Research Project

Students in the Summer STEM Institute (SSI) Research Program will also spend the 6-week program working on a mentored data science research project. The research program was designed for a completely virtual setting. Students will learn how to use modern technological tools such as open-source data analytics packages, publicly available datasets, and cloud computing resources to complete their data science research projects. Students will also have access to project resources being developed by Eric Zhang, a 2x gold medalist at the International Olympiad in Informatics (IOI).

Communication between students and mentors will be facilitated by remote collaboration software including Zoom, Coda, Piazza, and Slack. Students are not expected to be familiar with any of these tools prior to the start of the program. By exposing students to these technological tools, SSI hopes to further prepare students for future educational and professional endeavors as our world continues advancing digitally.

Virtual Labs

At the start of the summer, students will be assigned to a virtual lab of 1-3 other students with similar research interests. The virtual lab will be led by the students’ primary mentor. Mentors will have daily 1-on-1 meetings with each student in their lab to provide individual feedback and guidance. In addition, every weekday, virtual labs will have 30-minute all-hands meetings. Mentors will use this time to discuss project updates, guide students through the next steps of the research process, and keep students on track towards completing project deliverables.

On Saturdays, each virtual lab will host an hour-long meeting where students will present their weekly research deliverable. Students will receive feedback on their presentation from both their research mentor and lab student peers. The following is a list of weekly deliverables for the 6-week research program:

· Week 1:  Preliminary Project Wiki
· Week 2: Completed Project Wiki and Research Proposal Due
· Week 3: Critical Questions Report
· Week 4: Milestone Report
· Week 5: Paper Rough Draft
· Week 6: Final Paper and Presentation

Most university labs reserve time every week for lab bonding activities. In a similar spirit, there will be frequent opportunities for SSI mentors to lead social activities in their labs, such as lab dinners, social hangouts, and game nights. 

Mentor Lab Mixer

Once a week, all research students will participate in a 1-hour lab mixer, in which they’ll have a chance to meet other SSI mentors. The purpose of the mixer is to connect students with all SSI mentors to discuss their research. Through the mixer, SSI hopes to foster a collaborative environment where students can learn from not only their research mentor but also other mentors in the SSI community.

SSI Research Journal

On August 1st, all research students will submit a final paper for their projects. All papers will undergo a peer-review process led by SSI mentors, and students with approved projects will be asked for permission to have their papers included in the first publication of the Summer STEM Institute Research Journal. The research journal will be publicly shared by SSI to highlight student work.

Top Presentations

At the end of the program, students will be asked to present their research poster to a panel of SSI judges. SSI will recognize and award the top presentations. These students will have the opportunity to present their project again to the entire SSI community.

SSI Mentors

Prior to the start of the summer, SSI will send a questionnaire to students asking them to describe their fields of scientific interest and previous research or engineering projects they have worked on. Based on this information, SSI will match students with a primary research mentor.

UPDATE: Below is a current list of the 2020 SSI mentor team.  Over the past month, we have received tremendous interest in the SSI mentorship role. We have screened and interviewed 130 candidates-- including top undergraduates, Masters students, and PhDs. We are still wrapping up our last interviews and finalizing the mentorship team, but we guarantee the rest of our mentors will also be of the highest caliber and highly passionate about working with students.

Additionally, we decided that students would benefit most from having diverse mentors, ranging from undergraduates with extensive science fair experience to PhDs. Over the summer, we will be forming “mentorship groups” of three mentors with various backgrounds. On the weekends, students will be presenting their work to the entire mentorship group and will receive feedback from each mentor. While students will have a designated mentor to work closely with and receive guidance from, mentors will be cross-collaborating and students are encouraged to reach out to any mentor at any point in the program.

