Research @ ASDRP
Find the latest updates in student research here.
Research at ASDRP is grouped under one of three departments:
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Biological, Human, & Life Sciences
Department Chair: Soumya Suresh
The Biology Department encompasses research in a variety of life science disciplines, including molecular & cell biology, genetics, microbiology, biochemistry, ecology, environmental science, evolution, biotechnology, and psychology.
Chemistry, Biochemistry, & Physical Science
Department Chair: Edward Njoo
The Chemistry Department includes research in organic/medicinal, inorganic, physical, and biochemistry, as well as condensed matter physics, theoretical physics, and materials science and engineering.
Computer Science and Engineering
Department Chair: Robert A. Downing
The CS/Engineering Department includes research faculty in machine learning, data science, theoretical modeling, software/hardware engineering, quantum mechanics, mechanical engineering, and electrical engineering.
PUBLISHING
ASDRP student researchers present their work at a poster session (includes professional judges) and publish a research paper in our online journal, ASDRP Communications.
Further, many ASDRP student researchers are able to work with their mentors to submit their research to science fairs and peer-reviewed journals for publication. In fact, over 15 research papers from ASDRP 2022 students have been submitted for publication in undergraduate/high school level research journals. Multiple groups also presented posters at undergraduate research conferences. Such visible evidence of scholarly achievement provide students competitive advantages in matriculation to their choice of an institution of higher learning.
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Here is a list of research projects and research mentors from the 2019 and 2018 cohort. The projects spanned various disciplines across STEM, including chemistry, biology, computer science, and mechanical engineering. Each project group contained from 3-4 students. Please also see the actual research papers.
SAMPLE PAST RESEARCH| Summer 2018 & 2019
Assessing Echinoderms for Wasting Disease-Associated Densovirus (2018)
Laasya Babbellapati, Alysha Batada, Vibha Govindarajan, Shruti Janardhanan, Sarah Mughal; Advisor: A. M. Kruger
Field: Ecology, Molecular Biology
Along the west coast of North America, large populations of over 20 asteroid echinoderm species have been impacted by an epidemic influencing coastal communities. Sea star wasting disease (SSWD) has caused mass mortality of asteroids and other echinoderms which exhibit symptoms that include lesions, turgor loss, changes in behavior, limb loss, and more. SSWD has been traced to a single densovirus (Parvoviridae). For this project, we sampled tissues from sea stars and sea urchins from populations in the California north coast and extracted their DNA. We then conducted PCR to amplify viral DNA to look for its presence in both animals affected and unaffected by disease. [Poster] [PDF]
Implementing data mining to find potentially habitable exoplanets (2019)
Alan Guo, Alan Yao, Anish Sundaram, Cameron Chen, Dawson Lin, Grace Le McGahan, Jason Tse, Laasya Babbellapati, Meghna Kiran, Nihal Sundarrajan, Niserg Desai, Rayland Ho, Sushruth Booma, Timothy Gao; Advisor: R. A. Downing
Field: Data Science, Astronomy, Computer Science
As of August 8th, 2019, approximately four thousand stellar and planetary objects have been discovered and recorded by NASA and Caltech, with additions dynamically added as information is verified. Recorded in this dataset are hundreds of exoplanets, or planets that exist beyond the boundaries of our own solar system. Some of these exoplanets might have the ability to sustain liquid water, but as of now the process to sort through this ever-increasing dataset is time-consuming and ineffective. This paper seeks to solve this issue and simplify the procedure through the use of algorithms which identify any viable exoplanets within their parent star’s “Goldilocks” zone, meaning they have the potential to sustain liquid water, and thus life as we know it. We also seek to create a solution to determining habitability that functions on all stellar types, meaning that determination is possible regardless of the characteristics of a planet’s host star. A combination of Python and SQL was used to datamine the extensive public dataset provided by NASA and Caltech. With the exception of types L, O, and T due to extreme temperatures, all major spectral types were analyzed in the study. [Poster] [PDF]
Algorithmic Bias in Artificial Intelligence and Machine Learning (2019)
Atharva Gupta, Michael Lutz, Aria Lakhmani, Kevin Wang, Saniya Karwa, Anya Agarwal, Elaine Huang; Advisor: P. Mui
Field: Artificial intelligence, policy research, data analysis
Algorithmic bias is an increasing serious societal issue. It occurs when the outcomes of a software program are biased based on data collected or algorithms created by non-representative groups of humans. A few months ago, Amazon needed to scrap its "artificial intelligence" based recruiting tool because the selection was shown to be biased against women. Other examples include search engine results and social media platforms. All of these wonders of "AI" already have significant impact ranging from inadvertent privacy violations to reinforcing social biases of race, gender, sexuality, and ethnicity. In this research, we are interested to study algorithmic biases that reflect "systematic and unfair" discrimination. [Poster] [PDF]
