Agenda
Thursday, May 18, 2023 | |||
Session 1: Machine Learning Frameworks and Applications | |||
Time | Name | Institution | Talk Title |
8:00 – 8:45 AM | Registration and Breakfast | ||
8:45 – 8:50 AM | Saikat Guha | UArizona | Welcome remarks |
8:50 – 9:00 AM | Derya Cansever | Army Research Lab | Charge of the workshop |
9:00 – 9:30 AM | Surya Ganguli | Stanford | High dimensional geometry and dynamics of computing with many-body-physics |
9:30 – 10:00 AM | Lizhong Zheng | MIT | Feature-based Information Metrics and Applications |
10:00 – 10:30 AM | Prithwish Basu | Raytheon BBN | Generating conceptual designs via machine learning |
10:30 – 11:00 AM | Break | ||
11:00 – 11:30 AM | Hakan Tureci | Princeton | Eigentask Learning: Tackling the Challenge of Sampling Noise in Quantum Machine Learning |
11:30 AM – 12:00 PM | Na Young Kim | U Waterloo | Deep Neural Network Models for Complex Random Telegraph Signals |
12:00 – 1:00 PM | Lunch + Brainstorming on Session 1 | ||
Session 2: Classical AI for Quantum | |||
Time | Name | Institution | Talk title |
1:00 – 1:30 PM | Joseph Lukens | ASU | Quantum state tomography with Bayesian computational methods |
1:30 – 2:00 PM | Brian Kirby | Army Research Lab | Enhanced quantum state reconstruction with neural networks |
2:00 – 2:30 PM | Alex Greenwood (Li Qian group) | U Toronto | Machine-Learning-Derived Entanglement Witnesses |
2:30 – 3:00 PM | Break | ||
3:00 – 3:30 PM | Sanjaya Lohani | UIC | ML assisted variational quantum algorithm |
3:30 – 4:00 PM | Stefan Krastanov | UMass Amherst | Better Entanglement Distillation: Simulating better in order to optimize better |
4:00 – 5:00 PM | Brainstorming on Session 2 | ||
6:30 PM | Dinner at Dirk’s apartment | Address: 116 Pleasant St #3, Brookline, MA 02446 | |
Friday, May 19, 2023 | |||
Session 3: Quantum Intelligent Sensors and Networks | |||
Time | Name | Institution | Talk title |
8:00 – 8:45 AM | Registration and Breakfast | ||
8:45 – 9:00 AM | Recap of Day 1, Logistical remarks | ||
9:00 – 9:30 AM | Quntao Zhuang | USC | Quantum machine learning in intelligent sensors |
9:30 – 10:00 AM | Saikat Guha | UArizona | Optical-domain learning for super-resolution imaging |
10:00 – 10:30 AM | Valeria Saggio | MIT | Quantum-enhanced reinforcement learning |
10:30 – 11:00 AM | Break | ||
11:00 – 11:30 AM | Mihir Bhaskar | Amazon | Engineering efficient quantum nanophotonic systems |
11:30 AM – 12:00 PM | Dirk Englund | MIT | Programming Complex Systems for Quantum Information & Machine Learning |
12:00 – 1:00 PM | Lunch + Brainstorming on Session 3 | ||
Session 4: Algorithms for NISQ Processors | |||
Time | Name | Institution | Talk title |
1:00 – 1:30 PM | Nathan Killoran | Xanadu | Quantum machine learning: How far have we come, and how far do we have to go? |
1:30 – 2:00 PM | Jungsang Kim | IonQ/Duke | Quantum machine learning with trapped-ion quantum computers |
2:00 – 2:30 PM | Junyu Liu (Liang Jiang’s group) | UChicago | Quantum AI: From Near-Term to Fault-Tolerance |
2:30 – 3:00 PM | Break | ||
3:00 – 3:30 PM | Yanzhu Chen (Sophia Economou group) | Virginia Tech | Improving NISQ algorithms with an adaptive strategy |
3:30 – 4:00 PM | Gerry Angelatos | Raytheon BBN | Reservoir Computing for Quantum Measurement |
4:00 – 5:00 PM | Brainstorming on Session 4 |