Allen Huang

Massachusetts Institute of Technology (MIT)

Area of focus: Computational Biology

Experiences: Electrical Engineering and Computer Science @ MIT, Bioinformatics Researcher at Boston University Liu Lab and Geisinger Commonwealth School of Medicine, Undergraduate Developer at MIT Infolab Group, Research Intern at the United States Air Force

Honors/Awards: Regeneron STS Scholar, International Biology Olympiad Team Member (top 4 nationally), US National Chemistry Olympiad Finalist (top 20 nationally; did not attend training camp due to conflict with USABO training camp), AIME Qualifier (x6), poster presenter at Gordon Research Seminar on DNA Damage, Cancer and Mutation, published author in Biochimica et Biophysica Acta

Muntaha Samad

UC Irvine

Area of focus: Deep learning, Biology, and Healthcare

Experiences: B.S. in Computer Science and Engineering at UC Davis, M.S. in Computer Science at UC Irvine, Ph.D. in Computer Science at UC Irvine (in progress), Deep Learning on Healthcare Data at UCI Baldi Lab , Circadian Rhythms Research at UCI Baldi Lab, Machine Learning Research at UCD Tagkopoulos Lab, Machine Learning Research at UCD Eisen Lab, Robotics Education Research at UCD IEL Lab, Antibiotics Overuse Research at UCD iGEM, Deep Learning Intern at Syntiant, Software Engineering Intern Seagate Technology, Deep Learning Intern at Edwards Lifesciences

Honors/Awards: TEDx Youth Talk Speaker @ Intel Folsom, 3 papers published in Cell, NCWIT Student Seed Grant Recipient, Presented at STA Conference 2020, NCWIT Aspirations Award - Northern California Chair, UC Davis iGEM Team

Brian Huang

Massachusetts Institute of Technology (MIT)

Area of focus: Mathematics and Theoretical Computer Science

Experiences: Mathematics with Computer Science @ MIT, Quantitative Research Intern at WorldQuant, LLC, General Relativity Research at Stony Brook, Mathematics Research at Program in Mathematics for Young Scientists (PROMYS) (x2)

Honors/Awards: Siemens Competition National Finalist 3rd Place Individual, Regeneron STS Scholar, USA Mathematical Olympiad Qualifier (USAMO) (x2), USA Physics Olympiad (USAPhO) Bronze Medal, American Regions Mathematics League (ARML) 7th Place Individual

Ethan Weber

Massachusetts Institute of Technology (MIT)

Area of focus: Robotics, Computer Vision, and Machine Learning

Experiences: Research for 4 years in MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), Augmented Reality Intern at Niantic, Intern at Microsoft, Intern at Skydio, Computer Vision Contract Work

Honors/Awards: First author papers under review in ECCV and NeurIPS, Planned submission to CVPR, Presented satellite imagery work in ICLR 2020 AI for Earth Science Workshop, FIRST Robotics Dean's List Finalist

Karen Ge

Stanford University

Area of focus: Psychology/Social Science, Theoretical Mathematics, and Digital Humanities

Experiences: Algebraic Number Theory Research at MIT, Student Researcher at Center for Spatial and Textual Analysis, Teaching and Tutoring Experience

Honors/Awards: Math Olympiad Program (MOP), Research Science Institute (RSI) Scholar

Nithin Buduma

Massachusetts Institute of Technology (MIT)

Area of focus: Computational Biology and Bioinformatics

Experiences: B.S. in Computer Science and Engineering at MIT, M.S. in Electrical Engineering and Computer Science at MIT, Research Assistant in Deep Learning/Chemistry at MIT CSAIL, Software Intern at Optimizely & Samsara, Quantitative Research Intern at Goldman Sachs, Incoming Machine Learning Engineer and Data Scientist at XY.ai (Harvard-based startup)

Honors/Awards: USABO National Finalist, USAChO Semifinalist, AIME Qualifier (5 times), Co-Author of the 2nd Edition of the Fundamentals of Deep Learning

Rahul Khanna

University of Southern California

Area of focus: Natural Language Processing and Machine Learning

Experiences: B.S. in Computer Science at Columbia University’s SEAS, M.S. in Computer Science at USC’s Viterbi School of Engineering 2021 (current), Researcher at Columbia's WuLab, Datascience Engineer at Vimeo, Datascientist at Forensiq, NLP Researcher at USC’s INK Lab

Honors/Awards: Association for Computational Linguistics (ACL) 2020 Demo Paper, Columbia University's cFund Ignition Grant Recipient