Late-Stage Beckmann Rearrangements of Dibenzylidene Cyclohexanones Towards Development of Novel Caprolactam Non-Nucleoside Reverse Transcriptase Inhibitors
Sana Prasad, Amy Phi, Alicia Tee, Apurva Papolu, Rohan Adwankar, Simone Khandpekar; Advisor: E. S. Njoo
Field: Organic Chemistry, Medicinal Chemistry
HIV (human immunodeficiency virus) is a global health epidemic. HIV and other retroviruses rely upon reverse transcriptase (RT) for the conversion of their RNA genome into double stranded DNA, which in turn is essential for viral replication. Previously, much work has been done in the design and synthesis of RT inhibitors as potential therapeutics for slowing the progression of retrovirus infection by allosteric inhibition of reverse transcriptase - though diverse in structure, known RT inhibitors generally adopt a “butterfly” geometry with a central carbonyl moiety flanked by aromatic or aliphatic substituents. Here, we utilize the tools of synthetic chemistry, biophysical chemistry, and molecular biology in the design and evaluation of potential reverse transcriptase inhibitors. Specifically, we are interested in utilization of the Beckmann rearrangement as a strategy for introducing late-stage ring expansion towards the synthesis of a library of molecules that fit the “butterfly” pharmacophore model and share a common caprolactam core. [Poster] [PDF]
Agent-Based Modeling of Tumor Metastasis and Development (2018)
Rishi Jain, Anirudh Valiveru, Shivek Narang, Elaine Huang; Advisor: J. Qian
Field: Computational Biology and Biophysics
Here, we use agent-based modeling, a robust and important modeling approach used in computational biology and systems engineering that is able to capture biological complexity and emergent behavior in complex systems. We develop an ecologically-oriented, individual-based model capturing how tumor cells cooperate, compete, and evolve in a dynamic microenvironment. We model a tumor with heterogeneous cells that individually choose whether to expend energy to produce public goods from which all cells in the tumor can benefit. Meanwhile, cheaters may benefit from the resources without contributing to the tumor cellular society. We introduce evolution into our model and implement resource dynamics in a similar way to biochemical metabolic resource models. We find many interesting cellular dynamics in our model, including the scenarios in which metastasis or drug resistance may or may not occur. We find that historical contingency becomes important in certain circumstances. Our work represents an interdisciplinary approach bridging agent-based modeling, complex systems, evolutionary and ecological theory, and cancer biology. [Poster] [PDF]
Different Types of Music and Their Effects on Memory and Perception of Violence (2019)
Gianna Chan, Samantha Chou, Trisha Dharmapuri, Eryn Duong, Lauren Hung, Piusha Pandey, Catherine Chen Advisor: J. Teso
Field: Psychology, Cognitive Science
Research shows that the recollection of memory can be affected by a variety of factors. A particular situation where accurate recall memory is used could be during courtroom following a car accident, where an eyewitness’ testimony of an event is crucial. It is also important to understand the factors that affect people’s interpretation of events. Our experiment aims to identify the effects of different types of music on the ability to recall information, as well as the perception of violence while viewing car crash clips. In order to do this, participants in their teenage years (14-18) watched a car crash compilation with either violent, calm, or no music in the background. After participants watched the video, they answered a questionnaire designed to examine their memory of the car crashes, as well as their perception of how violent the crashes were. Our results do not show a significant difference in memory and violence perception between the three groups. However, the calm music group demonstrated the highest recall ability, which corresponds to findings of classical music sharpening the participants’ ability to remember. [Poster] [PDF]
Wind Turbine Blade Manufacturing and Optimization using 3D Printing (2018)
Parth Anjaria, Alex Wang, Jonathan Ye, Charley Zhao; Advisor: N. Papano
Field: Mechanical Engineering
Currently, wind turbine blades are unable to convert more than 30%-50% of the input energy to electricity (depending on if the turbine is onshore or offshore). Our research uses 3D printing to manipulate different aspects of the turbine blade: number of blades: length of the blades, curvature on the blades, base of the blades (flat bladed or not): the angle at which blades are set relative to the hub, and and the angle of the blade at the hub. The turbine blade was then exposed to wind to imitate real situations and deduce factors which can help optimize wind turbine blades for energy output. Using CAD and varying the shapes of the blades, our intent for the project is to discern if 3D printing is accurate enough to test and produce wind turbine blades in comparison to the current, more expensive method of injection-molded turbines. [Poster] [PDF]
