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The Evidence of Things Not Seen: Searching for Extraterrestrial Intelligence in an Enchanted Universe
No full textThis dissertation examines the search for extraterrestrial intelligence (SETI) as a site where scientific practice contributes to the enchantment of the universe through material and discursive processes that sustain openness to unknowable others. Rather than treating science and religion as exclusive frameworks for being in the world, this study argues that SETI practitioners engage in forms of religious work—mediating presence and absence, cultivating openness to transcendent figures, and managing radical uncertainty. The central problem addressed is how enchantment operates within ostensibly secular scientific spaces, challenging conventional narratives of disenchantment that position science as inherently opposed to mystery, wonder, and non-human agency.
Using ethnographic fieldwork, archival research, and textual analysis conducted between 2022 and 2024, this study traces how SETI researchers create what I term infrastructural and promissory enchantment. Ethnographic observations included participation in weekly research meetings, conferences, and observatory visits, supplemented by interviews with practitioners across major SETI institutions. Archival work at the National Radio Astronomy Observatory examined documents from SETI’s Cold War origins through the 1990s, while textual analysis explored peer-reviewed publications and public communications about extraterrestrial contact scenarios.
The dissertation concludes that SETI practitioners enact what I term ‘pre-enchantment’ through two primary modes: infrastructural practices that create material conditions for alien presence to become detectable (radio observatories, signal processing algorithms, institutional collaborations), and promissory practices that orient this infrastructure toward possible futures through narratives of imagined contact scenarios and experimental design. These practices do not simply await alien signals but actively constitute the conditions under which such signals might emerge as meaningful presences.
Rather than representing a re-enchantment that recovers pre-modern forms of mystery, SETI demonstrates how pre-enchantment emerges through scientific practice itself—creating effects of living in a universe populated by potential presences while remaining within naturalistic frameworks. This enchantment is neither transcendent revelation nor secular wonder, but an ongoing material and temporal arrangement that holds open possibilities for encounter with radical otherness
Learning Robot Manipulation Through Hands of Humans
No full textIntelligent robots should possess the capability to utilize diverse skills to complete a wide range of manipulation tasks. Moreover, they should be able to acquire new skills in a scalable manner. While imitation learning has shown promise for robot skill acquisition, it heavily relies on expensive robot data collection through human teleoperation, making it challenging to scale.
This dissertation aims to develop approaches for robot manipulation skill learning from human video, which is easy to obtain and widely available. The goal is to reduce robot learning's dependence on teleoperation data and develop methods to learn from cross-embodiment data, enabling more scalable skill acquisition. However, the embodiment gap between humans and robots prevents robots from learning manipulation directly from human video. Specifically, both the visual gap (e.g., appearance) and morphology gap (e.g., kinematics) pose significant challenges to transferring human knowledge to robots.
To address this, we propose using different interfaces to minimize the embodiment gap. Here, an interface is defined as a function that maps human knowledge to robot domain knowledge.
This dissertation presents a series of interfaces and associated systems that allow robots to learn directly from human video. First, we present using skills as an interface to implicitly close the visual and morphology gaps by enabling robots to identify skills demonstrated in human video and recompose these skills to complete unseen tasks. We present XSkill and ASPiRe for tasks requiring skill composition. Second, we introduce object flow as an interface to explicitly overcome the visual gap. Our approach, Im2Flow2Act, distills task knowledge by learning an object flow generator from human video while acquiring flow-conditioned manipulation policies from simulation. This system can complete a wide range of manipulation tasks in the real world without requiring real-world robot data.
Finally, we introduce the human hand as an interface to enable humans to teach robots dexterous hand manipulation skills. Our system, DexUMI, is equipped with an exoskeleton as a hardware adaptation layer to minimize the morphology gap and a data processing pipeline as a software adaptation layer to minimize the visual gap.
This dissertation demonstrates that leveraging human video enables robots to learn manipulation skills in a more scalable manner. Furthermore, the proposed interface-based approaches provide a systematic framework for addressing embodiment gaps and offer practical solutions for real-world robot deployment
The Nose Knows: Understanding the molecular underpinnings of learning and adaptation through the main olfactory epithelium
No full textIn order to survive, an animal must adapt to an often-dangerous environment. Natural environments are replete with sensory information that the animal must interrogate and respond to. One class of sensory information is odors. Odors are small volatile molecules that provide information about a range of environmental states, such as potential food, mates, and predators. In turn, olfaction guides adaptive behaviors.