Javier Echevarría Cuesta

Stanford University

Area of focus: Mathematics and Computer Science

Experiences: Mathematics with Honors (B.S.) @ Stanford, Computer Science (M.S.) @ Stanford, Mathematics Research at Undergraduate Research Institute in Mathematics at Stanford, Computer Vision Research at Undergraduate Research Opportunities Program at the University of Cambridge, Researcher at Mathematical Physics Lab at Rockefeller University

Honors/Awards: Preprint in Comet and the ACM Conference on Automotive User Interfaces, D.E. Shaw Fellowship, Mathematics Undergraduate Research Award

William Cannon Lewis II

Rice University

Area of focus: Robotics and Reinforcement Learning

Experiences: Mathematics (B.A.) @ Rice, Computer Science (B.S.) @ Rice, PhD Candidate in Computer Science @ Rice, Robotics and Deep Learning Researcher at Rice Kavraki Lab, Summer Journeyman Fellow at Army Research Laboratory, CPRIT Undergraduate Fellow at Baylor College of Medicine, Software Engineering Intern at Two Sigma

Honors/Awards: K2I Computational Science and Engineering Fellowship, Rice Engineering Alumni Distinguished Research Excellence Award, Rice Engineering Alumni Senior Merit Award in Computer Science, Rice Undergraduate Research Symposium Excellence in Research

Matthew Tan

Stanford University

Area of focus: Aero/Astrospace Engineering, Robotics, Autonomous Systems

Experiences: Aero/Astro Engineering @ Stanford, Hardware Integrated LiDAR Simulation for Drone Collision Avoidance Algorithms at Aurora Flight Sciences, Generating Gaussian beams with high coherence by using Fourier Optics at Nir Davidson Optics Lab, Real Time Implementation of Acoustic Detection at the Air Force Research Laboratory, Recurrent Neural Network for Highly Specific Local Speech Recognition for Inter-cockpit Communications (personal project), Autonomous aircraft Design and Construction for Advanced Agricultural Survey (personal project)

Honors/Awards: Research Science Institute Scholar (Co-Rickoid of the Year), Regeneron STS Semifinalist, ISEF Finalist, ISEF NASA Special Award, Weizmann Institute of Science Scholar

Anmol Warman

Duke University

Area of focus: Bioinformatics, Computer Vision, and Machine Learning

Experiences: Research in Duke Biochemistry, Integrated Mathematical Oncology at Moffitt Cancer Center, Teaching Assistant for Duke Graduate Computer Vision Class, Teaching Assistant for Cryptography and Topology at University of South Florida

Honors/Awards: Paper accepted to Experimental Biology 2020 and presented at GPCR Workshop 2019; Paper on non-Canonical GPCR Scaffolding in review at Science; COVID-AI paper in submission and posted on medRxiv; Patent for computer vision tool; 2x ISEF Finalist

Chris Wang

Stanford University

Area of focus: Computer Vision, Quantitative Finance, Bioinformatics

Experiences: Computer Science @ Stanford, Computer Vision Researcher at Stanford ML Group (Andrew Ng's AI and Healthcare Lab), Machine Learning Research Intern at Adobe Systems, Deep Learning Researcher at Stanford AI Lab (Emma Brunskill's Group), Astrophysics Researcher at New Mexico Tech (SSP), Software Engineering Intern at Citadel, Quantitative Trading Intern at Optiver, Venture Fellow at HOF Capital

Honors/Awards: Preprints in arXiv, patent pending for lung pathology detection app, USAMO And USAJMO qualifier, Scholastic Art and Writing National Gold Medalist, USACO Gold

Harisankar Sadasivan

University of Michigan

Area of focus: ML for Bioinformatics, Health and Embedded System Design

Experiences: B.S. in Electronics & Communication Engineering at NITK India, M.S. in Computer Science Engineering at University of Michigan, Ph.D. at University of Michigan (in progress), Sr. Hardware Engineering at Samsung R&D, Embedded System design at NITK, Engineering for Health in Precision Medicine at University of Michigan

Honors/Awards: Best Paper Award for first author paper at International Conference on Advances in Electrical, Electronic and Systems Engineering (ICAEES), First author paper at International Engineering Symposium (IES), First author accepted at ONT London Calling, Poster at IEEE Engineering in Medicine and Biology Society EMBC, NTSE scholar & INSPIRE fellow, Gold Medalist at SOF National Science Olympiad (NSO)

