Stefan Scherer, Ph.D.

Stefan Scherer is the CTO of Embodied, a Research Assistant Professor in the Department of Computer Science at the University of Southern California (USC; on leave), and the Associate Director of Neural Information Processing at the USC Institute for Creative Technologies (ICT). Stefan received the degree of Dr. rer. nat. from the faculty of Engineering and Computer Science at Ulm University in Germany with the grade summa cum laude (i.e. with distinction) in 2011. His research aims to automatically identify characterize, model, and synthesize individuals’ multimodal (non-)verbal behavior within both human-machine as well as machine-mediated human-human interaction. His work is focused on machine learning, multimodal signal processing, and affective computing with applications focussing on healthcare and education. His research was featured in the Economist, the Atlantic, and the Guardian and was awarded a number of best paper awards in renowned international conferences.

Learning Representations of Human Behavior

Advances in computational behavior analyses and machine learning provide an opportunity to profoundly impact a wide range of professions that heavily rely on the interpretation of human behavior (e.g., customer profiling, targeted advertising, interpersonal skill training, and mental health screening). For example, automatic algorithms to detect impairments in social-emotional functioning from individuals’ behavior have the potential to increase the objectivity, accessibility, and efficiency of mental health care. In other words, automatic techniques can provide professionals with a different set of eyes and ears that produce quantified and objective assessments where otherwise only subjective information would be available.

Within this presentation I discuss how we can automatically learn meaningful and discriminatory representations of human behavior while leveraging both (1) explicit descriptors of human behavior motivated by top-down knowledge about human nature as well as (2) advanced machine learning techniques that derive representations automatically and directly from the data; combining the best of both worlds (1) better interpretability of human behavior and (2) exceptional performance in tasks with large quantities of data.

Greg Barding, Ph.D.

Dr. Barding received his B.S. in Chemistry with a Biochemistry Option from California State University, San Bernardino in 2008 and graduated from UC Riverside in 2013 with a Ph.D. in Chemistry.  He was a post-doctoral fellow at the University of Washington, School of Medicine from 2013 – 2014 after which he started his current position as an Assistant Professor at Cal Poly Pomona.

Quantifying the Acetone-Butanol-Ethanol Fermentation Pathway Using NMR Spectroscopy

Biofuels have long been considered a clean alternative to fossil fuels with ethanol a key focus. However, ethanol has several disadvantages as a fossil fuel replacement including the repurposing arable land for corn production specifically to convert to ethanol (limiting corn available for food) and the need to modify gasoline engines to cope with high amounts of ethanol to prevent engine damage. Butanol, another biofuel, is a promising alternative to ethanol as it less hygroscopic than ethanol and can directly be used as a gasoline replacement without engine modification. Additionally, butanol can be produced through acetone-butanol-ethanol (ABE) pathways in some anaerobic bacteria, such as Clostridium beijerinkii, which does not require the reappropriation of arable land for fuel production. Understanding how these pathways interact to produce butanol are important for optimizing the production of the biofuel. Herein, we propose a novel approach using one-dimensional and two-dimensional NMR to quickly quantify the major components of ABE fermentation, including acetone, butanol, ethanol, isopropanol, and acetic acid. 1D NMR can quickly quantify most major components in less than 8 min using standard quantitative techniques, however 2D NMR is required to quantify trace amounts of butyric acid due to spectral convolution. We explored TOCSY and 2D-JRES for suitability when simultaneously quantifying the major products (butanol) while also quantifying the minor products (butyric acid). We developed a simple calibration curve to explore and found that the linearity of both 2D methods was at least than 0.998 and RSD of both 2D methods was less than 8%. Quantification using TOCSY was found to be best, with a RSD less than 5%, however the 2D-JRES method was significantly faster (34 min vs. 161 min). Currently, we are expanding this method to include the other major components and are applying it directly to the effluent produced by Clostridium beijerinkii strains.

Naira Hovakimyan, Ph.D.