We use the mouse olfactory system to probe how the animal adapts to salient stimuli. We use a behavioral conditioning paradigm called olfactory fear conditioning to teach the mouse to associate a specific odor with a aversive shock stimulus. Odor-shock pairing induces measurable changes in olfactory-guided behavior and in the physiology of the main olfactory epithelium (MOE), the primary sensory tissue of the olfactory system.
Odor-shock pairing induces robust odor aversion. This behavioral phenotype is coupled with transcriptional changes in the MOE that reflect two main adaptations in neuronal tissue: First, odor-sensing neurons become primed to sense the conditioned odor. Second, the identity of odor-sensing neurons becomes biased toward expressing the conditioned odor’s receptor. All in all, odor-shock pairing produces a physiological state that prepares the animal for future odor activity, which in turn facilitates adaptive behavior. This work provides insight into the molecular underpinnings of learning and adaptation, suggesting that sensory tissue itself can harbor experiential memory
Towards Large-Scale IoT Management: A Metadata-Oriented Approach
No full textInternet of Things (IoT) has significantly altered how we operate and interact with physical devices. With billions of connected devices generating vast amounts of data, enormous opportunities have emerged for IoT systems to leverage this data and optimize functionalities. However, this massive influx of devices introduces challenges in interpreting, managing, and utilizing IoT data, devices, and systems. Although the generated data dominates the volume of IoT data, the metadata, i.e., data about the data, is equally critical but, unfortunately, often neglected.
Metadata describes devices and data, playing a crucial role in building reliable IoT management systems, improving data analysis and decision-making, and facilitating interoperability between heterogeneous systems. Metadata provides the necessary contexts and instructions to make sense of devices and enables IoT systems to unlock their full potential.
This dissertation demonstrates how metadata can address the management complexities of large-scale IoT systems, where numerous independently developed devices interoperate and integrate. This is particularly significant as these systems expand beyond a single home or enterprise to span multiple domains. The proposed metadata-oriented IoT management system constructs an overlay on top of today's operational IoT devices. It prioritizes flexible descriptors over fixed identifiers and implements a suite of solutions that includes an IoT metadata name resolver, providing the backbone infrastructure across geographically distributed systems; an attribute-based distributed access control solution for fine-grained and distributed authorization; a policy server with identity-independent policy specifications to enhance system dependability by separating the management workflows from the operation; and a stringent firewall solution that responds to IoT network behavior to secure the systems. Together, these components empower IoT environments that are discoverable and accessible with granularity, safely operable, and robustly programmable on a large scale, thereby extending the functional scope beyond individual smart systems to integrate into broader, more complex networked environments.
This dissertation is organized as follows.
First, we delve into the exploration and categorization of metadata in general, highlighting their significance for managing large-scale computer systems, including file systems and the Web infrastructure. Centered on IoT metadata, we illustrate the challenges and opportunities associated with various facets of existing IoT solutions. We discuss the design principles and system implementation challenges for a reliable, efficient, and federated IoT management system, leading to the fundamentals of Metadata-Oriented IoT Systems (MOIS).
Second, we present the Name Resolver (MOIS-NR), the core infrastructure component of the MOIS system. MOIS-NR resolves IoT names as flexible queries, translating them into specific device metadata via an array of APIs. MOIS-NR organizes a federated set of hierarchically distributed directories. Computational nodes, such as IoT gateways, run discovery agents and mechanisms that collect device metadata to update these directories. Essential device metadata, which includes attributes, descriptive profiles, and recognized network behaviors, empowers the functionalities of MOIS-AC, MOIS-PS, and MOIS-FW, as described below.
Third, we introduce the Access Control (MOIS-AC), which retrieves metadata from MOIS-NR, primarily device attributes, to facilitate informed authorization decisions. MOIS-AC is a systematic, attribute-based access control solution that allows for distributed attribute provisioning with fine granularity. It utilizes metadata to enhance the access control solution, which in turn governs and authorizes access to the metadata itself. The system is bifurcated into two phases: initially granting access to metadata, including the exposure of device APIs, and subsequently utilizing a capability-based approach to obtain a token for extended services or device access.