Cierra Beck

Cornell University

Area of focus: Social Applications, Language Processing

Experiences: Operations Research Engineering @ Cornell, Software Engineer at Goldman Sachs, Founder and CEO of Dated, Robotics Mobility-On-Demand Systems Research at Cornell University

Honors/Awards: Yelp Dataset Challenge

Nicolas Rothbacher

Massachusetts Institute of Technology (MIT)

Area of focus: AI/Machine Learning and Public Policy

Experiences: Physics and Mathematics (B.S.) @ University of Puget Sound, Technology and Policy & Electrical Engineering and Computer Science (M.S.) @ MIT, Researcher at MIT Internet Policy Research Initiative (IPRI), Natural Language Processing Research at MIT, Researcher at Caltech LIGO SURF

Honors/Awards: papers in press

Eric Xia

UC Berkeley

Area of focus: Machine Learning, High-dimensional Statistics

Experiences: B.A. in Computer Science at Berkeley, Ph.D. in Statistics at Berkeley (in progress, Bayesian Nonparametrics Researcher in Professor Michael Jordan's group at Berkeley, Random Forest Algorithms Researcher in Professor Bin Yu's group at Berkeley, Portfolio Implementation Intern at AQR, NLP Engineering Intern at Unibit AI

Honors/Awards: Non-zero score on the Putnam

Yatin J. Chandar

Massachusetts Institute of Technology (MIT)

Area of focus: Materials Science and Engineering

Experiences: Aerospace Engineering and Materials Science @ MIT, Researcher at MIT Space Propulsion Lab, Machine Learning Researcher at MIT Center for Computational Engineering, Researcher at Washington University Nano Research Facility

Honors/Awards: Research Science Institute (RSI) Scholar, ISEF 2nd Place in Environmental Engineering, ISEF 3rd Place in Translational Medicine, published author in Advanced Biosystems and ACS Applied Nano Materials

Lyna Kim

Stanford University

Area of focus: Machine Learning and Energy

Experiences: Energy Resources Engineering and Public Policy @ Stanford, Climate Policy Modeling Research at Stanford Goulder Lab, Computer Vision Research at Stanford Jackson Lab, Computational Chemistry Research at MIT Kolpak Lab; Algal Fuel Optimization Research at UCLA Pellegrini Lab, Paleoclimate Modeling Research at UCLA Tripati Lab, Portfolio Manager at Distribute Capital

Honors/Awards: Research Science Institute Top 5 Paper & Top 5 Presentation, Siemens Semifinalist

Eric Frankel

Stanford University

Area of focus: Machine Learning

Experiences: Mathematics and Computer Science @ Stanford, Computer Vision Researcher at Stanford Vision Lab, Machine Learning Researcher at Stanford DAWN Lab, Functional Analysis Research at Arizona State University, Researcher at Translational Genomics Research Institute and Ford Greenfield Labs, Software Engineer Intern at Lumi Labs, Autonomous Vehicle Intern at Ford GFL, ex-cofounder and CFO at Roadata

Honors/Awards: published author in Journal of Emerging Investigators, CalHacks BlackRock Prize, AngelHack San Francisco Trulioo Prize, Neuroscience Research Prize Finalist, Arizona Science and Engineering Fair 1st Place in Mathematics

Gheric Speiginer

Georgia Institute of Technology

Area of focus: Mixed/Augmented/Virtual Reality Systems

Experiences: B.S. in Computer Science at Hampton University, Ph.D. in Human Centered Computing at Georgia Institute of Technology (in progress), XR Systems Researcher at Georgia Tech's Augmented Environments Lab, Mixed Reality Social Interaction Researcher at Microsoft Research, Real-time Guidance for Photo Aesthics UX Researcher at Intel Labs, Graduate Intern at Intel Labs, Analyst Intern at Goldman Sachs

Honors/Awards: First author papers published at International Conference on Human-Computer Interaction, International Conference on 3D Web Technology, International Symposium on Mixed and Augmented Reality Adjunct, National Science Foundation Graduate Research Fellowship Program, National GEM Consortium Ph.D. Science Fellowship, and National Physical Science Consortium

