BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Northeastern University College of Engineering - ECPv6.16.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Northeastern University College of Engineering
X-ORIGINAL-URL:https://coe.northeastern.edu
X-WR-CALDESC:Events for Northeastern University College of Engineering
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20270314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20271107T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260403T113000
DTEND;TZID=America/New_York:20260403T123000
DTSTAMP:20260525T013641
CREATED:20260326T184109Z
LAST-MODIFIED:20260326T184109Z
UID:56049-1775215800-1775219400@coe.northeastern.edu
SUMMARY:JOINT SPECIAL COLLOQUIUM: AI-Optimized Advanced Packaging for Next-Generation Computing
DESCRIPTION:JOINT SPECIAL COLLOQUIUM \nCollege of Science\, College of Engineering & Quantum Materials and Sensing Institute (QMSI)\nAI-Optimized Advanced Packaging for Next-Generation Computing\nDr. Rabindra Das\nMIT Lincoln Laboratory \nFriday\, Apr 3\, 2026; 11:30am to 12:30pm\nHosts: Prof. Arun Bansil & Prof. Kin Chung Fong \nVenue: Elliott Hall – Room 130C\, 147 S. Bedford St\, Burlington\, MA\nRemote: MS Teams Link \nAbstract \nThe rapid growth of artificial intelligence (AI)\, high-performance computing (HPC)\, and data-intensive sensing systems is creating unprecedented demands for computational capability\, energy efficiency\, and system integration. Applications such as autonomous sensing platforms\, satellites\, and unmanned aerial and underwater vehicles increasingly require powerful onboard processing to analyze large volumes of data in real time. As conventional transistor scaling slows\, advanced packaging and heterogeneous integration are emerging as critical technologies for enabling next-generation computing systems. \nThis talk presents a research vision for AI-optimized advanced packaging\, where artificial intelligence techniques—particularly decision-tree-based optimization—are used to guide the design and fabrication of complex heterogeneous microsystems. AI-driven approaches enable optimization of substrate fabrication\, chiplet placement\, interconnect routing\, power delivery\, and thermal management across multi-chip systems. A central focus is the development of heterogeneous System-on-Wafer (SoW) architectures\, integrating tens to hundreds of chiplets on a single wafer substrate to achieve extraordinary computing density. A case study on superconducting wafer-scale multi-chip modules with ultra-fine-pitch micro-bump interconnects demonstrates how advanced packaging can address key challenges in scalability\, interconnect density\, and system performance for future AI\, HPC\, and quantum computing platforms. \nBiography \nRabindra N. Das\, Ph.D. is a Member of the Technical Staff in the Advanced Technology Division at MIT Lincoln Laboratory\, Lexington\, MA. Previously\, he served as a Principal Engineer at Endicott Interconnect Technologies (formerly IBM Endicott). Dr. Das has more than 23 years of experience in microelectronics packaging and heterogeneous integration\, spanning high-performance computing\, medical electronics\, and superconducting quantum hardware systems. He has authored 135+ technical publications and holds 51 patents in microelectronics packaging technologies. He has been recognized for four consecutive years (2020–2023) in Stanford University’s list of the world’s top 2% most-cited scientists.