Fourth, we detail the Policy Server (MOIS-PS). MOIS-PS stores and assesses policies derived from authorities, regulatory agencies, developer communities, and manufacturers, integrating them into IoT management stages. Policies delineate desired and prohibitive behaviors of IoT applications and devices, ensuring operations remain within a normative range, thereby promoting security, safety, and energy conservation. For example, a policy might restrict room temperature settings from dipping below 60 degrees Fahrenheit. MOIS-PS employs a relationship-based design, as opposed to identity-based policies, which allows for device replacement, system upgrades, or software updates without needing the specific devices to be known to the system beforehand. This approach enhances the compatibility, scalability, and reusability of the policies. Serving as the guardian of the system, MOIS-PS ensures that all connected devices operate within predefined and accepted boundaries, thereby offering a unified platform for policy enforcement.
Finally, we outline the Firewall (MOIS-FW). MOIS-FW is a real-time firewall solution incorporating dynamic DNS observation and packet filtration based on DNS responses or static projected traffic behaviors. Here, metadata, predominantly network behavioral profiles, is extracted from MOIS-NR and embedded into firewall strategies. Unlike traditional firewalls, MOIS-FW employs a more aggressive and proactive way, defaulting to a whitelist approach and discarding suspicious packets. It also provides an interactive endpoint to involve administrators in the packet control, i.e., whitelist an endpoint or forward a packet. This dynamic and real-time solution is bolstered by the P4 technology through its runtime control.
To summarize, this dissertation develops a metadata-oriented approach to streamline the design and building blocks of IoT management systems. It introduces a comprehensive set of mechanisms designed to address challenges in device management, name resolution, cross-domain data access, fine-grained authorization, interoperability, and safe operation. By establishing a management plane that overlays the operational workflows, the MOIS solution stack includes, but is not limited to, cleanly decoupled subsystems for metadata-based name resolution and device discovery, distributed access control, policy enforcement, and a dynamic firewall. These components are capable of functioning independently or can be integrated seamlessly to provide a holistic solution for large-scale IoT management. This approach provides IoT system developers and administrators with a foundational and systematic strategy for managing IoT devices as a reliably interconnected and automated ecosystem
Machine learning and Bayesian modeling for quantitative biological imaging: from single molecule localization microscopy to mass spectrometry imaging
No full textThe aim of this work is to establish and demonstrate unbiased, reproducible, and robust approaches to analyzing large and complex data from biological images. With advances in imaging techniques, more comprehensive and detailed data is produced than ever before. Extracting meaning from this data requires careful consideration to avoid overfitting while also maximizing the information and insights that can be gained from the data. Herein, we present two forms of complex and challenging biological imaging data and propose approaches that can be used to extract key information from this data. By leveraging machine learning and Bayesian modeling, we demonstrate robust analysis pipelines for single molecule localization microscopy (SMLM) and mass spectrometry imaging (MSI) data.
In Chapter 1, we present background on the development of modern imaging techniques and discuss in detail the development of SMLM and MSI along with common approaches used to analyze the data produced by these methods.
In Chapter 2, we address a common problem in SMLM and clustering algorithms broadly by proposing a Bayesian optimized approach for selecting density-based clustering algorithm parameters in an unbiased manner that maximizes the density-based cluster validation (DBCV) score. Here, we developed a high-speed implementation of DBCV using a k-dimensional tree and paired it with Bayesian optimization to evaluate a range of clustering parameters, finding the parameters which maximizes the DBCV score. We demonstrate this method (DBOpt) on simulated and experimental data and show the efficiency and effectiveness of the approach.