Stephanie Brito

Stanford University

Area of focus: Heath Tech, Computer Vision, Data for Health and Education Equity

Experiences: Machine Learning Research at Stanford School of Medicine, Pediatric Cardiology Product Research, Pediatrics at Stanford School of Medicine, Engineering Practicum Intern at Google, Software Engineering Intern at Airbnb

Honors/Awards: Gates Millenium Scholar, National Hispanic Merit Scholar, Barbara Frye Scholarship, First Place Grand Prize and Best Understanding of an Unmet Need at Stanford's health++ Hackathon

Jesse Stern

University of Chicago

Area of focus: Theoretical Computer Science (Computational Complexity, Circuit Complexity, Cryptography, Algorithms)

Experiences: B.A. in Logic and Computation at University of Rochester, Ph.D. in Computer Science at University of Chicago, Computational Complexity and Theoretical Cryptography, SURF Program at Caltech, Trustable Computing Systems REU at UCONN

Honors/Awards: Published in INDOCRYPT, 1st Prize at Massachusetts State Science and Engineering Fair 2011 (published on arXiv)

Shrey Gupta

Duke University

Area of focus: Machine Learning & Computer Vision

Experiences: B.S. in Computer Science and Statistics @ Duke, Mathematics/Applied Physics Research @ Duke, Cybersecurity Research @ Carnegie Mellon (Institute for Software Research), Currently Software Engineering @ Autonomous Driving Startup, Software Engineering @ Google, Quantitative Research @ Hedge Fund, Data Science @ Infinia ML, Software Engineering @ Oracle

Honors/Awards: Published author in mathematics journal (ALEA), Duke DeNardis Memorial Award, Duke Faculty Scholar Award Nominee for Computer Science, D.E. Shaw Nexus Fellowship

Sydney Zink

Brown University

Area of focus: Human-Computer Interaction, Natural Language Processing

Experiences: Ph.D. in Computer Science at Brown (current), NLP and HCI research at Brown LUNAR (Language Understanding and Representation) Lab, low-resource languages research at Carnegie Mellon Workshop on Language Technology for Language Documentation and Revitalization, language technologies research for children with ASD at the University of Edinburgh Institute for Language, Cognition and Computation, NLP + speech + databases research supervised by the Cornell Robotic Personal Assistants (RPAL) Lab, distributed computing research at Cornell University, Technology Summer Analyst at Goldman Sachs and at J.P. Morgan Chase & Co., Unmanned Ground Sensors Intern at the U.S. Army Research Lab, Economics Research Intern at the FDIC (Federal Deposit Insurance Corporation)

Honors/Awards: journal publication in March 2019 ACM Transactions on Computer Systems, 2020 CoNLL workshop publication, CLS Scholarship alternate (2020) and Fulbright Austria alternate (2020), National Merit Scholar, Einaudi International Research Travel Grant recipient, selected SMART scholar (but denied the funding/placement due to already having been granted full masters funding), 2018 Women in STEM award & PhD fellowship recipient

Anurag Sengupta

University of California, Irvine

Area of focus: Natural Language Processing, Time Series Analysis, Prediction and Forecasting Mathematical Models

Experiences: Discrete Adaptive Control at PES Center for Intelligence Systems, Natural Language Processing at PES Center for Intelligence Systems, Device automation at PES Crucible of Research and Innovation, Mathematical Modeling at UCI Public Health department, Software Developer at Deloitte Consulting

Honors/Awards: Research paper in Natural Language Processing Journal SSCI, IEEE Symposium Series in Computational Intelligence

Ryan Tolsma

Stanford University

Area of focus: Theory (Math/Physics/CS), Public Health, Bioinformatics

Experiences: Mathematics, Physics, and Computer Science (AI) @ Stanford, Deep Learning in Genomics Researcher for Anshul Kundaje's Lab, Deep Learning and Robotics Researcher Stanford Iliad Lab, Quantitative Research Intern @ Wealthfront; Quantitative Trader @ Tibra Capital, Software Engineering Intern @ REX Real Estate

Honors/Awards: TreeHacks Google Prize Winner, USAPHO Bronze, USACO Gold

Jordan Wick

Massachusetts Institute of Technology (MIT)