The Detection and Sequencing of Coccidioides immitis in Soils Throughout Contra Costa County (2019)
Manal Ahmed, Manasa Raghavan, Ria Kolala, Krithikaa Premnath, Manish Kavuri; Advisor: P. Kaur
Field: Genetics, Microbiology
Coccidioides immitis, commonly known as valley fever, is an endemic and pathogenic fungus found in dry, semi arid soil areas. This fungus causes lung disease with flu like symptoms, and can be contracted by breathing in fungal spores Additionally, there are no vaccines available meaning the human immune system has a difficult time fighting off the Valley Fever disease. The fungus typically is thought to reside at least 50 centimeters underground, and prefers undisturbed desert climates. Recently, the soil has been found in California soils, identified through the Ribosomal DNA sequence containing the 18S gene. [Poster] [PDF]
In Silico Development of Novel Inhibitors of Retinoid X Receptor (RXR) (2019)
Ashish Basetty, Rishab Pangal, Jonathan Tao; Advisor: H.S. Brah
Field: Computational Biochemistry
Retinoid X Receptor (RXR) is a nuclear receptor that plays a crucial role in transcription, where the cell turns genetic code into RNA to be used to create proteins.Our procedure involved creating a model of a possible inhibitor in Avogadro, and then running a DFT (density field theory) optimization with ORCA to estimate the real structure of the molecule. We then used Autodock Tools and Vina to dock (see how the molecule binds) the inhibitor to a model of RXR, and visualize how they interact using PyMol. Our research yielded multiple novel inhibitor candidates, with high binding affinities for RXR. [Poster] [PDF]
Predicting Hartree-Fock Energies for Higher Orders of Moller-Plesset Calculations (2019)
Nidhir Guggilla, Maximilian Wang, Andy Fu, Andrew Le, Pratheek Sankeshi, Rishika Thorat; Advisor: L. McMahan
Field: Quantum Physics, Computer Science
Møller–Plesset perturbation theory is one of many quantum chemistry post-Hartree–Fock ab initio methods used to solve the wave function of many bodied systems in the field of computational chemistry. Møller–Plesset improves upon the energy approximations of particles, molecules, or systems that are input by more accurately accounting for the effects of each electron by every other electron (correlation energy). Using higher order Møller–Plesset calculations yields more accurate energies, but doing such calculations become too computationally expensive and time consuming to be practical. The purpose of this study was to use the lower order Møller–Plesset calculations to predict the values of higher order calculations. Of interest is that mathematically, Møller–Plesset calculations should result in data that can be modeled by a damped sine curve. The data collected does not match that prediction except in one case. Further studies should aim to determine the cause of the deviation from expected results. [Poster] [PDF]
Synthesizing and Optimizing Piezoelectric Potassium Sodium Tartrate Crystals (2019)
Parth Anjaria, Tiffany Zhang, Leo Yang, Arvind Jayaraman, Darren Tang; Advisor: Y. K. Johar
Field: Materials Engineering, Physical Chemistry
Piezoelectricity, or the ability to convert applied mechanical stress on specific axes into a voltage, is found in certain materials including crystals and poled ceramics. Our project focuses on Rochelle salt (KNaC4H4O6·4H2O), a naturally occurring crystalline solid that exhibits piezoelectric and ferroelectric properties between the Curie temperatures of -18°C and 24°C.1 Inside this Curie temperature range, Rochelle salt exhibits a monoclinic structure, meaning the dipole moments are at an angle —leading to the creation of a voltage (Figure 1).2 Outside this Curie temperature range, however, Rochelle salt exhibits an orthorhombic structure which prevents any net dipole moment from forming as the dipole moments cancel each other out. This project attempts to synthesize and utilize these piezoelectric properties exhibited by Rochelle salt to derive electricity by placing mechanical stress on the crystals. With emphasis on the direct piezoelectric effect, multiple factors including the synthesis procedure, crystal mass, voltage generation, and the size of the crystal are analyzed to possibly optimize the voltage generated from each crystal. As the search for clean renewable energy is becoming increasingly dire, usage of piezoelectricity may become increasingly important as an alternative green energy source. The results of this study can be used on a multitude of other applications that are both environmentally and economically friendly.​ [Poster] [PDF]
Analyzing eDNA to Detect Presence of O. mykiss and G. aculeatus (2019)
Meher Mehta, Jeffy Li, Sriansh Pasumarthi; Advisor: S. Suresh
Field: Molecular Biology, Environmental Science
The Oncorhynchus mykiss (Steelhead Trout) and Gasterosteus aculeatus (Threespine Stickleback) are endangered fish indigenous to North America. Both are anadromous, meaning they travel from the ocean to freshwater to spawn. The construction of a replacement Calaveras Dam in 2019 without a suitable fish ladder for O. mykiss meant most anadromous species would no longer have a migration route, through a fish ladder was built at a diversion dam rather than the primary Calaveras Dam. Therefore, some scattered reports have documented declining numbers of both fish. eDNA (environmental DNA) was collected from two locations along Alameda Creek: one in Sunol Regional Wilderness and one at the Upper Rubber Dam. [Poster] [PDF]