In Chapter 3, we present an analysis pipeline for extracting key analytes from MSI data. In particular, we analyze lipid abundance and spatial distribution of lipids in MDA-MB-231 breast cancer cells that have an oncogenic mutant-p53 protein compared to those where the protein is knocked down. Here, we employ supervised learning with a support vector machine to segment the data into regions of interest that correspond to cell invasion. We then leverage a Bayesian hierarchical model to quantify the probabilities that analytes are impacted by the knockdown of mutant-p53 and we identify the spatially dependent role of p53 in modulating key phospholipids and metabolites across the sample
Orbital Analysis, Microwave Power Beaming and Semiconductor Material Damage Assessment for Space-Based-Solar Systems
No full textTechnological advancements must keep pace with the earth’s rising demand for energy, while minimizing the carbon footprint on earth. One such option is using space based solar (SBS) energy harvesting and radiofrequency (RF) microwave power beaming. In 1968, Dr. Peter Glaser published "Power from the Sun: Its Future", qualitatively illustrating that SBS can be, at some time in the future, a solution to solar intermittency on earth. However, the high cost of this option and the drastically reduced cost of terrestrial solar energy combined in leaving this concept as aspirational as a trip to other planets. This technology is currently being explored under a renewed prism, to address not only terrestrial photovoltaic (PV) intermittency but also in high latitude remote areas and to transmit power to spacecraft in various orbits. A catalyst of this renewed interest is the promise of reusable launch vehicles (RLV) which can drastically reduce the cost of bringing SBS components to orbit.
This dissertation offers an overview of the current status on SBS research and space industry capabilities. It includes a discussion of reliance of SBS initiatives on (RLV) to place SBS spacecraft in various designated orbits, as well as the technological, economic, and operational challenges associated with power beaming to earth and other spacecraft. Moreover, this dissertation presents a novel investigation of the pros and cons for SBS deployment in different orbits coupled with semiconductor material damage analysis associated with each orbital environment.
Power beaming will be accomplished via microwave emissions, and transmit power to both terrestrial ground stations, as well as other space vehicles (SV) in various earth orbits. This dissertation includes the mechanics of energy transferred from point to point, as well a detailed analysis of the medium (i.e., atmospheric scattering due to gaseous attenuation of the wireless energy) in which the energy must pass, with a comprehensive explanation of the associated losses therein. Power beaming is the” The limitations of wireless power transfer (WPT) are explored, where power beaming “efficient point-to-point transfer of electrical energy across free space by a directive electromagnetic beam” utilizes directive propagated waves that exclude waveform that can be used in destructive applications. In this dissertation, the use of power beaming is suggested primarily for use in delivering power to remote terrestrial areas such as forward operating bases (FOB), industrial sites, and unmanned vehicles (both on ground and in the air).. The use of microwave emissions is the focus for this dissertation as this mode offers the ideal solution in terms of efficiency for transmitting large amounts of power over long distances. A conceptual framework and mathematical model are developed to quantify the system limitations for power beaming based on current technology.
Radiation impacts on space-based systems operating on various orbits were evaluated. The software utilized for this dissertation include: (1) COMSOL Multiphysics v2.1, where Monte Carlo simulations were run for charged particle tracing and particle matter interactions, which were additionally tailored for different materials (i.e., GaAs, SiC). (2) Matlab was used for developing unique simulations to complete numerous orbital analysis, transmission of RF energy through the atmosphere, and lunar trajectories; Matlab was also used in the materials assessment of GaAs/InP PV cells, using the (3) MC-SCREAM software developed by the Naval Research Laboratory. This software was modified and expanded to use the specific PV cells for space vehicles, various types of cover glass and dielectric coatings, and a new radiation library database for radiation spectra in various orbits using (4) SPENVIS. Calculations for various material non-ionizing energy loss (NIEL) profiles were completed in (5) SR-NIEL to input into MC-SCREAM, further expanding the software to meet the analysis needs in this dissertation. Specifically, satellite operations in LEO, MEO, and Geosynchronous Orbit (GEO) were analyzed. Special focus is given on quantifying the effect of high energy particle space radiation on materials used for critical power components, where component fault can lead to total mission failure.