Area of focus: Evolution and Evolutionary Algorithms, Transportation, Biology

Experiences: B.S. and M.S. in Computer Science @ MIT, RL/Evolutionary Algorithms at MIT Media Lab (Human Dynamics Group), Evolutionary Algorithms for Program Synthesis at MIT CSAIL, Software Engineer at Loon, Software Engineer at Flexport, Software Engineer at NASA

Aansh Shah

Brown University

Area of focus: Data Science and Supervised Learning

Experiences: B.S. 2019 in Applied Mathematics and Computer Science at Brown University, M. S. in Computer Science at Brown University, RL and NLP Researcher at Brown's Intelligent Robotics Lab, Bioinformatics and ML Researcher at Brown's Artificial Intelligence Laboratory, Game Theory and ML Researcher at Brown's Self-Driving Car Laboratory, ML Researcher at Brown's Neural Computation and Cognition Lab, Researcher at Brown's Universal Programming of Devices Lab (Brown University), Data Science Intern at Upserve, SWE Intern at Wayfair, SWE Intern at Oblix, SWE Intern at Uplift Together

Honors/Awards: First author submission to JAMIA (in review), Published in ICSR, ISEF Finalist, 1st place from the American Psychological Association at ISEF

Gaeun Kim

Stanford University

Area of focus: Bioinformatics, Microfluidics/fluid dynamics, Medical imaging

Experiences: Microfluidics and bioengineering research at Stanford Fordyce Laboratory, Bioinformatics research at Stanford Covert Laboratory, Microfluidics research at Stanford Codiga Resource Recovery Center, Medical imaging and machine learning research at Harvard Visual Attention Lab, Teaching Assistant for first year writing at Stanford

Honors/Awards: Co-author of publications in Lab on a Chip and ACS Central Science, Stanford SPARK Translational Research Program Fellow, Stanford Bio-X Undergraduate Fellow, Woods Institute Mel Lane Grant recipient, Best Hardware Project at Stanford Big Earth Hackathon, Research Science Institute Scholar and Top 10 oral presentation, Synopsys Silicon Valley Science Fair 1st place in Biological Sciences, Korea Science and Engineering Fair gold medal

James Boggs

University of Michigan

Area of focus: Social Dynamics, Public Policy, and Big Data

Experiences: 3rd year Ph.D. at University of Michigan, B.S. in Computer Science and B.A. in Philosophy at Union College, Online Learning of Soft Robot Gaits at Union College, Explainable AI and Rebellious Agents at the U.S. Naval Research Lab, Embodying a Cognitive Architecture at the University of Michigan Soar Lab, Integrating Non-Symbolic Knowledge with a Symbolic AI at University of Michigan Soar Lab, Summer Research Intern at the U.S. Naval Research Lab, Research Contractor with the U.S. Naval Research Lab, Lead Developer at Nochi Studios

Honors/Awards: First author on paper & presentation at IJCAI 2018, Paper in Proceedings of the 2019 IEEE International Conference on Soft Robotics, NSF Graduate Research Fellow, Sigma Xi Associate Member, Union College Best Computer Science Thesis Award, Union College Seward Fellow

Harshal Agrawal

Stanford University

Area of focus: Environmental Science, Sustainability, and Public Policy

Experiences: Management Science and Engineering @ Stanford, Environmental Science and Mobile Application Development at the MIT Institute for Data, Science, and Society, Environmental Science and Public Policy Researcher at Montclair State University,  Engineering Intern with JC Division of Engineering, Traffic, and Transportation

Honors/Awards: Research Science Institute Scholar, 3x ISEF Finalist, 1st Place Environmental Protection Agency (EPA) Sustainability Award at ISEF, Regeneron STS Scholar (top 300)

Allison Tam

Massachusetts Institute of Technology (MIT)

Area of focus: Interpretability for Health AI, Reinforcement Learning Planning

Experiences: B.S. in Computer Science and Engineering at MIT, M.S. in Computer Science (with a concentration in AI) at MIT, Machine Learning research at Computer Science and Artificial Intelligence Laboratory (CSAIL) and IBM Research, Computer Vision research at Cognite and Stanford Medical School, Software Engineering Intern at Google Brain, Software Engineerinig Intern at Addepar, Analyst at Point72