URL:https://coe.northeastern.edu/event/joint-special-colloquium-ai-optimized-advanced-packaging-for-next-generation-computing/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260401T113000
DTEND;TZID=America/New_York:20260401T123000
DTSTAMP:20260525T013641
CREATED:20260326T183643Z
LAST-MODIFIED:20260326T183643Z
UID:56047-1775043000-1775046600@coe.northeastern.edu
SUMMARY:JOINT SPECIAL COLLOQUIUM: Scalable Quantum Applications: Synergies in Control\, Learning and Co-design
DESCRIPTION:JOINT SPECIAL COLLOQUIUM\nCollege of Science\, College of Engineering & Quantum Materials and Sensing Institute (QMSI)\nScalable Quantum Applications: Synergies in Control\, Learning and Co-design\nDr. Hong-Ye Hu\nHarvard University \nWednesday\, Apr 1\, 2026; 11:30am to 12:30pm\nHosts: Prof. Arun Bansil & Prof. Kin Chung Fong \nVenue: Elliott Hall – Room 130C\, 147 S. Bedford St\, Burlington\, MA\nRemote: MS Teams Link \nAbstract \nThe rapid advancement of quantum science and technology has ushered in a new era where analog simulators can now control thousands of qubits and digital processors are approaching break-even points for error correction. However\, bridging the gap to large-scale quantum applications demands synergistic innovation across hardware-aware control\, rigorous learning protocols\, and algorithm-hardware co-design. In this talk\, I will demonstrate the utility of this full-stack approach\, focusing first on the untapped potential of analog platforms. I will show that globally controlled systems can exhibit universal quantum dynamics even without local addressability. \nBy leveraging a novel direct optimal control technique\, we experimentally realized effective three-body interactions in a globally driven Rydberg atom array\, a critical resource for simulating exotic quantum phases. As system sizes scale\, the ability to efficiently learn and benchmark devices also becomes critical. Traditional methods like quantum process tomography are exponentially expensive\, while scalable alternatives\, such as Hamiltonian learning\, typically rely on structural ansätze that induce bias. To address this\, we introduced the first Hamiltonian learning algorithm that functions without any structural ansatz while retaining optimal experimental scaling. This paradigm shift enables the rigorous\, in-situ benchmarking of large-scale devices\, allowing us to characterize unknown interactions and noise sources without preconceptions. Finally\, I will conclude with perspectives on the future of scalable quantum systems\, specifically focusing on AI-assisted quantum control and fault-tolerant architectural designs. \nBiography \nHong-Ye Hu is a Harvard Quantum Initiative (HQI) Fellow working at the intersection of quantum information theory\, quantum many body physics and machine learning. His research focuses on developing scalable methods for quantum control\, verification\, and learning in complex quantum systems\, with applications to quantum simulation\, early fault-tolerant quantum computation and quantum error correction\, as well as modern deep-learning approaches for quantum physics.
URL:https://coe.northeastern.edu/event/joint-special-colloquium-scalable-quantum-applications-synergies-in-control-learning-and-co-design/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260330T113000
DTEND;TZID=America/New_York:20260330T123000
DTSTAMP:20260525T013641
CREATED:20260326T182534Z
LAST-MODIFIED:20260326T184433Z
UID:56044-1774870200-1774873800@coe.northeastern.edu
SUMMARY:JOINT SPECIAL COLLOQUIUM: New Degrees of Freedom for Quantum Hardware
DESCRIPTION:JOINT SPECIAL COLLOQUIUM\nCollege of Science\, College of Engineering & Quantum Materials and Sensing Institute (QMSI)\nNew Degrees of Freedom for Quantum Hardware\nDr. Haoxin Zhou\nUniversity of California\, Berkeley \nMonday\, Mar 30\, 2026; 11:30am to 12:30p.m.\nHosts: Prof. Arun Bansil & Prof. Kin Chung Fong \nVenue: Elliott Hall – Room 130C\, 147 S. Bedford St\, Burlington\, MA\nRemote: MS Teams Link\nAbstract \nRealizing the full potential of quantum information processing requires overcoming fundamental limitations in qubit coherence\, connectivity\, and scalability. One promising pathway is to harness new quantum degrees of freedom in emerging materials to build hybrid quantum hardware. Advances in condensed matter physics have revealed rich macroscopic quantum phenomena in solids\, arising from collective dynamics of electrons and lattice vibrations. Harnessing these excitations opens new opportunities for storing\, transmitting\, and manipulating quantum information. \nIn this talk\, I will explore how such phenomena emerge and how they can be integrated into quantum devices. I will first briefly illustrate how strong electronic interactions generate macroscopic quantum coherence\, for example in graphene van der Waals heterostructures. I will then present recent work revealing interface-induced piezoelectric coupling in superconducting circuits\, which introduces a new qubit decoherence channel while also enabling coherent coupling to acoustic phonons. Finally\, I will outline future directions for hybrid quantum platforms integrating phonons and other collective excitations\, and discuss how artificial intelligence may assist the control and optimization of these complex architectures.\nBiography \nHaoxin Zhou is a postdoctoral researcher at the University of California\, Berkeley\, working with Prof. Alp Sipahigil. His research lies at the intersection of circuit quantum electrodynamics and condensed matter physics\, exploring hybrid quantum systems that couple superconducting qubits to acoustic phonons. He received his Ph.D. in Physics from the University of California\, Santa Barbara\, in 2021\, where he worked with Prof. Andrea Young on correlated electronic phases in graphene Van der Waals heterostructures utilizing cryogenic electrical measurements. He received his B.S. in Physics from the University of Science and Technology of China in 2015.
URL:https://coe.northeastern.edu/event/joint-special-colloquium-new-degrees-of-freedom-for-quantum-hardware/
END:VEVENT
END:VCALENDAR