Methods, using multiple computational platforms for the quantification of NIEL and displacement damage dose (DDD), are used to assess semiconductor damage as a function of orbital altitude. Detailed simulations were conducted for Gallium Arsenide Indium Phosphide (GaAs/InP) solar cells with various cover glass thicknesses. It was assessed that radiation exposure due to high energy protons at 10000 km is more prevalent than 20000 km orbits and that electrons are the major electronics damage culprits. For MEO at 10000 km, MEO at 20000 km, and GEO at 36000 km, we determined 1-year maximum power (Pmax) losses due to protons to be 23%, 8%, and 1%, and losses due to electrons at 11%, 14% and 10%. Total combined spectra Pmax losses for those altitudes are 25%, 16%, and 10%, respectively. The results of the simulations were verified with previous limited scope damage analysis of satellites operating in LEO, and the survivability of GaAs cells was compared with that of Si cells. The intended spacecraft mission will often dictate the orbit in which it operates, with particular attention to the tradeoffs between operational requirements (i.e., time on top overhead of the receiver site influenced by orbital period) and orbital considerations (i.e., radiation impacts, thermal ranges, altitude deconfliction with other SVs, space debris deconfliction).. There is also a cost evaluation to consider for each orbit, specifically for the launch vehicle (LV).
This dissertation identified and assessed system efficiencies, and the orbital analysis required for SBS power beaming to remote terrestrial areas and to other spacecraft from SBS systems operating in LEO, MEO and GEO. Specific scenarios are presented to demonstrate simulation capabilities using Matlab/Simulink which provide orbit visualization, control of classical orbital elements (COEs) to determine power beaming overhead time to remote locations and other satellites, as well as eclipse cycles and solar capture forecasts. Other simulation results to support SBS operations include earth space propagation and transmission losses for desired RF microwave power beaming wavelengths. The various orbits presented as candidates for power beaming satellites are additionally presented with the associated radiation spectra for trapped protons and electrons. Radiation spectra data collection methodology is also presented, and was used for determination of radiation shielding materials, satellite survivability, and longevity for a specified mission duration. From our analysis, we identified the SBS orbit requirements for continuous space-to-earth power beaming using criteria such as overhead time, earth coverage and RF spot size, solar capture, and power delivered at the receiver site. 10000 km MEO circular orbits with 55-degree inclination are potential candidates for SBS satellites, with overhead time for a single satellite forecasted at 28%, covering 30% of earth, while optimizing solar capture at 97%. Technology improvements can increase predicted power transmission efficiencies by 5-10% through RF beam and phase focusing.
This research stems from the Air Force Research Laboratory’s (AFRL) Space Solar Power Incremental Demonstrations and Research (SSPIDR) initiative, which includes the power beaming demonstration payload known as Space Solar Power Radio Frequency Integrated Transmission Experiment (SSPRITE)
Parent-Child Language Gaps and Empathic Accuracy in Conflict Discussions: A Mixed Methods Study of Bilingual Chinese Immigrant Parent-Child Dyads
No full textChinese immigrant families in the United States are often bilingual, defined as having the knowledge of two languages (e.g., English and a heritage language such as Chinese) and using those languages in everyday life with varying proficiency levels for each language. These varying proficiency levels in both languages, otherwise termed language gaps (i.e., language matches or mismatches), have been shown to impact parent-child relationships. Language gaps may contribute to communication difficulties and increased family conflict during middle childhood (roughly ages 6-12), which places school-age children at increased risk for poorer psychological outcomes.
Some of these communication challenges may be due to differences in empathic accuracy, defined as the degree to which a person accurately infers another person’s thoughts and feelings. Chinese immigrant parents and children who misinterpret one another’s emotions and demonstrate lower empathic accuracy may experience increased family conflict. Observations of conflict discussions are necessary to explore these constructs in real time, but many existing studies have not been able to examine parent-child conflict discussions as they occur due to the sensitive nature of these conversations, and especially not in bilingual Chinese immigrant families.
Utilizing multidisciplinary theoretical frameworks and multi-informant perspectives, this dissertation study used a convergent mixed methods design to examine how English and Chinese language proficiency gaps (i.e., match/mismatch) among Chinese immigrant parents and their school-age children are associated with parent-child empathic accuracy and evaluations of their conflict discussion. This study had two aims: 1) examine how parent-child language proficiency gaps in English and Chinese are associated with parent and child empathic accuracy and conflict evaluations, and 2) identify examples and patterns of conversational practices used between parents and children during the conflict discussions to corroborate the aforementioned relationships.