Synthesis, Characterization, and Antibiotic Efficacy of Pterin-based Inhibitors of Dihydropteroate Synthase (2019)
Warren Chang, Arielle Dong, Kimberly Huang, Vigasini Rajaram, Anirudh Valiveru, Harshith Yallampalli; Advisor: A. Gupta, E. Njoo, C. Truong
Field: Chemical Biology, Molecular Biology, Medicinal Chemistry
Antibiotic resistance evolution is a rapidly growing problem in pharmaceutical development; in the United States alone, antibiotic-resistant bacterial infections cause an estimated 23,000 deaths annually. A target for further pharmaceutical development is the enzyme Dihydropteroate Synthase (DHPS), which plays a key role in bacterial biosynthesis of folic acid. Sulphonamides, including drugs Sulfamethoxazole and Sulfatrim, bind and act as competitive substrates to p-aminobenzoic acid. However, the evolution of new resistant strains necessitates the continued development of new compounds. Here, we report the design, combinatorial synthesis, and antibacterial properties of a library of novel biaryl small molecules mimicking folic acid to target the pABA and pterin binding pocket. Compounds were first screened in silico via docking to the binding pocket in DHPS. Antibiotic efficacy of these compounds was then tested on four strains of bacteria related to human pathogens through a MIC assay. A folic acid rescue assay and ELISA were utilized to verify the mode of action as acting on DHPS in the biosynthetic pathway. These results establish a definitive structure-activity relationship for the compounds studied, and provide a basis for future development of antibiotics targeting DHPS. [Poster] [PDF]
The Emotional Impacts of Social Media Use (2019)
Srihitha Pallapothula, Suma Vintha, Sonali Pandey, Srila Palanikumar; Advisor: J. Guo
Field: Psychology, Data Science
This study looked into the potential causes of the recent dramatic increase in local high school suicides. Past studies have linked social media with several negative consequences including depression in young people and adolescents. In this study, the hypothesis being evaluated was that spending more time on social media negatively impacts one’s mood. Forty-five participants completed a nineteen question online survey reflecting their social media usage over a period of one week. The original hypothesis was disproven, and the authors concluded that time spent has no correlation with the individual’s emotional health. Instead, it is what an individual does in that time that affects the individual’s emotional health. For further accuracy, if this study is replicated with a broader range of participants, it
would yield more statistically significant results. [Poster] [PDF]
Generation of Escherichia coli Resistant Mutants using CRIPSR/Cas9 Knock-in Technology (2019)
Katrina Mae Reyes, Arezo Ahmadi, Avi Khanna, Sachi Goel, Shivani Naayak; Advisor: H. Dantara
Field: Molecular Biology, Genetics
The problem of antibiotic resistance affects two million people from the United States with 23,000 deaths being recorded due to these strains annually. Streptomycin resistance is traced back to mutations in rpsL gene coding for S12 ribosomal protein. This antibiotic functions by interacting with the small ribosomal unit. The recent proposed mechanism of CRISPR techniques, which is included in the defense mechanism of bacteria against bacteriophages, is organized in repeating sequences of base pairs that have spacers in between. Among the systems of CRISPR that are associated with various protein is CRISPR-Cas9. This system can identify the target sequence that is specific to the targeted sequence. The Cas9 protein has components that can cleave the target sequence. The efficiency of this system partly relies on homology directed repair which is activated through detection of breakage in the strands. This mechanism allows for the insertion or deletion of a sequence. Using the mechanism of CRISPR while also depending on the cells’ response to temperature changes and their natural repair system, homologous recombination, the genome of E. coli is edited. Through this mechanism, a mutagenized rpsL gene coding for the S12 ribosomal protein is generated into the bacteria’s genome, ultimately inducing resistance to streptomycin. [Poster] [PDF]
Using Total Phosphate-phosphorus and nitrates to determine pollution levels of water in Berkeley Marina (2019)
Dennis Cao, Lizhi Cen, Sai Sri Pranathi Kolavennu, Angela Xuan; Advisor: J. Shurtz
Field: Marine Biology, Analytical Chemistry
Due to the many factories in the Berkeley Marina and its surrounding areas, pollution has greatly affected the water and organisms that inhabit it. We went to Berkeley Marina to collect water samples and determine its concentration of phosphates, indicators of pollution. We report that the pollution that is created as a byproduct of human activity in the Berkeley Marina area could lead to the overgrowth of aquatic plant life which could potentially affect wildlife if continued. This was done by utilizing a dual-spectrophotometric approach utilizing absorbance data of both the phosphate content and nitrate content of the water at the sampling location.
[Poster] [PDF]
