a community that includes many of the researchers whose work I have learned from throughout my Ph.D. is both rewarding and encouraging. I am grateful to my advisor, Professor Vinod Srinivasan, for his guidance and support, and to Dr. Ankit Saini, whose careful experimental work made this research possible. I also thank the conference organizers and the award committee for this recognition. It encourages me to keep asking better questions and pursuing research that advances the field.”