Participants in the quantitative portion of the study were the full sample of 169 children between the ages of 7-11 (M = 9.16 years, SD = 1.05) and one of their parents (Mage = 40.93 years, SD = 4.88). Parents completed self-report questionnaires and interviews indicating their demographic information as well as parent and child language proficiency, and both parents and children self-reported their empathic accuracy and conflict evaluation ratings. Participants in the qualitative portion of the study (n = 9) were identified from the full sample using random sampling based on the parent-child language match (i.e., match in low Chinese proficiency, match in high Chinese proficiency, match in low English proficiency, match in high English proficiency).
To examine how parent-child language proficiency gaps in English and Chinese are associated with parent and child empathic accuracy and conflict evaluations, Response Surface Analysis (RSA) plots were utilized to examine the nonlinear relationships between parent-child language proficiency on the outcomes of interest. Path analyses using structural equation modeling examined the mediating role of parent-child empathic accuracy on the associations between parent-child language proficiency in English and Chinese and their conflict evaluations. To identify examples of conversational practices used between parents and children in conflict discussions, Conversation Analysis, an applied linguistics methodology, was used to identify themes of conversational practices that helped to explain the quantitative results.
Results through Response Surface Analysis (RSA) plots indicated that 1) compared to parent-child dyads with match in low English proficiency, parents in parent-child dyads who matched at higher levels of English proficiency exhibited higher levels of empathic accuracy, 2) compared to parent-child dyads in which parent English proficiency is higher than the child’s English proficiency, parents in parent-child dyads in which child English proficiency was higher than parent English proficiency exhibited higher levels of empathic accuracy, and 3) among parent-child dyads who matched at higher levels of English proficiency, children exhibited higher levels of empathic accuracy than among parent-child dyads who matched at lower levels of English proficiency. Path analyses results indicated that children with higher English proficiency reported a more positive conflict evaluation when their parents exhibited greater empathic accuracy. Conversation Analysis (CA) was used to identify the conversational practices that parents and children used during the conflict discussions that corroborated the quantitative findings. The integration of quantitative and qualitative findings identified domains and themes of conversational practices that help to explain parents’ greater empathic accuracy and children’s more positive conflict evaluations.
These findings have implications for future research and interventions addressing parent-child relationships and communication in bilingual Chinese immigrant families. Attention to the language gap and use among bilingual Chinese immigrant parents and their school-age children may generate more insight into immigrant family dynamics and culturally relevant ways to strengthen parent-child relationship quality within these families
Advancing the Monoaminergic Neurotransmission Investigative Toolbox: Integrating the Developments of Fluorescent Optical Tracers and Inhibitors
No full textMonoaminergic neurotransmission regulates numerous fundamental functions of the nervous system, including mood, cognition, learning, motor function, reward, sleep and wakefulness cycles. Its life cycle consists of the synthesis of modulatory neurotransmitters (namely, dopamine, norepinephrine, and serotonin) that are then sequestered into acidic synaptic vesicles (through vesicular monoamine transporter 2, VMAT2, in the brain) and subsequently released to the extracellular space upon vesicular fusion with the presynaptic bouton plasma membrane. These monoamines are then taken up by plasma membrane transporters, including dopamine (DAT), norepinephrine (NET), and serotonin (SERT) transporters, for either cyclic repetition of release and uptake, or degradation. Dysregulation of such processes, resulting in concentration imbalances, have been implicated in numerous pathologies including, depression, drug addiction, and Parkinson’s Disease. Consequently, modern tools, specifically fluorescent optical tracers and monoamine transporter reuptake inhibitors, are necessary for the rigorous investigation of these etiologies.
Chapter 1 highlights the development of novel small molecule fluorescent optical probes that enable the visualization of serotonergic reuptake molecular machinery. Exploring the acridones fluorophore core has yielded the introduction of the first serotonergic fluorescent false neurotransmitter, FFN246, and a bright Uptake 1 transporter system substrate, DD545. The development of a more hydrophilic serotonergic substrate that can be multiplexed with protein-based genetically encoded monoamine biosensors was catalyzed with the discovery of SERTlight after rigorous exploration of the quinolone molecular scaffold.