Honors/Awards: First author paper published in Medical Physics, Talk at American Medical Informatics Association symposium, Intel STS Semifinalist, Stanford Institute of Medical Research Scholar, AIME qualifier

Steven Okada

Massachusetts Institute of Technology (MIT)

Area of focus: Computational Epidemiology, Computational Social Sciences, Physics

Experiences: B.S. in Computer Science at MIT, Machine Learning and Knowledge Graph Research at MIT Media Lab, Gravitational Physics at MIT Kavli Institute, Software Engineer at Samsara

Honors/Awards: ISEF, National Merit, USNCO, National Science Bowl, National Ocean Sciences Bowl, Presidential Scholars Program

Nathaniel Lam

Princeton University

Area of focus: Computer Technology, Sustainability, Social Sciences

Experiences: Computer Science @ Princeton, Neural network research at Seung Lab at Princeton University, Unsupervised learning research at Gatsby Institute in London, Software Engineer Intern at Nova, Software Engineer at Yext, Software Engineer at Andrena

Jonathan Lu

Harvard University

Area of focus: Physics, Mathematics, and Chemistry

Experiences: Physics and Mathematics @ Harvard, Condensed Matter Computational & Theoretical Physics Research at Harvard, Biophysics Research at MIT, Software R&D Intern at Trend Micro, Statistical Modeling and Chemistry Research at University of North Texas, Biophysics & Biomedical Engineering Research at University of North Texas, Electrical Material Math Modeling and Materials Science Research at University of North Texas

Honors/Awards: 5 papers published in Elsevier and Taylor & Francis Journals (4 as first author), Research Science Institute Top 5 Presenters and Scholar, Barry M. Goldwater Scholar, American Physics Society Conference Co-author, American Junior Academy of Science Texas Delegate and Fellow, National Junior Science and Humanities Symposium Texas Delegate, Sigma Xi Student Research Conference

Dhamanpreet Kaur

Massachusetts Institute of Technology (MIT)

Area of focus: Healthcare and Biostatistics

Experiences: Computer Science, Biology, and Mathematics @ MIT, Statistical Modeling at Fred Hutchinson Cancer Research Center, Data Analytics and ML at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), Polio Diagnosis Model for World Health Organization, Machine Learning for Genomics Project in MIT Computational Biology Group, ML and Clinical Informatics Intern at Philips Research North America, AI Consultant for United Technologies Corporation, Data Analytics Intern at Singapore-MIT Alliance for Research and Technology

Honors/Awards: First author of paper published in Cancer, First author of paper published in International Journal of Medical Informatics

Ross Teixeira

Princeton University

Area of focus: Data Science, Web Scraping, Internet Measurements

Experiences: B.A. in Computer Science (Music Minor) at UC Berkeley, M.S. in Computer Science at Princeton University, Ph.D. in Computer Science at Princeton University (current), Network security and policy research at Princeton's Center for Information Technology Policy (CITP), Research on software-defined and programmable networks at Princeton University, Computer Science Education Research at Berkeley, Research Intern at Microsoft Research, Research Mentor at AI4All

Honors/Awards: First author submission to ACM Symposium on SDN Research (2 papers under submission), Siebel Scholar, SEAS Excellence in Teaching Award

Abhijit Shankar Mudigonda

Massachusetts Institute of Technology (MIT)

Area of focus: Theoretical Computer Science, Mathematics, Probability/Statistics

Experiences: Improving Classical and Quantum Complexity Theory and Algorithms Research at MIT CSAIL, Algebraic Geometry and Combinatorics Research at MIT Mathematics, Machine Learning and Mathematics Research at IBM Research Cambridge, and Bioinformatics and Machine Learning Research at the Knight Cancer Institute, Software Engineering Intern at Facebook, Computer Vision Intern at IBM Research, USA Biology Olympiad Teaching Assistant

Honors/Awards: International Biology Olympiad Silver Medalist (30th), North American Computational Linguistics Olympiad US Alternate (top 12), US National Chemistry Olympiad High Honors (top 50)

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