Naira Hovakimyan received her MS degree in Theoretical Mechanics and Applied Mathematics in 1988 from Yerevan State University in Armenia. She got her Ph.D. in Physics and Mathematics in 1992 from the Institute of Applied Mathematics of Russian Academy of Sciences in Moscow, majoring in optimal control and differential games. Before joining the faculty of UIUC in 2008, she spent time as a research scientist at Stuttgart University in Germany, French Institute for Research in Computer Science and Automation (INRIA) in France, Georgia Institute of Technology, and she was on faculty of Aerospace and Ocean Engineering of Virginia Tech during 2003-2008. She is currently a W. Grafton and Lillian B. Wilkins Professor of Mechanical Science and Engineering at UIUC. In 2015 she was named inaugural director for Intelligent Robotics Lab of Coordinated Science Laboratory at UIUC. She has co-authored two books, six patents and more than 350 refereed publications. She was the recipient of the SICE International scholarship for the best paper of a young investigator in the VII ISDG Symposium (Japan, 1996), the 2011 recipient of AIAA Mechanics and Control of Flight Award, the 2015 recipient of SWE Achievement Award, the 2017 recipient of IEEE CSS Award for Technical Excellence in Aerospace Controls, and the 2019 recipient of AIAA Pendray Aerospace Literature Award. In 2014 she was awarded the Humboldt prize for her lifetime achievements. In 2015 she was awarded the UIUC Engineering Council Award for Excellence in Advising. She is Fellow and life member of AIAA, a Fellow of IEEE, and a member of SIAM, AMS, SWE, ASME and ISDG. She is cofounder and chief scientist of IntelinAir. Her work in robotics for elderly care was featured in the New York Times, on Fox TV and CNBC. Her research interests are in control and optimization, autonomous systems, neural networks, game theory and their applications in aerospace, robotics, mechanical, agricultural, electrical, petroleum, biomedical engineering and elderly care.

Aerial Co-robots of the Future: Safety, Intelligence, Certification

This presentation discusses the key challenges of the 21st century and puts forward the right perspective for development of aerial co-robots of the future by emphasizing safety, intelligence and certification. Each of these three pillars hinges on fundamental theoretical developments for support. Challenges with flight control, cyber-resilience, cooperative path planning, intelligent control, and certification are discussed, and fundamental limitations of feedback loops are revisited for development of safe intelligent control. The new metrics for certification, important in the era of the fourth industrial revolution and requiring new paradigms for certification, are presented. Applications in elderly care, scalable e-commerce, and precision agriculture are discussed.

Jahan Dawlaty, Ph.D.

Jahan Dawlaty is an associate professor of chemistry at the University of Southern California. He obtained his B.A. in chemistry from Concordia College in Moorhead MN in 2001. He joined the department of chemistry and chemical biology of Cornell University as a graduate student and finished with a Ph.D. degree in 2008. After that, he went to UC Berkeley to complete his postdoctoral work. He started his independent career at USC in 2012 and got promoted to associate professor in 2018. His research is in the area of physical chemistry, with particular attention to fundamentals of structure and dynamics related to charge and energy transfer at the molecular scale.

Light, Electrons, Protons: Lessons from Model Systems and Potentials for Photocatalysis

The inspiration for this talk comes from the photoelectrochemical interface, which is a place rich with unknowns and unrealized potentials. Electrons are excited by light either in the electrode or in the adsorbed molecules, charges traverse the electrode-electrolyte interface, protons flow from the bulk to complete redox reactions, and interfacial electric fields develop to balance chemical potential differences between the opposing phases. In this talk, the complex chemistry at the interface will be used as a point of reference to motivate several chemical dynamics studies in small molecules, solids, and interfaces with the goal of generating new directions and ideas for understanding and driving interfacial reactions. New concepts that will be discussed are basicity in the excited state, solvation near an interface, electronic-vibrational dynamics in a solid made of a redox couple, and influencing proton conductivity with light. Several avenues on how to use this knowledge will be proposed.

Varoujan Gorjian, Ph.D.

Varoujan Gorjian got his B.S. in astronomy at the California Institute of Technology (Caltech) in 1992 and his Ph.D. at the University of California, Los Angeles (UCLA) in 1998. He has been working as a part of the Spitzer Space Telescope project at NASA’s Jet Propulsion Laboratory (JPL) since 1998 and has used it and other telescopes to study supermassive black holes at the centers of galaxies, the star formation history of the Universe, and planets around other stars. He is also engaged in education and public outreach working with Caltech’s Infrared Processing and Analysis Center Communication and Education team.