The second part of the thesis delves into the pharmacological development of novel monoamine transporter reuptake inhibitors amongst different natural product-based scaffolds. In Chapter 2, a thorough investigation of the ibogaine scaffold (including its deconstructed components) has resulted in the introduction of a taxonomic class termed “Synaptic Reuptake Inhibitors”, which introduces concomitant inhibition of two critical serotonergic targets: SERT and VMAT2 inhibition. Chapter 3 details the discovery of speciociliatine as the alkaloid extracted from Mitragyna speciosa that has a sub-micromolar pharmacological as a selective and potent VMAT2 inhibitor.
The final two chapters of the thesis introduce nascent monoamine transporter inhibition structure-and-activity relationships of two molecular scaffolds with members that are becoming a growing societal burden. Chapter 4 examines the amphetamine molecular class and its SAR with respect to monoamine release versus uptake inhibition. Chapter 5 probes whether the adverse effects as witnessed from usage of methylmethcathinone and its derivatives can be attributed to monoamine transporter inhibition
Spatiotemporal imaging of exciton-polariton transport and nonlinear optics in van der Waals semiconductors under strong light-matter coupling
No full textThe development of quantum and nonlinear photonic technologies requires material systems that support both efficient light propagation and strong optical interactions—ideally under ambient conditions. Exciton-polaritons, formed by the strong coupling between excitons and cavity photons, represent a promising platform that combines the coherence and speed of photons with the interaction strength of matter. However, achieving robust, coherent transport and efficient nonlinear conversion at room temperature remains a major challenge due to phonon-induced dephasing and limited nonlinear phase-matching in solid-state systems. Additionally, controlling pseudospin light transport for spintronic applications has been largely constrained to photonic engineering and remains underexplored in van der Waals semiconductors.
This dissertation addresses these challenges by exploring coherent exciton-polariton transport dynamics through strong light-matter interaction in van der Waals semiconductor microcavities, including polariton-phonon scattering, nonlinear optics, and spin-orbit coupling. To investigate polariton transport, we developed momentum-resolved ultrafast imaging microspectroscopy capable of tracking polariton propagation in real space with sub-micrometer and femtosecond resolution. Using halide perovskites BA₂MAPb₂I₇ microcavities, we quantified the influence of exciton–phonon interactions on transport and coherence properties. For nonlinear optics, we applied ultrafast far-field imaging to rhombohedral-stacked MoS₂ waveguides, enabling direct measurement of phase-matching conditions, mode profiles, and optical losses. To study intrinsic spin-orbit coupling in polariton transport, we investigated the optical spin hall effect of waveguided photon currents in highly anisotropic NbOI₂ waveguides.
Together, these results demonstrate that strong light–matter coupling in van der Waals semiconductors enables coherent polariton transport up to a critical excitonic fraction, beyond which phonon scattering induces diffusive behavior. Efficient second-harmonic generation is achieved through birefringent phase matching and modal phase-matching, confirming the potential of van der Waals materials for integrated nonlinear photonic devices. Furthermore, the discovery of pronounced optical spin hall effect in NbOI₂ waveguides indicates the generality of spin-orbit coupled polariton transport in birefringent microcavities, allowing remarkably efficient on-chip beam steering for next-generation photonic computing and sensing architectures. This work lays the foundation for scalable, multifunctional optoelectronic and optical spintronic devices based on van der Waals semiconductors
Acceptance Speech of Robert E. Pollack, TANNENBAUM-WARNER AWARDEE
No full textIn this speech, Robert E. Pollack reflects on his lifelong connection to Columbia University, beginning in 1957 as an undergraduate and continuing through his roles as professor, Dean of Columbia College, Director of The University Seminars, and now Professor Emeritus of Biological Sciences. He emphasizes the enduring importance of the Core Curriculum in shaping the College’s educational mission and advocates for deeper faculty engagement from across the Arts and Sciences.
Pollack also honors the legacy of Robert Belknap, a formative mentor and former Director of The University Seminars, whose teaching and friendship exemplified the collaborative spirit of intellectual exchange that the Seminars were founded to promote. This speech captures not only a personal and institutional history but also a call to renew Columbia’s foundational commitments to dialogue, diversity, and undergraduate education