Lifting the Cosmic Veil: Spitzer Observations from our own Backyard to the Edge of the Universe

Since its launch in 2003, NASA’s Spitzer Space Telescope has used the infrared part of the spectrum to study the Universe near and far. In doing so it has discovered objects as wide raging from a previously unknown ring of Saturn to young galaxies at the edge of the observable Universe. Its greatest legacy though may be the study of the atmospheres of planets around other stars. Come hear about what Spitzer has accomplished and what is in store for its future before the mission is set to come to an end in January of 2020.

Shant Shekherdimian, M.D.

Dr. Shant Shekherdimian is an associate professor of surgery at University of California, Los Angeles. He holds a medical degree from Drexel University and a Masters in Public Health from UCLA. Apart from a busy clinical practice, Dr. Shekherdimian actively engages in clinical and basic science research pertaining to his specialty in pediatric surgery. In addition, he is involved in various initiatives aimed in health system strengthening in Armenia. Shant has mentored numerous medical students and residents, and presents frequently on topics pertaining to health care in Armenia, with a particular focus on defining and optimizing the role of the diaspora.

Armen Mkrtchyan, Ph.D.

Armen Mkrtchyan is a Senior Engagement Manager in McKinsey’s Los Angeles Office and is the co-leader of McKinsey’s Center for Future Mobility on the West Coast.  At the Firm, Armen’s clients primarily include Automotive passenger and truck manufacturers and their suppliers. He also serves electronics and semiconductor players across the value chain both on operational and strategic topics.  Previously, Armen was the Founding Director of the Entrepreneurship and Product Innovation Center (EPIC) at the American University of Armenia and served as an Assistant Professor in the College of Engineering.  Armen has a Ph.D. in Aeronautics and Astronautics from MIT and has worked on the development of various autonomous air and ground vehicles. He received his Bachelor’s degree in Electrical Engineering from the University of North Dakota and has multiple publications in the area of control systems, test and simulation, product development optimization.

Marianna Achemian

Marianna Achemian, born and raised in Yerevan, Armenia. Graduated from Yerevan State University Department of Oriental Studies in 1998, worked as an associate professor of Arabic language at the same department. American University of Armenia’s representative in Southern California since 2008, current position – Associate Director of Development.

AUA is a leading educational institution in Armenia since 1991. Its Zaven Akian College of Engineering and Computer Science (CSE) prepares specialists who continuously prove to be very competitive in Armenia’s tech field job market. A big fraction of the students at CSE are female, and the university has a goal to increase this number further by providing financial support to girls in need you want to pursue their education in these areas. We will show a video approximately 4.5 minutes long and I will talk about AUA and the campaign for about 2 minutes before that. So all in all about 7 minutes. I will be more than happy to answer any questions after the presentation.

Student Presenters:

Sarik Ghazarian: Automatically evaluation of open-domain dialogue systems
Ninareh Mehrabi: Leakage dynamics of faults: Effect of induced seismicity and multiphase flow
Sevan Menachekanian: Design and Optimization of a Low Frequency Raman Microscope for Liquid and Solid-state Sample Analysis
Daniel Minassian: Ecology and evolution of virulent burkholderia pseudomallei
Sophia Nguyen: Influencing Mitochondrial Biogenesis in Satellite Cells to Accelerate the Transition from Quiescence to Activation
Michael Pirjanloo, Armenuhi Sahakyan: Activation of Biologically Relevant Organic Acids
Lilit Vardanyan, Tenny Vasghanian: Challenges of Esterification of Gallic Acid and Its Derivatives
Nicholas Orchanian: Solar Fuels for a Sustainable Energy Future
Zaw Naing: Rapid Determination of the pH of Environmental Water Samples Using Smartphone Colorimetry
Desiree Sarmiento: High Performance Liquid Chromatographic Analysis of Naringin in Dry Pomace of Citrus Sinesis
Andranik Mihranyan: Oxidative Cleavage of Lignin Model Compounds Using Vanadium Catalysts
Natalie Kegulian: Uncovering Amelogenesis-Promoting Mechanism of Ameloblastin Interactions with Amelogenin and with Membranes
David Pogosyan, Aram Sahinyan: Are herbs actually beneficial or did Grandma lie?
Auhbon Amiri: Study of Performance of an Educational Institution in Addressing Academia and Community Needs

More to come! Please check back later.